Google History (The Complete Guide 2019)

History of Google

A Very Brief History of Google

Google was born in 1996. Originally called BackRub, it was the creation of Stanford University students Larry Page and Sergey Brin as a better way to organize and search the growing web.

 

Rather than ranking results by counting how many times search terms appeared on a page, as other search engines at the time did, they created a search engine that determined a website’s relevance by counting the number of pages, and the importance of those pages, that linked back to the original site.

 

Before incorporating in 1998, the name was changed to Google, a mis-spelling of googol, the mathematical term for a 1 followed by one hundred 0s.

 

It was chosen as the new name to reflect their desire to index the immense amount of data on the Internet. Since its incorporation, Google has expanded its offerings beyond the original search engine.

 

The company has developed its own products and has acquired other products, further expanding the Google empire.

 

Other Google Products and Services

Google Products and Services

This blog will focus on searching Google and History, but there’s much more than Google does. Here are just a few examples.

 

• Android: a Linux-based operating system for mobile devices such as smartphones and tablet computers. Android

 

• Gmail: Free webmail IMAP and POP e-mail service provided by Google, known for its abundant storage, intuitive search-based interface, and elasticity. It was first released in an invitation-only form on April 1, 2004.

 

• Google Chrome and Google Chrome OS/Chromebook

Google Chrome

Google Chrome is Google’s web browser and Chrome OS is a computer operating system based on the Chrome browser. In a few cases, we’ll be mentioning Google search features that are only available if you’re using one of these platforms.

 

• Google Glass

The head-mounted wearable computer, similar to eyeglasses but with a heads-up display instead of traditional lenses. 

 

• Google Driverless Car

Google Driverless Car

An experimental project that involves developing technology for driverless cars. The system combines information gathered from Google Street View with artificial intelligence software that combines input from video cameras inside the car and sensors on the outside. 

 

Common Search Elements

A note before we get started: unless otherwise stated, for all of our examples you do not need to be logged into a Google account. 

 

There are some features of Google searching that apply to all the different search interfaces we’ll be covering. Features specific to a type of search will be covered in the relevant blog.

 

• Autocomplete

As you type within the search box on Google, the autocomplete algorithm offers searches that might be similar to the one you’re typing. The algorithm predicts and displays search queries based on other users’ search activities and the contents of web pages indexed by Google.

 

• Search as you type

Search

In 2010, Google introduced Google Instant, a search enhancement that shows results as you type.

 

As soon as you start typing your search terms into the search box, Google brings up possible results based upon the first letters you type. As you type more, the results will change to match what you’ve now typed.

 

Once you see results that match what you need, you can stop typing and start browsing your results. Basically, Google Instant speeds up your search time and gets you your results a few seconds quicker.

 

If you don’t want to use Google Instant, you can turn it off. After you have your search results, click the gear icon in the upper right corner of the results and choose “Search Settings.”

 

You can choose to show Google Instant predictions “only when your computer is fast enough,” “always show Instant results,” or “never show Instant results.”

 

Voice search

Voice search

With an attached microphone, you can speak your search, rather than typing it. Click the mic icon in the Google Chrome search bar and start talking. This is one of those features that’s available only when you’re using the Google Chrome browser.

 

• Next/Previous page

If the web page or information you’re looking for is not on the first page of search results, you can click “Next” at the bottom of the page to see more results.

 

Remember, the further into the results pages you get, the less relevant the results may become.

 

• Result types

You can limit your search results to a particular type of content on the top above your search results: Web, Images, Maps, Shipping, Books, and so on. Click “More” to see additional types.

 

• Searching Google+

Searching Google+

In the past, you would use a + before a keyword word to require it. Today, all keywords are automatically considered required. Only use a + sign when you want to search for content within Google+.

 

• Quotes for phrases: To search for an exact phrase, put it in quotes

• Capitalization: Capitalization doesn’t matter; This is the same as ThiS.

• Special characters: Most special characters are ignored; ©, for example.

• Word order: To increase the relevance of search results, Google does pay attention to the order in which you enter your search terms.

 

Search Operators

Search Operators

Google search operators can be used to focus your search. Here we will detail the common operators. In each of the following blogs, you will learn the operators specific to that blog’s type of searching.

 

All these options are available to you when you do your basic search, but you need to know the syntax necessary to access them. If you go to an Advanced Search screen, you just fill out the fields you wish to use and click the “Advanced Search” button.

 

The first section of an Advanced Search form, “Find pages with . . . ,” is designed to find web pages that have the following:

• All these words This field works as a Boolean “AND.” Every word in this field will be considered in the search.

 

• This exact word or phrase: This field is used in place of the standard quotation marks to form a phrase. All words in this field will be considered in the order given.

 

• Any of these words: This field works as a Boolean “OR.” Any word in this field will be considered in the search, but only any one word of the list need be considered.

 

• None of these words: This field works as a Boolean “NOT” (AND NOT). Words in this field will be explicitly excluded from consideration in the results list.

 

• Numbers ranging from Separate numbers by two periods (with no spaces) to see results that contain numbers in a given range of things like dates, prices, and measurements.

 

For example, if you’re looking for reviews of digital cameras costing between $200 and $300, you could enter those values here.

 

You may have noticed that our wording is not exactly standard when it comes to explaining these items. Typically when describing a Boolean operator, such as “AND,” one would say that both words “must appear in the result.”

 

However, based on how Google’s search algorithm works, at times you can require a word to be present—but that word will not appear in the result.

 

Therefore, we needed to say that the words “will be considered in the search,” as opposed to the more standard “must appear” language.

 

More Search Options

More Search Options

The final section on the Advanced Search page, “You can also . . . ,” has links to other search types, which work independently of one another and anything else you may do on this page.

 

Find Pages That Are Similar to, or Link to, a URL

You can use special search operators to find pages that are similar to or link to a specific URL. For example, let’s say we’re looking for the websites of other libraries in our area.

 

We know that the URL for our home library is http://www.lincol-nlibraries.org/, 
​so we use the “related” operator and enter related:lincolnlibraries. org into the Google search box, and receive the results.

 

As you can see from the results, we’ve been presented with a list of other libraries and library-like institutions in Nebraska and surrounding states. The list is not geographically limited, but generally, the farther down the list we go, the farther out into the rest of the state the libraries are located.

 

The “link:” operator gives you a list of results to pages linked to the URL that you entered. For example, if we’d like to know what websites link back to a particular site, we would enter link:nlc.nebraska.gov into the Google search box.

 

Be aware that the “link:” operator will search only for pages that link to the exact URL that you enter. 

 

Thus, for the previous example, you will get results that link only to that web page but not to any other page on that website. To see links to any other page on the site, you would use link:nlc.nebraska.gov/ncompasslive, for example.

 

You can also “Search pages you’ve visited,” if you are logged into your Google account. Since that is not something that you would generally do when helping your patrons, we do not cover that option in this book.

 

If the Advanced Search options aren’t finding what you need, you can “Use operators in the search box.”

 

This is a more complex way of doing most of the searches that are available to you on the Advanced Search page. There is a list of these, with examples, from this link at the bottom of the Advanced Search page.

 

Search Settings

Search Settings

The Search Settings page is where you can customize your preferences in Google search. Changing any of these settings means you are changing them indefinitely for the computer you are using.

 

So, if you are on a computer that is used by more than one person, you may want to consider your changes carefully.

 

By signing in to Google, you can have these settings affect your own account as opposed to the particular computer. To reinstate your customized settings, just log in to your Google account.

 

There are multiple access points to your settings. The last option on the Advanced Search page is to “Customize your search settings”;

 

you can go to Preferences, or after you have done a search, you can click the gear icon in the upper right corner of the results page and choose “Search settings.”

 

To finalize any changes you make on these screens, click on the “Save” button at the bottom of the screen.

 

On the left side of the screen, you will see that there are three categories on the Search Settings page: Search results, Languages, and Location. In the Search results category, you have the following options:

 

• SafeSearch filters

SafeSearch is Google’s technology for filtering out potentially offensive content. This option allows you to change your browser settings to help eliminate adult content from your search results.

 

By default, the Safe-Search filter is disabled. To enable Safe Search, click the “Filter explicit results” checkbox.

 

This will filter sexually explicit video and images from Google Search result pages, as well as results that might link to explicit content. To disable the Safe Search filter, uncheck the “Filter explicit results” option. Please be aware that no filter is perfect. Even

 

Google says that “we do our best to keep Safe Search as up-to-date and comprehensive as possible, but inappropriate sites will sometimes slip through the cracks.”

 

Also, this is not a replacement for any filtering software you may be considering installing in your library. Anyone can easily get around this filter by coming back to this page and changing the setting.

 

• Google Instant predictions

Also discussed earlier in this blog, this is where you can choose to show Google Instant predictions “only when your computer is fast enough,” “always show Instant results,” or “never show Instant results.”

 

• Results per page

Here you can set how many results you would like per screen. The default is 10, but if you would like more, you can change this to 20, 30, 40, 50, or 100.

 

• Where results open

When this option is selected, the result you click on will be opened in a new window or tab (if your browser supports tabbed browsing). This will allow you to open multiple results at the same time instead of having to move back and forth between results and the Google results list.

 

If you are not comfortable working with multiple browser windows or tabs, checking this option is not recommended.

 

• The final two options, blocking unwanted results and web history, are available only when you are logged in to your Google account, and thus will not be covered in this blog. The second category on the Search Settings page is Languages.

 

• For Google text

Here you may choose whichever of the available languages you wish to use for Google’s interface.

 

Choosing an option here will “permanently” change Google’s interface for your computer. From this point forward (until you change it again), when you go to Google, you will be presented with the language you’ve selected.

 

• Search results

 Search results

The default setting for Google’s search language is “Search for pages written in any language.”

 

This instructs Google to retrieve all relevant results regardless of the language the result is written in. By changing this setting to “Prefer pages written in these language(s):” you can then select one or more of the 46 languages listed to limit your results.

 

Here you can limit your results to more than one language. However, you must remember that by choosing this option, Google will remember this limitation until you come back and change it again.

 

The last category on the Search Settings page is Location. This is where you can chose the location you would like Google to use for Google Search, Google Maps, and other Google products. You can enter a street address, zip code, city and state, or country.

 

By default, Google’s location detection technology will automatically set a location for you using your IP address, but you can change that location to anyplace you like and then save it as your default location.

 

So, now that we’ve got the common items covered, let’s get a little more specific and start searching.

 

Note

1. This is a bit of a simplification of how Google’s “Page Rank” works, as today Google determines relevancy using literally hundreds of factors. However, it’s a good enough explanation for our purposes.

 

Google Web Search

Google Web Search

This blog presents an overview of the basic Google Web Search, focusing on the major features to show how you can use them in your daily reference work.

 

Google’s central purpose is to search the whole web—as much as it can possibly index, anyway. 

 

There are also ways to search subsections of the web or certain types of material. For each of these services, we do not cover all the available features here.

 

In some cases, we cover topics in later blogs. In other cases, because some features may not be as useful at the reference desk, we focus on only the most useful features of these services.

 

Basic Search

Basic Search

Nearly every Internet user today is familiar with the Google homepage. But, just as a reminder.

 

By default, any search performed from this page will search Google’s database of web content. From here you can also click on links to search various other Google databases, such as Images, Videos, News, Books, and Maps.

 

Others are available through the “More” link, which we cover later in this blog. Google also offers users the ability to customize their Google home page through the “Sign in” to their Google account at the upper right corner of the page.

 

Basic searches are performed by entering your search terms, and any operators as needed, into the search box and clicking on one of the two available buttons. Those buttons are “Google Search” and “I’m Feeling Lucky.”

 

Clicking on the “Google Search” button—which can also be activated by pressing your Enter key while your cursor is in the search box—performs your search and presents you with a list of results.

 

Clicking on “I’m Feeling Lucky” performs your search, but instead of presenting you with a list of results, it takes you right to the page that was the first result. This is as if you had clicked on “Google Search,” retrieved your list of results, and clicked on the first result yourself.

 

The “I’m Feeling Lucky” option works very well when you’re pretty sure of where you’re going to end up. For example, searching on such terms as Microsoft, Nike, or Wikipedia will retrieve for you Microsoft, www.nike .com, and Wikipedia, respectively.

 

However, if you’re not sure of the end result, as with more complex searches, or if you don’t want to take the chance of displaying something potentially inappropriate to a patron, the standard “Web Search” option is your better choice.

 

Advanced Search

Advanced Search

If you’re still having trouble finding what you need, additional filtering is available via the Advanced Search page. Click on the gear icon in the upper right corner of your results page. From the pull-down menu, choose “Advanced Search.”

 

To start with, you will have the usual word-limiting options.

The next section of the form is “Then narrow your results by . . .” Here you have more options that are specific to the type of search you are doing. For a web search, the options are:

 

• Language

This field allows you to limit your results to only those in a particular language. At the time of this writing, there were more than 40 language choices, ranging from Afrikaans to Vietnamese. The default is “Any language.”

 

• Region

Here you’ll find a list of countries that Google can limit your results to, which is pretty much all of them, actually. Results in most cases will be from pages whose domain names contain the two-letter country code of the country you selected.

 

• Last update

This field allows you to limit your results to pages that are from the Past 24 hours, Past week, Past month, or Past year. Please keep in mind that this date is based on the date of the page when last indexed, not the date on the live page as it is the moment you search.

 

• Site or domain

This field allows you to limit your results to a particular domain or top level domain. For example, to retrieve results from only US government sites, enter .gov. To retrieve results from only Microsoft, enter Microsoft

.com.

 

• Terms appearing

As mentioned earlier, Google considers many locations when looking for your search terms, including ones that are not even part of the documents returned as results.

 

This field allows you to specify where you would like your terms to appear. These options are “anywhere in the page,” “in the title of the page,” “in the text of the page,” “in the URL of the page,” and “in links to the page”.

 

• Safe Search

As we’ve mentioned, SafeSearch is Google’s technology for filtering out potentially offensive content.

 

This option allows you to change your browser settings to help eliminate adult content from your search results. By default, the SafeSearch filter is disabled. To enable Safe-Search, open the pull-down menu, then click on “Filter explicit results.”

 

This will filter sexually explicit video and images from Google Search result pages, as well as results that might link to explicit content. To disable the SafeSearch filter, open the menu again and click “Show most relevant results.” Please be aware that no filter is perfect. Even

 

Google says that “we do our best to keep SafeSearch as up-to-date and comprehensive as possible, but inappropriate sites will sometimes slip through the cracks.”

 

• Reading level

Limit your search results to a specific reading level: Basic, Intermediate, or Advanced. You can also choose to see results annotated with reading levels, which includes a percentage breakdown of results by reading level.

 

• File type

This field allows you to limit or exclude results in a particular file format, such as PDF, Postscript, Word, Excel, PowerPoint, and RTF (rich text format). For example, many government reports are published in PDF format, so limiting to that format could make finding a particular report easier.

 

• Usage rights

If you are planning to reuse someone else’s content from the web, it’s always a good idea to check the usage rights that the original owner may have placed on their pages.

 

The Advanced Search usage rights filter can help you find content that you are allowed to use. The usage rights filter shows you pages that are either labeled with a Creative

 

Commons license or labeled as being in the public domain.

Creative Commons (http://creativecommons. org), a project started by Lawrence Lessig, allows content creators to assign a copyright-like license to their content, controlling attribution, commercial usage, and derivative creation.

 

Once created, this license can be attached to the content, allowing users to know what permissions they do and do not have when it comes to using that content.

 

But, before you use any content you find, you should check the actual license information on the original page. The Google Search usage rights filter can help you get started, but it should not be the only research you do before using someone else’s content.

 

The usage rights filtering options include:

rights filtering options

 Not filtered by license—limits your search results to pages on which Google could find no license or public domain indication.

 

Free to use or share—limits your search results to pages that are either labeled as public domain or carry a license that allows you to copy or redistribute its content, as long as the content remains unchanged.

 

Free to use, share, or modify—limits your search results to pages that are labeled with a license that allows you to copy, modify, or redistribute in ways specified in the license.

 

Commercially—Limits your search results to pages that are labeled with a license that allows you to use the content for commercial purposes, in ways specified in the license.

 

After setting any or all of these limiters, just click the “Advanced Search” button at the bottom right of the page to execute your search.

 

Web Search Results

Web Search Results

When you do a general web search on Google, your search results will contain a little of everything. It will not be restricted to a certain type of result, as you will see in future blogs. Since you haven’t yet chosen to focus on a particular type of result, Google will give you all of them.

 

There are some similarities across all search results pages, however. The search box, with your search terms included, is at the top, along with links related to your Google account and Google+ services. Just below this, the links to other types of searches are presented, followed by the Search tools link, which provides more search limiters.

 

Next, you will find the number of results and the length of time it took Google to perform the search, and all the way to the right is the gear icon to access your general search settings, advanced search options, and web history. If there are any Ads or Sponsored links, they will appear at the top of your results and/or off to the right.

 

If you have done a search for a person, place, or thing, you will see a box to the right of your search results with information gathered via Google’s Knowledge Graph.

 

These are quick facts and/or pictures related to your search that have been gathered from various sources, such as Wikipedia, subject-specific resources such as Weather Underground for weather information and the World Bank for economic statistics, and publicly available data from Freebase. com, a free and open database of over 24 million things.

 

Depending on the topic of your search, you may also find a block of “In-depth articles” at the bottom of the first page of results. Google uses an algorithm to look for high-quality, in-depth content related to your search and presents them to you in case you want to learn more about the subject you are researching.

 

At the bottom of the page are the standard next/previous page of results links and some suggested searches related to your search term(s).

 

Standard Result

Standard Result

Your standard search results list will show the most relevant match first, followed by the next relevant match, and so on. A typical result will include:

 

  • Title of the web page: This is a hot link that you can click to go to the web page.
  •  URL: In green, you’ll see the web address of that result’s web page.
  • Snippet: A few lines of text excerpted from the web page.

 

At the end of the URL, you will see a green down arrow. Click it to get a drop-down menu with up to three options. The first option is Cached, which will bring up the cached view of the page, a snapshot of the page as it appeared at a particular time.

 

The second option is Similar, which will bring up a list of pages like that page. If you are logged in to your Google account, it will also show a Share option, so that you can share the result on Google+.

 

Links within Snippets

 Snippets

For some results, Google provides links within the snippet to relevant sections of the page, making it faster and easier to find what you’re looking for.

 

Results with Site links and Search within the Site

If Google thinks it will be useful to a user, site links are showcased in a search result. An automated algorithm analyzes websites, looking for links that may help users jump quickly to the section they need of the main website.

 

In addition, if other algorithms determine that more refined searching within a site may be useful, there is a search box below the site links. This search box gives you the ability to search only within that site for the information you need.

 

Search Results Options and Tools

You can further refine your search using the filtering options in the panel above your search results. The options available will vary depending on your original search, so you won’t always see all the possible limiters.

 

If you would like to limit your search to certain types of content, you can switch to see results such as Images or Videos. Click “More” to see all the options. To see all types of content, choose “Web.”

 

Click “Search tools” for even more ways to limit your results. Three pull-down menus will appear below the content options: Time, Results and Location.

 

• Time

Time

This option limits your results to items posted during the following times: Past hour, Past 24 hours, Past week, Past Month, Past year; or with “Custom range . . .” you can enter specific dates. Click on “Any time” to return to the full results list.

 

The second Search tools menu is Results. By default, it is set to All Results. Other limiters that might be available are:

 

• Sites with images

This limits your search results to pages with images on them and shows a selection of those images, to help you decide if the entire site is what you’re looking for.

 

• Related searches

This gives you suggestions for other terms to combine with your original search term(s) that might help you narrow your search further. It will also show other terms that may be similar to your original search term(s).

  • Dictionary
  • Reading level

 

See results annotated with Basic, Intermediate, or Advanced reading levels, and a percentage breakdown of your results by reading level

 

• Nearby

This works geographically, using your IP address or your default location, to limit your search results to items that are relevant to that location. You can narrow down your results to the city, region, or state level.

 

• Translated foreign pages

This option uses Google’s automatic translator service, Google Translate. Google translates your search term into one or more languages and then performs a search using the translated terms.

 

The search results are then translated back into your default language. Click a translated result and you’ll be taken to an automatically translated version of the page.

 

• Verbatim

Google typically tries to help you get to the information you need by automatically improving the searches you enter.

 

Some of the improvements Google makes are suggesting spelling corrections and alternative spellings, including synonyms of your search terms to find related results and searching for words with the same stem, such as running when you search for a run.

 

To see results that contain the exact words you are searching for, click “Verbatim,” and Google will ignore these usual improvements and search only for the exact words you entered.

 

The third Search tools option is Location. The location used to customize your results is shown. Google’s location detection technology automatically sets a location for you using your IP address, but you can change that location to anyplace you like and then save it as your default location.

 

Google’s System of the World

Google’s System

Alphabet, Google’s holding company, is now the second-largest company in the world. Measured by market capitalization, Apple is first. Joined by Amazon, and Microsoft followed avidly by Facebook in seventh, the four form an increasingly feared global oligopoly.

 

Because Google, alone among the five, is the protagonist of a new and apparently successful “system of the world.” Represented in all the most prestigious U.S. universities and media centers, it is rapidly spreading through the world’s intelligentsia, from Mountain View to Tel Aviv to Beijing.

 

Under the leadership of Larry Page and Sergey Brin, Google developed an integrated philosophy that aspires, with growing success, to shape our lives and fortunes.

 

Google has proposed a theory of knowledge and a theory of mind to animate a vision for the dominant technology of the world; a new concept of money and therefore price signals; a new morality and a new idea of the meaning and process of progress.

 

The Google theory of knowledge, nicknamed “big data,” is as radical as Newton’s and as intimidating as Newton’s was liberating.

 

Newton proposed a few relatively simple laws by which any new datum could be interpreted and the store of knowledge augmented and adjusted.

 

In principle anyone can do physics and calculus or any of the studies and crafts it spawned, aided by tools that are readily affordable and available in any university, many high schools, and thousands of companies around the world.

 

Hundreds of thousands of engineers at this moment are adding to the store of human knowledge, interpreting one datum at a time.

 

“Big data” takes just the opposite approach. The idea of big data is that the previous slow, clumsy, step-by-step search for knowledge by human brains can be replaced if two conditions are met: All the data in the world can be compiled in a single “place,” and algorithms sufficiently comprehensive to analyze them can be written.

 

The Google theory of knowledge and mind are not mere abstract exercises. They dictate Google’s business model, which has progressed from “search” to “satisfy.”

 

Google’s path to riches, for which it can show considerable evidence, is that with enough data and enough processors it can know better than we do what will satisfy our longings.

 

Even as the previous systems of the world were embodied and enabled in crucial technologies, so the Google system of the world is embodied and enabled in a technological vision called cloud computing.

 

If the Google theory is that universal knowledge is attained through the iterative processing of enormous amounts of data, then the data have to be somewhere accessible to the processors.

 

Accessible in this case is defined by the speed of light. The speed-of-light limit—nine inches in a billionth of a second—requires the aggregation of processors and the memory in some central place, with energy available to access and process the data.

 

The “cloud,” then, is an artful name for the great new heavy industry of our times: gargantuan data centers composed of immense systems of data storage and processors, linked together by millions of miles of fiber-optic lines and consuming electrical power and radiating heat to an extent that excels most industrial enterprises in history.

 

So dependent were the machines of the industrial revolution on sources of power that propinquity to a power source—first and foremost, water—was often a more important consideration in deciding where to build a factory than the supply of raw material or manpower. Today Google’s data centers face similar constraints.

 

Google’s idea of progress stems from its technological vision. Newton and his fellows, inspired by their Judeo-Christian worldview, unleashed a theory of progress with human creativity and free will at its core.

 

Google must demur. If the path to knowledge is the infinitely fast processing of all data, if the mind— that engine by which we pursue the truth of things—is simply a logic machine, then the combination of algorithm and data can produce one and only one result.

 

Such a vision is not only deterministic but ultimately dictatorial. If there is a moral imperative to pursue the truth, and the truth can be found only by the centralized processing of all the data in the world, then all the data in the world must, by the moral order implied, be gathered into one fold with one shepherd.

 

Google may talk a good game about privacy, but private data are the mortal enemy of its system of the world.

 

Finally, Google proposes and must propose, an economic standard, a theory of money and value, of transactions and the information they convey, radically opposed to what Newton wrought by giving the world a reliable gold standard.

 

As with the gentle image of cloud computing, Google’s theory of money and prices seem at first utterly benign and even in some sense deeply Christian.

 

For Google ordains that, at least within the realm under its direct control, there shall be no prices at all. With a few small (but significant) exceptions, everything Google offers to its “customers” is free.

 

Internet searches are free. Email is free. The vast resources of the data centers, costing Google an estimated thirty billion dollars to build, are provided essentially for free.

 

Free is not by accident. If your business plan is to have access to the data of the entire world, then free is imperative. At least for your “products.” For your advertisers, it’s another matter. What your advertisers are paying for is the enormous data and the insights gained by processing it, all of which is made possible by “free.”

 

So the cascades of “free” began: free maps of phenomenal coverage and resolution, making Google master of mobile and local services; free YouTube videos of luminous quality and stunning diversity that are becoming a preferred vessel for Internet music as well;

 

Free email of elegant simplicity, with uncanny spam filters, facile attachments, and hundreds of gigabytes of storage, with links to free calendars and contact lists;

 

free Android apps, free games, and free search of consummate speed and effectiveness; free, free, free, free vacation slideshows, free naked ladies, free moral uplift (“Do no evil”), free classics of world literature, and then free answers, tailored to your every whim by Google Mind.

 

If you do not charge for your software services—if they are “open source”— you can avoid liability for buggy “betas”. You can happily escape the overreach of the patent bureau’s ridiculous seventeen-year protection for minor software advances or “business processes” like one-click shopping. But don’t pretend that you have customers.

 

Of all Google’s foundational principles, the zero price is apparently it's most benign. Yet it will prove to be not only its most pernicious principle but the fatal flaw that dooms Google itself.

 

Google will likely be an important company ten years from now. Search is a valuable service, and search it will continue to provide. On search, it may prosper, even at a price of zero. But Google’s insidious system of the world will be swept away.

 

Google’s Roots and Religions

Google’s Roots

Under the leadership of Larry Page and Sergey Brin, Google developed the integrated philosophy that currently shapes our lives and fortunes, combining a theory of knowledge (nicknamed “Big Data”), a technological vision (centralized cloud computing).

 

A cult of the commons (rooted in “open source” software), a concept of money and value (based on free goods and automated advertising), a theory of morality as “gifts” rather than profits, and a view of progress as evolutionary inevitability and an ever diminishing “carbon footprint.”

 

This philosophy rules our economic lives in America and, increasingly, around the globe. With its development of “deep learning” by machines and its hiring of the inventor-prophet Raymond Kurzweil in 2014, Google enlisted in a chiliastic campaign to blend human and machine cognition.

 

Kurzweil calls it a “singularity,” marked by the triumph of computation over human intelligence. Google networks, clouds, and server farms could be said to have already accomplished much of it.

 

Google was never just a computer or software company. From its beginning in the late 1990s, when its founders were students at Stanford, it was the favorite child of the Stanford Computer Science Department, married to Sand Hill Road finance across the street, and its ambitions far transcended mere business.

 

Born in the labs of the university’s newly opened (Bill) Gates Computer Science Building in 1996 and enjoying the patronage of its president, John Hennessy, the company enjoyed access to the school’s vast computer resources. (In 2018 Hennessy would become chairman of Alphabet, the Google holding company).

 

In the embryo, Google had at its disposal the full bandwidth of the university’s T-3 line, then a lordly forty-five megabits a second, and ties to such venture capital titans as John Doerr, Vinod Khosla, Mike Moritz, and Don

 

Valentine. The computer theorists Terry Winograd and Hector Garcia Molina supervised the doctoral work of the founders.

 

Rollerblading down the corridors of Stanford’s computer science pantheon in the madcap spirit of Claude Shannon, the Google founders consorted with such academic giants as Donald Knuth, the conceptual king of software, Bill Dally, a trailblazer of parallel computation, and even John McCarthy, the founding father of artificial intelligence.

 

By 1998, Brin and Page were teaching the course CS 349, “Data Mining, Search, and the World Wide Web.” Sun founder Andy Bechtolsheim, Amazon founder Jeff Bezos, and Cisco networking guru Dave Cheriton had all blessed the Google project with substantial investments. 

 

Stanford itself earned 1.8 million shares in exchange for Google’s access to Page’s patents held by the university. (Stanford had cashed in those shares for $336 million by 2005).

 

Google moved out of Stanford in 1999 into the Menlo Park garage of Susan Wojcicki, an Intel manager soon to be CEO of YouTube and a sister of Anne, the founder of the genomic startup 23andMe.

 

Brin’s marriage to Anne in 2007 symbolized the procreative embrace of Silicon Valley, Sand Hill Road, and Palo Alto. (They divorced in 2015.) By 2017, Google’s own computer scientists had authored more of the world’s most-cited papers in the subject than had Stanford’s own faculty.

 

Google’s founders always conceived of their projects in prophetic terms. An eminent computer scientist, Page is the scion of two Ph.D.s in the subject, and no one will deny, not even his mother, that his “PageRank” paper behind Google search is better than any doctorate.

 

His father, Carl, was an ardent evangelist of artificial intelligence at Michigan State and around the family dinner table in East Lansing.

Brin saw the word “googol,” meaning ten to the one-hundredth power—an impossibly large number—as a symbol of the company’s reach and ambition.

 

A leading mathematician, computer scientist, and master of “big data” at Stanford, Brin supplied the mathematical wizardry that converted the PageRank search algorithm into a scalable “crawler” across the entire expanse of the Internet and beyond.

 

By exploring search—what Page called “the intersection between computer science and metaphysics”—Google was plunging into profound issues of philosophy and neuroscience.

 

Search implies a system of the world: it must begin with a “mirror world,” as the Yale computer scientist and philosopher David Gelernter puts it, an authentic model of the available universe.

 

In order to search for something with a computer, you must translate its corpus into digital form: bits and bytes defined by Shannon as irreducible binary units of information.

 

Page and Brin set out to render the world, beginning with its simulacrum, the Worldwide Web, as a readable set of digital files, a “corpus” of accessible information, an enormous database.

 

As the years passed, Google digitized nearly all of the available books in the world (2005), the entire tapestry of the world’s languages and translations (2010), the topography of the planet (Google Maps and Google Earth, 2007), down to the surfaces and structures on individual streets (StreetView) and their traffic (Waze, 2016).

 

It digitized even the physiognomies of the world’s faces in its digital facial recognition software (2006, now upgraded massively and part of Google Photos). With the capture of YouTube in 2006, Google commanded an explosively expanding digital rendition of much of the world’s imagery, music, and talk.

 

Accessed through a password system named Gaia, after the earth goddess, this digital mirror world and its uncountable interactions comprised a dynamic microcosm worthy of a googolplex.

 

As Page put it, “We don’t always produce what people want; it’s really difficult. To do that you have to be smart—you have to understand everything in the world. In computer science, we call that artificial intelligence.”

 

Homogenizing the globe’s amorphous analogical tangle of surfaces, sounds, images, accounts, songs, speeches, roads, buildings, documents, messages, and narratives into a planetary digital utility was a feat of immense monetary value.

 

No other company came close to keeping up with the exponential growth of the Internet, where traffic and content double every year.

 

Weaving and wrapping copies of the URLs (universal resource locators) of the Web in massively parallel automated threads of computation, Google’s Web crawler technology has been a miracle.

 

By making the Internet’s trove of information readily accessible to the public, and extending its reach to the terrestrial plane, Google introduced a fundamentally new technology.

 

An ordinary company of the previous system might have sold access to this information or collect royalties on licenses for the software needed to reach it. By developing efficient and hassle-free transactional systems, optimizing its computer processing, and driving down costs as it expanded in scale, Google might have garnered massive profits over the years.

 

As little as a penny, a search on its forty-two-kilohertz (thousand-searches-a-second) find-and-fetch engine would produce some $13 billion of revenues per year, most of that falling to the bottom line. But as prices dropped, purchases would mount and accumulated profits would rise on the model of all capitalist growth.

 

Google, however, was not a conventional company. It made the fateful and audacious decision to make all its content and information available free: in economic terms, a commons, available to all, in the spirit of the Internet pioneer Stewart Brand, whose slogan was “Information wants to be free.”

 

Brin and Page were children of the American academy, where success is measured less in money than in prestige: summers of graceful leisure and research, and above all, tenure (America’s answer to a seat in the House of Lords).

 

The denizens of the academy covet the assurance that whenever they venture beyond their hallowed halls, they are always deemed the “brightest guys in the room.” Google culture is obsessed with academic grades, test scores, degrees, and other credentials.

 

The Google philosophy smacks of disdain for the money-grubbing of bourgeois society. As the former engineering director, Alan Eustace, puts it, “I look at people here as missionaries, not mercenaries.” Google doesn’t sweat to supply goods and services for cash and credit. It provides information, art, knowledge, culture, enlightenment, all for no charge.

 

Yet, as everyone now knows, this apparently sacrificial strategy has not prevented Google from becoming one the world’s most valuable companies. Still in first place as of this writing is Apple, twenty years older, riding on the crest of the worldwide market for its coveted iPhones, but Google is aiming for the top spot with its free strategy.

 

In 2006, it purchased Android, an open source operating system that is endowing companies around the globe, including itself, with the ability to compete with the iPhone.

 

Apple is an old-style company, charging handsomely for everything it offers. Its CEO, Tim Cook, recall, is the author of the trenchant insight that “if the service is ‘free,’ you are not the customer but the product.” Apple stores make ten times more per square foot than any other retailer.

 

If the market turns against its products, if Samsung or Xiaomi or LG or Lenovo or Techno or Zopo or whatever Asian knockoff pops up in the market fueled by Google at an impossibly low price, Apple may slip rapidly down the list.

 

Google’s success seems uncanny. Its new holding company, Alphabet, is worth nearly $800 billion, only about $100 billion less than Apple. How do you get rich by giving things away? Google does it through one of the most ingenious technical schemes in the history of commerce.

 

Page’s and Brin’s crucial insight was that the existing advertising system, epitomized by Madison Avenue, was linked to the old information economy, led by television, which Google would overthrow.

 

The overthrow of TV by computers was the theme of my book Life after Television. If Google could succeed in its plan to “organize the world’s information” and make it available, the existing advertising regime could be displaced.

 

Brin and Page began with the idea of producing a search engine maintained by a nonprofit university, operated beyond the corruption of commerce. They explained their view of advertising in their 1998 paper introducing their search engine:

 

Currently, the predominant business model for commercial search engines is advertising. . . . We expect that commercial search engines will be inherently biased towards the advertisers and away from the needs of the consumers. . . .

 

In general, it could be argued from the consumer point of view that the better the search engine is, the fewer advertisements will be needed for the consumer to find what they want. This, of course, erodes the advertising-supported business model of the existing search engines. . . .

 

[W]e believe the issue of advertising causes enough mixed incentives that it is crucial to have a competitive search engine that is transparent and in the academic realm.

 

Steven Levy’s definitive book on Google describes the situation as Google developed its ad strategy in 1999: “At the time the dominant forms of advertising on the web were intrusive, annoying and sometimes insulting.

 

Most common was the banner ad, a distracting color rectangle that would often flash like a burlesque marquee. Other ads hijacked your screen.”

 

The genius of Google was to invent a search advertising model that avoids all the pitfalls it ascribes to existing practices and establishes a new economic model for its system of the world. Google understands that most advertising most of the time is value-subtracted.

 

That is, to the viewers, ads are overwhelmingly minuses or even mines. The digital world has accordingly responded with ad-blockers, ad-filters, mutes, Tivos, ad-voids, and other devices to help viewers escape the minuses, the covert exactions, that pay for their free content.

 

Google led the world in grasping that this model is not only unsustainable but also unnecessary.

 

Brin and Page saw that the information conferred by the pattern of searches was precisely the information needed to determine what ads viewers were likely to welcome. From its search results, it could produce ads that the viewer wanted to see. Thus it transformed the ad business for good.

 

According to Levy, Google concluded that “the advertisement should not be a two-way transaction between publisher and advertiser but a three-way transaction including the user.”

 

But in practice, following its rule “to focus on the user and all else will follow,” Google made it a one-way appeal to the user.

 

Google understood that unless the user actually wanted the ad, it would not serve the advertiser either and would therefore ultimately threaten the advertising intermediaries as well.

 

In terms of Life after Television, the promise of the Internet under Google’s scheme would be that “no one would have to read or see any unwanted ads.”

 

Ads would be sought, not fought. To accomplish this goal, Google designated its ads as “sponsored links” and charged only for successful appeals measured by click-throughs.

 

They used the same measure to calculate an ad’s effectiveness and quality, forcing advertisers to improve their ads by removing those that did not generate enough click-throughs.

 

Levy tells the revealing story of the launch of Google Analytics, a “barometer of the world” for analyzing every ad, its click-through rate, its associated purchases, and its quality.

 

Analytics uses a “dashboard,” a kind of Google Bloomberg Terminal, that monitors the queries, the yields, the number of advertisers, the number of keywords they bid on, the return on investment of every advertiser.

 

Google initially planned to charge five hundred dollars per month for the service, with a discount for AdWords customers.

 

But as Google discovered, billing and collecting are hard. They raise questions of security and legal liability and put the seller in a less-than-amicable relationship with its customers.

 

It is easier and cooler altogether just to give things away. An easy-to-use source of instant statistics on websites and advertising performance would readily pay for itself.

 

Showing the superiority of Google ads and spurring purchases of them, Google Analytics was offered for free. It soon brought in at least $10 billion a year in additional ad revenue.

 

Google’s new free economic model has penetrated even its corporate lunch rooms, the company has made the remarkable discovery that a cafeteria can be far more efficient if it does not bother to charge its patrons. At first, Google set up a system of terminals to collect money from its employees for their food.

 

The system itself costs money, and it led to queues of valuable Google engineers wasting company time as they waited to pay.

 

The cheaper and easier and altogether trans-capitalistically cooler was simply giving away the food. The company now serves more than 100,000 meals a day at no charge. And so it goes, through almost the entire portfolio of Google products.

 

In 2009, the Stanford philosopher Fred Turner published a paper titled “Burning Man at Google: A Cultural Infrastructure for New Media Production,” in which he unveiled the religious movement behind Google’s system of the world.

 

An annual weeklong gathering at Black Rock in the Nevada desert, Burning Man climaxes with a kind of potlatch. While some thirty thousand ecstatic nerds, some of them half-naked, dance and ululate below, techno-priests ignite a forty-foot genderless wooden statue together with a temple in the sand full of vatic testimonies.

 

Like Google, Burning Man might be termed a commons cult: a communitarian religious movement that celebrates giving—free offerings with no expectation of return—as the moral center of an ideal economy of missionaries rather than mercenaries.

 

It conveys the superiority of “don’t be evil” Google, in contrast to what Silicon Valley regards as the sinister history of Microsoft in the North.

 

But Brin and Page see no contradiction between Burning Man’s ethos and Google’s. They attend Burning Man often, as does Eric Schmidt, whose hiring was allegedly eased by the knowledge that he was a fellow devotee.

 

Google’s headquarters, Building 43 in Mountain View, is often decorated with photographs of the desert rites. The first Google logo bore a burning man stick figure.

 

Focus on the user and all else will follow. (Google’s “gifts” to the user bring freely granted personal information, mounting to the revelatory scale of Big Data.)

 

You can make money without doing evil. (Academic preening that implies that “the greatest wealth is based on a great crime.” If fast and free covers a multitude of sins, Google is proud to compensate by running its data centers with a net-zero carbon footprint through solar and windmill offsets.)

 

  • There is always more information out there. (Big Data faces no diminishing returns to scale.)
  • The need for information crosses all borders. (We are citizens of the world and Google Translate gives us a worldwide edge.)

 

  • You can be serious without a suit. (Denim disguise and denial for the supreme wealth and privilege of Silicon Valley; no stuffed suits need to apply.)
  • Great just isn’t good enough. (We are casually great.)

 

As Scott Cleland and Ira Brodsky point out in their swashbuckling and passionate diatribe against Google, Search & Destroy, there is one supreme omission in this list of high-minded concerns.

 

Nowhere is there any mention of the need for security. As they point out, Google discusses security on a separate page, and its chirpy PR tone is not reassuring: “We’ve learned that when security is done right, it’s done as a community.

 

This includes everybody: the people who use Google services (thank you all!), the software developers who make our applications, and the external security enthusiasts who keep us on our toes. These combined efforts go a long way in making the Internet safer and more secure.”

 

In other words, “It takes a village.” Security is at the heart of the problems of the Net, and in this case, Google is a source of problems rather than answers.

 

End of the Free World

Free World

The Google world is a bounteous and providential kingdom. But it is still based on mediation through advertising at a time when many forms of advertising are in a slow but discernible death spiral.

 

As Jerry Bowyer writes in Forbes, “If advertising dies [as support for media], then what we call media dies too.

 

The whole system which started with newspapers moved on to the radio, then TV, and the various forms of blogging and streaming is basically the same business model: Gather a bunch of people together who think they’re there for one thing, but are really there for something else.”

 

It’s a bait and switch, and no one likes it. Despite all its heroic advances, Google still gets no less than 95 percent of its revenue from ads tied to its search engine.

 

For aggregating audiences and eyeballs, nothing works so well as giving services away for “free.” Sergey Brin asked the crucial question early in Google’s history: “How does the strategy change if the price is zero?”

 

The answer turned out to be: “We win the entire market.” In 2014, Google summoned Jeremy Rifkin to its lecture series to sum it all up. He heralded a “zero marginal cost society.”

 

Under the new regime, the price of every incremental good and service, from search to software, from news to energy, will plunge toward “free” as every device and entity in the world is subsumed in an Internet of Things, where exponential network effects yield a new economy of leisure and abundance.

 

Rifkin assured his audience that it is indeed a Google world.

But not only is “free” a lie, as we’ve seen, but a price of zero signifies a return to the barter system, a morass of incommensurable exchanges that the human race left behind in the Stone Age. You pay not with money but with your attention.

 

Above all, you pay in time. Time is what money measures and represents— what remains scarce when all else becomes abundant in the “zero marginal cost” economy. Money signals the real scarcities of the world concealed in the false infinities of free.

 

Larry Page’s burning ambition in starting Google, according to Doug Edwards, “Google Employee Number 59,” was to “stop the world wasting his time.”

 

He may well have succeeded by now, save for the occasional subpoena from an officious regulator somewhere.

 

But for the rest of us, all the free stuff leads to transactional tricks and traps: offers of only rarely desired subscriptions automatically renewable, spurious prizes, bonuses, and jackpots, with new pop-up or pop-under perils at every step.

 

It’s the “Free World,” and it is reaching past your wallet, spurning your earned money, to seize your time—which is actually your life.

 

While I was researching the economic effects of Google’s preoccupation with “free” goods, Jonathan Taplin revealed in Move Fast and Break Things that Google owns five of the top six multibillion-user Web platforms and thirteen of the top fourteen commercial functions of the Net, and yet it collects less than 5 percent of its revenue from final customers.

 

Beyond the suppliers of ads that no one wishes to see, Google’s main role is intermediator. Although Google’s list of business principles leads off with “The customer comes first,” Google has few end customers at all.

 

Beyond the coddled purchasers of its ads, Google’s customer base is tiny compared with Amazon’s, which unlike Google was never shy about collecting money.

 

Since the iPhone is the source of some 75 percent of all Google’s mobile ad revenues, Apple’s move struck at the heart of Google’s mobile strategy. Beyond its free, open source, “sharing-economy” Android platform, Google’s response did not arrive until a year later. Then it chose deceptively to copy Apple.

 

Google’s industry-leading advertising Analytics tools apparently revealed that its users liked the idea of blocking ads. Customers come first, so in its Chrome browser, Google introduced its own ad-blocker. Google’s angle was that its blocker would apply only to ads condemned by the Coalition for Better Ads.

 

In other words, since Google’s ads were famously discreet and camouflaged, it announced it would block the ads of flagrant, garish, or slaphappy rivals. James speculates that this action might be illegal for a search engine.

 

As James recognizes, for the online unwanted ads industry, ad-blocking is ultimately suicidal. Between 2015 and 2016, he reported, ad-blocking rose 102 percent, with 16 percent of smartphone users globally using the technology.

 

In the United States—the source of 47 percent of Google’s revenues—25 percent of desktop and laptop users were auto-deleting commercials.

 

Leading this movement were youthful cohorts coveted by advertisers. As James notes with some relish, only 0.06 percent of smartphone ads were clicked through. Since more than 50 percent of the clicks were by mistake, according to the surveys, the intentional response rate was 0.03 percent.

 

Acceptable chiefly for spammers, this result cannot be part of Google’s plan.

At the same time that Google was cagily capitulating to anti-ad sentiment, it was offering its YouTube users a taste of ad-free nirvana, dubbed YouTube Red.

 

A devout YouTuber user, I can attest that it is a revel—a truly lavish offering of “life after television” for $9.95 a month. I am an addict, and I wish that Google were adequately compensating its content suppliers.

 

But it is not. The world’s largest streaming music site, with a 52 percent share, YouTube pays only 13 percent of all music streaming royalties. Google faces intense competition from scores of vendors of streaming video for pay.

 

In this field, Google is just another player, experiencing the slings and arrows of real price discovery.

 

James’s second key point is that while pure info-search is still dominated by Google, commercial search—intentional searches for products to buy—is shifting dramatically to Amazon.

 

By 2017, Amazon had 52 percent of the product-search market, and its gains were accelerating; Google languished at 26 percent.

 

Viewers who wanted to buy something were beginning their searches with Amazon. The Seattle giant could actually sell it to them—with one click, no less—rather than leading them to the product with an ad followed by a rigmarole of passwords, usernames, CAPTCHAs, EULAs, and credit card bumf.

 

Amazon’s reviews, spurious though many presumably are, are simply more trusted than Google’s paid ads and intermediations. Why not?

 

This success followed Amazon’s coup in cloud services. Although Google by all measures commanded the world’s leading cloud deployment, somehow Amazon defeated them in marketing cloud services by 57 percent to 16 percent as of 2017. This advance in collecting money from real customers must have been baffling to Google.

 

It fought back, as it normally does, with a stream of YouTube speeches and technical presentations demonstrating the superiority of Google’s cloud offerings, its global SQL reach.

 

Its facile user interfaces, its instant responses, its MapReduce, Hadoop, and “Spanner” big-database schemes, its massive fiber deployments and world-spanning data centers, its idealism, its tech conference éclat.

 

But somehow when people had to choose a cloud service, they were turning not to Google but to Amazon Web Services. Who would have to thunk it?

 

Google, meanwhile, under its new CEO, Sundar Pichai, pivoted away from its highly publicized “mobile first” mantra, which had led to its acquisitions of Android and Ad Mob, and toward “AI first.” Google was the recognized intellectual leader of the industry, and its AI ostentation was widely acclaimed.

 

Indeed it signed up most of the world’s AI celebrities, including its spearheads of “deep learning” prowess, from Geoffrey Hinton and Andrew Ng to Jeff Dean, the beleaguered Anthony Levandowski, and Demis Hassabis of DeepMind.

 

If Google had been a university, it would have utterly outshone all others in AI talent. It must have been discouraging, then, to find that Amazon had shrewdly captured much of the market for AI services with its 2014 Alexa and Echo projects.

 

It launched actual hardware to bring AI to everyone’s household in the form of elegantly designed devices that answered questions and ordered products while eschewing ads.

 

Amazon’s edge, once again, was attributable to it's not fearing customers. Google had applied its AI tools to the unseen back end, where it targeted ads and analyzed responses to them. It took a full two years to respond with household devices that copied Amazon’s. But there was a deeper problem.

 

Both Google’s mobile-first strategy and Amazon’s Alexa turned the industry toward voice-accessed AI. Voice access largely nullifies Google’s search-ad dominance.

 

Barking voice ads into a search stream differs radically from inserting decorous text amid thousands of responses to a textual search request. This was a retrograde strategy harking back to the world of radio in its death spiral.

 

Here more and more ads were needed to prop up a dwindling supply of content, and the chief winners were charismatic un-Googly talkers, such as Rush Limbaugh.

 

Now Google Assistant is winning plaudits as the best of the speech recognizers, and LG has enlisted it for all ninety of its home appliances.

 

A pioneering voice in the Internet of Things, Google and LG envisage people confiding their inner ids and desires to their washing machines, ovens, refrigerators, gas ranges, heating-and-air-conditioning systems, dishwashers, and lighting panels. No longer will Google be restricted to data about online purchases.

 

When Amazon’s Whole Foods loads up the refrigerator, Google will know. It hopes to use these data to enrich its advertising systems and escape the problems of voice ads in the Google Assistant stream.

 

But if people don’t want ads in their search results, YouTube videos, and news streams, they don't want them in their dishwashers either.

 

The most important effect of free, though, is not avoidance of liabilities to real customers. It is an escape from the challenges of security. Who wants to steal free goods? If the vast bulk of your product line is free, you avoid many of the real-time demands of preventing hacks and thefts.

 

You rarely have to establish a ground state and defend it. Indeed, in a stream of free goods, the chief hacker is Google and its insidious ad-insert hocus pocus. Google can post cavalier assurances on its websites that place the burden of security on the customers.

 

“If you see something say something,” implies Google, echoing the TSA’s feel-good strategy, chiefly designed to shift the responsibility to the “customers.”

 

This very lack of concern with security, however, will be Google’s undoing. For every other player on the Net, the lack of security is the most relevant threat to its current business model.

 

The problem will be solved. Some thousands of companies you’ve never heard of are investing billions right now in that effort.

 

Collectively they will give birth to a new network whose most powerful architectural imperative will be the security of transactions as a property of the system rather than an afterthought. So fundamental will security be to this new system that its very name will be derived from it. It will be the cryptocosm.

 

Google’s Datacenter Coup

Google’s Datacenter Coup

The data center itself is wrapped in secrecy, with gates to keep out employees who do not have the correct clearance and airport-style millimeter-wave whole-body scanners for everyone entering the heart of the warehouse.

 

To handle the floods of bits and bytes, each of the three ten-million-cubic-foot glass-walled warehouses of Google’s Dalles fortress now holds 75,000 computer servers, interlinked with fiber-optic lines, arrayed in towering racks.

 

These servers, jammed as close together as possible to minimize speed-of-light delays, look like glowing horizontal books shelved in the stacks of a huge futuristic library.

 

Moore’s Law, which describes the growth in capacity of integrated circuits, has a corollary named after Gordon Bell, the legendary engineer behind Digital Equipment Corporation’s breakthrough VAX line of minicomputers of the 1980s and now a principal researcher at Microsoft.

 

According to Bell’s Law, every decade a hundredfold drop in the price of processing power engenders a new computer architecture. Just last century—you remember it well, across the chasm of two economic crashes—the PC was king.

 

Deposed and deceased was the lordly computer mainframe, which had sustained the dominance of IBM in information technology in the 1970s and the Digital Equipment and Data General minicomputers and their client-server systems of the 1980s.

 

Google’s cloud defines the current Bell’s Law regime. But as recently as the late 1990s, Larry Page and Sergey Brin were nonprofit googoos working in the Gates Center at Stanford seeking to search their 150-gigabyte index of the Internet.

 

At the time, when I wanted to electrify crowds with my uncanny sense of the future, I would talk terascale (10 to the twelfth power), describing a Web with an unimaginably enormous total of 15 trillion bytes of content.

 

The Google worldwide warehouse arises from this once futuristic terabyte paradigm, but its operating environment is now the peta-scale—petabytes, pet apps, petaflops. “Peta” means a quadrillion (that is, 10 to the fifteenth power, a million billion) but also, by felicitous coincidence, evokes before, the Latin verb “to search.”

 

Today Google reigns over a database of thousands of petabytes, called exabytes, swelled every twenty-four hours by scores of terabytes of Gmails, Facebook pages, presidential twitter feeds, and videos—a relentless march of daily deltas, each larger than the whole Web of a decade ago.

 

Google handles a billion YouTube videos and 3.5 billion searches every day and 1.5 trillion searches per year. Doubling annually, its internal bandwidth was up fifty times in six years through 2014 and is expected to expand another tenfold through 2018.

 

According to Google’s operations chief, Hölzle, that number will surge another tenfold within another two years.

 

This insight I dubbed Schmidt’s Law. Schmidt was not just a midnight email doodler. He soon left Sun and, after a stint as CEO of Novell trying to build the best networks and search engines in Utah, he joined Google and soon became CEO. There he found himself engulfed by the future he had predicted.

 

While competitors like Excite, Inktomi, AltaVista (DEC), and Yahoo were building out their networks with SPARCstations and IBM mainframes, Google designed and manufactured its own servers from cheap commodity components made by microprocessor star Intel and hard-drive king Seagate.

 

The continuing explosion of hard disk storage capacity makes Moore’s Law look like a cockroach race. In 1981, a gigabyte drive cost $500,000, and an Intel 286 processor ran at six megahertz and cost $360.

 

In 2018, a gigabyte costs less than two cents and a three-gigahertz processor costs roughly three thousand dollars.

 

In constant dollars, the price of processing has dropped some five hundredfold, while the price of a hard drive has dropped 250,000 times. By this crude metric, the cost-effectiveness of hard drives grew five hundred times faster than that of processors.

 

You would think that the cost-conscious folks at Google would have filled their warehouses with hard drives. But the miraculous advance of disk storage concealed a problem:

 

The larger and denser the individual disks, the longer it takes to scan them for information. The little arm reading the disks can’t move fast enough to keep up with the processor.

 

Google’s solution was to deploy huge amounts of fast random access memory chips.

 

By the byte, RAM is some one hundred times more costly than disk storage. Engineers normally conserve it obsessively, using all kinds of tricks to fool processors into treating disk drives as though they were RAM. But Google understands that the most precious resource is not money but time.

 

Search-users, it turns out, are sorely impatient. Research shows that they’re satisfied with results delivered within a twentieth of a second.

 

RAM can be accessed some ten thousand times faster than disks. Measured by access time, then, RAM is one hundred times cheaper than disk storage. So Google has long led the world in the use of RAM.

 

It’s not enough to reach users quickly. Google needs to reach them wherever they are. This requires access to the Net backbone, the long-haul fiber-optic lines that encircle the globe.

 

Google interconnects its hundreds of thousands of processors with hundred-gigabit-per-second Ethernet lines, now moving up to four hundred gigabits. Placing gigantic data centers near major fiber-optic nodes is well worth the expense.

 

Wasting what is abundant to conserve what is scarce, the G-men have become the supreme entrepreneurs of the new millennium. It is the Google era. But hovering over the massively parallel, prodigally productive petascale computer like a midday emanation over Death Valley is a shimmering haze of heat.

 

For now, though, Google has attained one of the holy grails of computer science: a scalable massively parallel architecture that can accommodate diverse software while poring through petabytes of big data. Its petascale search machine in place, Google then faced the question:

 

What else could it do? Google’s answer: just about anything. Thus the company’s expanding portfolio of Web services: delivering ads (AdSense, AdWords), maps (Google Maps), videos (YouTube), scheduling (Google Calendar), documents (Google Docs), transactions (Google Checkout), translations (Google Translate), email (Gmail), and productivity software (Writely), to name a few. The other heavyweights have tried to follow suit.

 

Our CPUs—those of our PCs, amplified by millions of smartphones—are both more powerful and less employed than ever. Google and the others suck into their proprietary clouds more and more of the duties once delegated to the CPU.

 

Optical networks, which move data over vast distances without degradation, allowing computing to migrate to wherever power is cheapest. The new computing architecture thus scales across the earth’s surface.

 

As I write in 2018, what is called the “cross-section bandwidth” of the internal networks spanning Google’s data centers has reached petabytes per second—a multiple of the total bandwidth of the entire Internet that Google searches and sorts, mines and monetizes. And it will never be enough.

 

The Googleplex at the center of the sphere will soon dwarf the Internet itself. Introducing Google’s networking technology leader, Amin Vahdat, in October 2015.

 

The magazine of the Association for Computing Machinery declared, “Everything about Google is at scale, of course—a market cap of legendary proportions.

 

An unrivaled talent pool, enough intellectual property to keep armies of attorneys in Guccis for life, and—oh yeah—a private Wide Area Network (WAN) bigger than you can imagine that also happens to grow faster than the Internet.”

 

Dally’s Parallel Paradigm

In the Tesla’s front seat, I face a two-foot-high screen displaying pale green and striated Google maps. Dally points out that self-driving vehicles “don’t care where the road lanes are.

 

They navigate on maps, register their place on a map. If they have an empty road, they just take a line down the middle, like they are riding a rail. It is only the presence of moving objects, such as pedestrians and other cars, that requires them to use all their motion-sensing capabilities.”

 

While the maps come from Google, the processing comes from Nvidia GPUs. These chips compute the car’s response to lidar, radar, ultrasound, and camera signals that free the missile to descend from the outer space of Elon Musk’s domains and enter the ever-changing high-entropy world beyond Google Maps.

 

Dally barks his command: “Navigate to California Avenue Caltrain station,” and the car crisply responds. Dally comments, “In the last couple years speech recognition has become dramatically better.

 

Thirty-percent better. Two years ago it was not really capable of getting it right. But now with machine learning on our Tegra chips, it gets it right every time.” Benefiting are all the users of Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, Google’s Go.

 

Dally has his hands on the steering wheel now as he negotiates the back streets. “It’s only level-two autonomy,” he explains, using the Society of Auto Engineers’ classifications, which range from level one, a mere driver assistant, to level five, full self-driving. Musk promises to get Tesla to level five in two years. That’s Elon for you.

 

But for now, Dally keeps his eye on the road as the Tesla makes its way, with several high-voltage bursts, up the ramp onto 101. Now Tesla’s self-driving mode enables him to turn and show me his film of the recent solar eclipse—a series of vivid high-contrast images of the rare event.

 

Machine learning, Dally points out, is mostly accomplished by graphics processing chips from Nvidia. Some advances in artificial intelligence spring from improvements in algorithms.

 

But the real source of these capabilities is the explosive improvement in computer speed achieved through a combination of Moore’s Law and parallel processing.

 

Nvidia’s graphics processors are the climax of Dally’s long career as a prophet of parallel processing, which began thirty years ago at Virginia Tech, where he studied the virtues of multiple processors functioning together.

 

As recently as 2012, Google was still struggling with the difference between dogs and cats. YouTube was famous for its cat videos, but it could not effectively teach its machines to recognize the cats.

 

They could count them; the data center dogs could dance, but it took sixteen thousand microprocessor cores and six hundred kilowatts.

 

And it still was a dog, with a 5 percent error rate—not an impressive portent for Google’s human face-recognition project or for car vision systems that need flawlessly to identify remote objects in real time. sit in the bank at near-zero interest rates while its vast data centers still could not identify cats, as well as a three-year-old, could.

 

Thiel is the leading critic of Silicon Valley’s prevailing philosophy of “inevitable” innovation. Page, on the other hand, is a machine-learning maximalist who believes that silicon will soon outperform human beings, however, you want to define the difference.

 

If the haphazard Turing machine of evolution could produce human brains, just imagine what could be accomplished by Google’s constellation of eminent academics devoting entire data centers full of multi-gigahertz silicon to training machines on petabytes of data. In 2012, though, the results seemed underwhelming.

 

Simultaneously with the dogs and cats crisis in 2012, the leader of the Google Brain research team, Jeff Dean, raised the stakes by telling Urs Hölzle, Google’s data center dynamo, “We need another Google.”

 

Dean meant that Google would have to double the capacity of its data centers just to accommodate new demand for its Google Now speech recognition services on Android smartphones.

 

Late in the year, Bill Dally provided an answer. Over breakfast at Dally’s favorite Palo Alto café, his Stanford colleague Andrew Ng, who worked with Dean at Google Brain, was complaining about the naming of cats.

 

Sixteen thousand costly microprocessor cores seemed inefficient. Dally suggested that Nvidia GPUs could help.

 

Graphics processors specialize in the matrix multiplication and floating-point mathematical operations that teach machines to recognize patterns.

 

A graphical image is an array of values readily mapped to a mathematical matrix. Running images through as many as twelve layers of matrices, machine learning could be seen as another form of iterative graphics processing.

 

Prove it, Ng told Dally, and Google would buy his chips.

 

Google now deploys ten-to-twelve-layer neural networks generating thirty exaflops of floating point mathematical computing capacity—and matrix multiplications galore.

 

In accord with Rosenblatt’s prediction that the “more images the perceptron is permitted to scan, the more adroit its generalizations,” the Google machine sorts tens of millions of images according to someone billion parameters.

 

It prompts Google Brain routinely to claim to be “outperforming humans.” Gee, a billion parameters, beats me! In Silicon Valley, where human beings program these machines, it is considered cranky to question the claim of “superhuman” powers.

 

None of this would faze Dally, except for one crucial change at Google. At the 2017 Hot Chips conference, the company, in a do-it-yourself mood, indicated that it would henceforth replace Nvidia’s devices with its own special-purpose silicon.

 

Jeff Dean celebrated Jouppi’s souped-up “Tensor” “matrix multiplier,” which eschewed graphics and floating point, focusing on the machine learning functions alone.

 

It’s a matrix multiplier ASIC (application-specific integrated circuit). Without their Tensor processing unit, say the Google guys, they would have had to double the size of their data centers.

 

Dally points out that it is always possible to make huge temporary gains by putting entire systems onto single slivers of ASIC silicon, special-purpose chips hard-wired to perform one complex function.

 

As Dally tells me, in performing parallel operations, graphics processors are ten times more cost-effective than general-purpose central processing units (CPUs), and ASICs are ten to a hundred times more cost-effective than ordinary GPUs.

 

But with ASICs, your market is reduced to just your chosen special purposes, and your data centers are no longer all-purpose Turing machines. They are ossifying into special-purpose factories like the aluminum plants they succeeded in The Dalles.

 

Google can afford to make its own custom ASICs for particular slots in its data centers, but Nvidia is dominating the entire domain of massively parallel processing.

 

In the third quarter of 2017, after the Hot Chips “setbacks,” Nvidia announced a 109 percent increase in revenues from cloud computing sales, to $830 million, lifting the company’s market value to almost $130 billion.

 

Now Nvidia is a potent force providing parallel processors across global industry and providing new platforms for life after Google. Is all this to come to an end with Google’s new prowess in making hardware as well as software, hiring industry hardware titans such as Dave Patterson and Norm Jouppi to contrive world-leading chip architectures?

 

I was visiting Dally to find out. A fifty-seven-year-old, brown-haired engineer with a black hat and backpack and hiking boots.

 

He is dressed Silicon-Valley-mountaineer style to take me on a high-altitude adventure in microchips and software, ideas and speculations, Google maps and Elon Musk “reality distortion fields” down Route 101 at five o’clock on a late-August Friday evening.

 

In the age of Big Data, the von Neumann bottleneck has philosophical implications. The more knowledge that is put into a von Neumann machine, the bigger and more crowded its memory, the further away from its average data address, and the slower it's functioning.

 

Danny Hillis, of the erstwhile Thinking Machines, writes, “This inefficiency remains no matter how fast we make the processor because the length of the computation becomes dominated by the time required to move data between processor and memory.”

 

That span, traveled in every step in the computation, is governed by the speed of light, which on a chip is around nine inches a nanosecond—a significant delay on chips that now bear as much as sixty miles of tiny wires.

 

What Dally saw is that the serial computer has reached the end of the line. Most computers (smartphones and tablets and laptops and even self-driving cars) are not plugged into the wall anymore.

 

Even supercomputers and data centers suffer from power constraints, manifested in the problems of cooling the machines, whether by giant fans and air conditioners or by sites near rivers or glaciers.

 

As Hölzle comments, “By classic definitions, there is little ‘work’ produced by a data center since most of the energy is converted to heat.”

 

Taking Back the Net

Syndicate could use storage facilities like Google Drive, Amazon’s S3, and Microsoft Azure as utilities by storing pointers and ID in the blockchain, with the data’s owners retaining control.

 

Nelson and Ali felt a surge of excitement about blockchain technology. Ali described it as “the most sophisticated and complex and yet elegant and beautiful program I ever came across. And the main thing it does is it gives power back to the people.”

 

He joined Nelson working on Syndicate, and two years later Nelson came to work for him in Manhattan at Blockstack, then called “OneName,” which Ali and Shea, on leave from Princeton, had started in 2013.

 

“Apps were not responsive to customers so much as designed to lock them in,” says Shea.

 

 “You go onto the net and Facebook or Google or Dropbox or Pinterest or Amazon and all want you to move in, giving them all your documents, music, providing storage for your life. Medical sites want to store all your health data.

 

You have to petition to get it when you want it”—when you need to move to a new provider, for example.

 

The Blockstack team wanted to reestablish the network on reliable, low-entropy foundations. Ali explains: “Decentralized identity systems enable users to control a unique identity recorded on the blockchain that can be recognized by any site.”

 

He contrasts this universal ID with the current “username and password combo that can only be recognized by the site that had you create an account.” With the blockchain, users can log in to the websites by automatically proving ownership of their identity.

 

Ali and Shea wanted to address the problem at a more fundamental level by developing a new secure protocol layer for the Internet by which the identification, money, power, and property could stay with their own rather than be sucked up to the apps at the top.

 

“I was impressed with Peter Thiel’s perspective,” says Shea. “Why would you want to compete with some existing company, be incrementally more efficient, and make the world only a slightly better place?”

 

In 2014, they took a $250,000 investment and moved out to Y-Combinator in Mountain View, California, for a stint and demo. Started by the entrepreneur Paul Graham, YC was a kind of reverse Hotel California for nerds—hard to get into and easy to leave.

 

Thiel told the Y-Combinator in 2015 to seek “apparently bad ideas” that “were actually good,” like Dropbox (cloud-based storage) and Airbnb (cloud-based lodgings). Both began nebulously at YC and now have a total market cap of many billions of dollars.

 

On July 27, 2017, I traveled west to see how the Blockstack people were doing and perhaps help them with a speech. Although still based in New York, Blockstack chose the Computer Museum in Mountain View, minutes from the Google campus, for its coming-out party: the Blockstack Summit 2017.

 

Its marketing chief, Patrick Stanley, asked me to speak on “Life after Google.”

 

A little more than two weeks before, Ali’s doctoral committee at Princeton had finally approved his dissertation, “Trust-to-Trust Design of a New Internet.”

 

Composed with Shea’s help, it was comparable in its scope and ambition to Larry Page’s “PageRank” thesis at Stanford.

 

Ali makes the case for a new Internet architecture and then declares that, in prototype, it has already been in place for three years, requiring only 44,344 lines of Python software language code. Google’s famously elegant Chrome browser, by comparison, took up 4,490,488 lines of mostly C++ language code.

 

The chief technical officer of Blockstack, Ali has created a new parallel peer-to-peer Internet. You can go to its site and download its browser and experience the benefits of a secure Internet where you control your own information.

 

A leaner and more constrained approach distinguishes Blockstack from Ethereum. Ryan Shea, the CEO, sums it up: “We are going for a much simpler system than Ethereum.

 

With a larger attack surface, more things can go wrong. We are using blockchain and software for the core functions of naming, the discovery of routing information, and payments. . . . [C]ore components like identity and discovery should not be done in a way that exposes a large attack surface.”

 

The Blockstack movement is founded on seven key principles:

 

Distributed cadastre: It assures security through logical centralization (maintaining only a single transparent and immutable view of its “state” of time-stamped records) while being organizationally decentralized (distributing control and replicating ledger accounts across all the nodes of the network).

 

Satoshi’s blockchain is the first embodiment of these two apparently contradictory concepts, which evoke the medieval concept of the cadastre, a public record of all real property in a jurisdiction.

 

Maximum scalability: It assures performance and scalability by separating the control plane (insulated in the blockchain) from the data plane, which can be dispersed across the network.

 

This principle saves the blockchain for critical path functions of identity, payments, security, and discovery while relegating bulk data storage and complex processing to any number of diverse cloud and edge facilities.

 

Single prototype: It establishes property rights by upholding the principle and precedence of singular documents, time-stamped, recorded, and algorithmically allocated. Because each item—even copies—always bears different immutable time-stamps, property claims can always be differentiated.

 

Parallel complement: Its expansion confers benefits of privacy and property on its participants without directly threatening incumbents, whose facilities are used by the system as a utility. As the Blockstack realm grows, its influence and power will rise, and incumbents will be motivated to accommodate it.

 

Low-entropy carrier: It provides a stable, predictable, and monolithic foundation for the high-entropy metaverse on the edge. It avoids capricious changes of law and structure that confuse entrepreneurial planning on the edges and cause security problems.

 

Free migration: It allows unobstructed passage from one blockchain or network to another without locking in users. This crucial feature is enabled by Jude Nelson’s coding for virtual chains, which run on top of the fundamental blockchain as Java Virtual Machines run on top of many operating systems.

 

End-to-end, trust-to-trust: All nodes rest on roots of trust that are not heavily dependent on outside authorities.

 

Block stacks initial goal was a domain name service (DNS) installed in a blockchain. Translating natural language names and site titles into Internet address numbers, a DNS participates in your every move on the Net.

 

A DNS constitutes a Trusted Third Party such as Verisign or GoDaddy or, increasingly, Google’s own free public DNS. It has become another case of segmentation of the Net and a point of vulnerability for phishing to usurp names and identities.

 

At the end of 2017, Blockstack launched a token sale to finance the system of distributed names. Raising $50 million, it was on its way, building a new trust, ID, and transactions layer for the Internet.

 

Better than cash, it offers exchanges that conceal personal information but also allow complete proof of compliance where necessary.

 

Not only can you exchange anonymously, you can also prove your record of behavior if a government makes untrue charges or a business makes spurious claims. This combination of security and attestation makes cryptocurrencies a fundamental improvement on existing moneys—a remedy for the monetary turbulence of our time.

 

Brave Return of Brendan Eich

“Hello. I’m to blame for JavaScript.” A slightly pudgy, affable, fifty-five-year-old American computer programmer stands on stage in the gilded Vienna Volkstheater.

 

This is Brendan Eich, the co-founder of Mozilla and the inventor of the Firefox browser, starting his 2016 TEDx talk “How to Fix the Web.” He bows, with his hands on his head miming his embarrassment.

 

The young Eich wrote JavaScript in ten days in 1995 as a prototype for Netscape; its name reflected the fame of the better-known Java, developed earlier at Sun by James Gosling and promoted into an industry standard by Eric Schmidt.

 

Eich’s JavaScript soon eclipsed Sun’s Java as the most widely used computer language in the world.

 

For years, Eich, like his programming language, went from strength to strength. By 2014, he had risen to be CEO of the Mozilla Foundation, with an office next to the Googleplex in Mountain View. Eich had turned fifty by then and already seemed to view his career as wrapping up.

 

With characteristic self-depreciation, he had written in his blog the previous year, “Mozilla is 15. JavaScript is nearly 18. I am old. Lately I mostly just make rain and name things. . . . Doesn’t make up for not getting to name JavaScript.”

 

These crypto-token sales, known as “initial coin offerings” (ICOs) are a type of cryptocurrency crowdfunding.

 

In generating these tokens, entrepreneurs have tapped as much as $7 billion in new capital by essentially pre-selling unbundled components of equity in the guise of products to be developed.

 

Ethereum, as an open-source “virtual machine,” allows end-users to construct specific binding programs, scrupulously assuring compliance with regulations. Thus it has become the preferred token engine.

 

Having already had a fabulously successful token sale, Brendan Eich speaks from the other side of the looking glass. He is one of the few people in the field who seem totally unruffled.

 

And his aim is high. He conceived these “Basic Attention Tokens” to bring down Google. Or at least send Page and Brin back to the drawing board for a new strategy. The mild-mannered Eich will hit them with a billion BATs.

 

Brave’s compendiously cogent and scrupulously documented white paper from March 2017 details this crisis of Internet advertising.

 

The situation is winner-take-all. Ninety-nine percent of the growth goes to Google and Facebook. Publishers—whether of websites, books, games, or music—are left with the final 1 percent.

 

It is fraught with fraud. In 2016, fake ad demand generated by Internet bots cost advertisers some $7.2 billion, with ad malware to trick users rising 132 percent since 2015.

 

The advertising catastrophe is most acute in the fastest-growing and most inviting market in the industry—smartphones. Customers increasingly are paying their bandwidth suppliers not for the content they seek but for the noise of ad delivery overhead. At popular publishers’ sites, as much as 79 percent of the mobile data are ads.

 

On average, smartphone users pay twenty-three dollars per month for ads, trackers, scripts, and other diversionary chaff that bears malware, slows load-times, piles on data-plan costs, depletes battery life, and tramples privacy and property rights.

 

Brave’s Basic Attention Token white paper drills in on Google, which “is at the center of the existing digital advertising ecosystem. They benefit from the complexity and opacity that defines it. BAT intends to empower the very users and publishers that are receiving less than they should.”

 

Regardless of what Google does, says Eich, the current system is unsustainable. It frustrates users with slow loads, wastes bandwidth on unwanted ads, and wipes out publishers’ profits—and it’s not even secure.

 

As Jonathan Kaplan documents relentlessly in Move Fast and Break Things, the Google regime of aggregate and advertise is drastically reducing the income of musicians, journalists, and other producers of the content that Google seeks to monetize with ads and search.

 

The torrent of advertising has provoked some 87.5 million Americans to resort to ad-blockers, which may ultimately bring down the whole kit and caboodle, including Google.

 

The most avid ad-blockers are millennials, whose typically limited bandwidth and high-cost data connections leave their smartphones clogged and jammed by advertising and its overhead.

 

Google, seeing the writing on the wall, now provides its own blocker for “unacceptable ads.” But traditional push-advertising is a failed technology, regardless of “acceptability.”

 

No one wants to sit through an ad, however cleverly or deceptively presented, before watching a YouTube video. As the ad-free subscription service, YouTube Red grows more popular, Google is discovering that no one really wants any gratuitous ads.

 

They are value-subtracted, minuses, or even mines—as Google itself acknowledges when it lets customers pay for their removal by subscribing to ad-free services.

 

Google Search Tips and Tricks

Google Search Tips and Tricks

Throughout this blog, we’ve focused mainly on how to perform searches, interpret the results, and filter those results to find what you’re looking for.

 

Though we’ve used plenty of different examples for those searches, we haven’t focused on specific content short of the broad categories of content, such as videos versus news.

 

However, there are some specific types of information that Google is very good at providing—not just links to sites that have your answer, but to the answers themselves. Also, even though we’ve focused on English-language results in this book, there are ways with Google to expand your search to more than one language for results.

 

In this final blog, we present many of these options and let you know just how to take advantage of them.

 

Google Search Features

Beyond the advanced search features and additional database searches that Google makes available, Google provides many built-in shortcuts via web search, known as “search features.” Below are the vast majority of the ones that were available at the time of this writing.

 

Google Knows Math

Just type in a mathematical formula and you’ll get your answer. Enter a formula that results in a graph and you’ll get the graph too, sometimes in three dimensions.

 

What makes this feature even better is that, as the previous two screenshots show, the results page also presents an on-screen graphing calculator you can use to do additional calculations. If you’d like to get to the calculator without first having to type in a formula, you can just enter calculator in the Google search field.

 

Google Knows Measurements

Just type in a mathematical formula or measurement conversion and you’ll get your answer.

Prior to the summer of 2011, asking Google to make this conversion would have just given you the answer. However, as you can see from our example, you are provided with not only the answer but also the ability to interactively change the type of conversion and the units being converted.

 

we’ve been given the answer that 45 miles are equal to 72.4205 kilometers.

 

But what you also see is that you can enter different numbers on either side of the equation, change the unit type from the drop-down list on either side of the equation, and even change the type of units available to convert from the drop-down list above the equation (which currently states “Length”) to other types of units, ranging from area to volume.

 

As you change numbers or units, the equation shown automatically updates to reflect the new answer. For example, if we change “Mile” to “Yard,” the value for kilometer automatically changes to 0.041148.

 

Google Knows Money

Need a quick currency conversion? Type in the amount and currency, then the new currency. Not only are you presented with the conversion rate, you’re also presented with a graph of the exchange rate over time.

 

Also, as with the unit conversion, there is also an interactive part to currency conversion results. From here you can change the amount in either currency and have the other one update automatically.

 

Google Knows Definitions

Simply type define followed by the word you want to be defined, and you will receive both a definition and also links to additional sites that can provide more information about that word.

 

Google Knows Movies

Search on a movie name or just movie to see theater locations and showtimes in your area. 

 

For each movie, you’ll be presented with the title (hyperlinked to additional information and show locations for that film), the film’s length, rating, and genre, and a link to the trailer.

 

Clicking the “Show more movies” link will extend the list of movies displayed and also give you a “See all movies” link, which takes you to a page with many more details and options for finding where and when your film is showing.

 

To find out when a movie will be in the theaters, search on the movie name with the phrase “release date”. This will also work for video games.

 

For a list of movies that an actor has been in, search on the actor’s name and movies.

 

The top of the results will appear as a side-scrolling list of the movies—with their DVD covers serving as links to a new search on the movie itself—while still maintaining the original list of the actor’ movies above the search results.

 

Speaking of Kevin Bacon, have you ever played Six Degrees of Kevin Bacon?

It’s a game based on the fact that Kevin Bacon has been in so many movies that you can link any actor through their film roles to him within six steps. The result is called the actor’s Bacon Number.

 

In 2012, Google added the Bacon Number search tool—search for an actor with the phrase “Bacon Number” and it will automatically calculate the actor’s number, showing you the connections between them and Kevin Bacon.

 

Google Knows Music

As with actors and movies, for a list of albums that a band or musician has released, search on the band’s or musician’s name and albums.

 

The top of the results will appear as a side-scrolling list of the albums, with their covers serving as links to a new search on the album itself—again, while still maintaining the original list of the band’s albums above the search results.

 

Google Knows Authors

And of course, for a list of books that an author has written, search on the author’s name and books. The top of the results will appear as a side-scrolling list of the books, with their covers serving as links to a new search on the book itself, while still maintaining the original list of the author’s books above the search results.

 

Google Knows Flights

View live arrival and departure information for U.S. flights just by searching the name of the airline and the flight number. To see flight schedules to or from a particular destination, type “flights from” or “flights to” followed by the city or airport of interest.

 

Google Knows Numbers

Google can automatically recognize several types of numbers. These include UPS (United Parcel Service), FedEx, and USPS (United States Postal Service) tracking numbers, as well as VINs (vehicle identification numbers) and UPCs (Universal Product Codes). Just type any of these into Google to get a link to the results you need.

 

Google Knows Stocks

Looking for information on your favorite stock? Enter the ticker symbol and you’ll get back the name of the company, the current stock price, a graph of recent values, and other information, such as the most recent open, high, and low prices.

 

You’ll also be presented with links to sites with additional information such as Google Finance, CNN Money, and Reuters.

 

Google Knows the Weather

Start your search with the word weather followed by a city and state or zip code to receive the current and forecasted weather for that area. You’ll also be provided with links to pages with additional information such as the Weather Channel, Weather Underground, and AccuWeather.

 

Google Knows Sunrise and Sunset

If you’re wondering when the sun is going to rise or set, just ask Google. If you omit the location, Google will attempt to figure out where you are and give you the time for that location.

 

Google Knows the Time

What time is it in San Francisco? Enter time and the location to find out. Google Knows Holidays

 

When you want to know the day or date of a particular holiday, just ask Google. For example, let’s say that you want to know what day of the week Halloween falls on this year. Just search for when is Halloween; at the top of the search results, you’ll see the answer.

 

You can also search for some of those more obscure holidays, like National Mole Day. Note that many holidays are region-specific, so you may see different holidays depending on your location settings.

 

Google Knows the Score

Wondering what the score was of your favorite team’s last game or when their next game is scheduled? Just enter the name of your team to find out.

 

If the game is currently on, you’ll be provided with the most current statistics available. If you’re interested in seeing more of a team’s upcoming schedule, just click the “+ Show more games” link.

 

Google Knows When the Ground Shakes

Heard about a recent earthquake somewhere in the world and want to know more? Type in the earthquake and a location to get the data you’re looking for. For information on recent quakes, don’t specify a location.

 

Google Knows Public Data

Google has access to an immense amount of public data—so much that we couldn’t possibly cover it all here. But as just one example, enter population and a location. This provides you with the current population figure, that figure’s date and source, and a graph of the population change over time.

 

Additionally, if you click on the graph, you’ll be taken to another page with even more detailed data and plenty of options for customizing the graph with additional information.

 

Google Knows Maladies and Medications

Have some medications that you’re researching? When you search on the name of a medication, Google gives you the brand and chemical names, a brief description, and links to “Side effects,” “How to take,” “Precautions,” and “Missed a dose”.

 

You can also search for diseases and generalized maladies, for which Google will return details and/or further options.

 

Google knows food

If you’re looking for nutritional information for basic foods try doing a simple search on the name of that food. Searches for natural foods like apples, grapes, and tomatoes will result in nutritional data appearing to the right of the Web search results.

 

Google is adding more foods all the time so something that receives no similar results now may do so in the future. However, don’t expect to get detailed nutritional information for prepackaged foods for the foreseeable future.

 

Google knows when to stop

Google knows when to stop

Need a simple countdown? Just tell Google to set the timer for and then enter the length of time you need.

 

At the top of your search results, you’ll see a live countdown timer along with a blue line that fills in as the time runs out, stop and restart links, and a speaker icon to turn off the audible alert that will occur when time runs out.

 

When the time does run out, the stop link will turn into an OK link, which you’ll need to click to turn off the alarm.

 

Google knows where to begin

Google has a little-known separate Web site titled “What do you love?”. Head over there and you’ll be asked to answer the question “What do you love?”.

 

In this case, instead of receiving specific results from a specific type of Google search, you’ll be presented with a long page of both results and links to further searches from across many Google services.

 

For example, a search here for libraries returns results ranging from “Latest news about libraries” (Google News), “Start a libraries discussion group” (Google Groups), “Scour the Earth for libraries” (Google Earth), “Explore libraries in #d” (Google SketchUp), “Measure popularity of libraries on the web” (Google Trends), “See pictures of libraries” (Google Images), and many more.

 

Results do vary significantly (for example, searching for an author’s name offers the ability to find patents about that author), but if you’ve got a patron who doesn’t know where to start on a somewhat broad topic, this can be a great way to get them to think about just what type of resources they’re looking for.

 

Google Translate

Although Google Translate isn’t a way to perform a search, it can still come in handy when dealing with search results that appear in a language that you don’t read. Granted, if you’re using English keywords, chances are you’ll get back only English-language pages.

 

However, searches for things such as place names or events that happen in the non-English-speaking world are more likely to return foreign-language results. This is where Google Translate comes into play.

 

There are four ways that you can take advantage of Google Translate: three that are browser neutral, and one that’s specific to Google Chrome.

 

Google can translate text, translate a web page, translate a document, and (Chrome only) give you an on-the-fly translation. Let’s take a brief look at each operation.

 

The first three are all available by going to the Google Translate page at Google Translate. Here you’ll find two boxes, one for the original text on the left and the translated text on the right.

 

To translate a block of text, all you need to do is type or paste it into the box on the left and click the blue “Translate” button.

 

By default, Google automatically detects the original language and translates it into your default language, based on your location (for us, that would be English) then displays the translation in the box on the right.

 

If either of those assumptions is incorrect, you can use the “From:” and “To:” buttons above the translation boxes to change either or both of the languages.

 

If instead you have the URL of a web page you wish to translate, you can enter the URL in the box on the left and click the link displayed in the right box.

 

In this case, the page will be loaded and displayed as if you had gone directly to that page, but it has been translated into the language you chose.

 

If you find yourself with an electronic document such as a Word file that you need to translate, find the “translate a document” link beneath the box on the left. Clicking this link takes you to another page, where you can browse for and upload a document to Google for translation.

 

Lastly, if you’re a user of the Google Chrome browser, the web page translation feature is actually built in. As shown in the figure when you go to the Italian Wikipedia home page, a toolbar appears at the top of the page that states, “This page is in Italian. Would you like to translate it?”

 

Here you can choose a different source language (should Google have gotten that wrong) and then choose either to “Translate” the page or to decline the translation by clicking the “Nope” button. If you do choose to translate, as you continue to surf, Chrome will continue to translate until you tell it to stop.

 

If you use this feature regularly, you may want to explore the “Options” button off to the right of the translation bar. You can instruct Chrome to always translate pages in a particular language, never translate pages from that language, or never to translate pages from the current site.

 

Granted, Google’s translation service may not be as good as hiring a professional, but we can say from experience that it’s been good enough every time we’ve needed it.

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