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Google’s robot acquisitions likely cost less than $100 million

Andy Rubin

There is much speculation about Google’s intentions with its acquisition of eight robot companies in the fall of last year. What has been missing in this speculation is just how much it has spent on the eight companies.

The acquisitions of the robot companies appear to have been completed in the last quarter of 2013, they were announced in December.

At the end of the third quarter of 2013 Google stated in their financial reporting that they had completed twenty-one acquisitions with a total value of $1,338 billion. They confirmed that $969 million of this was spent on the purchase of mapping company Waze.

The remaining $369 million was spent on purchasing an additional twenty companies.

None of these were material so the company does not have to account for them individually in its regulatory filings.

Some of these acquisitions can be found online. The largest of them was Channel Intelligence for which Google reportedly paid $125 million. Then there are lots of smaller acquisitions ranging from file sharing app, Bump for $35 million, motion detector device Flutter, which cost $40 million. The acquisition of Wavii for $35 million enhances Google’s natural language technology. They boosted their cloud computing capabilities when they brought in Talaria Technologies for around $20 million, their green energy capacity with the addition of Makani Power to the Google X team for around $30 million. They also brought in some great recruits with the purchase of DNNResearch headed up by Machine Learning pioneer Geoff Hinton for around $5 million, and employees from the venture fund Hatter again for around $5 million. Google also bought 217 patents from IBM during the first 9 months although it’s not clear where these have been accounted for and could be expensed in R&D.

This is a nominal selection of the 20 non-material acquisitions in the first three quarters of 2013, accounting for $318 million of the $369 million expenditure, but it helps establish a baseline for the cost of the robot companies they bought.

Yesterday Google posted their annual report, form 10K, on the Securities and Exchange Commission (SEC) website. In the annual report they confirm that during the twelve months ended 31st December 2013 they spent a total of $489 million on acquisitions that were not material and therefore did not require specific details. They also accounted for the Waze acquisition at $969 million – “The (Waze) acquisition is expected to enhance our customers’ user experience by offering real time traffic information to meet users’ daily navigation needs.”

Now we know that they spent $369 million on non-material companies in the first three quarters and $489 million during the whole twelve months we can safely calculate that $120 million was spent in the fourth quarter on non-material acquisitions.

The announcement of French company Flexycore for a rumored $23 million took place in the fourth quarter (end of October) and its not clear when they closed the deal for Flutter on whom they spent $40 million, as the media picked this up on 2nd October, but I’ll ‘assume’ they closed it in the 3rd quarter.

Taking the deal for Flexycore off the table indicates that Google spent an additional $97 million during the last quarter of 2013 on acquisitions, the time they bought the 8 robot companies

It’s likely that somewhere between $50 million and $90 million of the $1,458 billion Google spent on acquisitions in 2013 went on the purchase of those eight robot companies.

It’s fascinating that these acquisitions have created such media speculation given the nominal size of the purchase costs.

Of course this is very good news for the robotic industry as it possibly increases the value of the sector in the eyes of investors, raises awareness about the advances being made in robotics and brings an important subject about the future direction of technology and jobs into the public domain.

As I have said before, Google’s acquisition of robots and Artificial Intelligence technologies is anything but scary.

Photo: Andy Rubin Head of Google’s Robot Revolution, former head of Android

Artificial Intelligence raises deeper questions than nuclear weapons technology

With so much press around Google’s acquisition of DeepMind (which I wrote about here and here) and the establishment of an ethics board (a good thing in my opinion). I thought I would highlight some text from one of the dominant textbooks in the field of Artificial Intelligence; AI: A Modern Approach. The book is apparently used in 1200 universities, and is currently the 22nd most-cited publication in computer science and 4th most cited publication of the 21st century.

The authors, Stuart Russell, Professor of Computer Science and Smith-Zadeh Professor in Engineering, University of California, Berkeley, Adjunct Professor of Neurological Surgery, and Peter Norvig (director of Research at Google) devote significant space to A.I. dangers and Friendly A.I., “The Ethics and Risks of Developing Artificial Intelligence.”

What initially got my attention whilst reading this chapter was this statement: “AI raises deeper questions than, say, nuclear weapons technology.”

The authors continue outlining various risks. The first 5 risks they discuss are:

  • People might lose their jobs to automation.
  • People might have too much (or too little) leisure time.
  • People might lose their sense of being unique.
  • AI systems might be used toward undesirable ends.
  • The use of A.I. systems might result in a loss of accountability.

The last subset listed above indicates: “The Success of AI might mean the end of the human race.” Below is an extract:

The question is whether an A.I. system poses a bigger risk than traditional software. We will look at three sources of risk. First, the AI system’s state estimation may be incorrect, causing it to do the wrong thing. For example…a missile defense system might erroneously detect an attack and launch a counterattack, leading to the death of billions.

Second, specifying the right utility function for an A.I. system to maximize is not so easy. For example, we might propose a utility function designed to minimize human suffering, expressed as an additive reward function over time… Given the way humans are, however, we’ll always find a way to suffer even in paradise; so the optimal decision for the AI system is to terminate the human race as soon as possible – no humans, no suffering…

Third, the A.I. system’s learning function may cause it to evolve into a system with unintended behavior. This scenario is the most serious, and is unique to AI systems, so we will cover it in more depth.

They then write:

I.J. Good wrote, “Let an ultra-intelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultra-intelligent machine could design even better machines; there would then be unquestionably be an “intelligence explosion,” and the intelligence of man would be left far behind. Thus the first ultra-intelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.”

The authors also reference that in Computer Power and Human Reason, Joseph Weizenbaum argued that the effect of intelligent machines on human society will be such that continued work on artificial intelligence is perhaps unethical.

Norvig and Russell do leave us with much to think about:

Looking on the bright side, success in AI would provide great opportunities for improving the material circumstances of human life. Whether it would improve the quality of life is an open question. Will intelligent automation give people more fulfilling work and more relaxing leisure time? Or will the pressures of competing in a nanosecond-paced world lead to more stress? Will children gain from instant access to intelligent tutors, multimedia online encyclopedias, and global communication, or will they play ever more realistic war games? Will intelligent machines extend the power of the individual, or of centralized governments and corporations?

The Founders Fund, which was one of the backers of DeepMind has written:

“While we have the computational power to support many versions of AI, the field remains relatively poorly funded, a surprising result given that the development of powerful AIs (even if they aren’t general AIs) would probably be one of the most important and lucrative technological advances in history.”

It is clear that computers with human-level intelligence (or better) would have a huge impact on our everyday lives and on the future course of civilization.

Google’s DeepMind acquisition in reinforcement learning

Google Now

I recently read a description of economists attributed to Robert Solow: “There are two kinds of economists: those who look for general results and those who look for illuminating examples.” Maybe this is the divide that separates Artificial Intelligence from cognitive science. AI seeks general results while the latter explains illuminating examples. Google’s recently reported $400 to $500 million acquisition of DeepMind, the University of Oxford’s Future of Humanity Institute affiliated company, brings it closer to achieving illuminating examples instead of general results.

DeepMind specializes in an advance form of Machine Learning called Reinforcement Learning. They have effectively developed algorithms to solve high-dimensional uncertain sequential decision-making problems. The more advanced reinforcement learning methods improve mechanisms for knowledge representation, search, and human-level reasoning.  (A paper by the DeepMind founders on reinforcement learning can be found here).

So far the developed methods of Machine Learning and AI have mostly been about the task of prediction. With DeepMind Google gets a reinforcement learning tool deep rooted in behavioral psychology and neuroscience to improve on predicted modeling and provide a solution to reduce the amount of human intervention and enhance decision making.

It can be used with Google’s self-driving cars to improve knowledge of routes. Through high-dimensional sensory inputs like vision and speech; reinforcement learning will improve Google Glass and Google Now and perhaps most fundamentally it will improve how Google delivers adverts to Google users.

The academic research by the DeepMind team is extremely complimentary to Google’s products with experts in machine learning of imagery and robotics and people that have worked or studied with Geoffrey Hinton who recently joined Google on their AI development.

Effectively reinforcement learning algorithms can help people make better decisions, as it will provide users with the best data available.

This acquisition brings Google closer to building a “cybernetic friend” that listens in on your phone conversations, reads your e-mail, and tracks your every move — if you let it, of course — so it can tell you things you want to know even before you ask.

A great move if you ask me, which will considerably enhance Google’s services to its advertisers and users.

Below is an interesting presentation by Demis Hassabis, one of the founders of DeepMind:

Are maps and localization driving Google’s robot strategies?

Now that Google has confirmed reports of the acquisitions of eight robotic companies much speculation is being made of where the search giant is heading.Google where to?

My own belief is this is very much part of their mobile strategy, and if it is not, it certainly has generated a significant amount of press and media attention, despite the probable sizes of the deals being small by Google’s standards. In their latest 10Q filing (pdf), the company reported during the nine months ended September 30, 2013, they completed 21 acquisitions and purchases of intangible assets, 20 of these, (which are likely to be most of the robotic companies) were for a relatively small amount of approximately $369 million. The other acquisition during this period was Waze, a provider of a mobile map application, which provides turn-by-turn navigation and real-time traffic updates powered by incidents and route information submitted by a community of users, for a total cash consideration of $969 million. Google writes:

The acquisition is expected to enhance our customers’ user experience by offering real-time traffic information to meet users’ daily navigation needs.

Effectively the acquisition of Waze is nearly 3 times as much as the combined purchase price of the 20 other companies. Let us also remember that as recent as April 2012 Google paid a staggering $12.4 billion total purchase price for Motorola (they subsequently sold Motorola home for $2.4 billion and retain focus on Motorola mobile).

In Google’s 2012 10K (pdf annual report) the company reflects on the acquisition of Motorola:

We expect to continue to devote significant resources to the creation, support, and maintenance of mobile products and services… to capture the opportunities available as consumers and advertisers transition to a dynamic, multi-screen environment.

The multi-screen environments move from personal computers to “mobile phones, smartphones, handheld computers such as netbooks and tablets, video game consoles, and television set-top devices.”


The acquisition is expected to protect and advance our Android ecosystem and enhance competition in mobile computing. 

It’s not uncommon for Google to spend a lot on acquisitions, some of which would never get the press coverage a robot or big dog will. Yet during the year ended December 31, 2012, Google spent over $1 billion ($1,171) on 52 other acquisitions (in addition to Motorola) that ‘generally enhance the breadth and depth of our expertise in engineering and other functional areas, our technologies, and our product offerings.’  But little is written of what that $1,171 was spent on, despite it being significantly higher than the acquisition spending in the 9 months ended September 2013 (excluding Waze). Although at least some of the cash in 2012 went on speech recognition technology!

The man spearheading Google’s robotic acquisitions and project is Andy Rubin, the former head of the hugely successful Android development, the person that was effectively challenged with establishing Google’s foothold in mobile, the area they see as being strategically important to their future cash-flows as users turn more and more to multi-screen browsing.

So why the question — Are maps and localization driving Google’s robot strategies?

It’s clear the Motorola and Waze acquisitions together with Google Maps, StreetView, Nexus 7 (Google’s tablet) and Android are establishing a mobile ecosystem and Google sees Maps as a crucial part of an operating system for mobile devices.

Maps is already generating around 20% of search queries and according to the New York Times article (link above) Google indicates the same amount of advertising revenues is connected to map searches. It seems Google has a clear vision of combining maps and mobile to ensure it continues to grow its $50 billion plus per year revenues.

The sheer amount of human effort that goes into Google’s maps is just mind-boggling and the geographic data Google has assembled is not likely to be matched by any other company. We can now navigate around shopping malls with Google’s Indoor maps, in fact Street View now includes the ability to navigate inside of Gatwick Airport, Waterloo Station, and even inside an Airbus A380 on the runway at Dubai Airport.

Sergey Brin, Google’s co-founder, has promised to release self-driving technology within four years, and Google’s maps will then be a standard feature in its robot cars. Likewise maps are integral to Google Glass another of the ‘moonshot’ projects Google is working on.

Google Ventures recently announced a $250 million investment in Uber the ‘taxi service’ and again maps will be one of the driving factors behind this investment.

Google’s home delivery service, Shopping Express, which provides same day delivery service, relies heavily on maps.

Maps are clearly at the core of Google’s development strategy, from driverless cars, online shopping and search, to wearable technology. Many of the recent robot acquisitions will enhance Google’s mobile strategy and improve its delivery services, hardware capabilities and above all localization experiences.

Google revenues are dependent upon growing advertisement revenues and the closer it gets to users through localization and awareness of consumer habits through mobile technology and maps the more it can increase its sophisticated and timely service to advertisers.

According to Alexis Madrigal writing in The Atlantic magazine: “Google’s geographic data may become its most valuable asset. Not solely because of this data alone, but because location data makes everything else Google does and knows more valuable.

Google is reshaping the computer question “where do you want to go today?” And that makes for improved search and services for all of us. It seems that Google has a big part to play in the Robot Economy…

UK Government betting on driverless cars and robotics

The UK is the latest government to announce large scale investments into driverless cars and robotics. Through its infrastructure plan (pdf) the British government has indicated projected investments in the region of £375 billion ($612 billion) by public and private entities over the next decade or so to create an advanced infrastructure.

Reporting specifically on driverless cars the roadmap states:

Driverless cars are innovative technology that will change the way the world’s towns and cities look and the way people travel; they present opportunities for the British automotive industry in the manufacture of the cars and the wider science and engineering sectors in the design of towns.

To ensure that UK industry and the wider public benefit from the development of driverless cars, the government announces in the National Infrastructure Plan that it will conduct a review, reporting at the end of 2014, to ensure that the legislative and regulatory framework demonstrates to the world’s car companies that the UK is the right place to develop and test driverless cars

Of course the British government are not the first to seek to be a ‘champion’ for driverless cars; Google has permission to test its autonomous cars in several states in the US. Volvo received permission to test driverless cars in Gothenburg, Sweden. Researchers are testing driverless cars in Berlin and earlier this year the French government laid out a ten year roadmap to be leaders in driverless cars, robotics and other advanced technologies.

The UK government report indicates:

This investment will support UK capabilities by funding research and its commercialisation
in priority areas such as robotics, synthetic biology and biologic medicines, regenerative
medicine, agricultural technologies, the exploitation of space, high performance computing and big data analytics.

In its efforts to establish itself as a leading player in autonomous and furthermore, environmentally friendly, cars, the UK Government would be well advised to woo Tesla Motors to set up a European manufacturing facility in the UK. Tesla, who have also announced their plans for an autonomous car, has one of the most advanced robotic factories and electric cars available today.

Google buys seven robot companies

Over the last half-year, Google has quietly acquired seven technology companies in an effort to create a new generation of robots. And the engineer heading the effort is Andy Rubin, the man who built Google’s Android software into the world’s dominant force in smartphones.

According to a report in the New York Times, Rubin says that Google’s robotics efforts should be viewed as a ten-year vision. The company has secretly acquired seven robotics-related companies in the US and Japan, which have technologies capable of creating a mobile robot. Rubin notes that breakthroughs are still needed for software and sensors, but hardware issues like moving hands and arms have been solved.

Google CEO Larry Page says in a Google+ update that he is excited about Rubin’s project. “His last big bet, Android, started off as a crazy idea that ended up putting a supercomputer in hundreds of millions of pockets.  It is still very early days for this, but I can’t wait to see the progress.”

The company is tight-lipped about its specific plans, but the scale of the investment, which has not been previously disclosed, indicates that this is no cute science project.

The NY Times reports:

Earlier this year, Mr. Rubin stepped down as head of the company’s Android smartphone division. Since then he has convinced Google’s founders, Sergey Brin and Mr. Page, that the time is now right for such a venture, and they have opened Google’s checkbook to back him. He declined to say how much the company would spend.

Mr. Rubin has secretly acquired an array of robotics and artificial intelligence start-up companies in the United States and Japan.

Among the companies are Schaft, a small team of Japanese roboticists who recently left Tokyo University to develop a humanoid robot (and is taking part in the DARPA Challenge), and Industrial Perception, a start-up here that has developed computer vision systems and robot arms for loading and unloading trucks. Also acquired were Meka and Redwood Robotics, makers of humanoid robots and robot arms in San Francisco, and Bot & Dolly, a maker of robotic camera systems that were recently used to create special effects in the movie “Gravity.” A related firm, Autofuss, which focuses on advertising and design, and Holomni, a small design firm that makes high-tech wheels, were acquired as well.

The seven companies are capable of creating technologies needed to build a mobile, dexterous robot. Mr. Rubin said he was pursuing additional acquisitions.

The seven startups acquired by Google, include Japanese robotics company SchaftRedwood Robotics, 3D vision company Industrial Perception, and Bot & Dolly (which built the robots that helped film Gravity). Google has also acquired Meka Robotics, advertising and design firm Autofuss, in addition to advanced wheel design firm Holomni.