Tag Archives: Sundar Pichai

Power sharing?

Just to keep you up to speed, everything is on schedule or ahead of schedule.

In the race toward a superintelligence or ubiquitous AI. If you read this blog or you are paying attention at any level, then you know the fundamentals of AI. But for those of you who don’t here are the basics. Artificial Intelligence comes from processing and analyzing data. Big data. Then programmers feed a gazillion linked-up computers (CPUs) algorithms that can sort this data and make predictions. This process is what is at work when the Google search engine makes suggestions concerning what you are about to key into the search field. These are called predictive algorithms. If you want to look at pictures of cats, then someone has to task the CPUs with learning what a cat looks like as opposed to a hamster, then scour the Internet for pictures of cats and deliver them to your search. The process of teaching the machine what a cat looks like is called machine learning. There is also an algorithm that watches your online behavior. That’s why, after checking out sunglasses online, you start to see a plethora of ads for sunglasses on just about every page you visit. Similar algorithms can predict where you will drive to today, and when you are likely to return home. There is AI that knows your exercise habits and a ton of other physiological data about you, especially when you’re sharing your Fitbit or other wearable data with the Cloud. Insurance companies extremely interested in this data, so that it can give discounts to “healthy” people and penalize the not so healthy. Someday they might also monitor other “behaviors” that they deem to be not in your best interests (or theirs). Someday, especially if we have a “single-payer” health care system (aka government healthcare), this data may be required before you are insured. Before we go too far into the dark side (which is vast and deep), AI can also search all the cells in your body and identify which ones are dangerous, and target them for elimination. AI can analyze a whole host of things that humans could overlook. It can put together predictions that could save your life.

Googles chips stack up and ready to go. Photo from WIRED.

Now, with all that AI background behind us, this past week something called Google I/O went down. WIRED calls it Google’s annual State-of-the-Union address. There, Sundar Pichai unveiled something called TPU 2.0 or Cloud TPU. This is something of a breakthrough, because, in the past, the AI process that I just described, even though lighting fast and almost transparent, required all those CPUs, a ton of space (server farms), and gobs of electricity. Now, Google (and others) are packing this processing into chips. These are proprietary to Google. According to WIRED,

“This new processor is a unique creation designed to both train and execute deep neural networks—machine learning systems behind the rapid evolution of everything from image and speech recognition to automated translation to robotics…

…says Chris Nicholson, the CEO, and founder of a deep learning startup called Skymind. “Google is trying to do something better than Amazon—and I hope it really is better. That will mean the whole market will start moving faster.”

Funny, I was just thinking that the market is not moving fast enough. I can hardly wait until we have a Skymind.

“Along those lines, Google has already said that it will offer free access to researchers willing to share their research with the world at large. That’s good for the world’s AI researchers. And it’s good for Google.”

Is it good for us?

This sets up another discussion (in 3 weeks) about a rather absurd opinion piece in WIRED about why we should have an AI as President. These things start out as absurd, but sometimes don’t stay that way.

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Promises. Promises.

Throughout the course of the week, usually on a daily basis, I collect articles, news blurbs and what I call “signs from the future.” Mostly they fall into categories such as design fiction, technology, society, future, theology, and philosophy. I use this content sometimes for this blog, possibly for a lecture but most often for additional research as part of scholarly papers and presentations that are a matter of course as a professor. I have to weigh what goes into the blog because most of these topics could easily become full-blown papers.  Of course, the thing with scholarly writing is that most publications demand exclusivity on publishing your ideas. Essentially, that means that it becomes difficult to repurpose anything I write here for something with more gravitas.  One of the subjects that are of growing interest to me is Google. Not the search engine, per se, rather the technological mega-corp. It has the potential to be just such a paper, so even though there is a lot to say, I’m going to land on only a few key points.

A ubiquitous giant in the world of the Internet, Google has some of the most powerful algorithms, stores your most personal information, and is working on many of the most advanced technologies in the world. They try very hard to be soft-spoken, and low-key, but it belies their enormous power.

Most of us would agree that technology has provided some marvelous benefits to society especially in the realms of medicine, safety, education and other socially beneficial applications. Things like artificial knees, cochlear implants, air bags (when they don’t accidentally kill you), and instantaneous access to the world’s libraries have made life-changing improvements. Needless to say, especially if you have read my blog for any amount of time, technology also can have a downside. We may see greater yields from our agricultural efforts, but technological advancements also pump needless hormones into the populace, create sketchy GMO foodstuffs and manipulate farmers into planting them. We all know the problems associated with automobile emissions, atomic energy, chemotherapy and texting while driving. These problems are the obvious stuff. What is perhaps more sinister are the technologies we adopt that work quietly in the background to change us. Most of them we are unaware of until, one day, we are almost surprised to see how we have changed, and maybe we don’t like it. Google strikes me as a potential contributor in this latter arena. A recent article from The Guardian, entitled “Where is Google Taking Us?” looks at some of their most altruistic technologies (the ones they allowed the author to see). The author, Tim Adams, brought forward some interesting quotes from key players at Google. When discussing how Google would spend some $62 million in cash that it had amassed, Larry Page, one of the company’s co-founders asked,

“How do we use all these resources… and have a much more positive impact on the world?”

There’s nothing wrong with that question. It’s the kind of question that you would want a billionaire asking. My question is, “What does positive mean, and who decides what is and what isn’t?” In this case, it’s Google. The next quote comes from Sundar Pichai. With so many possibilities that this kind of wealth affords, Adams asked how they stay focused on what to do next.

“’Focus on the user and all else follows…We call it the toothbrush test,’ Pichai says, ‘we want to concentrate our efforts on things that billions of people use on a daily basis.’”

The statement sounds like savvy marketing. He is also talking about the most innate aspects of our everyday behavior. And so that I don’t turn this into an academic paper, here is one more quote. This time the author is talking to Dmitri Dolgov, principal engineer for Google Self-Driving Cars. For the whole idea to work, that is, the car reacting like a human would, only better, it has to think.

“Our maps have information stored and as the car drives around it builds up another local map with its sensors and aligns one to the other – that gives us a location accuracy of a centimetre or two. Beyond that, we are making huge numbers of probabilistic calculations every second.”

Mapping everything down to the centimeter.
Mapping everything down to the centimeter.

It’s the last line that we might want to ponder. Predictive algorithms are what artificial intelligence is all about, the kind of technology that plugs-in to a whole host of different applications from predicting your behavior to your abilities. If we don’t want to have to remember to check the oil, there is a light that reminds us. If we don’t want to have to remember somebody’s name, there is a facial recognition algorithm to remember for us. If my wearable detects that I am stressed, it can remind me to take a deep breath. If I am out for a walk, maybe something should mention all the things I could buy while I’m out (as well as what I am out of). 

Here’s what I think about. It seems to me that we are amassing two lists: the things we don’t want to think about, and the things we do. Folks like Google are adding things to Column A, and it seems to be getting longer all the time. My concern is whether we will have anything left in Column B.


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