DeepMind is definitely at the top of its game with cutting edge projects like AlphaGo, AlphaStar, and, most recently, AlphaFold, but it has even bigger plans. Curiously, it will retain control of any AGI it creates. Granted, an AGI is still years, maybe even decades away. I do, however, find it interesting that DeepMind is already planning a corporate power struggle.

Very Blade Runner-esque, don’t you think?

DeepMind — quite prominently — claims to be the “world leader in artificial intelligence research.” AlphaGo and AlphaStar certainly lend credence to that title, but the Alphabet division’s end goal is artificial general intelligence (AGI). If it ever achieves that landmark accomplishment, DeepMind — and not its parent company — will reportedly retain control.

OpenAI raised some eyebrows last month when it announced it had figured out a way to get an AI to write more naturally. They, however, decided not to release their entire research for fear that it could cause havoc.

From an article in The Register.

Last month, researchers at OpenAI revealed they had built software that could perform a range of natural language tasks, from machine translation to text generation. Some of the technical details were published in a paper, though the majority of materials was withheld for fear that it could be used maliciously to create spam-spewing bots or churn out tons of fake news. Instead, OpenAI released a smaller and less effective version nicknamed GPT-2-117M.

While grabbing coffee at a recently renovated McDonald’s, Frank ponders the future of work: both low-skill and higher skill work. There’s going to be no hiding from this: we are truly on the Eve of Disruption, where AI will impact everyone everywhere.It’s not all gloom and doom and there might be a strategy to survive and even thrive now and in the next economy.  Press the play button below to listen here or visit the show page at DataDriven.tv

Here’s an interesting article in Forbes on how John Deere is using computer vision to optimize agricultural output.

In just 30 years’ time, it is forecasted that the human population of our planet will be close to 10 billion. Producing enough food to feed these hungry mouths will be a challenge, and demographic trends such as urbanization, particularly in developing countries, will only add to that. Intelligent […]

In this interview with Geoffrey Hinton, Martin Ford asks the pioneering AI researcher about the economics of a world dominated by AI and what to do about making sure the future is for everyone.

If you can dramatically increase productivity and make more goodies to go around, that should be a good thing. Whether or not it turns out to be a good thing depends entirely on the social system, and doesn’t depend at all on the technology. People are looking at the technology as if the technological advances are a problem. The problem is in the social systems, and whether we’re going to have a social system that shares fairly, or one that focuses all the improvement on the 1% and treats the rest of the people like dirt. That’s nothing to do with technology.

Ricky Brundritt, PM in the Azure Maps team, walks Olivier through data driven styling with Azure Maps. Data driven styling allows you to dynamically style layers at render time on the GPU using properties on your data. This provides huge performance benefits and allows large datasets to be rendered on the map. Data driven style expressions can greatly reduce the amount of code you would normally need to write and define this type of business logic using if-statements and monitoring map events.

Related links:

The interesting thing about autonomous vehicle technology is that it’s not just about cars. Here’s an interesting story about an autonomous snowplow in Canada.

Otto, the airport’s self-driving snowplow. Winnipeg’s airport is now the home of North America’s first ever autonomous snowplow. Richardson International Airport collaborated with Manitoba companies Northstar Robotics and Airport Technologies to create the plow, which was unveiled Thursday. #ICYMI : WAA partnered with @NorthStarRobot and Airport Technologies Inc. to […]

We rarely think about the infrastructure at the hear of the internet, except maybe lamenting that there are not enough cell phone towers. However, there’s a massive network of cables under the oceans that connect the world together. These undersea cables are the backbone of the internet.

These submarine fiber optic cables permit the world’s web traffic to flow and I can’t help but thinking of the NYC Subway map when looking at where the cables are.

submarine cables

One such cable is called Marea. It runs from Virginia Beach in the U.S. to Balboa, Spain and it just set a speed record of  26.2 terabits per second, more than enough to stream 793,000 ultra-high-def movies at once.

Infinera makes the “equipment that puts the light into the optical fiber,” Bennett explains. To hit data transfer rates of 20 percent over the capacity of the fiber, Bennett says they did two things. First, they implemented “multiple wavelengths on a single optical chip, so that we could squeeze the individual wavelengths closer together, and get more wavelengths on the fiber,” he explains. “And the second part is, each wavelengths is transmitted as a set of subcarriers that also allows tighter spacing.” So, while the pipe remained the same, they increased how much data could be sent through it in a given amount of time. [Read more]

One of the questions that I get asked a lot is how to get started in Data Science. In some ways, it’s easier now than when I started — there’s a lot more learning resources. In others, it’s harder — there’s a lot more competition for data science jobs.

Here’s a great article from towardsdatascience.com with six bits of advice for those wanting to get into this field.

Building experience before landing a job Data science is a field with a huge demand, in part because it seems to require experience as a data scientist to be hired as a data scientist. But many of the best data scientists I’ve worked with have diverse backgrounds ranging from

[Read More]