Emergent // Future - TensorFlow 1.0, the Ultimate Breakthrough, Ford Invests $1B Into AI

Issue 42
This week we look at
Google’s release of  TensorFlow 1.0, what the Microsoft CEO thinks the ultimate breakthrough is, why Ford is investing $1B into AI, our top reads of the week, and things to try at home.

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TensorFlow Turns 1.0 ????

Google released the 1.0 version of its open-source deep learning framework last week.

The new release brings more speed, flexibility, and stability to the TensorFlow platform, which features more than 6,000 open-source repositories.

The big feature is the experimental release of XLA, a domain-specific compiler for linear algebra that optimizes TensorFlow computations. This is big news because the improvements in speed and memory usage open the door to a new class of apps that can run on smartphone-grade hardware

In addition, the Python APIs have been changed to more closely resemble NumPy. Experimental APIs for Java and Go are also available.

TensorFlow has helped researchers, engineers, artists, students, and others make progress with everything from language translation to early detection of skin cancer and preventing blindness in diabetics.

It’s now as simple as pip install tensorflow

AI: The Ultimate Breakthrough ⚡️

Microsoft CEO Satya Nadella is stressing the immense potential of artificial intelligence lately, calling it the “ultimate breakthrough” in technology.

For all the advances in computer interfaces, nothing has come close to beating human-level speech recognition than deep neural networks.

Nadella says they’re “fundamentally giving us human perception, whether it is speech or image recognition, and that’s just magical to see.”

That could explain why Ford Motor plans to invest $1 billion over the next five years in Argo AI, an artificial intelligence start-up that is focused on developing autonomous vehicle technology.

The move is Ford’s biggest effort to move into self-driving car research.

Argo AI will develop the technology exclusively for Ford at first, and then plans to license its technology to others.

What We’re Reading ????

  • The state of today’s autonomous vehicle market. Only five years ago, the autonomous vehicle future seemed like a distant vision. This year at CES, the “frenzy” over autonomous vehicles stole the show with dozens of live demos, partnerships, and product announcements.  (VentureBeat)
  • Evolution of business logic from monoliths through microservices, to functions. We’ve seen an evolution from monolithic applications to microservices and are now seeing the rise of serverless event driven functions, led by AWS Lambda. What factors have driven this evolution? (Adrian Cockcroft)
  • How is deep learning changing data science paradigms? At the latest conference on Neural Information Processing Systems, Andrew Ng shared some ideas about deep learning. Let me share them with you. (Schibsted)
  • Is attacking machine learning easier than defending it? In this post, we’ll take adversarial examples as an illustration of why attacking machine learning seems easier than defending it. (Clever Hans)
  • Reverse engineering the YouTube algorithm. The big takeaway from the paper’s introduction is that YouTube is using Deep Learning to power its algorithm. Part I and Part II
  • Artificial intelligence has achieved much of its recent success by mimicking biology. Artificial intelligence has achieved much of its recent success by mimicking biology. Now it must go further. (The New Yorker)

Things To Try At Home ????

Emergent // Future is a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. 

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