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Robots that steal human jobs should pay taxes, Gates says

Taxation and redistribution.


Bill Gates, the co-founder of Microsoft and world’s richest man, said in an interview Friday that robots that steal human jobs should pay their fair share of taxes.

“Right now, the human worker who does, say, $50,000 worth of work in a factory, that income is taxed and you get income tax, Social Security tax, all those things,” he said. “If a robot comes in to do the same thing, you’d think that we’d tax the robot at a similar level.”

Gates made the remark during an interview with Quartz. He said robot taxes could help fund projects like caring for the elderly or working with children in school. Quartz reported that European Union lawmakers considered a proposal to tax robots in the past. The law was rejected.

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Artificial Vision, Artificial Retina, Optogenetics, José Alain Sahel MD, CMU RI Seminar

For those interested in life extension and bionic / cyborg type enhancements, this CMU Robotics Institute Seminar gives an overview of the background and current developments in artificial vision. José Alain Sahel MD is a world leading ophthalmologist with a lengthy bio and numerous honors and appointments.

In the future, if you’re going blind, these sight restoration technologies may be used to remediate your vision loss.

Three major ideas are covered. 1) Implanting arrays of tiny 3-color LEDs under a failed retina to stimulate still-okay cells, and 2) using gene therapy to express a novel photoreceptor, borrowed from algae, to restore a form of sight to failed cells. These can be done together. Lots of studies in mice, primates, and humans. Some coverage is also given to 3) directly implanting electronics in the brain to send complete images to vision centers, but this is still at an early stage.

None of this is anywhere near total restoration. The patients can make out a few words for the first time. And unlike normal vision, the range of light intensity levels remains very narrow. But obviously it’s much better than nothing and will get better over time.

As a point of humor, he tells the story of one of his blind patients who totally redesigned one of his experiments for him.

DeepMind just published a mind blowing paper: PathNet

Potentially describing how general artificial intelligence will look like.

Since scientists started building and training neural networks, Transfer Learning has been the main bottleneck. Transfer Learning is the ability of an AI to learn from different tasks and apply its pre-learned knowledge to a completely new task. It is implicit that with this precedent knowledge, the AI will perform better and train faster than de novo neural networks on the new task.

DeepMind is on the path of solving this with PathNet. PathNet is a network of neural networks, trained using both stochastic gradient descent and a genetic selection method.

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Ford just invested $1 billion in a secretive AI startup founded by former Google and Uber execs

Ford is investing $1 billion in a secretive artificial intelligence startup headed by former Google and Uber execs to advance its self-driving car efforts.

The startup, Argo AI, was founded by Bryan Salesky, the former director of hardware for Google’s self-driving-car efforts, and Peter Rander, Uber’s engineering lead at its autonomous cars center.

The $1 billion investment will be spread out over five years as Ford looks to commercialize its self-driving technology by 2021.

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Google teams up with Kaggle to host $100,000 video classification challenge

Google and Kaggle today announced a new machine learning challenge that asks developers to find the best way to automatically tag videos.

The challenge, which comes with a $30,000 prize for the first-place finisher (and $25,000, $20,000, $15,000 and $10,000 for the next four teams), asks developers to classify and tag videos from Google’s updated YouTube-8M V2 data set. This data set features a total of 7 million YouTube videos that add up to 450,000 hours of video. YouTube-8M already includes labels, too, and developers can use this as their training data. The challenge then is to tag 700,000 previously unseen videos.

kaggle

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Wide & Deep Learning: Memorization + Generalization with TensorFlow (TensorFlow Dev Summit 2017)

Wide models are great for memorization, deep models are great for generalization — why not combine them to create even better models? In this talk, Heng-Tze Cheng explains Wide and Deep networks and gives examples of how they can be used.

Check out our blog post, paper, YouTube video, TensorFlow tutorials: https://goo.gl/MwVlVa

Visit the TensorFlow website for all session recordings: https://goo.gl/bsYmza

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Robots could be injected into the body to fight cancer

We have stated this for a while; time to make it commercially available.


Our bodies are full of immune cells that circle around the blood, ready to see off any invaders.

And soon they could be getting a helping hand from tiny disease-fighting robots.

Scientists have created an army of magnetically-controlled robots which they say could help our bodies fight off diseases such as cancer.

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