Post is pinned.Post has attachment
Making It Easier for Mere Mortals to Train Machines

Some of you may have read about the recent breakthroughs by DeepMind and OpenAI for making it easier to use human preferences as inputs to machine learning. In this post, I outline some of the implications of these experiments.

There are a number of takeaways, but I think the most compelling is what this new approach could mean for building better AI governance.

#MachineTraining #MachineLearning #ReinforcementLearning
Add a comment...

Post has attachment
Fei Fei Li speaks about the importance of keeping AI grounded in human considerations.

This is a quick read and well worth it.

Researching cutting-edge AI is very satisfying and rewarding, but we’re seeing this great awakening, a great moment in history. For me it’s very important to think about AI’s impact in the world, and one of the most important missions is to democratize this technology. The cloud is this gigantic computing vehicle that delivers computing services to every single industry.

When you are making a technology this pervasive and this important for humanity, you want it to carry the values of the entire humanity, and serve the needs of the entire humanity. If the developers of this technology do not represent all walks of life, it is very likely that this will be a biased technology. I say this as a technologist, a researcher, and a mother. And we need to be speaking about this clearly and loudly.

Add a comment...

Post has attachment
Intel's New AI Chip

Intel’s Loihi is different because its crude analogs of neurons are burned into hardware, and its design differs fundamentally from the computer chips the world runs on today. In conventional chips, data shuttles back and forth between a processor and separate memory. Loihi’s “neurons” and the adjustable connections between them function as both processor and memory, saving time and energy required to shuffle data around. The connections—analogous to synapses—between neurons can adjust to patterns in their activity over time, mimicking a learning mechanism seen in real brains. Tests of this ability have included showing the chip videos of people performing movements such as bicep curls, and challenging it to recognize the same motion in fresh video clips.


HT +Wayne Radinsky (over on Twitter)
Add a comment...

Post has attachment
Increasing Returns to AI

Artificial intelligence pioneer, Yoshua Bengio:

"AI is a technology that naturally lends itself to a winner take all," Bengio said. "The country and company that dominates the technology will gain more power with time. More data and a larger customer base gives you an advantage that is hard to dislodge. Scientists want to go to the best places. The company with the best research labs will attract the best talent. It becomes a concentration of wealth and power."

Add a comment...

Post has attachment
How Does Deep Learning Work?

A new theory seeks to explain the success of Deep Learning by highlighting generalization as a kind of algorithmic 'forgetting.'

As an example, some photos of dogs might have houses in the background, while others don’t. As a network cycles through these training photos, it might “forget” the correlation between houses and dogs in some photos as other photos counteract it. It’s this forgetting of specifics, Tishby and Shwartz-Ziv argue, that enables the system to form general concepts. Indeed, their experiments revealed that deep neural networks ramp up their generalization performance during the compression phase, becoming better at labeling test data.
Add a comment...

Post has shared content
But Hinton suggested that, to get to where neural networks are able to become intelligent on their own, what is known as "unsupervised learning," "I suspect that means getting rid of back-propagation."
Artificial intelligence pioneer says we need to start over

In 1986, Geoffrey Hinton co-authored a paper that, four decades later, is central to the explosion of artificial intelligence. But Hinton says his breakthrough method should be dispensed with, and a new path to AI found. Speaking with Axios on the sidelines of an AI conference in Toronto on Wednesday, Hinton, a professor emeritus at the University of Toronto and a Google researcher, said he is now "deeply suspicious" of back-propagation, the workhorse method that underlies most of the advances we are seeing in the AI field today, including the capacity to sort through photos and talk to Siri. "My view is throw it all away and start again," he said..... In back propagation, labels or "weights" are used to represent a photo or voice within a brain-like neural layer. The weights are then adjusted and readjusted, layer by layer, until the network can perform an intelligent function with the fewest possible errors. But Hinton suggested that, to get to where neural networks are able to become intelligent on their own, what is known as "unsupervised learning," "I suspect that means getting rid of back-propagation." "I don't think it's how the brain works," he said. "We clearly don't need all the labeled data."
Add a comment...

Post has attachment
Fighting Fire with Fire


To stay ahead of the curve, Wallace recommends that security firms conduct their own internal research, and develop their own weaponized AI to fight and test their defenses. He calls it “an iron sharpens iron” approach to computer security. The Pentagon’s advanced research wing, DARPA, has already adopted this approach, organizing grand challenges in which AI developers pit their creations against each other in a virtual game of Capture the Flag. The process is very Darwinian, and reminiscent of yet another approach to AI development—evolutionary algorithms. For hackers and infosec professionals, it’s survival of the fittest AI.
Add a comment...

Post has attachment
Decent overview on Artificial Intelligence. Nothing new, and kind of basic, but a decent way to get the big picture.
Add a comment...

Post has attachment
Good insights from +Daniel Estrada​ on getting past the hype, while not ignoring the need for solid research into AI safety.
Add a comment...

Post has attachment
China's deep embrace of data gives it an edge on AI.
Add a comment...
Wait while more posts are being loaded