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Perceptron: AI saving whales, steadying gaits and banishing traffic

Research in the field of machine learning and AI, now a key technology in practically every industry and company, is far too voluminous for anyone to read it all. This column, Perceptron, aims to collect some of the most relevant recent discoveries and papers — particularly in, but not limited to, artificial intelligence — and explain why they matter.

Over the past few weeks, researchers at MIT have detailed their work on a system to track the progression of Parkinson’s patients by continuously monitoring their gait speed. Elsewhere, Whale Safe, a project spearheaded by the Benioff Ocean Science Laboratory and partners, launched buoys equipped with AI-powered sensors in an experiment to prevent ships from striking whales. Other aspects of ecology and academics also saw advances powered by machine learning.

The MIT Parkinson’s-tracking effort aims to help clinicians overcome challenges in treating the estimated 10 million people afflicted by the disease globally. Typically, Parkinson’s patients’ motor skills and cognitive functions are evaluated during clinical visits, but these can be skewed by outside factors like tiredness. Add to that fact that commuting to an office is too overwhelming a prospect for many patients, and their situation grows starker.

Space-cleaning robots could be developed thanks to novel device that was inspired by wilting passion fruits

Turns out, dehydrated passion fruits exhibit a type of symmetry not previously known, inspiring self-adapting robots that could one day ‘grasp’ space junk.

A previously unknown type of wrinkling pattern on the surface of dehydrated passion fruits inspired the invention of a device that could be used to clean up space debris and hazardous materials, according to South Morning China Post (SMCP)

The real-life application comes after Fan Xu, Xi-Qiao Feng and colleagues at Fudan University in Shanghai reported an unknown type of chiral wrinkling pattern on the surface of dehydrated passion fruits in their study published in the journal Nature Computational Science the same day. previously unknown type of wrinkling pattern on the surface of dehydrated passion fruits inspired the invention of a device that could be used to clean up space debris and hazardous materials, according to South Morning China Post (SMCP).

FDA gives clearance to Philips for its AI powered MRI scans

The artificial intelligence software speeds up the process of taking scans.

Philips received clearance from the FDA for its artificial intelligence MR platform that is used to detect cancerous tumors in the head and neck.


FDA clearance for AI technology

The company announced that the FDA gave clearance for Philip’s AI-enabled MRCAT radiotherapy. The clearance, also known as the 510(k) clearance, requires device manufacturers to register, and notify FDA of their intent to market a medical device at least 90 days in advance.

At internal AI conference, Amazon executives discuss using machine learning to revolutionize drug discovery, genomics, clinical trials, and more

Insider obtained documents that reveal the topics, goals and challenges discussed. Together, they show Amazon’s ambition to take on Google’s DeepMind, a pioneer in AI-powered scientific discovery. This could take Amazon from dabbling in healthcare services, and turn it into a potentially serious player in the future of medicine.

“The demarcation line between core Amazon/AWS business and life science and healthcare is shifting,” said Amazon scientist and senior solutions architect Sergey Menis, according to a transcript of his comments seen by Insider. “We are increasingly more specialized in healthcare and life sciences.” An Amazon spokesperson declined to comment.

Menis developed a nanoparticle that underpins a promising HIV vaccine candidate. He was joined at last week’s Amazon Machine Learning Conference by Amazon’s chief medical officer Taha Kass-Hout.

IBM announces system-on-chip AI hardware

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Recent years have seen a growing demand for artificial intelligence (AI) acceleration hardware. IBM has taken note.

In the earliest days of AI, commercial CPU and GPU technologies were enough to handle the technology’s data sizes and computational parameters. But with the emergence of larger datasets and deep learning models, there is now a clear need for purpose-built AI hardware acceleration.

The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence

This highlights the promise and the peril of achieving HLAI: building machines designed to pass the Turing Test and other, more sophisticated metrics of human-like intelligence.8 On the one hand, it is a path to unprecedented wealth, increased leisure, robust intelligence, and even a better understanding of ourselves. On the other hand, if HLAI leads machines to automate rather than augment human labor, it creates the risk of concentrating wealth and power. And with that concentration comes the peril of being trapped in an equilibrium where those without power have no way to improve their outcomes, a situation I call the Turing Trap.

The grand challenge of the coming era will be to reap the unprecedented benefits of AI, including its human-like manifestations, while avoiding the Turing Trap. Succeeding in this task requires an understanding of how technological progress affects productivity and inequality, why the Turing Trap is so tempting to different groups, and a vision of how we can do better.

This is how Artificial Intelligence will Control Humans

NVIDIA’s Megatron Turing AI Model can now have conversations with itself to perpetually improve itself in the hopes of understanding how to best control and influence other people in debates. This sparked a lot of discussions in the AI Community because ever-improving Artificial Intelligences pose real dangers to humanity.

TIMESTAMPS:
00:00 The biggest Black Box.
01:54 Nvidia’s GPT-3 Competitor.
03:23 How these AI’s work.
04:50 The Ethical issues of Black Box AI’s.
08:19 Last Words.

#ai #agi #nvidia