Lifeboat Foundation

DeepMind, part of Google, announces General AI breakthrough with a true learning AI. First, they built a dynamic environment (like a game) that can change it’s own layout — XLand. Then, they use Deep Learning and Reinforcement Learning combined — Deep Reinforcement Learning — to create an AI the can learn without training at all or data about what it’s doing. The AI played 700,000 games in 4,000 unique worlds! The AI performed 200 BILLION training steps while performing 3.4 million UNIQUE (non-taught/programmed) tasks.

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Continue reading “General Artificial Intelligence BREAKTHROUGH? You decide! [EP 149]” »

The technology aims to deliver cost and power consumption improvements for deep learning use cases of inference, the companies said. This development follows NeuReality’s emergence from stealth earlier in February with an $8 million seed round to accelerate AI workloads at scale.

AI inference is a growing area of focus for enterprises, because it’s the part of AI where neural networks actually are applied in real application and yield results. IBM and NeuReality claim their partnership will allow the deployment of computer vision, recommendation systems, natural language processing, and other AI use cases in critical sectors like finance, insurance, healthcare, manufacturing, and smart cities. They also claim the agreement will accelerate deployments in today’s ever-growing AI use cases, which are already deployed in public and private cloud datacenters.

NeuReality has competition in Cast AI, a technology company offering a platform that “allows developers to deploy, manage, and cost-optimize applications in multiple clouds simultaneously.” Some other competitors include Comet.ml, Upright Project, OctoML, Deci, and DeepCube. However, this partnership with IBM will see NeuReality become the first start-up semiconductor product member of the IBM Research AI Hardware Center and a licensee of the Center’s low-precision high performance Digital AI Cores.

If you had told college-aged Anne, “22 years from now, you’re going to be leading a research group focused on AI,” I would have said you’re insane. It would not have been possible to make this shift into machine learning without having made friends with machine learning experts — particularly Jones.

After he and I finished our training at MIT, we started a lab together at the Broad Institute in 2,007 and we brainstormed a lot about how machine learning could help biologists. What allowed these ideas to percolate and develop was both of us hopping over the fence and getting familiar with the terminology and power of both sides, biology and computer science. It’s really a productive partnership.

And it’s not just Jones anymore. My group is about 50–50 in terms of people coming from the biology side versus the computational side.

Facebook plans to shut down its decade-old facial recognition system this month, deleting the face scan data of more than one billion users and effectively eliminating a feature that has fueled privacy concerns, government investigations, a class-action lawsuit and regulatory woes.

Jerome Pesenti, vice president of artificial intelligence at Meta, Facebook’s newly named parent company, said in a blog post on Tuesday that the social network was making the change because of “many concerns about the place of facial recognition technology in society.” He added that the company still saw the software as a powerful tool, but “every new technology brings with it potential for both benefit and concern, and we want to find the right balance.”

The decision shutters a feature that was introduced in December 2010 so that Facebook users could save time. The facial-recognition software automatically identified people who appeared in users’ digital photo albums and suggested users “tag” them all with a click, linking their accounts to the images. Facebook now has built one of the largest repositories of digital photos in the world, partly thanks to this software.

The continuation of Processors and GPU’s improving exponentially through Moore’s Law has become very uncertain over the last few years, but recently the top hardware makers: Intel, AMD and Nvidia are now getting ready to deliver the biggest increases in performance we have ever seen. The fastest GPU’s and CPU’s with secret new features are about to release in the next few years to bring Moore’s Law back from the dead. How they manage to create these new powerful chips, I’ll explain in this video. One thing is for sure, Nvidia Lovelace 4,000 series, Zen 4 and Intel Meteor Lake are the future of Hardware and will accelerate the performance gain of next generation hardware.
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.

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TIMESTAMPS:
00:00 The Return of Moore’s Law.
01:19 What is Moore’s Law?
03:33 Intel & Nvidia: New Players in the field?
05:42 How Moore’s Law and AI are connected.
08:02 TSMC to continue Moore’s Law?
10:07 Last Words.
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#nvidia #intel #mooreslaw

For the first time ever, Scientists working for the United States Government and Google have managed to read and understand a portion of a brain in real time. This is going to enable abilities such as reading minds and memories from humans in the future. The question is how long it will take until the government starts secret projects in that area for bad purposes.

The Human Brain Project is the biggest secret scientific research project, based on exascale supercomputers, that aims to build a collaborative ICT-based scientific research infrastructure to allow researchers across Europe and the United States Government to advance knowledge in the fields of neuroscience, computing, and brain-related medicine and in the end to create a device in the form of a brain computer interface that can record and read memories from a human brain.
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.

Continue reading “Reading Memories from the Human Brain — SECRET Brain Project” »

A new algorithm created by researchers at Mount Sinai Hospital, New York, has learned to identify subtle changes in electrocardiograms (ECGs) to predict whether a patient is developing heart failure.

Advances in Artificial Intelligence, neuroscience and robotics have gotten us to a point where people might want to replace their biological limbs with robotic limbs due to there being more and more advantages with every passing day. Things like improved movement, intelligent controlling systems with the help of machine learning AI can help you control these limbs better than you could control your regular old arms, legs and hands.

But how long until we can finally live out our transhuman fantasies and become cyborgs? All this, and a bunch of new and futuristic scientific discoveries in this one review showcasing the most advanced AI Controlled Prosthetics.
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.

Continue reading “YOU WILL want these New Robotic Limbs! — AI-Controlled Prosthetics” »

𝙏𝙝𝙚 𝙒𝙤𝙧𝙡𝙙’𝙨 𝙁𝙞𝙧𝙨𝙩 “𝙏𝙝𝙞𝙣𝙠𝙞𝙣𝙜 𝙍𝙤𝙗𝙤𝙩” 𝙃𝙖𝙨 𝘽𝙚𝙚𝙣 𝘾𝙧𝙚𝙖𝙩𝙚𝙙!

𝙐𝙨𝙞𝙣𝙜 𝙗𝙧𝙖𝙞𝙣-𝙡𝙞𝙠𝙚 𝙣𝙚𝙪𝙧𝙤𝙣𝙨 𝙜𝙧𝙤𝙬𝙣 𝙞𝙣 𝙖 𝙡𝙖𝙗, 𝙅𝙖𝙥𝙖𝙣𝙚𝙨𝙚 𝙨𝙘𝙞𝙚𝙣𝙩𝙞𝙨𝙩𝙨 𝙢𝙖𝙣𝙖𝙜𝙚𝙙 𝙩𝙤 𝙜𝙚𝙩 𝙩𝙝𝙚 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙩𝙤 𝙨𝙩𝙚𝙚𝙧 𝙞𝙩𝙨 𝙬𝙖𝙮 𝙖𝙧𝙤𝙪𝙣𝙙 𝙖 𝙨𝙢𝙖𝙡𝙡 𝙢𝙖𝙯𝙚.

A technique called ‘physical reservoir computing’ enabled it to make sense of the brain waves and dodge barriers. It’s the first time intelligence has ever been “taught” to a robot.

Continue reading “Tech & Science Daily: The world’s first ‘thinking’ robot” »