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Humans to attain immortality by 2029? Ex-Google scientist makes striking claim

“You won’t live forever” is a catchphrase which has often been touted and has so far remained the proven truth of life — of humans and almost every other living being on planet earth. But soon, this catchphrase may well become the truth of the past, as humanity steps forward to attain immortality.

A former Google scientist has made a prediction, which if proven right, may redefine human civilisation as we know it. Ray Kurzweil, whose over 85 per cent of 147 predictions have been proven right, has predicted that humans will become immortal by 2029.

The revelation came when the 75-year-old computer scientist dwelled upon genetics, nanotechnology, robotics and more in a YouTube video posted by channel Adagio.

OpenAI CEO responds to Jordan Peterson criticism | Sam Altman and Lex Fridman

Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=L_Guz73e6fw.
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The Open Letter on AI Doesn’t Go Far Enough

The real move at play here, by so called AI Ethics clowns, is a complete shut down of Ai, and AI research. That IS their end goal — end game. See if can really turn it off 6 months. ha! Ok, how about 2 more years! etc… etc…

Ya publicly tipped your hand.


An open letter published today calls for “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.”

This 6-month moratorium would be better than no moratorium. I have respect for everyone who stepped up and signed it. It’s an improvement on the margin.

I refrained from signing because I think the letter is understating the seriousness of the situation and asking for too little to solve it.

Elon Musk and more than 1,000 people sign an open letter calling for a pause on training AI systems more powerful than GPT-4

The non-profit said powerful AI systems should only be developed “once we are confident that their effects will be positive and their risks will be manageable.” It cited potential risks to humanity and society, including the spread of misinformation and widespread automation of jobs.

The letter urged AI companies to create and implement a set of shared safety protocols for AI development, which would be overseen by independent experts.

Apple cofounder Steve Wozniak, Stability AI CEO Emad Mostaque, researchers at Alphabet’s AI lab DeepMind, and notable AI professors have also signed the letter. At the time of publication, OpenAI CEO Sam Altman had not added his signature.

AI computing startup Cerebras releases open source ChatGPT-like models

OAKLAND, California, March 28 (Reuters) — Artificial intelligence chip startup Cerebras Systems on Tuesday said it released open source ChatGPT-like models for the research and business community to use for free in an effort to foster more collaboration.

Silicon Valley-based Cerebras released seven models all trained on its AI supercomputer called Andromeda, including smaller 111 million parameter language models to a larger 13 billion parameter model.

“There is a big movement to close what has been open sourced in AI…it’s not surprising as there’s now huge money in it,” said Andrew Feldman, founder and CEO of Cerebras. “The excitement in the community, the progress we’ve made, has been in large part because it’s been so open.”

How energy-generating synthetic organelles could sustain artificial cells — a powerhouse of the future

Energy production in nature is the responsibility of mitochondria and chloroplasts, and is crucial for fabricating sustainable, synthetic cells in the lab. Mitochondria are “the powerhouses of the cell,” but are also one of the most complex intracellular components to replicate artificially.

In Biophysics Reviews, by AIP Publishing, researchers from Sogang University in South Korea and the Harbin Institute of Technology in China identified the most promising advancements and greatest challenges of artificial mitochondria and chloroplasts.

“If scientists can create artificial mitochondria and chloroplasts, we could potentially develop synthetic cells that can generate energy and synthesize molecules autonomously. This would pave the way for the creation of entirely new organisms or biomaterials,” author Kwanwoo Shin said.

The Futurists Podcast — Cognitive AGI& Robotics with Ben Goertzel

In this weeks episode of The Futurists, cognitive scientist and AI researcher Ben Goertzel joins the hosts to talk the likely path to Artificial General Intelligence. Goertzel is the founder of SingularityNet, Chairman at OpenCog Foundation, and previously as the Chief Scientist at Hanson Robotics he helped create Sophia the robot. Goertzel is on a different level, get ready to step up. Follow @bengoertzel.

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Subscribe and listen to TheFuturists.com Podcast where hosts Brett King and Robert TerceK interview the worlds foremost super-forecasters, thought leaders, technologists, entrepreneurs and futurists building the world of tomorrow. Together we will explore how our world will radically change as AI, bioscience, energy, food and agriculture, computing, the metaverse, the space industry, crypto, resource management, supply chain and climate will reshape our world over the next 100 years. Join us on The Futurists and we will see you in the future!

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Researchers achieve the first silicon integrated ECRAM for a practical AI accelerator

The transformative changes brought by deep learning and artificial intelligence are accompanied by immense costs. For example, OpenAI’s ChatGPT algorithm costs at least $100,000 every day to operate. This could be reduced with accelerators, or computer hardware designed to efficiently perform the specific operations of deep learning. However, such a device is only viable if it can be integrated with mainstream silicon-based computing hardware on the material level.

This was preventing the implementation of one highly promising accelerator—arrays of electrochemical random-access memory, or ECRAM—until a research team at the University of Illinois Urbana-Champaign achieved the first material-level integration of ECRAMs onto . The researchers, led by graduate student Jinsong Cui and professor Qing Cao of the Department of Materials Science & Engineering, recently reported an ECRAM device designed and fabricated with materials that can be deposited directly onto silicon during fabrication in Nature Electronics, realizing the first practical ECRAM-based deep learning accelerator.

“Other ECRAM devices have been made with the many difficult-to-obtain properties needed for deep learning accelerators, but ours is the first to achieve all these properties and be integrated with silicon without compatibility issues,” Cao said. “This was the last major barrier to the technology’s widespread use.”