Elon Musk

Rishi Sunak

Kamala Harris

Bill Gates

Andrew Ng

Yoshua Bengio

Fei-Fei Li

Demis Hassabis

Melanie Mitchell

Sam Altman

Dario Amodei

Geoffrey Hinton

Yann LeCun

Gary Marcus

Max Tegmark

Connor Leahy

Eliezer Yudkowsky

Jaan Tallinn

Marc Andreessen

Eric Schmidt

Norbert Wiener

Arthur Clarke

Irving John Good

Claude Shannon

Hans Moravec

John Smart

There's a "wall of fear-mongering and doomerism" in the AI world right now.

"Worrying about AI today is like worrying about overpopulation on Mars."

Concerns that AI could pose a threat to humanity is "preposterously ridiculous."

Claiming AI poses an existential threat is "such an extreme" and risks "wip[ing] out some of its potential benefits."

"I'm more concerned about... the risks that are here and now [than the existential threat of AI]."

Current AI is "not anywhere close" to posing an existential threat but it could in the future.

AI is the "biggest existential threat" to humanity.

AGI's worst-case scenario would be "lights-out for all of us."

Powerful AI systems "taking control" pose an "existential threat."

AI has a "10 to 25 per cent" chance of destroying humanity.

"The most likely result of building a superhumanly smart AI... is that literally everyone on Earth will die."

Does AI Pose an Existential Threat to Humanity?

Joe Biden

Stuart Russell

Tristan Harris

Cédric O

"AI may cause the most dramatic and sustained economic boom of all time."

AI will make the world "way wealthier" and lead to a "productivity boom."

AI is an "amplifier of human intelligence" and will help the economy thrive.

AI will enable "universal high income" in place of "universal basic income."

"AI may become the heart of future economic growth in the coming decades."

AI harms could include "disrupting economies."

AI could "disrupt job markets."

"AI and technological unemployment" are the "biggest problem we face" from an "economic point of view."

"The moment superintelligent AI emerges, the human economy will end."

Will AI Bring Economic Risks?

Vladimir Putin

Hod Lipson

Yuval Noah Harari

Sundar Pichai

"[T]here will be far greater jobs" thanks to AI and "the jobs of today will get better."

AI will probably "take over a lot of jobs," but could also "create new kinds of jobs"

"[W]e might witness the creation of a massive new unworking class."

AI "is not going to put a lot of people out of work permanently" but work will change.

AI might take away more than just "drudge work."

"AI software will be in direct competition with a lot of people for jobs."

"Automation and AI will take away pretty much all of our jobs."

Eventually, "AI will be able to do everything" and jobs will exist only for "personal satisfaction."

Will AI Replace All Jobs?

Shane Legg

Metaculus

Society is more likely to get "cat-level" or "dog-level" AI years before human-level AI.

"[W]e will eventually reach AGI... and quite possibly before the end of this century."

"Superhuman AIs" will be achieved "between a few years and a couple of decades."

"Digital intelligence" could overtake us within "5 to 20 years."

We may achieve "something like AGI or AGI-like in the next decade."

"[W]e could get to real AGI in the next decade."

"Human-level" AI could occur in "two or three years."

"I'd be surprised if we don't have AGI by [2029]."

Will AI Surpass Human Intelligence, and When?

Extropic, a Boston-area startup founded by former Google quantum computing researchers, has developed thermodynamic sampling units that use probabilistic bits rather than traditional processing methods, claiming energy efficiency gains of up to 10,000 times those of current GPUs.

WinBuzzer

Wired

Extropic, a Boston-area startup founded by former Google quantum computing researchers, has developed thermodynamic sampling units that use probabilistic bits rather than traditional processing methods, claiming energy efficiency gains of up to 10,000 times those of current GPUs.

The XTR-0 development platform consists of a CPU, an FPGA and two sockets for thermodynamic sampling units. Early testing partners include weather modeling companies and government representatives who are evaluating the probabilistic computing approach.

Extropic

The XTR-0 development platform consists of a CPU, an FPGA and two sockets for thermodynamic sampling units. Early testing partners include weather modeling companies and government representatives who are evaluating the probabilistic computing approach.

U.S. data centers consumed 183 terawatt-hours of electricity in 2024 — over 4% of the country's total electricity consumption — and this figure could reach 426 TWh by 2030, according to International Energy Agency estimates.

Pew Research Center

Digital Watch Observatory

U.S. data centers consumed 183 terawatt-hours of electricity in 2024 — over 4% of the country's total electricity consumption — and this figure could reach 426 TWh by 2030, according to International Energy Agency estimates.

Natural gas supplies over 40% of electricity for U.S. data centers as of 2024, while renewables provide about 24%, nuclear power around 20% and coal approximately 15%. Natural gas is projected to remain the largest energy source through 2030.

Scientific American

Natural gas supplies over 40% of electricity for U.S. data centers as of 2024, while renewables provide about 24%, nuclear power around 20% and coal approximately 15%. Natural gas is projected to remain the largest energy source through 2030.

Extropic's thermodynamic sampling units harness electron fluctuations to model probabilities directly in silicon, using probabilistic circuits that sample from distributions rather than performing the traditional matrix-multiplication operations required by current AI systems.

Extropic's thermodynamic sampling units harness electron fluctuations to model probabilities directly in silicon, using probabilistic circuits that sample from distributions rather than performing the traditional matrix-multiplication operations required by current AI systems.

Data center expansion could lead to an 8% increase in average U.S. electricity bills by 2030. High-demand markets are potentially seeing increases exceeding 25%, as utilities pass infrastructure upgrade costs to consumers through rate adjustments.

Data center expansion could lead to an 8% increase in average U.S. electricity bills by 2030. High-demand markets are potentially seeing increases exceeding 25%, as utilities pass infrastructure upgrade costs to consumers through rate adjustments.

Extropic, a Boston-area startup founded by former Google quantum computing researchers, has developed thermodynamic sampling units that use probabilistic bits instead of traditional processing methods, claiming energy efficiency gains of up to 10,000 times over current GPUs.</span

WinBuzzer #

Wired #3082

Extropic, a Boston-area startup founded by former Google quantum computing researchers, has developed thermodynamic sampling units that use probabilistic bits instead of traditional processing methods, claiming energy efficiency gains of up to 10,000 times over current GPUs.

U.S. data centers consumed 183 terawatt-hours of electricity in 2024, representing over 4% of the country's total electricity consumption, with projections showing this figure could reach 426 TWh by 2030 according to International Energy Agency estimates.</span

Pew Research Center #

Scientific American #3812

U.S. data centers consumed 183 terawatt-hours of electricity in 2024, representing over 4% of the country's total electricity consumption, with projections showing this figure could reach 426 TWh by 2030 according to International Energy Agency estimates.

The XTR-0 development platform consists of a CPU, FPGA and two sockets for thermodynamic sampling units, with early testing partners including weather modeling companies and government representatives who are evaluating the probabilistic computing approach.</span

Extropic #

The XTR-0 development platform consists of a CPU, FPGA and two sockets for thermodynamic sampling units, with early testing partners including weather modeling companies and government representatives who are evaluating the probabilistic computing approach.

Natural gas supplies over 40% of electricity for U.S. data centers as of 2024, while renewables provide about 24%, nuclear power around 20% and coal approximately 15%, with natural gas projected to remain the largest energy source through 2030.</span

Natural gas supplies over 40% of electricity for U.S. data centers as of 2024, while renewables provide about 24%, nuclear power around 20% and coal approximately 15%, with natural gas projected to remain the largest energy source through 2030.

Extropic's thermodynamic sampling units harness electron fluctuations to model probabilities directly in silicon, using probabilistic circuits that sample from distributions rather than performing traditional matrix multiplication operations required by current AI systems.</span

Extropic's thermodynamic sampling units harness electron fluctuations to model probabilities directly in silicon, using probabilistic circuits that sample from distributions rather than performing traditional matrix multiplication operations required by current AI systems.

Data center expansion could lead to an 8% increase in average U.S. electricity bills by 2030, with some high-demand markets potentially seeing increases exceeding 25%, as utilities pass infrastructure upgrade costs to consumers through rate adjustments.</span

Data center expansion could lead to an 8% increase in average U.S. electricity bills by 2030, with some high-demand markets potentially seeing increases exceeding 25%, as utilities pass infrastructure upgrade costs to consumers through rate adjustments.

Thermodynamic computing represents a revolutionary breakthrough that harnesses thermal noise as a computational resource instead of fighting it. This paradigm shift eliminates the massive energy waste of digital systems that artificially generate pseudo-randomness, delivering true efficiency gains for AI and optimization tasks.

Thermodynamic computing represents a revolutionary breakthrough that harnesses thermal noise as a computational resource instead of fighting it. This paradigm shift eliminates the massive energy waste of digital systems that artificially generate pseudo-randomness, delivering true efficiency gains for AI and optimization tasks.</span

Viggo Hansen

LinkedIn

LinkedIn #

Explaining Extropic AIs Thermodynamic Computing Through TRIZ: Embracing Randomness as the Solution

The AI boom mirrors the unsustainable telecom bubble of the late 1990s, with massive investment in technology that can't deliver profits fast enough. Companies are already installing polluting generators because the grid lacks capacity for their data centers, threatening economic collapse when reality hits.

The AI boom mirrors the unsustainable telecom bubble of the late 1990s, with massive investment in technology that can't deliver profits fast enough. Companies are already installing polluting generators because the grid lacks capacity for their data centers, threatening economic collapse when reality hits.</span

Paul Krugman

Substack

Substack #

What Happens If AI Hits An Energy Wall?

Artificial Intelligence

Startup Claims 10,000x Energy Savings Over GPUs with New Chip

Environment/energy

Science & technology

Thermodynamic computing is a revolutionary breakthrough that harnesses thermal noise as a computational resource instead of fighting it. This paradigm shift eliminates the massive energy waste of digital systems that artificially generate pseudo-randomness, delivering true efficiency gains for AI and optimization tasks.

Thermodynamic computing is a revolutionary breakthrough that harnesses thermal noise as a computational resource instead of fighting it. This paradigm shift eliminates the massive energy waste of digital systems that artificially generate pseudo-randomness, delivering true efficiency gains for AI and optimization tasks.

Extropic's XTR-0 is recycled stochastic computing dressed in thermodynamic buzzwords — a tiny FPGA toy for niche RNG tasks. Lacking scalable benchmarks, it ignores analog pitfalls like chip variability and verification nightmares. Amid GPU dominance, this unproven prototype risks vaporware status, fooling investors with sci-fi flair.

Extropic's XTR-0 is recycled stochastic computing dressed in thermodynamic buzzwords — a tiny FPGA toy for niche RNG tasks. Lacking scalable benchmarks, it ignores analog pitfalls like chip variability and verification nightmares. Amid GPU dominance, this unproven prototype risks vaporware status, fooling investors with sci-fi flair.

Y Combinator

Extropic is building thermodynamic computing hardware

AI has hit an energy wall. The AI boom mirrors the unsustainable telecom bubble of the late 1990s, with massive investment in technology that can't deliver profits fast enough. Companies are already installing polluting generators because the grid lacks capacity for their data centers, threatening economic collapse when reality hits.

AI has hit an energy wall. The AI boom mirrors the unsustainable telecom bubble of the late 1990s, with massive investment in technology that can't deliver profits fast enough. Companies are already installing polluting generators because the grid lacks capacity for their data centers, threatening economic collapse when reality hits.

Startup Claims 10,000x Energy Savings Over GPUs with New Chip

Startup Claims 10,000x Energy Savings Over GPUs with New Chip

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Mitchell

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