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Artificial Intelligence

Poll: Despite global pressure, Americans want the tech industry to slow down on AI

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From The Deep View

A little more than a year ago, the Future of Life Institute published an open letter calling for a six-month moratorium on the development of AI systems more powerful than GPT-4. Of course, the pause never happened (and we didn’t seem to stumble upon superintelligence in the interim, either) but it did elicit a narrative from the tech sector that, for a number of reasons, a pause would be dangerous.
  • One of these reasons was simple: sure, the European Union could potentially instate a pause on development — maybe the U.S. could do so as well — but there’s nothing that would require other countries to pause, which would let these other countries (namely, China and Russia) to get ahead of the U.S. in the ‘global AI arms race.’
As the Pause AI organization themselves put it: “We might end up in a world where the first AGI is developed by a non-cooperative actor, which is likely to be a bad outcome.”
But new polling shows that American voters aren’t buying it.
The details: A recent poll conducted by the Artificial Intelligence Policy Institute (AIPI) — and first published by Time — found that Americans would rather fall behind in that global race than skimp on regulation.
  • 75% of Republicans and 75% of Democrats said that “taking a careful controlled approach” to AI — namely by curtailing the release of tools that could be leveraged by foreign adversaries against the U.S. — is preferable to “moving forward on AI as fast as possible to be the first country to get extremely powerful AI.”
  • A majority of voters are also in favor of the application of more stringent security measures at the labs and companies developing this tech.
The polling additionally found that 50% of voters surveyed think the U.S. should use its position in the AI race to prevent other countries from building powerful AI systems by enforcing “safety restrictions and aggressive testing requirements.”
Only 23% of Americans polled believe that the U.S. should eschew regulation in favor of being the first to build a more powerful AI.
  • “What I perceive from the polling is that stopping AI development is not seen as an option,” Daniel Colson, the executive director of the AIPI, told Time. “But giving industry free rein is also seen as risky. And so there’s the desire for some third way.”
  • “And when we present that in the polling — that third path, mitigated AI development with guardrails — is the one that people overwhelmingly want.”
This comes as federal regulatory efforts in the U.S. remain stalled, with the focus shifting to uneven state-by-state regulation.
Previous polling from the AIPI has found that a vast majority of Americans want AI to be regulated and wish the tech sector would slow down on AI; they don’t trust tech companies to self-regulate.
Colson has told me in the past that the American public is hyper-focused on security, safety and risk mitigation; polling published in May found that “66% of U.S. voters believe AI policy should prioritize keeping the tech out of the hands of bad actors, rather than providing the benefits of AI to all.”
Underpinning all of this is a layer of hype and an incongruity of definition. It is not clear what “extremely powerful” AI means, or how it would be different from current systems.
Unless artificial general intelligence is achieved (and agreed upon in some consensus definition by the scientific community), I’m not sure how you measure “more powerful” systems. As current systems go, “more powerful” doesn’t mean much more than predicting the next word at slightly greater speeds.
  • Aggressive testing and safety restrictions are a great idea, as is risk mitigation.
  • However, I think it remains important for regulators and constituents alike to be aware of what risks they want mitigated. Is the focus on mitigating the risk of a hypothetical superintelligence, or is it on mitigating the reality of algorithmic bias, hallucination, environmental damage, etc.?
Do people want development to slow down, or deployment?
To once again call back Helen Toner’s comment of a few weeks: how is AI affecting your life, and how do you want it to affect your life?
Regulating a hypothetical is going to be next to impossible. But if we establish the proper levels of regulation to address the issues at play today, we’ll be in a better position to handle that hypothetical if it ever does come to pass.

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Alberta

AI-driven data centre energy boom ‘open for business’ in Alberta

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From the Canadian Energy Centre

By Deborah Jaremko and Will Gibson

“These facilities need 24/7, super-reliable power, and there’s only one power generation fuel that has any hope of keeping up with the demand surge: natural gas”

Data centres – the industrial-scale technology complexes powering the world’s growing boom in artificial intelligence – require reliable, continuous energy. And a lot of it.

“Artificial Intelligence is the next big thing in energy, dominating discussions at all levels in companies, banks, investment funds and governments,” says Simon Flowers, chief analyst with energy consultancy Wood Mackenzie.

The International Energy Agency (IEA) projects that the power required globally by data centres could double in the next 18 months. It’s not surprising given a search query using AI consumes up to 10 times the energy as a regular search engine.

The IEA estimates more than 8,000 data centres now operate around the world, with about one-third located in the United States. About 300 centres operate in Canada.

It’s a growing opportunity in Alberta, where unlike anywhere else in the country, data centre operators can move more swiftly by “bringing their own power.”

In Alberta’s deregulated electricity market, large energy consumers like data centres can build the power supply they need by entering project agreements directly with electricity producers instead of relying solely on the power of the existing grid.

Between 2018 and 2023, data centres in Alberta generated approximately $1.3 billion in revenue, growing on average by about eight percent per year, lawyers with Calgary-based McMillan LLP wrote in July.

“Alberta has a long history of building complex, multi-billion-dollar infrastructure projects with success and AI data centres could be the next area of focus for this core competency,” McMillan’s Business Law Bulletin reported.

In recent years, companies such as Amazon and RBC have negotiated power purchase agreements for renewable energy to power local operations and data centres, while supporting the construction of some of the country’s largest renewable energy projects, McMillan noted.

While the majority of established data centres generally have clustered near telecommunications infrastructure, the next wave of projects is increasingly seeking sites with electricity infrastructure and availability of reliable power to keep their servers running.

The intermittent nature of wind and solar is challenging for growth in these projects, Rusty Braziel, executive chairman of Houston, Texas-based consultancy RBN Energy wrote in July

“These facilities need 24/7, super-reliable power, and there’s only one power generation fuel that has any hope of keeping up with the demand surge: natural gas,” Braziel said.

TC Energy chief operating officer Stan Chapman sees an opportunity for his company’s natural gas delivery in Canada and the United States.

“In Canada, there’s around 300 data centre operations today. We could see that load increasing by one to two gigawatts before the end of the decade,” Chapman said in a conference call with analysts on August 1.

“Never have I seen such strong prospects for North American natural gas demand growth,” CEO François Poirier added.

Alberta is Canada’s largest natural gas producer, and natural gas is the base of the province’s power grid, supplying about 60 percent of energy needs, followed by wind and solar at 27 percent.

“Given the heavy power requirements for AI data centres, developers will likely need to bring their own power to the table and some creative solutions will need to be considered in securing sufficient and reliable energy to fuel these projects,” McMillan’s law bulletin reported.

The Alberta Electric System Operator (AESO), which operates the province’s power grid, is working with at least six proposed data centre proposals, according to the latest public data.

“The companies that build and operate these centres have a long list of requirements, including reliable and affordable power, access to skilled labour and internet connectivity,” said Ryan Scholefield, the AESO’s manager of load forecasting and market analytics.

“The AESO is open for business and will work with any project that expresses an interest in coming to Alberta.”

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Artificial Intelligence

Elon Musk is building the ‘most powerful Artificial Intelligence training cluster in the world’

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News release from The Deep View

Elon Musk’s xAI has ended talks with Oracle to rent more specialized Nvidia chips — in what could have been a $10 billion deal — according to The Information.
Musk is instead buying the chips himself, all to begin putting together his planned “gigafactory of compute.”
The details: Musk confirmed in a post on Twitter that xAI is now working to build the “gigafactory” internally.
  • Musk explained that the reason behind the shift is “that our fundamental competitiveness depends on being faster than any other AI company. This is the only way to catch up.”
  • “xAI is building the 100k H100 system itself for fastest time to completion,” he said. “Aiming to begin training later this month. It will be the most powerful training cluster in the world by a large margin.”
xAI isn’t the only one trying to build a supercomputer; Microsoft and OpenAI, also according to The Information, have been working on plans for a $100 billion supercomputer nicknamed “Stargate.”
Why it matters: The industry is keen to pour more and more resources into the generation of abstractly more powerful AI models, and VC investments into AI companies, as we noted yesterday, are growing.
But at the same time, concerns about revenue and return on investment are growing as well, with a growing number of analysts gaining confidence in the idea that we are in a bubble of high costs and low returns, something that could be compounded by multi-billion-dollar supercomputers.
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