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

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.

Related Topics:AISlowDown ArtificialIntelligence PauseAI TheDeepView

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Apple bets big on Trump economy with historic $500 billion U.S. investment

Published on February 24, 2025

Todayville

Quick Hit:

Apple is committing a historic $500 billion to the U.S. economy in a sweeping initiative aimed at bolstering American innovation and manufacturing. The investment, announced Monday, includes building an AI server factory in Texas, expanding research and development efforts, and hiring 20,000 workers.

Key Details:

Apple’s $500 billion investment will roll out over the next five years, with a focus on artificial intelligence, manufacturing, and workforce development.
The company is doubling its Advanced Manufacturing Fund from $5 billion to $10 billion and establishing an Apple Manufacturing Academy in Detroit.
President Donald Trump took to Truth Social to credit his administration’s economic policies for the massive investment, stating, “Without which, they wouldn’t be investing ten cents.”

Diving Deeper:

Apple’s unprecedented $500 billion investment marks what the company calls “an extraordinary new chapter in the history of American innovation.” The tech giant plans to establish an advanced AI server manufacturing facility near Houston and significantly expand research and development across several key states, including Michigan, Texas, California, and Arizona.

Apple CEO Tim Cook highlighted the company’s confidence in the U.S. economy, stating, “We’re proud to build on our long-standing U.S. investments with this $500 billion commitment to our country’s future.” He noted that the expansion of Apple’s Advanced Manufacturing Fund and investments in cutting-edge technology will further solidify the company’s role in American innovation.

President Trump was quick to highlight Apple’s announcement as a testament to his administration’s economic policies. In a Truth Social post Monday morning, he wrote:

“APPLE HAS JUST ANNOUNCED A RECORD 500 BILLION DOLLAR INVESTMENT IN THE UNITED STATES OF AMERICA. THE REASON, FAITH IN WHAT WE ARE DOING, WITHOUT WHICH, THEY WOULDN’T BE INVESTING TEN CENTS. THANK YOU TIM COOK AND APPLE!!!”

Trump previously hinted at the investment during a White House meeting Friday, revealing that Cook had committed to investing “hundreds of billions of dollars” in the U.S. economy. “That’s what he told me. Now he has to do it,” Trump quipped.

Apple’s expansion will include 20,000 new jobs, with a strong focus on artificial intelligence, silicon engineering, and machine learning. The company also aims to support workforce development through training programs and partnerships with educational institutions.

With Apple’s announcement, the U.S. economy stands to benefit from a major influx of investment into high-tech manufacturing and innovation—further underscoring the tech industry’s continued growth under Trump’s economic agenda.

Artificial Intelligence

Everyone is freaking out over DeepSeek. Here’s why

Published on January 28, 2025

Todayville

From The Deep View

$600 billion collapse

Volatility is kind of a given when it comes to Wall Street’s tech sector. It doesn’t take much to send things soaring; it likewise doesn’t take much to set off a downward spiral.

After months of soaring, Monday marked the possible beginning of a spiral, and a Chinese company seems to be at the center of it.

Alright, what’s going on: A week ago, Chinese tech firm DeepSeek launched R1, a so-called reasoning model, that, according to DeepSeek, has reached technical parity with OpenAI’s o1 across a few benchmarks. But, unlike its American competition, DeepSeek open-sourced R1 under an MIT license, making it significantly cheaper and more accessible than any of the closed models coming from U.S. tech giants.

But the real punchline here doesn’t have to do with R1 at all, but with a previous language model — called V3 — that DeepSeek released in December. DeepSeek was reportedly able to train V3 using a small collection of older Nvidia chips (about 2,000 H800s) at a cost of about $5.6 million.
Still, training is only one cost of many tied to AI development/deployment; while the costs associated with researching, developing, training and operating both R1 and V3 remain either unknown or unconfirmed, DeepSeek’s apparent ability to reach technical parity at a far reduced cost, without state-of-the-art GPU chips or massive GPU clusters, has a lot of implications for America’s now tenuous position in AI leadership. (Though DeepSeek says it is open-sourced, the company did not release its training data).

Since the release of R1, DeepSeek has become the top free app in Apple’s App Store, bumping ChatGPT to the number two slot. In the midst of its spiking popularity, DeepSeek restricted new sign-ups due to large-scale cyberattacks against its servers. And, as Salesforce Chief Marc Benioff noted, “no Nvidia supercomputers or $100M needed,” a point that the market heard loud and clear.

What happened: Led by Nvidia, a series of tech and chip stocks, in addition to the three major stock indices, fell hard in pre-market trading early Monday morning. All told, $1.1 trillion of U.S. market cap was erased within a half hour of the opening bell.

Performance didn’t get better throughout the day. Nvidia closed Monday down 17%, erasing some $600 billion in market capitalization, a Wall Street record. TSMC was down 14%, Arm was down 11%, Broadcom was down 17%, Google was down 4% and Microsoft was down 2%. The S&P fell 1.4% and the Nasdaq fell 3.3%. An Nvidia spokesperson called R1 an “excellent AI advancement.”
This is all going into a week of Big Tech earnings, where Microsoft and Meta will be held to account for the billions of dollars ($80 billion and $65 billion, respectively) they plan to spend on AI infrastructure in 2025, a cost that Wall Street no longer seems to feel quite so good about.

It’s hard to miss the political tensions underlying all of this. The tail end of former President Joe Biden’s time in office was marked in part by an increasingly tense trade war with China, wherein both countries issued bans on the export of materials needed to build advanced AI chips. And with President Trump hell-bent on maintaining American leadership in AI, and despite the chip restrictions that are in place, Chinese companies seem to be turning hardware challenges into a motivation for innovation that challenges the American lead, something they seem keen to drive home.

R1, for instance, was announced at around the same time as OpenAI’s $500 billion Project Stargate, two impactfully divergent approaches.

What’s happening here is that the market has finally come around to the idea that maybe the cost of AI development (hundreds of billions of dollars annually) is too high, a recognition “that the winners in AI will be the most innovative companies, not just those with the most GPUs,” according to Writer CTA Waseem Alshikh. “Brute-forcing AI with GPUs is no longer a viable strategy.”

Wedbush analyst Dan Ives, however, thinks this is just a good time to buy into Nvidia — Nvidia and the rest are building infrastructure that, he argues, China will not be able to compete with in the long run. “Launching a competitive LLM model for consumer use cases is one thing,” Ives wrote. “Launching broader AI infrastructure is a whole other ballgame.”

“I view cost reduction as a good thing. I’m of the belief that if you’re freeing up compute capacity, it likely gets absorbed — we’re going to need innovations like this,” Bernstein semiconductor analyst Stacy Rasgon told Yahoo Finance. “I understand why all the panic is going on. I don’t think DeepSeek is doomsday for AI infrastructure.”

Somewhat relatedly, Perplexity has already added DeepSeek’s R1 model to its AI search engine. And DeepSeek on Monday launched another model, one capable of competitive image generation.

Last week, I said that R1 should be enough to make OpenAI a little nervous. This anxiety spread way quicker than I anticipated; DeepSeek spent Monday dominating headlines at every publication I came across, setting off a debate and panic that has spread far beyond the tech and AI community.

Some are concerned about the national security implications of China’s AI capabilities. Some are concerned about the AI trade. Granted, there are more unknowns here than knowns; we do not know the details of DeepSeek’s costs or technical setup (and the costs are likely way higher than they seem). But this does read like a turning point in the AI race.

In January, we talked about reversion to the mean. Right now, it’s too early to tell how long-term the market impacts of DeepSeek will be. But, if Nvidia and the rest fall hard and stay down — or drop lower — through earnings season, one might argue that the bubble has begun to burst. As a part of this, watch model pricing closely; OpenAI may well be forced to bring down the costs of its models to remain competitive.

At the very least, DeepSeek appears to be evidence that scaling is one, not a law, and two, not the only (or best) way to develop more advanced AI models, something that rains heavily on OpenAI and co.’s parade since it runs contrary to everything OpenAI’s been saying for months. Funnily, it actually seems like good news for the science of AI, possibly lighting a path toward systems that are less resource-intensive (which is much needed!)

It’s yet another example of the science and the business of AI not being on the same page.