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It’s been only a few days since OpenAI revealed its newest flagship generative mannequin, o1, to the world. Marketed as a “reasoning” mannequin, o1 basically takes longer to “think” about questions earlier than answering them, breaking down issues and checking its personal solutions.
There’s a fantastic many issues o1 can’t do properly — and OpenAI itself admits this. However on some duties, like physics and math, o1 excels regardless of not essentially having extra parameters than OpenAI’s earlier top-performing mannequin, GPT-4o. (In AI and machine studying, “parameters,” normally within the billions, roughly correspond to a mannequin’s problem-solving expertise.)
And this has implications for AI regulation.
California’s proposed invoice SB 1047, for instance, imposes security necessities on AI fashions that both value over $100 million to develop or have been educated utilizing compute energy past a sure threshold. Fashions like o1, nonetheless, display that scaling up coaching compute isn’t the one manner to enhance a mannequin’s efficiency.
In a submit on X, Nvidia analysis supervisor Jim Fan posited that future AI techniques might depend on small, easier-to-train “reasoning cores” versus the training-intensive architectures (e.g., Meta’s Llama 405B) that’ve been the pattern these days. Current educational research, he notes, have proven that small fashions like o1 can vastly outperform giant fashions given extra time to noodle on questions.
So was it short-sighted for policymakers to tie AI regulatory measures to compute? Sure, says Sara Hooker, head of AI startup Cohere’s analysis lab, in an interview with TechCrunch:
[o1] sort of factors out how incomplete a viewpoint that is, utilizing mannequin measurement as a proxy for threat. It doesn’t have in mind the whole lot you are able to do with inference or operating a mannequin. For me, it’s a mixture of dangerous science mixed with insurance policies that put the emphasis on not the present dangers that we see on the planet now, however on future dangers.
Now, does that imply legislators ought to rip AI payments up from their foundations and begin over? No. Many have been written to be simply amendable, beneath the idea that AI would evolve far past their enactment. California’s invoice, as an example, would give the state’s Authorities Operations Company the authority to redefine the compute thresholds that set off the regulation’s security necessities.
The admittedly tough half can be determining which metric may very well be a greater proxy for threat than coaching compute. Like so many different facets of AI regulation, it’s one thing to ponder as payments across the U.S. — and world — march towards passage.
Information
First reactions to o1: Max bought preliminary impressions from AI researchers, startup founders, and VCs on o1 — and examined the mannequin himself.
Altman departs security committee: OpenAI CEO Sam Altman stepped down from the startup’s committee liable for reviewing the security of fashions resembling o1, doubtless in response to issues that he wouldn’t act impartially.
Slack turns into an agent hub: At its mother or father firm Salesforce’s annual Dreamforce convention, Slack introduced new options, together with AI-generated assembly summaries and integrations with instruments for picture era and AI-driven internet searches.
Google begins flagging AI pictures: Google says that it plans to roll out modifications to Google Search to make clearer which pictures in outcomes have been AI generated — or edited by AI instruments.
Mistral launches a free tier: French AI startup Mistral launched a brand new free tier to let builders fine-tune and construct take a look at apps with the startup’s AI fashions.
Snap launches a video generator: At its annual Snap Companion Summit on Tuesday, Snapchat introduced that it’s introducing a brand new AI video-generation software for creators. The software will permit choose creators to generate AI movies from textual content prompts and, quickly, from picture prompts.
Intel inks main chip deal: Intel says it would co-develop an AI chip with AWS utilizing Intel’s 18A chip fabrication course of. The businesses described the deal as a “multi-year, multi-billion-dollar framework” that might doubtlessly contain further chip designs.
Oprah’s AI particular: Oprah Winfrey aired a particular on AI with friends resembling OpenAI’s Sam Altman, Microsoft’s Invoice Gates, tech influencer Marques Brownlee, and present FBI director Christopher Wray.
Analysis paper of the week
We all know that AI may be persuasive, however can it dig out somebody deep in a conspiracy rabbit gap? Properly, not all by itself. However a brand new mannequin from Costello et al. at MIT and Cornell could make a dent in beliefs about unfaithful conspiracies that persists for at the very least a pair months.
Within the experiment, they’d individuals who believed in conspiracy-related statements (e.g., “9/11 was an inside job”) speak with a chatbot that lightly, patiently, and endlessly supplied counterevidence to their arguments. These conversations led the people concerned to stating a 20% discount within the related perception two months later, at the very least so far as this stuff may be measured. Right here’s an instance of one of many conversations in progress:
It’s unlikely that these deep into reptilians and deep state conspiracies are more likely to seek the advice of or imagine an AI like this, however the strategy may very well be more practical if it have been used at a crucial juncture like an individual’s first foray into these theories. As an example, if an adolescent searches for “Can jet fuel melt steel beams?” they might be expertise a studying second as an alternative of a tragic one.
Mannequin of the week
It’s not a mannequin, but it surely has to do with fashions: Researchers at Microsoft this week revealed an AI benchmark known as Eureka aimed toward (of their phrases) “scaling up [model] evaluations … in an open and transparent manner.”
AI benchmarks are a dime a dozen. So what makes Eureka totally different? Properly, the researchers say that, for Eureka — which is definitely a set of current benchmarks — they selected duties that stay difficult for “even the most capable models.” Particularly, Eureka checks for capabilities typically ignored in AI benchmarks, like visual-spatial navigation expertise.
To indicate simply how tough Eureka may be for fashions, the researchers examined techniques, together with Anthropic’s Claude, OpenAI’s GPT-4o, and Meta’s Llama, on the benchmark. No single mannequin scored properly throughout all of Eureka’s checks, which the researchers say underscores the significance of “continued innovation” and “targeted improvements” to fashions.
Seize bag
In a win for skilled actors, California handed two legal guidelines, AB 2602 and AB 1836, proscribing using AI digital replicas.
The laws, which was backed by SAG-AFTRA, the performers’ union, requires that corporations counting on a performer’s digital duplicate (e.g., cloned voice or picture) give a “reasonably specific” description of the duplicate’s meant use and negotiate with the performer’s authorized counsel or labor union. It additionally requires that leisure employers achieve the consent of a deceased performer’s property earlier than utilizing a digital duplicate of that individual.
Because the Hollywood Reporter notes in its protection, the payments codify ideas that SAG-AFTRA fought for in its 118-day strike final yr with studios and main streaming platforms. California is the second state after Tennessee to impose restrictions on using digital actor likenesses; SAG-AFTRA additionally sponsored the Tennessee effort.
