Sam Altman on the one AI policy where OpenAI and Anthropic still disagree:
Brendan Bordelon asked Altman to name a specific policy that Anthropic supports and OpenAI doesn't, at either the federal or state level.
First, he pointed out how much the two companies now agree on:
"You guys are now on the same page when it comes to pacing the frontier of China. Same page with third party evaluators. What's just one differentiator?"
Altman says the difference is which models should face oversight at all:
"The last I heard, one of the differentiators is we don't want any restrictions or testing on anything but the frontier models. We do not want to slow down people that make very powerful, but not the absolute frontier."
Both companies support testing and third-party evaluation. Where they split is scope.
In Altman's framing, OpenAI wants restrictions and testing applied only to frontier models, with nothing below them. That leaves out models he himself calls "very powerful."
He explains the reasoning:
"In the spirit of really focusing on the potential catastrophic risks…"
Then he names the cost directly:
"…even though I believe that if you don't put any testing or any oversight on models that are one or two generations behind the frontier, I accept that bad things will happen with those. I would not go advocate a licensing regime for those."
So OpenAI's position, as @sama states it, has three parts:
Oversight should concentrate on the potential catastrophic risks at the absolute frontier.
Models one or two generations behind should face no testing or oversight requirements.
That will lead to some harm, and he accepts that rather than advocate licensing for those models.
Altman knowingly makes this trade-off and says so plainly. He openly concedes that sub-frontier models will cause harm, and he judges that cost worth paying to keep regulatory attention on catastrophic risk at the top.
The Only Thing That Can Say No Is Not Legally AI
🔗https://t.co/mAmC6n9YJe
hashtag#AIGovernance hashtag#AISafety hashtag#AI hashtag#AutonomousIntelligence hashtag#AgenticAI hashtag#AIAgents
@SingaporeMDDI@MAS_sg@GovTechSG@IMDAsg@AIVerify@AISecurityInst
Twelve roles govern enterprise AI. Not one owns whether it pays.
We can describe AI’s risk in exhaustive detail. Ask for its value and the picture dissolves: governance’s own uncertainty principle.
Part I of my AI governance trilogy:
https://t.co/G0l4eXiDra
Part 1. MAS Finalises AI Risk Guidelines: What Actually Changed :
🔗https://t.co/bqk2T3qfLe
Part 2. How Singapore's AIRG Compares with the EU, and US
🔗https://t.co/V8Um7sahrW
https://t.co/lRMYmOMRXe
#AI#AIGovernance@MAS_sg@IMDAsg@AIVerify@GovTechSG@AISecurityInst
Paid to Disappear: The Five Wages AI Cannot Pay https://t.co/Dztlf4hCqg
A cheque can replace an income. It cannot replace a reason to get up in the morning.
#AI#FutureOfWork#UBI#AIGovernance
Warp founder and CEO Ayush Sharma (@ayushswrites) on what it means to build an AI native product.
Build the product, platform and architecture so every task, starting with deep tax compliance workflows, can be performed by an agent.
(Warp runs payroll, taxes and HR for fast-growing companies using AI agents.)
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Full video on "YC Root Access" YouTube channel, (link in comment)
#Trust is the only currency of the AI age. And once again, #Singapore is minting it first - if we can't govern AI, we can't scale it. @MAS_sg led by example in finalising its #AI Risk Guidelines for the #FinancialServices sector. #AI#AIGovernance#AIRG https://t.co/bVMCqt9Wty