Replying to @johncrickett
Agreed. Though companies on the flip side will struggle, too. Specifically the ones that do a poor job with retention will also be losers in the end. Doesn't matter how well you grow juniors when the leadership/HR is toxic towards people/labor.
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Replying to @GaryMarcus
You been around too long to be startled by the diminishing returns of “scaling at all costs” lol. All signs pointed to this from years ago 😂
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Replying to @timnitGebru
He has been incredibly disappointing to me the past few months spewing talking points of the big ai industry. And even more so trying to pass a mechanism to bail them Out when they financially fail.
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Joe Muoio retweeted
Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure.
1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity.
2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same.
As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed."
3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: ftc.gov/news-events/news/pre…).
Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead.
4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible.
this.weekinsecurity.com/doze…
ftc.gov/news-events/news/pre…
5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.
They have a vested interest in continuing to push the narrative of agents hacking not being actual hacking so I wonder if this was a mistaken agent loop running inside their networks driven by the 3P taking data …or randomly probing and it worked.
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It’s all security theater.
They got hacked last week and released a cursor Claude extension with malware.
Something makes me think despite the agents running amok internally, they don’t have anything close to 0-trust security practices…
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Replying to @2sush
Not really. Goals are different in industry and school.
I couldn’t use a calculator in elementary maths but I was encouraged to in high school physics. Because the former is for learning basic math and the latter learning physics which builds upon maths being applied.
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Can someone ELI5 what yall think “solving alignment” even means?
Why is this a goal? There is no one point of view or set of principles that ai should align to. The premise is absurd.
Spoke to an Anthropic employee today. They have a near-100% p(doom), but they think the only chance of survival is that they're somehow completely wrong about alignment and it turns out to be solvable, and the only way to get there is by accelerating capabilities as fast as possible. They were much more confident that humanity would never have the political will to do what needs to be done to stop ASI development than that alignment would be solved, even though they think alignment will almost certainly not be solved
They have not called their elected representatives to inform them that this is what they believe
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Replying to @dabit3
Yep!
Tactical issue holding back a lot of teams is the mishmash of ai tooling too. If I’m on a personal cursor sub and you’re on Claude we have totally different cloud tools and no shared notion of identity and access control. So you can’t really get these benefits.
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Replying to @bengoertzel @GaryMarcus
Sure, so ask yourself if there is financial ROI for unproven future algorithms running in data centers being built at both a cost and debt premium today. Debt which they start servicing 3-5 years before the data center is online.
I’d say highly unlikely for ROI
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Replying to @czexan_cowboy @dexhorthy
Earliest I found of the term software factory is 1969. It’s not a new term.
My point is the best software factory is the one bespoke to how you build and deliver your software systems.
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Replying to @mberg2007 @johncrickett
That’s part of the bloat for sure (recent examples including anti game copying and reverse engineering). Surely the engineers and product folks know putting negative instruction in a harness is not very effective, right? …right?
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Replying to @JoeMoCode @d4m1n
Also, my agents don't raise 10k PRs without my having reviewed the important pieces of this prior to that lol. I think we work quite different with AI. If I do raise such a large PR it's made of independently reviewable chunks that I preserve the ability to go back to.
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Replying to @d4m1n
ya, Plans are more important to review. And I am in no way arguing you should look at every line.
But you HAVE to look at SOME of the code. Your initial premise says otherwise :) the code is the only thing that tells you what the code will do (outside the bytecode)
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Replying to @METR_Evals
This is meaningless without you running the benchmarks independently. And would be more meaningful if you run different benchmarks that do not exist in their training set.
Please do this in the future, otherwise you are not actually independently verifying anything of substance
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Replying to @MrPeterLMorris @GaryMarcus
Yep! Now, let's get METR the ability to actually independently verify. Probe models against their own benchmarks that Anthropic has no say in. Maybe not just take the word of whatever Anthropic employees decide to tell them...
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Replying to @mikesimonsen
I am sure Sam is deeply passionate and very good at his job.
Unfortunately, systems are complicated and there are many competing interests. We should still judge the actions (or lack of actions) being taken. There are huge glaring gaps in what he is saying here. I judge that.
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Replying to @d4m1n
Correct. But you miss my point. Maybe because English is so imprecise.
Ai cannot tell you if ai understood your intention. Only you can do that. All your tests and static analysis can pass and the code can still not do what it should.
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