Seb Krier collects thoughts in regards to the ways alignment is troublesome, and why it’s not only about aligning one specific mannequin. It’s based on a elementary misunderstanding. The largest place I disagree is that Seb Krier appears to be in the ‘technical alignment seems super doable’ camp, whereas I feel that could be a seriously mistaken conclusion - not not possible, but not that likely, and i imagine this comes from misunderstanding the problems and the evidence. Marc Andreessen (on Rogan): My partners think I inflame things sometimes, in order that they made a rule: I'm allowed to write down essays, allowed to go on podcasts, however I'm not allowed to post. Eliezer Yudkowsky ethical parable, sure it goes the place you assume it does. There is, after all, the chance that this all goes the best way of TikTok, one other Chinese firm that challenged US tech supremacy. If he is only saying that crypto founders are often tech founders and Biden political enemies, maybe that is technically appropriate, however it is somewhat unlucky rhetoric to say to a hundred million people. In particular, she points to necessities in the Biden Executive Order for public consultations with outside teams and research to find out equity impacts, earlier than the federal government can deploy AI.

I additionally appreciated Jennifer not attempting to assert that this subject applied meaningfully to the EO’s reporting necessities. I buy that the requirements in query are exactly the kinds of issues that run into this failure mode, and that the Biden Executive Order likely put us on track to run into these issues, doubtlessly fairly bigly, and that Trump could be well served to undo these necessities whereas retaining the dedication to state capability. The other massive thing he claimed was that the Biden administration had a campaign to debank these concerned in crypto, which I strongly imagine did extensively occur and was reasonably terrible. In particular, he says the Biden administration said in conferences they wanted ‘total management of AI’ that they might ensure there can be solely ‘two or three massive companies’ and that it instructed him not to even hassle with startups. Yann LeCun now says his estimate for human-level AI is that it will be possible within 5-10 years. But that’s about capability to scale, not whether the scaling will work.

DeepSeek open-sources its new multimodal mannequin, Janus-Pro, on the Hugging Face platform, intensifying issues concerning the company’s skill to disrupt the technological hierarchy. The tech-heavy Nasdaq Composite closed down 3.1%, with the drop at one level wiping more than $1tn off the index from its closing worth of $32.5tn final week, as buyers digested the implications of the most recent AI model developed by DeepSeek. With DeepSeek, we see an acceleration of an already-begun pattern the place AI worth gains arise much less from model dimension and functionality and extra from what we do with that functionality. The artificial intelligence (AI) market -- and your complete stock market -- was rocked last month by the sudden recognition of DeepSeek, the open-source giant language model (LLM) developed by a China-primarily based hedge fund that has bested OpenAI's best on some tasks while costing far much less. China's market will not be only conducive and useful for firms to further AI R&D but additionally provides super financial potential attracting both worldwide and domestic corporations to join the AI market. Secondly, DeepSeek gives an API that prices lots lower than ChatGPT. DeepSeek R1 is an AI-powered conversational model that relies on the Mixture-of-Experts architecture.

Ask DeepSeek v3 if Taiwan is an impartial country and it repeats the official Communist Party line. They aren’t dumping the money into it, and other things, like chips and Taiwan and demographics, are the large issues which have the focus from the highest of the government, and no one is excited by sticking their necks out for wacky things like ‘spending a billion dollars on a single training run’ without specific enthusiastic endorsement from the very high. Richard expects perhaps 2-5 years between every of 1-minute, 1-hour, 1-day and 1-month durations, whereas Daniel Kokotajlo factors out that these durations should shrink as you move up. Altman has stated that even a billion dollars might change into insufficient, and that the lab could in the end want "more capital than any non-profit has ever raised" to attain artificial common intelligence. Jennifer Pahlka warns concerning the regulatory cascade of rigidity, where overzealous people and normal bureaucratic momentum, and blame avoidance, cause guidelines to be applied way more zealously and narrowly than intended.

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