Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
#Anthropic
Andrej Karpathy@karpathyAI 评分6060引用Andrej Karpathy@karpathy
Anthropic@AnthropicAIAI 评分4242
Anthropic@AnthropicAIAI 评分5858Anthropic 宣布向 Genesis Mission 投入 1.5 亿美元,以加深对科学研究与技术发现的投入。同时,Anthropic 将向 15 个以上联邦机构提供 Claude 及技术支持。
Anthropic@AnthropicAI精选AI 评分7070Anthropic 发布 Claude Haiku 5.5,称其是迄今最快、最强的小模型。官方称其平均运行成本比 Claude Haiku 4.5 低约 75%。
引用Claude@claudeaiIntroducing Claude Haiku 5.5: the cheapest, fastest, and most capable small model we’ve ever released. On average, it costs around 75% less to run than Claude Haiku 4.5.
推荐理由:官方给出 Haiku 5.5 的定位与相对上一代的成本降幅,可据此判断小模型选型。
Emad@EMostaqueAI 评分1717引用David Krueger 🦥 ⏸️ ⏹️ ⏪@DavidSKruegerPeople at Anthropic keep telling me they can't coordinate to slow down because of anti-trust, but I've talked to leading lawyers who disagree. Meta spent $2,400,000,000 on lawyers in a single quarter fighting charges that its products hurt kids. How much has Anthropic spent on this anti-trust thing?
Andrej Karpathy@karpathyAI 评分2222很酷的评测。只需问 LLM "陆地还是水域?",并以文本形式给它一个经纬度坐标。问 16,200 次,绘制成图像。模型知道答案。来自对互联网的压缩。
引用Celeste@celestepoastsresults for all claudes
Anthropic@AnthropicAI精选AI 评分6868推荐理由:读者可了解 Claude 在散射振幅九圈计算上的实际表现、成本与独立验证情况。
Anthropic@AnthropicAIAI 评分5858
Andrej Karpathy@karpathyAI 评分4242
Andrej Karpathy@karpathyAI 评分5858引用Claude@claudeaiIntroducing Claude Tag, a new way for teams to work with Claude. In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work.
Andrej Karpathy@karpathy精选AI 评分8282Andrej Karpathy 评价 Claude Fable 5 发布,称其与 Mythos 是同一底层模型但增加了安全防护,基准测试全面 SOTA 且领先明显。
引用Claude@claudeaiFable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.
推荐理由:Karpathy 以第一手使用体验评价 Claude Fable 5 在长任务和复杂问题上的跃升,并给出对软件需求变化的判断。
Andrej Karpathy@karpathyAI 评分2222个人动态:我已加入 Anthropic。我认为未来几年处于 LLM 前沿的工作将尤其具有塑造性。我非常兴奋能加入这里的团队,重回研发工作。我依然对教育怀有深厚的热情,并计划适时恢复这方面的工作。
Andrej Karpathy@karpathyAI 评分3636引用staysaasy@staysaasyThe degree to which you are awed by AI is perfectly correlated with how much you use AI to code.
Mira Murati@miramuratiAI 评分5858