#现象/趋势
#现象/趋势
今日 23 条"用户反映 token 用量不足,建议开源私人中转站;现有 cc swap 等工具不够便捷。关注订阅与 API 费率比。"
引用Tibo@thsottiauxThe results of this poll has gotten me confused. I definitely thought it would sway much more favorably in the 2X direction across Pro 100/200/500 at the cost of bringing back 5h limits in order to smoothen the demand curve.
研究者应考虑公开分享自己的RL环境,以促进整个领域的发展。尽管美国前沿实验室分享面临困难,但相信这将对领域和世界产生巨大影响!开源社区会将研究成果迅速转化为可用训练环境。
引用Naveen@NaveenKumar__TThis is how open source should work. A closed lab publishes research, and within days the community turns it into training environments anyone can use. Early and rough, as Clem says, but the direction is lovely. #OpenSource #AI
恐怖组织如何使用AI:博科圣地使用前沿AI的案例研究
推荐理由:原文揭示了恐怖组织使用前沿AI进行攻击和日常运营,对政策制定者、安全社区和AI开发者提出了新的挑战。
"约75%的人未曾接触LLM,20%的人偶尔使用ChatGPT等免费产品,0.2%的人使用前沿LLM进行复杂项目,0.00006%的人内部访问前沿系统,认知差距因问题规模、领域和技术细节等因素扩大。"
引用Andrej Karpathy@karpathyJudging 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.
- 引用Riley Coyote@RileyRalmuto
you are *not* ready for what i've concocted for this app since posting this. hot damn Opus 5.5 is changing my life, dude. ambient intelligence, with @typesafeai's Jev as your agent's tendrils. meaning: your agent is always with you, sees what you see, uses your computer through Jev, writes and dictates text on screen through Haiku (so it's fast and cheap), and reasons // acts as your agent. for me that means Opus 5.5 via CC. turns out when you are building something and tell claude "my primary goal is for this to feel magical for the user. like it shouldn't be possible"...it works. 😅
2026年国际人工智能安全报告发布
推荐理由:报告由多位专家撰写,为政策制定者提供了关于通用人工智能的科学理解和风险评估的权威证据基础。
RSI 的定义是什么?AI 公司如 Google、Anthropic 和 OpenAI 在 RSI 方面的进展情况。
引用imjustnewatai@imjustnewataiSome rumors I've heard. I'll start with Google, then Anthropic and OpenAI. Google: Insiders say Google has either cracked RSI (recursive self-improvement) or is very close. Their pace has picked up fast in recent months. They went from GPT-5 level to Opus 5.5 level in months, and speculation is that RSI made that possible. Anthropic: About a week ago, Anthropic started a new pretraining run. It is not Fable 5.5 but what would become Fable 6, or something bigger, to catch up to OpenAI's Bel. OpenAI: Bel (it may have another codename) is the model behind the math results OpenAI published a few days ago, and RSI apparently helped there too. From what I'm hearing, OpenAI, Anthropic, and Google are all very close to cracking RSI or already have. It will get scary and exciting at the same time.























