2026 被视为 AI 拐点：Claude Fable 5.2 发布与超智能预测提前

竞争层面，Google 的 Gemini 4 Carbon 被评价为已大幅追平，且 Google 声称正用自己的模型开展研究并做出新发现，传闻中的后继版本 Krypton 已在测试。预测方面，AI 2027 的作者团队 AI Futures Project 更新了时间表：在无重大放缓的前提下，能完成一队顶级人类 AI 研究员工作的 AI 可能于 2027 年出现，AI 加速 AI 研究的进程比原剧本提前了五个月。OpenAI 还表示其内部系统给出了纳维-斯托克斯千禧年大奖难题的一个解。

作者认为从 2024 年底 o1 发布以来能力增速持续加快，判断 2026 年起飞已经开始，2027 年可能是超智能之年。

Let me briefly sum up where we are with AI.

Everyone can feel it and everyone can see it. I believe 2026 is the turning point. We see major advances every day, but with all the excitement about the latest benchmarks, it’s easy to lose sight of the bigger picture.

Anthropic has just released Claude Fable 5.2, its latest flagship model. It’s outstanding. Anyone who has tested it knows how good it is, and in its blog posts, Anthropic has also highlighted advances beyond coding: new findings in physics and hardware design, as well as a method for predicting viral protein structures developed with Mythos 5.2.

Fable 5.2 even built an operating system prototype by coordinating more than 1,000 subagents over eight days. At the same time, Anthropic acknowledged in its system card that it has a separate, unreleased research model that is somewhat more capable than Mythos 5.2. This could be “Model 4,” although that connection has not been confirmed.

Meanwhile, the competition isn’t slowing down. Google has caught up in a big way, and Gemini 4 Carbon is outstanding. Google also says it is using its own models for research and making new discoveries. Rumors suggest that a successor called Krypton is already being tested, though its capabilities remain unconfirmed.

Today, the authors of AI 2027 updated their prediction. The AI Futures Project now forecasts that AI capable of doing the work of a team of top human AI researchers will likely arrive in 2027, absent a major slowdown. They estimate that AI-driven acceleration of AI research is already five months ahead of their original scenario.

And we shouldn’t forget what AI systems have already achieved in mathematics. OpenAI says an internal system produced a solution to the Navier–Stokes Millennium Prize Problem. And this model is already outdated, as OpenAI said in their blogpost.

What I’m trying to say is this: I regularly say that the takeoff began in 2026 and that 2027 will be a crazy year. Perhaps the craziest year in human history. But when we look back on this year, I think it will become clear just how crazy 2026 already was.

I’ve devoted myself to AI since GPT-3.5, and I now work full-time to make this technological revolution tangible. Just a few years ago, LLMs like GPT-4 seemed like stochastic parrots. They hallucinated and, compared with today’s models, felt like trivial machines. Of course, they were never actually trivial. But looking back, the pace of development since o1 in late 2024 has kept increasing, and now the sudden explosion in capabilities feels tangible.

So enjoy these last months of relative calm. I believe 2027 will be the year of superintelligence. And nothing will be the same again.

This report is categorized under AITOP's "Industry" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Claude Fable 5.2, Gemini 4 Carbon, OpenAI, Anthropic.

Source attribution: curated from kimmonismus (@kimmonismus). Cross-source corroboration: 11 independent sources have covered this development (including TestingCatalog, Rowan Cheung, Artificial Analysis), confirming industry-wide signal strength.