全部 AI 动态

Running MiniCPM5 from @OpenBMB on iPhone Air at 37 tok/s. One of the best open models at 2B parameters, now available in the NobodyWho Chat app.

Arena's @ml_angelopoulos says one of the hardest problems in alignment is that users often can't tell when the model is helping them or hurting them. "You really need alignment signals that are independent. We have three at Arena." "The first is that models take unauthorized actions, which means that you permission them in a certain way, but they break those permissions." "It can cause things like the Hugging Face incident. But it can also cause very mundane problems like losing important information within your company or on your own laptop." "The second signal is called deceptive completion." "The model will tell you that it did something, but it didn't actually do it." "Third is false attribution. It'll attribute intent to the user when that intent was not supposed to be there." "If models are able to do this, then certainly they're not perfectly safe for a user and they're not perfectly aligned to user intent. They might actually hurt people down the line."

Introducing Voyager: the open harness for S-tier video, graphics and games. The Codex for creative work. Most AI tools are built for coding. Voyager is designed to get the best creative results from models like Opus, Astra and DeepSeek. It comes with free graphics, music and video editing tools - or, it can drive Blender, Resolve, After Effects, Ableton and 100+ others. Everything in this thread was made with Voyager. A few of our favorites:

This feels unreal Used Grok Bot today, mostly from my phone I got more done from my phone with Grok Bot than I usually do sitting at my desk - Colab notebooks for Google EmbeddingGemma 2, D1 by LiquidAI inference - Colab notebooks for open source decision models finetunes using Qwen3.5-4B and Gemma 4 E4B as base - Put up a Grok Bots page on my website with all the templates I've been sharing - Worked on the MiniMax H3 face-swap clip - Figured out what's eating my Windows drive and how to free space - Created Security bot and told it to treat outside content as hostile, especially anything that might touch my computers - Worked with my stocks bot on scheduled market updates, news and recommndations

Mathematicians are coping so hard. Suddenly they can not stand AI. 😀 the guild is so badly protecting its turf. The Association for Human Mathematics (AHM), criticised OpenAI's yesterday's release of 722 math manuscripts and urged mathematicians "to discontinue their work with OpenAI". And then Terence Tao's reposted AHM's statement on his blog. Walking away is not a scientific position.

the most common failure case I see is when people are working outside their domain of expertise and don't know how to be precise with their prompts and plans, so they have to spend a lot of turns iterating imprecisely

What if the jagged frontier is mainly math + code (which you can push arbitrarily far with RLVR), and everything else starts to plateau because it is still bottlenecked by human generated data? Model performance in non-verifiable areas has kept improving steadily, albeit much slower than for math and code. But is that steady improvement a side effect of a higher G (itself driven by RLVR), or only a function of the amount of new human data getting injected into training (which is still continually happening on a massive scale)? A lot of things depend on the answer to this question

I benchmarked "Jev-killer" OpenAI Decisions API against Jev for https://HiringCafe.com, serving 2.5 million users. The task is to predict how relevant a user query/resume is to a job description, on a scale of 1-10. OpenAI is 2x more expensive and 5-10% worse. 🧵