There's a world in which the most useful model for a lawyer is not the generalist model that knows how to solve math theorems and write Rust pipelines, but one that's designed to be useful just for them.
We're starting to see what that could look like. Incredibly cool to see
Today we're publishing our first research blog, Understanding a Law Firm through Study.
We're sharing a glimpse of a future where agents are trained with native memory:
In collaboration with @harvey, we’re excited to build a new kind of agent environment to reflect realistic knowledge work: an entire synthetic law firm, Calderwood & Harkness, with over 100M (!) tokens of documents and 250 client cases. 💼
Today’s AI models know a lot about the
Our founder @jxmnop recently issued some unfounded claims that got community noted. We deeply apologize for the confusion caused by his original post, the follow-up post, and the follow-up to the follow-up post.
Nevertheless, we stand by his conviction in his own takes---and in
people are underestimating what a big deal this is
this is the ONLY open-weight model that's trained without distilling from OpenAI or Anthropic
• Kimi distills
• GLM distills
• Qwen distills
• Nemotron distills (Kimi & DeepSeek, which counts)
basically a fully different
Readers added context
Per its announcement, Inkling was pretrained from scratch but used a small SFT bootstrap on synthetic data from open models incl. Kimi K2.5. Other models like Llama 3.1 were also trained from scratch without OpenAI/Anthropic distillation.
thinkingmachines.ai/news/introduci…ai.meta.com/blog/meta-llam…
