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 Harvey blowing the frontier models out of the water with their first post-train on very hard economically valuable tasks (2x'ing performance on Legal Agent Bench). We're proud to be working alongside them towards this vision.
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 law, but don’t understand how the law is practiced, because this information remains proprietary within firms. Unlike how agents are benchmarked today – starting each task from scratch with a new set of context — lawyers accumulate knowledge over time, building on years of experience.
Calderwood & Harkness makes it possible for agents to do the same. Legal agents do many tasks in the same environment, making it possible to leverage memory and experience to do better work over time.
We’ve had a great time co-developing this benchmark with Harvey’s research team, partnering @ItsJulioPereyra@nikogrupen@gabepereyra. We’ll share more results on this soon.
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 strong open-source models like Inkling.
Congrats to our friends at @thinkymachines !
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
Our CEO @dan_biderman might be the best in the world in the niche intersection of leading an AI lab and cooking delicious food.
We're rolling out our m̶e̶a̶t̶b̶a̶l̶l̶s̶ models to some early customers. Let us know if you want a taste!
In this episode, @EngramLab co-founder and CEO @dan_biderman joins @allenpark to cook Mediterranean meatballs with yellow rice and talk about building AI that actually learns from you: why long context, RAG, and compaction eventually break down, how Engram compresses knowledge
We are thrilled to announce Engram's pivot to dairy farming. Our primary activity will be fostering 🐐s like @jxmnop -- who recently won an ICML outstanding paper award for his work on language model memorization and capacity!
We're incredibly proud to work with Jack every day, and you can too. Come join the farm 🌾
my paper won an award at icml 😁
some thoughts:
• this work was rejected from NeurIPS. i cleaned it up a small amount and it got great reviews from ICML! don't give up
• ICML received 24k submissions and only gives out 7 awards, which is crazy. feeling grateful
• i
John and Jordi from @tbpn are in the pretraining data, but most people aren't.
Frontier models train on trillions of tokens and still have no idea who you are. We're fixing that.
Thanks for hosting us – and banging the gong for Engram. This meant more than you'll ever know.
Engram cofounder @jxmnop just raised $98M to build a new type of AI.
He says models don't need to get smarter over time. Instead, they just need to know you better and better over time.
Jack describes what he's building:
"Our product is a new type of AI. We have a pretty
Models know the internet. @EngramLab believes they should know you.
Congrats to @dan_biderman and the team. few have worked on continual learning longer.
Thank you to @Nasdaq for supporting Engram on our launch day yesterday!
Some have commented that this photo looks AI-generated. It's not. This really happened.
Feel free to send this picture to your moms. We're certainly going to.
By scaling compute on user context, we reduce token spend. But it's about more than lowering cost. To develop expertise is to reduce the energy it takes to solve a problem, freeing capacity to solve harder problems yet
Was great chatting about this with the amazing @LM_Braswell!
The models we use every day are brilliant strangers. They forget your organization the moment a chat ends, then relearn it on the next query.
@EngramLab fixes that. It learns your world once and reuses that memory, matching frontier systems on 1-10% of the tokens.
@Microsoft,
The models we use every day are brilliant strangers. They forget your organization the moment a chat ends, then relearn it on the next query.
@EngramLab fixes that. It learns your world once and reuses that memory, matching frontier systems on 1-10% of the tokens.
@Microsoft,
The models we use every day are brilliant strangers. They forget your organization the moment a chat ends, then relearn it on the next query.
@EngramLab fixes that. It learns your world once and reuses that memory, matching frontier systems on 1-10% of the tokens.
@Microsoft, @NotionHQ, and @Harvey are already testing it within their organizations.
Congratulations to the team, and hear directly from @dan_biderman (CEO and co-founder) and Sabri Eyuboglu (CTO and co-founder) with @LM_Braswell ⬇️
The models we use every day are brilliant strangers. They forget your organization the moment a chat ends, then relearn it on the next query.
@EngramLab fixes that. It learns your world once and reuses that memory, matching frontier systems on 1-10% of the tokens.
@Microsoft,
Today we announced our Initial Public Offering, a humble article on X.
Thanks to the @NYSE for supporting us so early in our journey!
And thanks to all of our lovely supporters here on X dot com for following along. More soon 🔜
629 Followers 7K FollowingIndependence OS :
A machine for human flourishing: making easy things easy and hard things possible, with limitless human agency as both the means and the end.
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2K Followers 2K FollowingAI × XR × Culture | Co-founder @MidBrainAi and @thepointlabs | ex-@volvocars innovation lead |Teaching machines to make sense. Nerd by day rock star by night 🎸