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Today we’re introducing Navigator n2. It’s a frontier computer-use model, with just 27B parameters.
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Got "Flowers for Things I Don't Know How to Say" and the Canary Cardboard Cutter for opening packages!
The holidays are fast approaching, so I’m back with my sixth (!!) annual gift guide.
It's got over 100 gift ideas—all things I actually use, love, and recommend.
This started out as a random post idea, but now you’d be surprised how many people ping me asking when the new list , the collection includes a mix of practical stuff with a lot of fun and delight, from high-end products to very affordable items. There are no affiliate links here, and I’m not benefiting from recommending any of these products.
Pro tip: After reading it, point your favorite AI agent at the post and have it brainstorm gifts for your family, friends, and coworkers.
Here's the guide: lennysnewsletter.com/p/lennys-newsl…
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In the @ouraring app, if you scrub over the graph of your heart rate over different times of the day, a dot pulsates with tactile feedback, and it pulsates at a frequency that matches your heart rate at that time :)
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Devi Parikh retweeted
So excited to be part of Warp founding team and partnering with Kevin, Sol & DJ on building out Warp to accelerate scientific discovery starting with helping drug discovery! Checkout warp.xyz
💥 Introducing Warp Sciences, a new company applying AI and robotics to help the world develop new medicines faster.
We’ve raised a $215M Series A led by @lightspeedvp to bring frontier AI out of the browser and into the lab, and build scientific capacity here in America.
I co-founded Warp with my long-time friend @dpatil, FAIR co-founder @manohar_paluri, and drug hunter Sol Reisberg. The early team is full of incredible people like @bkspears9, who helped achieve Q>1 fusion at LLNL.
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Devi Parikh retweeted
There are too many robot companies. I kept having questions like:
• Does Tesla build everything in-house?
• Who uses grippers vs. dexterous hands?
• Who trains on robot data vs. human data?
• Where does NVIDIA fit into the stack?
So I built Robot Overflow, check it out 👇
• Does Tesla build everything in-house?
• Who uses grippers vs. dexterous hands?
• Who trains on robot data vs. human data?
• Where does NVIDIA fit into the stack?
So I built Robot Overflow, check it out 👇
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Devi Parikh retweeted
Today, we’re excited to launch the Datology Curation Studio, customizable frontier data curation for every team training its own models.
Data quality is the ultimate compute multiplier, and Curation Studio makes it easy for everyone.
Data quality is the ultimate compute multiplier, and Curation Studio makes it easy for everyone.
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Devi Parikh retweeted
Today we're launching WebCloneBench: a benchmark which measures a model's ability to explore, copy, build and test various web apps.
For each task, we give the model a reference site from one of Gmail, Google Sheets, Jira, DocuSign, Shopify Admin, Craigslist, Figma, Slack and ed to build a fully feature-complete clone of every part of the application with an 8 hour time limit.
For each task, we give the model a reference site from one of Gmail, Google Sheets, Jira, DocuSign, Shopify Admin, Craigslist, Figma, Slack and ed to build a fully feature-complete clone of every part of the application with an 8 hour time limit.
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Congrats @Jerr_Wu and team! 🚀
Today we're excited to announce @HalluminateAI's $30M Series A led by @oakhcft with participation from @ycombinator, @orangecollectv, @FTPartners, @heavybit, and more.
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Devi Parikh retweeted
Thanks to @hi_angelinayang and Two Set AI for having me on yesterday! I shared how we trained N2, our latest frontier-level computer-use model
Recording is up if you’re curious about the recipe!
youtube.com/watch?v=BB0Cak…
Recording is up if you’re curious about the recipe!
youtube.com/watch?v=BB0Cak…
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Devi Parikh retweeted
Tomorrow, 10am PT: Skanda Vaidyanath from Yutori on how they trained Navigator n2, a 27B computer-use model that leads 4 of 5 industry benchmarks at $1.46 per task.
Free, live, with Q&A. luma.com/1bj2munj
Free, live, with Q&A. luma.com/1bj2munj
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Devi Parikh retweeted
1/ Computer-use agents ≠ GUI agents.
Clicking is only one way to use a computer.
The best agents will code, call tools, use the CLI, and click—using everything a computer provides, and choosing the right interface for each step.
Clicking is only one way to use a computer.
The best agents will code, call tools, use the CLI, and click—using everything a computer provides, and choosing the right interface for each step.
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I haven’t been crocheting as much. And most of it has been very satisfying discs of varying sizes and colors. But this one I am excited about!
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Computer-use in 2026
"What's left? The obvious answer is longer tasks. More steps, more hours. An agent that clicks for longer.
I think this is the wrong answer, ..."
"They can code. They can click. They can't choose."
"Choosing has to be trained, and it can only be trained where it matters."
"What's left? The obvious answer is longer tasks. More steps, more hours. An agent that clicks for longer.
I think this is the wrong answer, ..."
"They can code. They can click. They can't choose."
"Choosing has to be trained, and it can only be trained where it matters."
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Devi Parikh retweeted
Frontier models: $13 to $40+ per task on OSWorld 2.0.
Yutori's Navigator n2: $1.46. 🎯
Served on Crusoe by a 14-person team with no inference stack of their own.
"Because Crusoe maximizes throughput, every token costs less." - @DhruvBatra_, @yutori_ai
↪ crusoe.ai/resources/cust…
Yutori's Navigator n2: $1.46. 🎯
Served on Crusoe by a 14-person team with no inference stack of their own.
"Because Crusoe maximizes throughput, every token costs less." - @DhruvBatra_, @yutori_ai
↪ crusoe.ai/resources/cust…
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