Tara Rezaei

Stopped by their office last week. Awesome group.

Lots of excitement around the product. Would be a special time to join the team.

@ekellbuch Nice!

Very excited to release Terminal-Bench 2.1! Coding agents are among the most economically consequential deployments of LLMs to date. As agents improve, benchmark reliability matters more. We audited TB2.0 and found and corrected issues in 28/89 tasks. 30% of the benchmark! But the rankings survived, absolute scores moved up to 12pp!

@PreetumNakkiran 🤔

Doing good research (in any domain) is hard. But why, exactly? Can we identify and unblock these barriers to science in a generic way, using technology? What would it mean to “solve research”? If these questions excite you… come build with us.

Quick updates.

@eumycotan A banger

Whiteboarding is a critical skill to wallpaper R&D process🤝

Enterprise wallpaper design doing well🤝

Anthropic reaearcher leaves to rethink wallpaper design with AI! @bneyshabur congrats, amazing timing.

@flappyairplanes Soaring high! Congrats! 🛫

Announcing Flapping Airplanes! We’ve raised $180M from GV, Sequoia, and Index to assemble a new guard in AI: one that imagines a world where models can think at human level without ingesting half the internet.

@0xSigil @gabriel1 @0xSigil gods work

The most capable individuals are learning and shipping 1000x faster using AI. I sat down with Gabriel Petersson (@gabriel1) - a high school dropout who self-taught Math & ML with AI and is now an AI Researcher at OpenAI. We deep dive into the most important traits to thrive in the age of infinite leverage: – How to learn hard skills insanely fast with AI – Dropping out in Sweden → America on the O-1 @extraordinary visa - How to get hired by the best when you are a nobody – How to turn prompting into a daily habit – Why America is still the launchpad for ambitious builders - Breaking down Gabriel's most iconic tweets Curiosity + Agency + AI will take you further than any legacy credential Timestamps: 01:12 - Swedish high-school dropout → OpenAI research scientist 03:04 - First startup & sales hacks: door-knocking, instant A/B tests 05:28 - Couch-life grind & learning to code under pressure 08:16 - Learning by doing: top-down vs bottom-up; what schools miss about AI 12:10 - Recursive learning with ChatGPT: ELI5, intuition, gap-filling 16:20 - Prompting habits, make AI your always-on tutor 22:16 - Research workflow: papers, code inserts; “shortcuts to foundations” 27:13 - Feedback obsession, elite code reviews, AI as reviewer 33:12 - Path to the US🇺🇸 Midjourney, getting the O-1 @extraordinary visa, shipping demos that signal skill 39:29 - bypass recruiters via proof of work, risk-free trials & academia hot takes 55:06 - why San Francisco; visas & how to move; final pep talk

@appliedcompute Congrats!

Generalists are useful, but it’s not enough to be smart. Advances come from specialists, whether human or machine. To have an edge, agents need specific expertise, within specific companies, built on models trained on specific data. We call this Specific Intelligence. It's what we're building at Applied Compute. We unlock the latent knowledge inside a company, use it to train custom models, and deploy an in-house agent workforce that reports to your team. We work with sophisticated companies that have already captured early gains from general models, like @cognition, @DoorDash, and @mercor_ai. They’re pulling even further ahead with proprietary in-house agents that don’t need to wait for the next public model release. Together, we are building and validating models and agents in days instead of months, achieving state-of-the-art performance on customer evals. Our team has high density and low latency. Our founders all worked on different parts of this problem while they were researchers at OpenAI — @ypatil125 as a key member on the agentic software engineer effort (Codex), @rhythmrg as a core contributor to the first RL-trained reasoning model (o1), and @lindensli as a core contributor on ML systems and infrastructure for RL training. Two-thirds of the team are former founders, and everyone brings a deep technical background, from top AI researchers to Math Olympiad winners. We are backed by $80M in funding from Benchmark, Sequoia, Lux, Elad Gil, Victor Lazarte, Omri Casspi, and others. With their support, we are growing the team, scaling deployments, and bringing to market the first generation of agent workforces built on specific models. In short: 1. We are building Specific Intelligence for specific work at specific companies. 2. That will power in-house agent workforces to support their human bosses. 3. That in turn will unlock AI’s full potential through humanity’s greatest engine of progress: thriving corporations in a free market.

@eumycotan No way I’m friends with you both lol

@velvetatom Congrats!

Spent three years looking for a team in Biodefense to invest in. But never found one. So we built it ourselves. Valthos builds next-generation biodefense. As AI and biotech rapidly advance, we're approaching near-universal access to tools with the potential to cure humanity or make biological weapons. We have a short period of time to ensure that our capabilities to protect advance faster than the threats we face. At Valthos, we apply frontier methods to identify threats and compress the time from a biological sequence to validated medical countermeasures. Excited to share more with you all soon. Grateful to start Valthos with $30M in backing from @OpenAI @Lux_Capital @foundersfund, and many others incl. @Definition_Cap @topology_vc We are actively hiring - if you know engineers interested in solving this mission, reach out contact@valthos.com.

@extraordinary @hoomanrenezhad @solcoatech @hoomanrenezhad beast.

Hooman Reza Nezhad, Founder of Solcoa (Clean, Western Rare Earth Metals), Thiel Fellow, & O-1 extraordinary visa

@origin_bio Congrats!

Introducing Axis: the first AI model that generates regulatory DNA elements and predicts their function. Gene therapies suffer from poor efficacy, toxicity & specificity. Models like Axis can help overcome such risks. Axis beats Google DeepMind's AlphaGenome at predicting regulatory element binding activity by 6.7%.

@origin_bio 🔥🔥

@BrendanFoody @mercor_ai Beast beast

Mercor (@mercor_ai) scaled from $1-500M in revenue run rate in the last 17 months, making us the fastest growing company of all time. Our growth is accelerating. We averaged 11% week over week growth in July, 18% WoW growth in August, and 19% WoW growth in September. One trend driving this meteoric growth: the Economy is Becoming an RL Environment Machine. Reinforcement learning is becoming so effective that agents can hillclimb any benchmark, but humans need to define the rewards to automate everything. While everyone fears job loss, we’re creating a new category of knowledge work faster than any other time in history. The future of work will converge on training agents. We're paying out over $1M / day to people in our marketplace and hiring experts rapidly across nearly every domain: software engineers, doctors, lawyers, consultants, bankers, and many more.