Ahmad Beirami
stealth // Gemini RL+inference @ Google DeepMind // Conversational AI @ Meta // RL Agents @ EA // ML+Information Theory @ MIT+Harvard+Duke // Georgia Tech PhD
📍{NYC, SFO, YYZ}
🔗 beirami.github.io
- I haven't used ChatGPT for a month now and haven't missed it. Today felt like a good day to cancel my subscription.
- We are hiring Members of Technical Staff (Research Engineers)! Current LLM agents lack reliability, creating a gap between demos and production. We solve this by automating the complex workflow of debugging, evaluation, and iteration required to make agents robust. 👇
- What we do - Advance the state-of-the-art by analyzing the latest research on agentic AI, coding agents, self-improving systems, memory architectures, and agent evaluation, and translating them into production code. - Build an agentic system that analyzes and writes production codebases for agents.
- - Iran is in a humanitarian crisis. - Thousands are reported dead in 72 hours. - We are past the point of solidarity. Empty words do not stop bullets. Action does. - The world must intervene now.
- For years, Iran’s masked plainclothes regime thugs have abducted and murdered citizens with absolute impunity for wanting prosperity and refusing to fear them. Officials call it law enforcement and smear protesters as paid agents of the state’s enemies. This must end. Iranian people must prevail!
- Found myself repeating this to several students at NeurIPS: When you’re choosing an internship or a job, what you work on and who you work with matter way more than the logo. Don’t optimize for brands. Become the brand!
- Hiring researchers & engineers to work on –building reliable software on top of unreliable LLM primitives –statistical evaluation of real-world deployments of LLM-based systems I’m speaking about this on two NeurIPS workshop panels: 🗓️Saturday – Reliable ML Workshop 🗓️Sunday – LLM Evaluation Workshop
- Woke up to this email this morning - Wow, I won a NeurIPS award?! - …runner-up, but I’ll take it. - Wait, I didn’t submit a paper. - Ah, I’m chairing the session and I’m supposed to give the award. Huge congratulations to the actual winners and runners-up!
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- Will be at NeurIPS Thu Dec 4 to Sun Dec 7, excited to reconnect with old friends and make new ones. If you are excited about AI engineering (orchestration, evals, and optimizing scaffolds), we are hiring! On Saturday I’ll be on panels at the Reliable ML & UniReps workshops.
- Once you see a math concept geometrically, it becomes much easier to think about, and it’s hard to go back to any other way of seeing it.
- I am sorry for what many of my excellent former colleagues are going through. Layoffs can be emotionally challenging for everyone, whether you are directly affected or not.
- The math that LLMs can do today is novel enough to be considered publishable, but it's not the kind of math that would be consequential.
- My thoughts on the broken state of AI conference reviewing. www.linkedin.com/feed/update/...
- Let's regress from here to AGI!
- This is the conclusion slide of a talk I gave more than a year ago on RL/Alignment! It still holds true today.
- This also applies to telling your story (e.g., in a CV, bio, interview, etc). Focus on what you have accomplished and what you are excited about doing next; not just where you did it!
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- I occasionally get messages asking how to follow my path and get into Meta, DeepMind, or similar places. That is the wrong question. Do not focus on the brand! Focus on what you want to work on, then find the opportunity that fits your goals best.
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- Corollary: If you lack bandwidth or expertise to act as the verifier, then you shouldn't sign up to be the senior author of a paper!
- Unpopular opinion: When a paper has a senior mentor and a junior mentee, the senior author must make sure the claims are correct and well supported. They must check every claim and gate the submission until it meets that bar.
- This is the recipe for many provable claims: Make enough assumptions and narrow down the claim, then prove a narrow result with caveats. Present it as broad, hide the caveats, and declare “XYZ is provable!”
- Today, Industry research is focused on short term (3-6months) bets. Academics have an opportunity to balance their portfolio with medium term (1-2 years) and long term (5-10 years) bets. Putting all academic efforts in short-term basket is suboptimal!
- When I worked in corporate, I was often first in the office because that routine worked for me. It was a personal preference, not a benchmark for anyone else. We should not judge commitment by hours, especially in research. We should look for thoughtful work and steady progress.
- Common mistake in LLM prompting projects: jumping into full-scale pipelines (datasets and inference) without testing feasibility. Iterating at scale is expensive and time-consuming. Start with ONE example to validate the hypothesis, verify context, debug the design, then scale.
- Thoughts that are explained clearly are more respected. Clarity is a scarce skill. Many of us (me included) leave out key context and make people work too hard to understand us. AI models should get better at this: not just reasoning, but communicating with the right amount of context.
- Enjoyed speaking with @DeltaInstitutes about going from information theory to ML, recent safety alignment/RL work, and lessons on RL for LLMs that stuck! Check out the podcast episode here: lnkd.in/eb6dWHDv
- In 2009, a prominent signal processing professor said the market was tough and h-index ≥6 was needed just to get a faculty interview. We now seem to be drifting toward the same bar for PhD program entrance.
- Congratulations to the Google team on the release of the newest Gemini Image generation model! 🍌🍌 I am super impressed with what the model did here (no other model gets even close -- including Google's previous model). This is truly bananas!
