Eric Alcaide

Design is not finished. Common prosperity. LLMaxxing @poolsideai

[Eric Alcaide @eric_alcaide]

Everything needs to be overlapped. Everything needs to be parallelized. Remove transport overhead where possible. TOTAL FACTORIO MINDSET. Everything that can run SHOULD RUN.

[Eric Alcaide @eric_alcaide]

@christiancooper @PrimeIntellect 🚀🚀🚀 keep us posted !

[Eric Alcaide @eric_alcaide]

@PrimeIntellect @qijia_shen @AltalibKhalid let's go guys ! 🛠️

[Eric Alcaide @eric_alcaide]

Demand is so high it’s unreal 🚀

[Andrea Badia @Badiaserra]

A finance friend brought this up at lunch the other day and I couldn’t help it… it’s such a simplistic take it’s ridiculous. Growth-adjusted multiples are Finance 101. A multiple without a growth rate next to it is half a sentence.

Walmart is growing at ~5%/yr. OpenAI ~3x. Anthropic ~10x. Now put the multiple over the growth rate and it inverts: Anthropic screens around 0.02 on a revenue-PEG vs Walmart’s ~0.26, roughly an order of magnitude lower.

Want to make the bear case? Argue margins or FCF. A naked EV/Rev multiple isn’t it.

[Eric Alcaide @eric_alcaide]

Very happy to see Laguna-M.1 on this discussion!

Worked on both sides of inference and training on this one, and we'll keep pushing the RL infra to fly higher every time 🚀

[Luke J. Huang @whatthelukh]

New blog! Is frontier asynchronous RL solved?

The blog covers Async RL theory and infrastructure, surveying 8 open-weight frontier labs for the algorithmic techniques and systems fixes to handle train-inference mismatch. Also answered: why do current methods still fail at high policy lag? Which methods scale with horizon and compute?

[Luke J. Huang @whatthelukh]

New blog! Is frontier asynchronous RL solved?

The blog covers Async RL theory and infrastructure, surveying 8 open-weight frontier labs for the algorithmic techniques and systems fixes to handle train-inference mismatch. Also answered: why do current methods still fail at high policy lag? Which methods scale with horizon and compute?

[Eric Alcaide @eric_alcaide]

@sheriyuo "Who will rise next?" We will 💪

[Eric Alcaide @eric_alcaide]

@jdthewlis @poolsideai @WUFang40615703 Really looking forward to this !

[Eric Alcaide @eric_alcaide]

Really like this use of Laguna-XS.2 from ;) 🤖

Made me remember the drug discovery and CoFolding days 🧬⚗️🧪🧑‍🔬

[James Thewlis @jdthewlis]

The @poolsideai Hackathon is over but I'm continuing to teach Laguna XS.2 to be a better scientist 🧑‍🔬. Our Protein-Ligand Design Gym now has 1000+ examples with harder protein/ligand interaction problems.

[Eric Alcaide @eric_alcaide]

@nv_pavlichenko That MTP boost of +50% relative accuracy in HumanEval is quite crazy. Any insights / groups of cases it improved?

[Eric Alcaide @eric_alcaide]

@nv_pavlichenko Congrats ! Happy to see it come out ! 💻

[Eric Alcaide @eric_alcaide]

@stspanho Ironic to log off and go out in nature just to compete with a past ghost 😂

[Eric Alcaide @eric_alcaide]

The cool blogpost was authored by @alexdzm @aalSonOfRavi , @ConnorBAdams and the wider Evals team at @poolsideai

[Eric Alcaide @eric_alcaide]

Glad to see more teams raising awareness on SWE-style benchmarks reliability ! We discussed this same problem on our blog post earlier last month as part of our reward hacking investigations 🔍🕵️

https://t.co/5p6iiiM8YW

[Serena Ge (Datacurve) @serenaa_ge]

Today we’re releasing DeepSWE, a new standard for agentic coding benchmarks.

On public leaderboards, top models often look relatively close in capability. DeepSWE shows where they actually diverge, reflecting the realistic experience of developers in their day-to-day work.

[Eric Alcaide @eric_alcaide]

@AlessandroDuico @Badiaserra @poolsideai @eloquake Design is not finished, the job is never fully done. The important bit is to learn, improve, and create usable outputs along the way so others can join the party 💪 🥳

[Pope Leo XIV @Pontifex]

In the era of #ArtificialIntelligence, when human dignity is threatened by new forms of dehumanization, ours is the pressing duty to remain profoundly human. We must lovingly safeguard the grandeur of humanity bestowed upon us and revealed in its fullness in Christ, the splendor of which no machine can ever replace. #MagnificaHumanitas
https://t.co/6i9MWs6LJl

[Eric Alcaide @eric_alcaide]

Start warming up guys, we're coming and we want to cook hard 🧑‍🍳

[Poolside @poolsideai]

London raised the bar. SF, gear up 👀

[Alessandro Duico @AlessandroDuico]

The level of the @poolsideai hackathon in London was higher than the average in SF.

We tried distilling Laguna XS.2 into a dense model. A ~11x parameter reduction from 33B to 3B.

https://t.co/9bwmzRr2kc

Many thanks to the organizers @poolsideai @eloquake @Badiaserra

[vLLM @vllm_project]

🚀Great to see @RedHat_AI and @poolsideai team up to make Laguna XS.2 faster and cheaper to serve in vLLM. A DFlash speculator built with Speculators drafts 8 tokens per forward pass for 2-3x faster decoding at no quality loss, and LLM Compressor adds FP8 / NVFP4 / INT4 checkpoints so you can match your hardware budget.

🔗 https://t.co/3mguMKtwTt

[Eric Alcaide @eric_alcaide]

@ar0cket1 For M.1, it is heavy. For XS.2, not so much as it's SWA for 3/4 layers... So basically ~5Gb in FP8