Math is just tautologies and I still haven’t made my mind up on whether that’s based or cringe

Pretty cool to see Celestia unlocking a new use case for Midnight, a team I really respect. I see this at not only an exciting new frontier for DA, but also a potential wedge for Celestia to expand it's TAM dramatically over the long run. TL;DR Midnight uses Celestia DA as a substitute for a P2P network to publish and match trades in a privacy preserving way. What's nice about this is: 1. Midnight saved a bunch of effort they would have had to spend building a P2P networking stack 2. DA gives stronger guarantees than traditional gossip over a P2P network would It takes a really smart team like Midnight to identify this new use case for DA and harness it, but now that it's been done I expect other teams will follow suit. In the long run, Celestia could serve as a kind of layer 0 (overloaded term I know) as the message publishing network underneath many chains. This doesn't stop at just messaging within a particular chain, it could extend to cross-chain messaging replacing relayers, and eventually chains being able to prove things about their state to other chains (i.e. trust-minimized interop, the holy grail that has always been Celestia's ultimate goal). It's worth mentioning that this kind of application wouldn't be possible without the recent advance in DA called Fibre (s/o @angeris and @alexhevans) making DA fast, abundant and cheap enough for this to be practical. It has been a pleasure working with the Midnight team on this. If you're interested in building using Celestia in this way, please reach out.

Blueprint of BinarySpartan: Spartan instantiated with Ligerito PCS and well-known optimizations. A lot of the optimizations were originally developed in the elliptic curve setting!

you mean I need to Drive The Car to Pick Up my Beautiful Wife from the Airport like a Wifeguy™ ???

guys you do know you can just disable thinking, and instead give it a "deep_think" tool, and it will call it with internal CoT reasoning format right? gl fixing that

screen printing is sick

Excited to share I’ve joined @zksecurityXYZ 😃 I’ve known the amazing team for years, and I’m happy to be part of this team that has been involved in securing and creating important parts of cryptographic infrastructure across the industry Grateful to the inspiring @stefancoh, @alexhevans, @angeris and the rest of the team for the time together in @BainCapCrypto, and all the awesome founders I got to know and work with during my time there Reach out to me with anything related to security, cryptography, formal verification, distributed systems, protocols or otherwise need help with!

After listening for a number of years, it was an honor to call in and chat with @AnnaRRose and @angeris about @commonwarexyz's latest consensus research: zeroknowledge.fm/podcast/408

Before and after

wait wtf, does the chatgpt app now hide even the thinking trace summary?

we are in for some wild timelines

Today we’re releasing Poolside Laguna S 2.1 It is a 118B-total, 8B-active open-weight model built for agentic coding and long-horizon work, with context up to 1M tokens poolside.ai/blog/introducing… Laguna S 2.1 sits at the top of its weight class and competes with open models many times larger, while remaining small enough to run on a single NVIDIA DGX Spark It is available today under OpenMDW-1.1 via Hugging Face, OpenRouter, the Poolside API, and pool This is a remarkable model by any measure. As much as we can gather, it's the best open weight model in the West, regardless of size But the model itself is only part of the story There is a prevailing narrative that building capable models requires ever more capital, compute, and people. We believe the more important question is how efficiently you can turn those resources into intelligence At Poolside, we approach model building as an industrialized process spanning data, pre-training, reinforcement learning, evaluation, and inference. We call that system the Model Factory. We have written about our approach to model building extensively in a 6 part blog series: poolside.ai/blog/introducing… Laguna S 2.1 went from the Model Factory kicking it off to release in 52 days. The model is the output. The ability to keep building better models, faster and more efficiently each time is the actual innovation. The Model Factory is Poolside's compounding asset And so here we are, 52 days after kicking this off, releasing a 118B/8B MOE that tops 70% on TB 2.1, 78% on SWE-Bench Multi, 59% on SWE-Bench Pro, and 40% on DeepSWE. And it's fully open, from an American company I grew up in the Linux and Python communities, then spent much of my career at Canonical (Ubuntu), Heroku and GitHub. Those communities shaped my belief that important technology becomes more useful when people can understand it, challenge it, and build upon it. And even more important than being useful is being trusted. That is what open weights mean to me. They are not a marketing or distribution exercise. They give people control: the ability to inspect the work, reproduce the claims, modify the model, and run it inside their own environment I believe the West needs a credible open path to frontier intelligence. I believe it should be from an American company. We intend to be that company Laguna S 2.1 is another step in that direction and yet more evidence of Poolside's long held, often times contrarian beliefs and views on how intelligence will be built. One last note. We are doing something very different that we hope becomes industry norm going forward. We recognize that releasing a 118B/8B MOE that performs as well as Laguna S does would be met with some degree of skepticism. Models of this size are not supposed to outperform models 4-25x larger. We double and triple checked our benchmark trajectories to be sure. But we wanted to go another step and release those trajectories for you to see and help us quadruple check them. trajectories.poolside.ai/ If you find something we missed, we genuinely want to hear about Have fun building whatever thing you can think of with the most persistent little model that could

huh, I remember people telling me it was impossible to catch up with rsi and all

I read @slatestarcodex 's latest on Plan A. Originally I wasn't going to write a response because I have a hard time picturing someone at the margin that would be swayed by my arguments. But in the spirit of trying to contribute in good faith to the dialogue...

fifa has a new rule that goals can only be scored in stoppage time

👀

roko’s basilisk… in an AAA videogame? twitter really is becoming real life huh

Excited to announce Flock! A new SNARK for efficiently proving batched Boolean computations, in collaboration with @benediktbuenz and @kleptographic . The key use case for Flock is proving standard hash function such as SHA-256, Keccak and BLAKE3. For example, on an m4 max MacBook Pro it proves over 660k BLAKE3 compressions per second. nitter.net/SuccinctLabs/status/20…