There’s also a whole cohort of people who don’t understand how good Deepseek are because they believe it’s all hype due to the OG hype-cycle
In reality they’re absolutely destroying all western AI in the race to tokens too cheap to meter
Every time there’s a new Chinese model release after some meaningful event - Xi visit to US - and new round of of fear-mongering, I breathe a sigh of relief 🧘♂️
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
1/4
I just wish it was back near the OG price
Luna/Haiku are far inferior but the subsidies make them difficult to beat rn, around 98% of my tokens go to smolbois
.@willob of @ulyssesinc joins @sacca and me for a pint to discuss how subsea robotics is unlocking Earth’s last frontier. We talk about the physical constraints of operating 1,500 meters underwater, why seagrass holds 20% of the ocean’s carbon, how green tape hinders environmental restoration, and why hard tech startups are verticalising hardware manufacturing. (Plus, Will's interesting Guinness history facts.)
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
https://t.co/zHij5zwKGT
@krishnanrohit Feels like slowly/stalling growth could cause a significant macro crash if this is accurate
Was surprised this wasn’t noticed more: https://t.co/VB3IyYbsNs