(1/5) Great to be at @sequoia to give a sneak peek of one of our research directions!
TL;DR one path to data-efficiency may be to “abuse GPUs like they’ve never been abused before”
I asked people: "which AI data startups are most interesting?" The focus was on startups that sell data to labs, excluding the massive ones (Mercor, Surge, Handshake, Turing):
22 votes: Mechanize
12: Proximal
11: Fleet
9: AfterQuery
8: Datacurve
5 each: Bespoke Labs, Preference Model
4: Abundant
3 each: Andon Labs, Latch, microagi, Prime Intellect, Snorkel, XDOF
2 each: Build, Datology, Design Arena, dmodel, Good Start Labs, hillclimb, HUD, Inheritance, Mecka, Sieve, Taste Labs, Trajectory, Vmax
1 each: 37 companies, info in image and below
Disclosure: I'm a small angel in Abundant, Fleet, Inheritance, Latch, Trajectory, and Vmax. I didn't vote.
We’ve raised $11M in seed funding led by Threshold Ventures, with participation from Informed Ventures, Alpaca VC, VitalStage Ventures, Correlation Ventures, Darkmode Ventures, Mike Mahlkow, Cross Atlantic Angels, Max Keller, JD Montgomery, Adam Grosser, and others, to continue to build AI capable of autonomous scientific discovery.
We’re excited to announce that we’ve raised a $40M Series A!
co-led by @MarathonMP and @chemistry, with participation from @Wing_VC, @AMD Ventures, @outsetcap, @fiftyyears, and @ycombinator, and our existing investors doubling down on @wafer_ai. we are also joined by an incredible list of angels, including @JeffDean (CEO, @DiscoLoopAI), @rauchg (CEO, @vercel), @andyfang (CTO, @DoorDash), @kvogt (CEO, Bot), @akothari (COO, @NotionHQ), @eastdakota (CEO, @Cloudflare), @deepgramscott (CEO, @DeepgramAI), and more!
Most inference optimization today is manual, service-heavy, and done one-time before deployment. Wafer’s vision is AI that optimizes AI. Wafer continuously learns from your workload’s traffic patterns and performance constraints, then finds the optimal deployment across model, engine, kernels, and hardware.
This capital helps us accelerate automating more of the inference optimization loop, giving every deployment the leverage of an expert inference-performance team that continuously finds ways to improve performance per dollar.
Thank you to the customers who trusted us with their workloads, the partners who built alongside us, the investors who believed in our mission, and the Wafer team members who have worked tirelessly to turn this vision into reality.
🫶🧇
As VARA AI Fund (Value Aligned Research Advisors) is reportedly getting liquidated, it might be a good idea to revisit this paper I wrote on the risk of excessive leverage in Hedge Funds (Situational Awareness LP in July 2026)
https://t.co/7AedJ8uNV6
@leopoldasch
@theweb3jess Anthropic’s math team and @__alpoge__ always be cooking up some crazy stuff. Glad to have shared this article with you so you could write up this tweet lol (Elliptic curves have so much aura)
🚨BREAKING: Nous Research has raised $90 million at a $1.5 billion valuation after its open-source Hermes agent exploded in usage.
Hermes has been downloaded 22.7 million times since February.
Nous was at roughly $36 million in annualized revenue by mid-September. It expects to pass $100 million later this year.
Sources: AI inference-chip startup Etched is in early talks to raise funding at a $40B-$50B valuation, up from $21B in August (@mtemkin / TechCrunch)
(Visit Techmeme dot com for the link and full context!)
Most of us don't have access to multi-million dollar NVIDIA gpu sleds (if you do, hit me up).
But I wanted to learn how they work, so i build a 3d guide!
Unified GPU / CPU systems like this are what's powering all these mega-ai DCs. Incredible what educational tools you can build with llms.