Are we actually facing diminishing returns from model scaling? What happens when we extrapolate scaling laws for the next few model build outs?
New essay (full link below):
Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
Congrats to @WisprFlow on their Series A!
Has been a privilege to be involved from the Seed
I initially invested because I heard that @tankots and @SahajGarg6 were the top students in their Stanford class. It tracked!
Incredible product, team, everything. Onwards!
@8vc
I’m thrilled to announce @OutsetAI's $17M Series A funding round, led by @8vc!
Since day one, @AaronLCannon and I were driven by a simple truth: Companies build better products when they actually talk to their users. YC drills "talk to your customers" into founders for a reason—it works. But scaling those conversations has always been challenging.
I’m proud that we've created a platform that enables companies to have deeper conversations with more customers at unprecedented scale.
What's even more special: not a single employee has left the company since we were founded three years ago. We believe the journey is just as important as the destination, and it's truly a privilege to work with our all-star team each and every day.
We approached Series A strategically, raising exactly what we needed to fuel our growth to the next stage. Thank you to 8VC and our other investors (Future Back Ventures by Bain & Company, @ycombinator (including our partner, the incredible @garrytan), @Adverbvc, @RebelFund_VC, Genius Ventures, Ritual Capital, Alt Capital, and Mute Ventures).
We're focused on what truly matters: serving our customers and growing responsibly. We believe in building a sustainable business that creates real value.
To our customers who trust us, our investors who believe in our vision, and our incredible team who make it all possible—thank you.
Time to scale.
We’re thrilled to share that @OutsetAI has raised $17M in Series A funding, led by @8vc to help companies better understand their customers.
When @mchlhess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be.
We believed AI could change this by focusing on the human side of AI.
So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans.
By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible.
So what was the moment we knew we were onto something?
When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer.
We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?"
That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights.
All of this built on the backs of a truly special early team with 0 employee turnover.
This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, @ycombinator / @garrytan, @Adverbvc /@aunder / @jess ), @_altcapital / @jaltma , Rebel Fund, Genius Ventures, Ritual Capital, and many more.
So what's next?
We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans.
To our customers, investors, and team - thank you for believing in this vision.
Now check out the video to see Outset in action, testing the video itself with real people!
Privileged to lead @OutsetAI’s Series A and support them in making user research more scalable—and meaningful—than ever.
@AaronLCannon & @mchlhess have brought rare product chops, deep customer understanding, & impressive velocity to a $140 bn industry that has quickly emerged as one of the best use cases for an AI native approach we have seen to date
@kevinniechen and I wrote about how Outset is changing the equation (below):
Understanding customers is existential for any business. @OutsetAI is redefining how it’s done, with pioneering AI-led interviews blending survey scale & human depth. We’re proud to lead their $17mm Series A. More below from @jack_moshkovich & @kevinniechen:
After nine months in stealth, we’re excited to announce Augment has raised $25M, led by @8VC, and is launching Augie—the first AI teammate for logistics.
We are applying AI—the most transformative tech of our time—to logistics, the largest industry in the world.
🚀 We’re hiring! If you want to build AI that moves freight, let’s talk.
20+ years ago, @Meta & @PalantirTech formed in dorm rooms, enlisting bold young builders to create enduring companies.
AI revolutionized the toolset, but courageous top talent is still paramount. The @8VC Llama Stack Innovation Challenge is your invitation to be discovered.
We're incredibly excited to be launching the 8VC Llama Stack Challenge today for university students in the US!!
The first challenge is about building desktop, field, and edge AI applications using Meta's open source Llama models: 3/7 - 4/19!
Join now at https://t.co/RcnXs153Jn
Our friends @Meta are taking part in the 8VC Llama Stack Innovation Challenge!
First challenge: 3/7-4/19. Use Llama Stack to build desktop, field, and edge AI applications that run locally for privacy and performance. Join now:
https://t.co/B5ncyoB9UD
We are proud to announce 8VC Fund VI, with $998 million in new LP capital to back the most fearless and ambitious builders.
The world is broken. Let's fix it.
To the frontier!
Looking for a couple great founding engineers...
A diligent dwarf, Thorin, loves routing incoming comms to the right colleagues, and mining them to create replies, processes and alerts. He has a lot of cool tricks up his sleeve, and will save me hours per week; other friends agree they need his help ASAP.
We’re building something awesome around AI, email, and team processes at @8VC.
Our team co-founded the AI CRM used by 3500 firms (Affinity!), and after Palantir, we co-founded a lot of other mission-driven, billion-dollar companies — Addepar, Saronic, Resilience, OpenGov, Epirus, etc.
I know a billion-dollar product mission when I see it. Our internal technical and design teams are building, and we're looking for a couple more A+ engineers to work with us and build a generational company.
Thorin will be based out of our offices in SF and Austin, TX. You’ll have the opportunity to work directly with me and 8VC’s CTO.
If you are based and obsessed, or even just a really great engineer who wants a new challenge: come win with us. DM @8VC, or visit https://t.co/yHWuubRvVx.
Introducing Bespoke-Stratos-32B, our reasoning model distilled from DeepSeek-R1 using Berkeley NovaSky’s Sky-T1 recipe.
The model outperforms Sky-T1 and o1-preview in reasoning (Math and Code) benchmarks and almost reaches the performance of DeepSeek-R1-Distill-Qwen-32B while being trained on 47x fewer examples!
Crucially, we open-source the dataset (DeepSeek open-sourced the model, not the data). Let's work together on this exciting direction of reasoning distillation!
🧵More info and link to the blog below!
New blog post on the case for developing oral drugs for antibody targets.
In an era of antibody me-toos, this strategy stands to truly differentiate.
Full post below:
@Miles_Brundage that's my mistake, good catch
i wrote the sentence, then later added 100M gpus as a point of comparison, and forgot to update the spreadsheet and blog now. fixing now, thanks
Are we actually facing diminishing returns from model scaling? What happens when we extrapolate scaling laws for the next few model build outs?
New essay (full link below):
@Calclavia is there a specific type of data youre thinking of like video, embodiment, code, etc? i think the q is the scaling laws for each of these domains and we have some early data for some