Triton
product on 8 shows · 4 statements across 4 episodes · said 43 times in 17 episodes since 2023
Latent Space 27 
the Y Combinator Startup Podcast 5 
TBPN 2 
In Depth 1 
BG2 Pod 1 
the MAD Podcast 1 
the a16z Podcast 1 
20VC 1
Mentions by year, every show
tap a year for its mentions
Latent Space 27the Y Combinator Startup Podcast 5TBPN 220VC 1BG2 Pod 1the a16z Podcast 1In Depth 1the MAD Podcast 1
2026 5 mentions in 1 episode
2025 24 mentions in 10 episodes 2 per episode
- How Zyphra went all-in on AMD + Why Devs feel faster with AI but are slower — with Quentin Anthony
- ⚡️ Beyond Transformers with Power Retention
- ChatGPT Turns Three, OpenAI x Thrive, David Sacks vs. The New York Times | Diet TBPN
- The pivot that paid off: How fal found explosive growth | Gorkem Yurtseven (Co-founder and CTO)
- A Technical History of Generative Media
- Dylan Patel on GPT-5’s Router Moment, GPUs vs TPUs, Monetization
- The Shape of Compute (Chris Lattner of Modular)
- Jeremy Howard on Building 5,000 AI Products with 14 People (Answer AI Deep-Dive)
- 2 more episodes that year, every mention in 2025 →
2024 1 mention in 1 episode
2023 9 mentions in 4 episodes 2 per episode
- The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
- The End of Finetuning — with Jeremy Howard of Fast.ai
- Ep 18: Petaflops to the People — with George Hotz of tinycorp
- Vince Hankes: Why We Put $300M into OpenAI; Sam Altman's Pitch; Lessons from Josh Kushner | E1009 · 20VC with Harry Stebbings
- every mention in 2023, scene by scene →
every mention on every show, scene by scene, with the transcript →
4 statements about Triton, every show
AI coding assistants degrade quickly on low-level CUDA and PTX code
“Getting Below Triton or level or anything else down to like CUDA or below there's orders of magnitude less public good kernels at that level. And I think that really shows and models capabilities. So when I try and get a model to do something in CUDA or PTX or…”
Bachman: Manifest Switched Power Retention from Triton to Custom CUDA
“Actually, our initial version of power retention was written in Triton, but we realized quickly that it just didn't offer the flexibility to really squeeze the performance that we wanted out of the GPU. So we took a step back and dove into CUDA.”
Patel: Hardware vendors and developers are coalescing around OpenAI's Triton
“Likewise, there's OpenAI's Triton, like, what they're trying to do there, and like you know, everyone's really coalescing around Triton. You know, people, you know, third-party hardware vendors”
Howard: Mojo-like languages will unlock thousands of FlashAttention-scale breakthroughs
“There is a thousand flash attentions out there for us to build. You just got to make it easy for us to build them. So like Triton definitely helps. But it's still, Not easy. You know, it still requires kind of really understanding the VPU architecture, writing…”