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Daniel Dines Cliff Weitzman
+4 more
David Heinemeier Hansson Jerry Murdock Matt Garman Greg Isenberg

Fireworks AI

Software

4 creators

Open-source model inference and deployment for enterprise AI workloads; potential on-prem deployment for European customers

"I'm a big fan of Fireworks and we are using them quite a bit. Yes, we like them a lot. I also tried to convince them to make their software available on prem right now."

Daniel Dines

Daniel Dines on Why Work Processes Not Models Will Be The Most Valuable Asset in AI ▶ 53:37
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AI inference and supplemental data or model serving

"I suggest you use Fireworks. Fireworks is amazing. Lyn, the founders — she's one of the co-founders of PyTorch."

Cliff Weitzman

How to Build Your Own Data Center & Why Every Startup Should Do It ▶ 19:42

Inference for open-weight models like Kimi K3 without using Chinese servers

"I inference on Fireworks, which is a really nice service where you can just pay by the token, and if you're using these open weight models, they're not that expensive by token. So that's a great way to do that."

David Heinemeier Hansson

DHH: Future of Programming, AI, Agentic Engineering, Vibe Coding & Linux | Lex Fridman Podcast #501 ▶ 1:40:40
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Hugging Face

Software

3 creators

Tracking trending open-source models

"I look at what's trending on Hugging Face. I am fascinated by open source, so I try to find any resources on open source."

Matt Garman

Gemini 4 Argon Can Finally Compete With Claude and ChatGPT ▶ 48:27
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Finding and understanding open models, reading model cards, finding quantized versions of models

"If you're new to local AI, one of the best exercises is actually just to open Hugging Face and read a model card really slowly. You're going to learn a lot. That's the first place I would go. They're the biggest at it."

Greg Isenberg

I'm Obsessed With Local AI. Here's Why ▶ 3:23

Training and experimenting with AI models for the Kaizen project

"HuggingFace is where the world's AI models and training data sets live. I've spent a lot of time there as a part of what we're doing on Kaizen so that we can really get a singular output."

Tom Bilyeu

This Is the AI Nightmare Everyone Warned About — and It Just Happened ▶ 4:07
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About these recommendations

Products are related to this topic through catalog tags. Quotes describe the creator’s stated use; they are not necessarily recommendations for this topic.

Creator counts cover all uses and all dates. Each person counts once per product family. Paid promotions and passing mentions are excluded. Items are ordered by creator count, then name.

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