Jordan Hagan (@jtothehagan) 's Twitter Profile
Jordan Hagan

@jtothehagan

Field Eng @ Groq

ID: 21945053

calendar_today26-02-2009 00:24:55

3,3K Tweet

143 Takipçi

205 Takip Edilen

Groq Inc (@groqinc) 's Twitter Profile Photo

It’s official: McLaren F1 x Groq Bringing inference speed at a winning cost to the grid and beyond. See you in Singapore. 🧡🏁

kraken (@kraken_9076) 's Twitter Profile Photo

Groq now decrements cached tokens against your rate limits on the way out, giving developers a much higher effective rate limit for cached workloads.

Groq Inc (@groqinc) 's Twitter Profile Photo

“AI does have a cost problem, and we think this breaks through that.” -Rob Thomas, Chief Commercial Officer at IBM, on why Groq was IBM's obvious choice for an inference partner.

Pydantic (@pydantic) 's Twitter Profile Photo

Pydantic #AI #Gateway is now in open beta 🚀 One API key for OpenAI, Anthropic, Google, Groq, and Bedrock. BYOK and Built-in providers. Real cost limits. Built-in observability. Zero translation delays. Free during beta. pydantic.dev/ai-gateway

Groq Inc (@groqinc) 's Twitter Profile Photo

Shipped: Google Workspace MCP Connectors, fully compatible with OpenAI. Gmail. Drive. Calendar. Connect to your workspace at LPU speed.

Nina Schick (@ninadschick) 's Twitter Profile Photo

Three years ago, a million tokens of AI inference cost $60. Today? Six cents. A 99.9% cost collapse. When something this powerful becomes this cheap, it doesn’t stay confined to research labs, It is able to flood the economy. AI is now diffusing faster than any technology in

elvis (@omarsar0) 's Twitter Profile Photo

Banger paper from DeepSeek. Math AI models have a fundamental problem. (bookmarks this one!) The issue isn't accuracy on benchmarks. It's that correct answers don't mean correct reasoning. Models can brute-force solutions numerically, guess, or stumble into right answers

Banger paper from DeepSeek.

Math AI models have a fundamental problem.

(bookmarks this one!)

The issue isn't accuracy on benchmarks. It's that correct answers don't mean correct reasoning. Models can brute-force solutions numerically, guess, or stumble into right answers
Alex Prompter (@alex_prompter) 's Twitter Profile Photo

This paper from Stanford and Harvard explains why most “agentic AI” systems feel impressive in demos and then completely fall apart in real use. The core argument is simple and uncomfortable: agents don’t fail because they lack intelligence. They fail because they don’t adapt.

This paper from Stanford and Harvard explains why most “agentic AI” systems feel impressive in demos and then completely fall apart in real use.

The core argument is simple and uncomfortable: agents don’t fail because they lack intelligence. They fail because they don’t adapt.
Andrej Karpathy (@karpathy) 's Twitter Profile Photo

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become

The All-In Podcast (@theallinpod) 's Twitter Profile Photo

Chamath: Two terms you need to pay attention to in AI are Prefill and Decode “There's two terms that I think you're going to hear a ton about over these next few years.” “The first term is prefill, and the next is decode.” “What prefill and decode are, are two very distinct