huge fan of @bycloudai ever since I started my AI YT channel. i feel so honoured to finally meet him in person.. thanks for inspiring me!

Nemotron 3 Full Breakdown With the help of Joey Conway from @NVIDIAAI getting into the specifics around why Nemotron 3 is kind of a big deal Biggest headline with Nemotron is: Hybrid Mamba Transformer, Latent MoE, and MTP Hybrid Mamba Transformer essentially attacks right at the Attention mechanism to make the overhead sub-quadratic, but unlike quantizing KV Cache or swapping out attention head, NVIDIA chose Mamba-2 Latent MoE helps further optimize on sparsity by down projecting the dimensions so you're doing less math and less memory movement between HBM and SRAM, you're saving a ton, and NVIDIA made a conscious choice to add more experts given the surplus Finally, MTP or multi token prediction where the model can see future tokens to be more expressive in training and also option to use for speculative decoding during inference Oh, also the model adopts the new OpenMDW 1.1 License

MiniMax M3 ditched full attention and adopts sparse attention This is yet another trend as more labs are focusing on token efficiency and inference throughput which M3 model demonstrates which cleverly in the M3 architecture in how KV is processed I'm personally impressed by the I/O between HBM and SRAM and how tokens are read in tiles contiguously - not wasting operations. Great work @MiniMax_AI

in case the first message wasn't clear

Pi framework that built OpenClaw So many coding agents these days all look the same and feel the same. Pi goes against the current by shedding weights rather than gaining more And harness is changing with ebbs and flow which means being a minimalist adds durability

Thank you for hosting me. And huge thanks to greg and tilde for the interview 🐐

Typical day: Gemini, ChatGPT, Claude for research

California weather is not friendly to my hair but here's a quick interview about me and my journey as a content creator covering AI. Shout out to Greg and Tilde for the interview! youtu.be/TjPr_-X0Mko?si=w0Y1…

Brief history of harness engineering In case the buzzwords around what harness even is and why we're even talking about harness in general, here's a video explaining why the industry evolved from prompt, to context, and now to harness engineering. Enjoy.

Great chat with @Sam_Witteveen last night. Sam is the 🐐 with insane insights into the AI industry.

Assuming YC team of 2-3 people, you're trading around 3 years of running Codex (~70TPS at $14/M tokens running 24/7) for equity. I wouldn't take the deal.

Ran into @twominutepapers at Google IO and Dr. Károly said he's seen my videos 🤯

Gemini's new AI glasses encapsulates my cultural identity ( Nano Banana)

Gemini 3.5 Pro not being released in Google IO is somewhat suspect..

Gemini 3.5 Flash in benchmark

and the plot thickens...

Google IO about to start 😇

Got here early at Google IO..

OpenAI spent billions on training infrastructure. Two Aussie brothers made AI training 30x faster ~ with $500K total. 🤯 Meet Daniel & Michael Han 🇦🇺 > Brothers from Sydney, Australia > Daniel was an engineer at NVIDIA > Sped up the t-SNE algorithm 2000x. Cut SVD memory in half. > Found and fixed 20 bugs in Meta’s Llama, Google’s Gemma, Mistral, and Phi > Big AI labs missed bugs in their own models. He caught them. > Started Unsloth in December 2023 with his brother Michael > Built tools that make LLM fine-tuning 2-30x faster, with 70-90% less memory Released it 100% open source. Free for everyone. 🚀 > 64,000 GitHub stars > 10 million model downloads every month > NASA and Canva use their code > Raised only $500K total in seed funding > Got into Y Combinator S24 > Led by two brothers with a small team of 8 shipping code While big labs burn billions, they made AI accessible to everyone. Absolute Legends 🐐

touching some grass with my homeboy Logan