Keep on to blur preview images; turn off to show them clearly
Ironically, Apple defaults to NVIDIA for rendering, lol. I don't think they've used their "superior" chips for training either.
Founder and CEO of https://t.co/5MjtfpwEU3 | Your guide to radiance fields | Host of the podcast @ViewDependent | FTP: 279 | discord: https://t.co/lrl64WGvlD
I love the expression “food for thought” as a concrete, mysterious cognitive capability humans experience but LLMs have no equivalent for. Definition: “something worth thinking about or considering, like a mental meal that nourishes your mind with ideas, insights, or issues that require deeper reflection. It's used for topics that challenge your perspective, offer new understanding, or make you ponder important questions, acting as intellectual stimulation.” So in LLM speak it’s a sequence of tokens such that when used as prompt for chain of thought, the samples are rewarding to attend over, via some yet undiscovered intrinsic reward function. Obsessed with what form it takes. Food for thought.
Building @EurekaLabsAI. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets.
I love the expression “food for thought” as a concrete, mysterious cognitive capability humans experience but LLMs have no equivalent for. Definition: “something worth thinking about or considering, like a mental meal that nourishes your mind with ideas, insights, or issues that require deeper reflection. It's used for topics that challenge your perspective, offer new understanding, or make you ponder important questions, acting as intellectual stimulation.” So in LLM speak it’s a sequence of tokens such that when used as prompt for chain of thought, the samples are rewarding to attend over, via some yet undiscovered intrinsic reward function. Obsessed with what form it takes. Food for thought.
Building @EurekaLabsAI. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets.
The @Lovable story will be one for the history books: - Valued at $6.6B just 2 years after founding - $200M ARR in under 1 year - Just ~100 employees (!!) - Based in Stockholm, Sweden @ElenaVerna joined Lovable 8 months ago to lead growth, and in our in-depth conversation, we discuss: 🔸 Why she's had to throw out 70% of her growth playbook at Lovable 🔸 The specific growth tactics driving Lovable’s unprecedented growth 🔸 Why giving away product is a key growth strategy in AI 🔸 Her take on Lovable's retention numbers 🔸 Why in AI you have to re-find PMF every 3 months 🔸 Whether you should join an AI startup (her honest tradeoffs) 🔸 Much more Listen now 👇 • YouTube: https://t.co/mLo1D4MJ5c • Spotify: https://t.co/O1Wzbm9ifR • Apple: https://t.co/DFGrlzLH1c Thank you to our wonderful sponsors for supporting the podcast: 🏆 @WorkOS — Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://t.co/XH3bKmeEkH 🏆 @vercel — Your collaborative AI assistant to design, iterate, and scale full-stack applications for the web: https://t.co/7ERE84KPFV 🏆 @Persona_IDV — A global leader in digital identity verification:
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lmao @jpmorgan investment bankers took my chart and changed the text even added a kink because idk gen z ibanker kids these days just be vibe charting
(for the record i have no problem with it, idea wasn’t mine alone, and anyone else could’ve done the chart , whatever, it’s kinda cool to see it show up in new places)
Is there already such a thing as an "external hardware LLM" like we have external hard drives? Instead of having to run/maintain a local model, I want an inference machine that I can just plug in and point my prompts at. Single GPU, maybe a few in parallel. Who's building this?
Building https://t.co/od97B0HVrk and https://t.co/666FnyVVE0 in Public. Raising all the boats with kindness. 🎙️ https://t.co/6w69DZmi8H · ✍️ https://t.co/lpnor5rsTW
