TMS-EE

Cyril Hilsum obituary: physicist who developed displays used in iPhones. Wonderful obituary of my father @thetimes thetimes.com/article/799ea9f…

New season of Cheeky Pint starts tomorrow! First up: @dwarkesh_sp and I sit down with @elonmusk to discuss space GPUs and much more.

After spending a splendid day speaking at the IBM AI HW Forum, I will be at the "IBM IEEE CAS/EDS – AI Compute Symposium" to present "The Next Shift in AI: Autonomous Agents and Proactive Intelligence." I will share my slides on Substack afterwards. zurich.ibm.com/thinklab/AIco…

Dave Ricks has been at @EliLillyandCo for 20% of its 150-year history. He came to the pub, poured his own Guinness, and gave us a 2-hour state of the pharma union: drug prices, clinical trials, patent clocks, the rise of generics, Chinese peptides, compounding pharmacies, the US healthcare system, and how the broad success of GLP-1s have transformed Lilly's business. If you've never heard Dave speak before, you're in for a treat. Timestamps: 00:00 Intro 05:08 Making R&D decisions 10:11 Clinical trials 24:59 Drug pricing 32:43 Stimulating more R&D 45:16 Pros and cons of US healthcare 58:20 New pharma business models 01:05:53 Stripe + enterprises 01:07:00 China 01:16:31 Generics 01:22:37 GLP-1s 1:37:43 r/Peptides 01:41:25 LillyDirect 01:46:35 Why do investors love LLY?

What is AI Engineering? No better person to talk about it than @chipro, author of the recently released O'Reilly book "AI Engineering" - which is an excellent read. Listen to or watch the whole episode: • YouTube: youtube.com/watch?v=98o_L3jl… • Spotify: open.spotify.com/episode/6NX… • Apple: podcasts.apple.com/us/podcas… --- Brought to you by: 🌟 @SwarmiaHQ — The engineering intelligence platform for modern software organizations. swarmia.com/pragmatic/ 🌟 @withgraphite — The AI developer productivity platform. gt.dev/pragmatic 🌟 @TrustVanta — Automate compliance and simplify security with Vanta. vanta.com/pragmatic ---- 3 takeaways from this episode: 1. “AI engineering” feels closer to software engineering than to ML engineering. The term itself is very new, and “AI engineering” evolved from ML engineering. A big difference is that thanks to LLMs being easy to use (both via APIs, and locally) “AI engineering” is much more about building a product first – and later on, getting around to tweaking the model itself. 2. To get good at AI engineering, focus on the basics. Understand what an LLM is (and how it works), how to evaluate them, how to use RAG, what finetuning is, and how to optimize inference. All of these techniques are foundational, and will remain important in a few years’ time as well. 3. Solving the problem is more important than using the latest AI tools. Amusingly, a lot of teams miss this part: and they build overcomplicated AI solutions that do practically nothing for the business. Thank you, Chip, for this great chat. I can not recommend her new book, AI Engineering, enough either.

Honored to be @lexfridman podcast with the homie @natolambert 5 hour podcast dropped and it's a banger covering a lot of different topics. We had so much fun riffing. The secret to the hostage images Lex takes are now revealed with this nato selfie

Felix from @tenstorrent talks about their technology at @hipeac, providing scaling up with a data first architecture based upon #riscv. By making this a fundamental primitive of the architecture they can accelerate both #AI and #HPC

Every general-purpose technology creates new opportunity across the economy. But it requires companies and countries to invest in new infrastructure and equip people with the right skills. And that’s what we are doing in this AI era, starting in the US. blogs.microsoft.com/on-the-i…