🍜 Meta quits on AI..

Welcome, Noodle Networkers.

Meta’s head of AI research is stepping down after 8 years 🧠—which in tech years is basically a century. Joelle Pineau helped build Meta’s open-source AI cred, but now she’s peacing out just as Zuck is trying to Llama his way to chatbot glory. Let’s hope the new team can keep the AI projects on track—and not accidentally turn them into another VR legs demo. Meanwhile, Nvidia is open-sourcing its Run:ai Scheduler 💻, a fancy name for software that tells your GPUs to stop fighting and take turns. Think of it as a kindergarten teacher for your data center—except it never needs a coffee break and knows exactly who hogged all the compute. And DeepMind’s pharma spinoff Isomorphic Labs just scored $600 million to design drugs with AI 💊. The goal? Let algorithms find the next miracle pill before your grandpa finishes complaining about the price of aspirin. Here’s hoping the AI doesn’t confuse cough syrup with rocket fuel.

Are we witnessing the next AI-powered medical revolution—or just handing GPUs to robots and hoping they pass organic chemistry? Let’s find out...

In today’s AI digest:

• Meta’s head of AI research steps down after 8 years 🧠

• Nvidia open-sources Run:ai Scheduler for GPU management 💻

• DeepMind spinoff raises $600M for AI drug discovery 💊

Read time: 5 minutes

WHAT’S HAPPENING TODAY

$META ( ▲ 0.86% ) 

Meta’s head of AI research steps down after 8 years 🧠

(source: CNBC)

The Digest: Joelle Pineau, Meta’s head of AI research, is stepping down after 8 years, officially becoming one of the few people to survive that long in Big Tech without spontaneously combusting. As the VP behind some of Meta’s biggest AI moves (like the open-source Llama model), she’s bowing out gracefully, probably before the next LLM decides it wants a promotion.

Key Details:

• From FAIR to Farewell – Pineau has been running the Fundamental AI Research (FAIR) team since 2023, taking over from AI legend Yann LeCun, who’s still kicking around as Meta’s chief AI scientist (and occasional Twitter philosopher). She helped guide Meta through the chaotic rise of generative AI—with only minor existential dread.

• Making Space, Not Headlines – In her farewell message, she said it’s time to “create space for others”—which is CEO speak for “I’m out before this whole AGI thing gets weird.” No drama, no scandal—just a well-timed Irish exit from the AI party.

• Zuck’s AI Dreams March On – Pineau’s exit comes while Zuckerberg is throwing billions at AI like it’s the metaverse all over again (but with slightly more user interest this time). With Meta banking big on AI chatbots, assistants, and who-knows-what-else, the timing couldn’t be more strategic.

Why It Matters: Pineau helped build Meta’s open-source AI street cred, steering the company through major breakthroughs while keeping things mostly ethical and explainable. Her departure raises a key question: who’s next in line to babysit the Llama models and make sure they don’t go rogue?

$NVDA ( ▲ 0.27% ) 

Nvidia open-sources Run:ai Scheduler for GPU management 💻

(source: insideainews)

The Digest: Nvidia just open-sourced its Run:ai Scheduler—now called KAI Scheduler—which helps juggle GPU resources like a caffeinated circus performer. If you’ve ever tried managing multiple AI workloads on limited hardware and felt like you were playing Tetris with Tesla chips, this one’s for you.

Key Details:

• GPU Scheduler, But Make It Kubernetes – KAI Scheduler is designed to optimize GPU usage for AI workloads, meaning your models stop fighting over hardware like kids on a road trip arguing over the iPad.

• Open-Source Energy – Nvidia open-sourced the whole thing under Apache 2.0, inviting the dev community to jump in, contribute, and hopefully not break everything with a single pull request.

• Techie Superpowers Included – The scheduler comes with goodies like gang scheduling (scheduling jobs that need to run together), GPU sharing, and hierarchical queuing—aka the ability to tell your LLMs, “Take a number and wait your turn like the rest of us.”

Why It Matters: GPU demand is hotter than a crypto farm in July, and Nvidia just gave the world a shiny new toy to help keep things from melting down. Open-sourcing this tool could make life easier for AI teams everywhere—especially the ones who are duct-taping together Kubernetes clusters at 2 a.m.

DeepMind

DeepMind spinoff raises $600M for AI drug discovery 💊

(source: PYMNTS)

The Digest: Isomorphic Labs, DeepMind’s pharma-flavored sibling, just raised a casual $600 million to use AI for drug discovery—because apparently, the cure for everything from cancer to that weird rash on your arm might come from a neural net. Backed by Google’s finest and led by AI rockstar Demis Hassabis, this spinoff is basically trying to make your next prescription powered by protein folding and Python.

Key Details:

• AlphaFold’s Glow-Up – Isomorphic Labs is building on DeepMind’s AlphaFold, the AI that predicts protein structures faster than your immune system can panic. Now, it’s being used to design brand-new drugs—think ChatGPT, but instead of essays, it’s cranking out molecules.

• $600M: Not Your Average Piggy Bank – The round was led by Thrive Capital, with Alphabet and GV also throwing in cash, because clearly, Big Tech loves AI that can save lives (and maybe get them on the cover of Nature).

• Demis Hassabis: Still Undefeated – Sir Demis is running the show like the AI Avengers’ Nick Fury. As co-founder of DeepMind and CEO of Isomorphic Labs, he’s now aiming to get AI-designed drugs into clinical trials by the end of the year. If he pulls this off, someone better start engraving that next Nobel Prize early.

• Big Pharma’s In Too – With partnerships from Novartis and Eli Lilly, Isomorphic is basically saying: “We’ve got the brains, you’ve got the drugs—let’s fix humanity.” It’s like assembling a superhero team, but with fewer capes and more lab coats.

Why It Matters: AI isn’t just writing poems or generating Ghibli-style selfies anymore—it’s trying to cure actual diseases. Isomorphic’s massive raise signals that investors believe algorithms can crack what decades of whiteboard scribbles couldn’t.

THE NOODLE LAB

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