Both Meta and Google just joined the launch party Anthropic kicked off, but on very different trajectories — Zuck and co. keep climbing into rarefied AI territory, while Google is out to prove it still has a pulse after a year to forget.In today’s AI rundown:
- Meta, Google join the September AI launch party
- Nate's Notebook: Tech literacy = your AI ceiling
- Nail job interviews with the “Proof Project” method
- Report: OpenAI’s loops hit AI safety monitoring
Image source: Meta/ GoogleThe Rundown: Meta and Google both just shipped new models, with Mark Zuckerberg pitching Meta’s Muse Spark 1.3 as “frontier performance almost too cheap to meter,” and Google’s Gemini 3.8 Flash showing a stronger bounce-back from its 2026 struggles. The details: - Spark 1.3 (Max) comes in at a 62 on AA’s Intelligence Index, now trailing only Claude Fable 5.1 and Opus 5 despite being significantly cheaper to use.
- Zuckerberg said “next up” is Meta’s larger model codenamed “Watermelon,” as well as releasing the weights for Muse Spark.
- Gemini 3.8 Flash keeps 3.7’s pricing ($0.75 / $3.75) with gains in coding, reasoning, and agentic tasks, slotting in at a 59 on the Intelligence Index.
- DeepMind’s Koray Kavukcuoglu admitted Gemini sits “a little below the frontier”, and said, “there’s nothing other than being at the frontier that’s important for us.”
The Rundown: Every enterprise racing to adopt AI eventually hits the same walls: where does the model run, where does the data go, and who can see it. Join experts from CoreWeave and Cosine on Sept. 10 for a practical session for teams deploying AI in regulated environments.Attend to learn how to:- Define “sovereign” for your org across data residency, deployment, model provenance, and more
- Turn governance requirements into automated checks with the open-source Responsible AI Toolkit
- See the full sovereign AI stack come together in a live technical demo
The Rundown: Each week, Rundown AI educator Nate Grahek breaks down what he's seeing while teaching real teams to use AI.Nate: Two weeks ago it was Uber's engineers. Last week it was the AI-pilled people at your small business. Notice what they have in common: they were already technical, or at least really tech-savvy. That's the truth about the ceiling I promised.Here's what changed for me: I stopped nodding along. When a developer mentions a webhook or an environment variable, I don't file it under "not my department" anymore. I turn on voice mode on the walk home and say, "Explain that to me like I run the company but not the codebase." There are no bad questions in that room, and it will re-explain at whatever altitude you ask for.AI raises the floor, but the ceiling stays low if you don't build your tech literacy along with your AI fluency. And I'm talking about a pretty basic level, the way a CEO talks to their CTO. You don't write the code, but you know what a server is, which of your files live in the cloud versus on your laptop, and how to keep them organized enough to find one.If that's already you, keep going. The two skills help each other immensely, and every bit of it compounds.If you closed that door years ago ("I'm not a technical person, I never will be"), here's the great news: there has never been a better time to open it. You now have the most incredible tech support, explainer, and duet partner sitting alongside you. With screen recording or an agent driving your browser, it walks you through things that used to require hours and hours of tech support.So slow down and let AI teach you your own machine. What's one term you've been nodding along to for years? Ask AI to explain it this week, at exactly the level you want.AI TRAINING- Pick one AI workflow you know well. Choose something simple but useful, like an AI reporting routine, research process, or content workflow
- Use a tool like Loom to record a five-minute video of your screen and face. Walk through the AI solution, but emphasize the “human-in-the-loop” aspect
- Paste the Loom transcript, link, and job description into ChatGPT/Claude. Tell it: “Create a five-slide deck with the video embedded on one slide. Use the other slides to explain my thought process and how the workflow operates”
The Rundown: Apps and agents increasingly need to run long-running background tasks — but serverless is too restrictive, and managing workers and queues by hand is a headache. Render Workflows gives you the best of both in a lightweight SDK.With Render Workflows, you can:- Define tasks in a few lines of code and chain them into long-running, distributed workflows
- Launch agents and batch jobs on demand, without spinning up infrastructure
- Let Render handle queuing, orchestration, and retries automatically
- “Recurrent depth” has the model analyze the same text in repeated loops before answering, squeezing extra intelligence out of the model without making it larger.
- The loops reportedly improve performance but come with thinking outputs that are pure math, instead of the more readable reasoning in past models.
- OAI reportedly dialed the loops back so Astra still writes its reasoning out, and its blog promises extra monitoring of that reasoning at launch.
- Chief Scientist Jakub Pachocki posted that he wants to "prevent a race into unmonitorability" from "confused reporting," while calling monitoring "fragile."
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Gemini 3.8 Flash - Google's strongest Flash model yet for coding and agents
Muse Spark 1.3 - Meta’s new cost-effective, near-frontier model
H3 Max Turbo - Fal's video model at twice the speed, half the cost
- Read our last AI newsletter: Fable 5.1 kicks off launch week at the frontier
- Read our last Tech newsletter: Dyson puts AI in a $499 toothbrush
- Read our last Robotics newsletter: Hugging Face’s robot duck is a hit
- Today’s AI tool guide: Nail job interviews with the “Proof Project” method
- RSVP to next workshop on Sept. 9: Build your ad creative strategy with Claude
Source: https://therundownai.beehiiv.com/p/meta ... unch-party