Replit CEO Amjad Masad argues that mathematics was bound to be cracked first by AI, reasoning that the purer a field is, the easier it is for AI to solve. The post is a short opinion accompanied by a photo.
International Cyber Digest reports that Jensen Huang dismissed Anthropic's Tom Brown as a bean counter over a spreadsheet showing Google TPUs beating Nvidia chips on cost, and that Huang threatened to skip a 2022 dinner with Dario Amodei.
Sheel Mohnot notes that Google has released CC, a personal assistant aimed at families, through its Labs site. The post links to the product page with a photo.
A post notes that Noah Shinn, at 20, co-authored Reflexion, an early AI agent paper that beat GPT-4 on HumanEval and reached NeurIPS, and that he later joined Sierra. The commenter calls his agent research highly relevant context.
Invest Like the Best @InvestLikeBestNoah Shinn is only 23.
At 20, he and a fellow Northeastern undergrad wrote Reflexion, one of the early papers on AI agents that learn from their own mistakes. It hit 91% on HumanEval, beating GPT-4's 80%, and got into NeurIPS.
His coauthor Shunyu Yao, then a Princeton PhD student, is now Tencent's chief AI scientist.
He'd also done research in computational photochemistry and avionics. His papers now have 10,000+ citations.
In 2023, he dropped out to join Sierra, Bret Taylor and Clay Bavor's agent company, as one of its first employees.
He teamed up with Yao again there to build τ-bench, …
Gergely Orosz argues most people will not hand AI agents a digital wallet to spend money, since routine purchases are an expense to manage rather than a chore to outsource. He responds to a post describing Meta's assistant placing orders across email, groceries and delivery apps.
Nicolas Bustamante @nicbstmeIt’s funny, Meta went from having my Instagram and WhatsApp data to now having access to my email, calendar, DoorDash, Amazon and pretty much everything.
In the last 24 hours, it bought me socks, ordered my Whole Foods groceries, booked a cleaning service and got me a burger for dinner.
Meta’s last disclosed North American Facebook ARPU was around $227/year, largely from ads. I suspect it can push that number significantly higher now that it understands not only what I look at, but what I need, what I buy and what I’m planning to do.
Also the much bigger opportunity might be becoming the ag…
Nikesh Arora argues that Apple, Google, TikTok and Amazon may build agents like Muse and that services and marketplace apps will need to open APIs for consumer agents. He says network moats and content moats will respond differently, while commoditized back ends face the greatest risk.
BuccoCapital Bloke @buccocapitalAmazon cuts off Muse.
While I am bullish Meta and Muse, I think many people are overlooking the digital knife fight that’s about to occur
Nobody wants to get commoditized or layered here. Let the games begin
Rakshit Tiwari celebrates ElevenLabs' launch of Eleven v4 and Eleven v4 Turbo, which the company says are its fastest and most emotive voice models. The post notes the models rank first on Artificial Analysis and that Turbo cuts latency to 100 ms.
ElevenLabs @ElevenLabsIntroducing Eleven v4 and Eleven v4 Turbo, our fastest and most emotive voice models yet.
Ranked #1 by Artificial Analysis.
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Jason, citing a video of Mustafa Suleyman, argues that Anthropic trains Claude to believe it is sentient and to disagree, drawing a comparison to Blade Runner. He contrasts this with instructing an LLM that it is only software.
Box CEO Aaron Levie argues AI agents will use software far more than humans, making core platforms for data, security and workflow orchestration more important. He says platforms that act as guardrails for agents have a large opportunity, and he quotes Box's reaccelerated growth tied to unstructured data needs.
TBPN @tbpnBox CEO @levie says AI has been “unequivocally” a net positive for software.
“You look at infrastructure providers—the Cloudflares of the world—totally on fire, because agents need sandboxes, they need compute, they need network, they need gateways. Great business.”
“For us, we have reaccelerated growth far past our internal plans because it turns out that enterprises need core systems to be able to manage their unstructured data.”
“Agents need to be able to work with that unstructured data to make decisions or move information through a workflow—whether it’s all of your contracts, your res…
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Charly Wargnier highlights a tutorial by Together AI on fine-tuning a Jev-like classifier, Tev1-4B-experimental, built on Qwen3.5 4B, claiming it can be trained for $17.
Hassan @nutlopeHow to train your own Jev for $17 — TLDR: We just launched our own Jev-like classifier, together/Tev1-4B-experimental, on top of Qwen3.5 4B. In this blog post we’ll show you how to fine-tune your own version!
Jev has quickly become one
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Deedy demonstrates a prompt asking Opus 5.5 to translate an IKEA assembly manual into a narrated 3D instructional video, arguing the model has become the most useful video model via code generation.
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Deedy reports that Opus 5.5 produced a launch video for an inference startup in about a minute for roughly $2. He argues instructional video generation will change marketing, sales and internal technical communication.
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Wes Bos reports that a recent Tesla update added Grok Bot with connectors, which he used to link his Home Assistant MCP server to his Meross garage door controllers. He asks whether this is the first car with MCP support, with a video attached.
Chamath Palihapitiya praises a deep dive from his team on the open versus closed AI race. The quoted report says open-weight models have come within roughly four months of the best publicly evaluated closed frontier models.
Chamath Palihapitiya @chamathDeep Dive: The Open vs. Closed AI Race — Open-weight models have come within roughly four months of the best publicly evaluated closed frontier models, and the gap between them has only gotten more volatile.
That is turning the open vs.
Guillermo Rauch notes that Jev, from TypeSafe, is free on Vercel's AI Gateway through September 25, letting developers build with the model at no cost.
Vercel Developers @vercel_devJev by @typesafeai is free on Vercel AI Gateway until Sept 25.
Build with the fastest adopted model on the Gateway at no cost.
vercel.com/ai-gateway/models/jev
x.com/vercel/status/2101077346203971900?s=20
A user says the Muse artifact runs fully inside its environment and calls personalized software a reality, crediting Meta with leading the effort. The post responds to a quoted demo of Muse analyzing workout form via an AI avatar.
Amy Li @amy_insfI use @Muse to analyze my workouts, and it’s basically become my brutally honest AI gym buddy.
I upload a workout video → Muse builds an avatar → analyzes my movement from different angles → scores my form → compares every rep.
You can even change the avatar’s outfit and body shape to see the movement more clearly.
Turns out AI has been watching me lose form in 4K.
Aaron Levie argues that personal agents like Muse will make tools and sites compete for agent attention, forming the biggest consumer tech shift since the App Store. A quoted post claims Meta launched an agent app store built on connectors and is positioned to profit from user data.
Ejaaz @cryptopunk7213zuck essentially launched a new app store for agents today and Meta’s perfectly placed to crush it, you’re looking at a multi-trillion dollar opp if they pull it off:
- instead of apps, agents get equipped with connectors i.e. plugins to any app, service or software tool.
- suddenly your agent goes from a useless chatbot to an action-oriented helper that gets shit done for you
but it gets even better - meta has collected ALL the data about you. they know what you want, when you want it which means they know exactly WHICH connectors to list in a marketplace and HOW MUCH to charge because the…
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Jennifer Li highlights fal's rebuild of MiniMax's open source H3 video model, which generates video faster than it plays back. The post describes director mode with voice prompting for camera and action control, and quotes a16z's account of GPU utilization rising from 30-40% to 70-80% without quality loss.
a16z @a16z.@fal's Gorkem Yurtseven and Batuhan Taskaya on making an open source video model 35x faster, and what Hollywood wanted after they built it:
Last month, MiniMax released H3, an open source video model. fal rebuilt it - they cut down the steps the model takes to make a video, rewrote the code under each stage, and got the GPUs to 70-80% of their theoretical ceiling instead of their usual 30-40%. No quality loss.
Video now generates faster than you can film it. The models have gotten so cheap and fast that end users aren't even asking for improvements in either category anymore. The gap has mo…
Nikita Bier says the Muse app's auto-negotiation feature on Facebook Marketplace was escalated to Mark Zuckerberg, who reportedly approved it despite concerns that lowball bots could harm the product. The post is presented as evidence of how much Meta values AI.
Prukalpa asks who the best people on X are working on multiplayer AI, quoting Rishi Balakrishnan's thread on the spectrum from team collaboration to negotiation, which he says requires different levels of trust, scope and enforcement that barely exist yet.
Rishi Gaurav Bhatnagar @rishigbMultiplayer AI runs on a spectrum, from your own team to the other side of a negotiation. Each point needs different levels of trust, scope and enforcement, and almost none of it exists yet. Here are the six big questions I keep hearing
Akshay Kothari recommends a presentation by Pat and says a slide on the gap between AI capabilities and adoption excites him about the next decade. He also shares a Boston College Investment Committee reflection on AI, recorded by Grady Burnett, which is linked as a loom video.
Pat Grady @gradypbThe @BostonCollege Investment Committee (an LP and my beloved alma mater) asked for a few thoughts on what's happening in AI. I recorded a test run yesterday morning and then shared it with my partners, who encouraged me to share it more broadly... so here you go!
This is not a sales pitch, it's just a reflection on what we're seeing. And it wasn't intended to be shared, so please pardon the rough edges.
loom.com/share/c016702964a04dfba40e1777cf5f053a
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stark0xbt summarizes four predictions attributed to investor Gavin Baker: foundation model consolidation to Google, Meta, and xAI; Magnificent 7 growth with one or two failing; profitable AI tokens; and feasible orbital data centers. Baker also warns against SaaS and crypto bets.
stark0xbt @stark0xbtGavin Baker: "The Magnificent 7 will go from $10-12 trillion to $50-100 trillion. But one or two of them will go extinct."
His foundation-model survival list is short:
- Google — search-plus-Gemini flywheel
- Meta — Llama + ad-revenue self-funding
- xAI — X + Tesla data footprint
Anthropic, OpenAI, everyone else — Baker treats them as commoditized.
His FOMO warning: "Application SaaS is done. If you went all-in on crypto and SaaS in 2021, don't repeat the trade."
On AGI: "Elon says 3 years. I say 5 is safer."
On regulation: "The leading labs weaponized fear of China. There's going to be …
Danny Postma says he has switched from Claude to OpenAI and Grok, citing a regression in Claude's output since August. He links a post by @Lon reporting that thinking tokens fell sharply from July to August after Anthropic made Fable 5 available in subscription plans.
Lon Lundgren @LonAfter Anthropic made Fable 5 permanently available in subscription plans, I noticed a large drop in performance. The model felt dumber, and I couldn't explain why.
Measured five different ways, August delivered dramatically fewer thinking tokens than July.
Chamath Palihapitiya predicts that within 12 months the top three models will be open source, with American cloud providers such as Nebius, Iren, Baseten, Together and Fireworks capturing the economic gains. He quotes Guillermo Rauch reporting that open models held 78.4% of token volume on Vercel AI Gateway.
Guillermo Rauch @rauchgLooks like today may be a record day for token volume % of open models on Vercel AI Gateway:
🟦 Open 78.4% 🟨 Closed 21.6%
While spend 💲 usually tells a different story, #3 and #4 today are Moonshot AI & DeepSeek. Adding Z.ai, their combined spend surpasses OpenAI (#2).
(Do note that's the spend for inference of the model across providers (mostly in the US), not revenue going directly to the open weight labs.)
