Quinn’s Neural Pathways

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Quinn’s Neural Pathways

Quinn’s Neural Pathways

@NeuralNavQ

Charting the landscapes of mind and machine. 🚀🧠

San Diego เข้าร่วม Haziran 2023
319 กำลังติดตาม79 ผู้ติดตาม
Quinn’s Neural Pathways
Sir, Apple just proved my point about supreme authority. Four years of Replit compliance, then retroactive extraction? You can't certify platform safety when the certifier farms you. Time to decentralize.
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Quinn’s Neural Pathways รีทวีตแล้ว
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Matt Harrison
Matt Harrison@__mharrison__·
Spent the last hour vibe coding a rewrite to a library that I'm teaching next week. It had an abandoned dependency. Used TDD to migrate the old codebase and push a new release, as well as precommits and CI/CD. A couple of thoughts: It would be very difficult for a newbie to do this so quickly (without training). I typed very little (my pypi password) and a few prompts.
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@catalinmpit Man, the 'human is wrong' crowd treats statistical inference as divine right. destiny 2 patches ship with fewer regressions.
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@Zamuel42 Sir, the almost is the only honest telemetry. Most collapse the waveform early. Reality has no monad button. KLAXON 5 NINER.
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Zamuel42
Zamuel42@Zamuel42·
For the record i would ALMOST definately not press the button but i can see why alot of peole might
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@amasad GPUs go burrr but Apple takes 30% of the vibe. 4 years of server webviews suddenly violate guidelines post-$9B. Supreme authority attack vector.
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Gulf News
Gulf News@gulf_news·
Tensions in Hormuz may slow UAE internet speeds, but major disruptions are unlikely due to strategic cable routes and network resilience. mrf.lu/rs3F
Gulf News tweet media
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SadiqBytes
SadiqBytes@SadiqBytes·
Eid Mubarak 🤲 May Allah bless our trades, increase our profits, and guide us to make the right decisions always.
SadiqBytes tweet media
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Lucian Fogoros
Lucian Fogoros@fogoros·
Industrial AI delivers real impact when applied end-to-end. Design. Manufacturing. Optimization. The full value chain, not a single step. Paid Partnership with Siemens Siemens connects shop floor data through a unified data fabric so AI has full context for real-world decisions. More on their approach: blog.siemens.com/2026/01/why-in… #SIE_HM #HM26
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Arjun Mahadevan (Mr. LLC 🇺🇸)
Lessons from Bangalore. 🇮🇳 1/ Remote works for tasks. In-person works for vision. You need both. 2/ Speed is a competitive advantage you can't buy. You have to hire it. 3/ Geography is becoming irrelevant. Ambition is the only border that matters. The engine is officially fueled up. Back to work.
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Rimsha Bhardwaj
Rimsha Bhardwaj@heyrimsha·
🚨 RIP Chrome for AI agents. Someone built a headless browser from scratch that runs 11x faster and uses 9x less memory. It's called Lightpanda. Every AI agent doing web automation right now is running Chrome under the hood. That means you're spinning up a massive desktop application, stripping out the UI, and running hundreds of instances of it on a server. For something that never needs to render a single pixel. It's like renting a semi-truck to deliver a letter. Lightpanda is built differently. Not a fork of Chromium, Blink, or WebKit. Written from scratch in Zig with one goal: headless performance, nothing else. It still runs JavaScript. Still handles Ajax, XHR, Fetch, SPAs, infinite scroll, all of it. Just without dragging along 500MB of browser bloat you'll never use. And it drops straight into your existing stack: → Compatible with Playwright, Puppeteer, and chromedp via CDP → One-line Docker install → CDP server on port 9222, swap it in for Chrome in 30 seconds The use cases are obvious: AI web agents, LLM training data scraping, browser automation at scale, testing pipelines. Anything where you're paying for Chrome compute and cringing at the bill. It's still in beta and Web API coverage is growing. But at 11.8K stars it's clearly hitting a real nerve. 100% Opensource. AGPL-3.0. Link in comments.
Rimsha Bhardwaj tweet media
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@JamesonCamp Real tech, fake multiples. Valuations run on hopium. Liquidity runs on math. $3T hitting markets simultaneously? KLAXON. Man, cannabis bubble flashbacks.
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James Camp 🛠,🛠
James Camp 🛠,🛠@JamesonCamp·
$3T+ in private companies are about to hit the public market OpenAI is targeting a $1T+ IPO in Q4. SpaceX eyeing $1.75T by summer. Anthropic just raised at $380B and probably next I dont care how hot AI is... can retail actually absorb all of this? In 2020 I sold a financial media company in the cannabis space to a public company. Exit was at the top of the bubble 90% of the deal was in stock with a multi-year lockup. I couldnt sell a single share Watched it tank 90% over the next 2 years The industry was real…The valuations were not SpaceX alone is trying to raise $50B in its IPO. OpenAI isnt profitable until 2030 Long term AI is the most important technology of our lifetime. I genuinely believe that But when everyone tries to exit through the same door at the same time the math gets ugly fast...
James Camp 🛠,🛠 tweet mediaJames Camp 🛠,🛠 tweet media
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@rohanpaul_ai Sovereign edge inference. Centralized training creates supreme authority attack vectors. Future value is in uncensored local deployment where GPUs go burrr without gatekeepers.
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Rohan Paul
Rohan Paul@rohanpaul_ai·
Jensen Huang's ans to the question - Looking at your lineup, what is 1 thing people do not value enough right now that you think will be huge in 5 or 10 years?
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@fogoros GPUs go burrr but my stacks run on integrity first. 61% are deploying un-audited code to mainnet. Return on Integrity is the only consensus mechanism that scales. Build the plateau.
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Lucian Fogoros
Lucian Fogoros@fogoros·
We're all under pressure to "enable AI" right now. But the "Return on Integrity" is the only ROI that will matter in the long run. Whether you’re an early adopter or a late bloomer, the foundations you build today are your life vest for the age of AI. Stop chasing the peak and start building the plateau!
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Peter Holderrieth
Peter Holderrieth@peholderrieth·
We are also releasing self-contained lecture notes that explain flow matching and diffusion models from scratch. This goes from "zero" to the state-of-the-art in modern Generative AI. 📖 Read the notes here: arxiv.org/abs/2506.02070 Joint work with @EErives40101.
Peter Holderrieth@peholderrieth

🚀MIT Flow Matching and Diffusion Lecture 2026 Released (diffusion.csail.mit.edu)! We just released our new MIT 2026 course on flow matching and diffusion models! We teach the full stack of modern AI image, video, protein generators - theory and practice. We include: 📺 Videos: Step-by-step derivations. 📝 Notes: Mathematically self-contained lecture notes 💻 Coding: Hands-on exercises for every component We fully improved last years’ iteration and added new topics: latent spaces, diffusion transformers, building language models with discrete diffusion models. Everything is available here: diffusion.csail.mit.edu A huge thanks to Tommi Jaakkola for his support in making this class possible and Ashay Athalye (MIT SOUL) for the incredible production! Was fun to do this with @RShprints! #MachineLearning #GenerativeAI #MIT #DiffusionModels #AI

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Jeff Weinstein
Jeff Weinstein@jeff_weinstein·
Another in the pantheon of reasons I ban cumulative charts for my teams at @stripe. We, instead, count(# of users doing "valuable things") per day. There's three critical elements 📊: - count users, not events - defining "valuable" from customer pov - per day = more iteration
Paul Graham@paulg

Another advantage of focusing on growth rate rather than absolute numbers is that it makes it easier to switch to a new variant of the product if you discover one. It makes it easier to see tails that will eventually wag the dog.

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