please honor commit. accept permadeath

PHASEONE(big)
Based in Nigeria
Women discuss issues from different loci. And the loci depends on how they woke up that morning. So women can discuss an issue from the woman's perspective as a positive thing & example of her independently doing what she want. Or from male loci as negative thing done to her
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Huge thanks to everyone who helped us push this one further ❤️ @juliewdesign_ obviously as she's part of the team, but also @invideoOfficial for their support throughout. Also the folks inspiring me on this journey such as @chrizmillr and @philiplord who I hope will take a look :)
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🤯 We made a 16-minute, feature-quality animated episode with a tiny team. In under a month. ⚔️🌿 JUNKYARD KING | CH. 3 | THE OTHER SIDE 🌿⚔️ Now here’s where it gets really interesting: if this technology keeps moving forward, what happens to filmmaking? 🎬 More stories? More creators? Writers building their own worlds? A complete reshuffling of what creative talent actually does? I thought editing was safe, but here come agentic workflows. 😅 The end-to-end democratization of high-end production is starting to feel very real. FULL 16-MIN EPISODE ↓
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Reduce (cut) benefits to elderly people & health benefits to repeat chronically ill (80/20 rule, majority users of benefits) Strictly enforce legal migration only, and for skilled workers only (they tend to contribute more taxes and use less benefits)
The solution is to bill interest payments separately to voters as a flat tax (flat rate, not flat amount), with a $50 yearly minimum.
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A few people asked how I made the isometric objects and cities, so I packaged it into a Claude skill. Describe an object, device or building, and ISO-GLOW creates a single interactive HTML file. Try it out yourself! isoglow.dev
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1. Rent a VPS on @Hetzner_Online or similar. Start small, like 4GB of RAM 2. Install the Codex or Claude CLI on the VPS and set up ssh by creating an ssh key on your laptop. 3. Add the ssh key to Codex Desktop, Claude desktop or Cursor in the “remote connections” settings. 4. Great! You can now manage your cloud agents on your laptop as if they are local. Bonus: You can close your laptop and they’ll keep running 5. Similarly, you can set up ChatGPT mobile or Claude mobile so you can talk to your agents from your phone. Create an ssh key for your phone using the @TermiusHQ app, and add it in the “remote connections” settings 6. You can now manage cloud agents from both your laptop and phone. The only downside I see so far is that cloud agents on a VPS cannot leverage computer use, as the VPS runs Ubuntu without a browser. There’s probably a way to fix that 👀
i've gotten pretty comfy with my local tools and files and skills. now you're telling me cloud is better. how do i do that? genuine qs
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Yes, you can now build an inbox in an afternoon. Congratulations, you are now responsible for: - Deliverability. - Bounce management. - SPF, DKIM, DMARC. - A domain that slowly drifts into spam. - Finding out it why the hell it's drifting into spam?! - Parsing emails from a mail server last updated in 2007 - HTML, plain text, and emails somehow containing neither. - Outlook’s interpretation of HTML. - Outlook’s other interpretation of HTML. - Threading that breaks when someone changes the subject. - Someone starting a new conversation by replying to an email from 2022. - Forwards inside forwards inside forwards. - CC, BCC, reply-all, and someone who really shouldn’t have clicked reply-all. - Attachments. - Attachments with malware.. - Inline images that become attachments. - Attachments that were supposed to be inline images. - A company logo attached to every reply, forever. - Quoted replies. - Distinguishing a quoted reply from the actual reply. - Someone answering your five questions inside the quoted reply. - Signatures longer than the conversation. - The out-of-office that answers your out-of-office. - Two autoresponders having a productive weekend together. - Notifications that fire twice. - Notifications that never fire. - A reply sent from the notification itself. - A reply to a notification about an internal note. - Making absolutely sure that notes stays internal. - Permissions. - Two teammates writing the same reply. - Drafts that sync across devices. - Drafts that overwrite other drafts across devices. - A confidently displayed “Saved” that was optimistic. - Snoozed conversations. - Time zones (!) - Daylight saving time (!!) - A conversation snoozed until a time that technically doesn’t exist. - One customer showing up as three people across email, chat, and Slack. - Three different people sharing one email address. - Merging them. - Undoing the merge. - Search. - Search that finds the thing you can literally see on screen. - Webhooks arriving twice. - Webhooks arriving out of order. - Webhooks not arriving. - Retrying a failed send without sending the customer six apologies. - Rate limits you discover during your first traffic spike. - Training your AI on your product. - Scraping your website. - Scraping the pages that need JavaScript. - Not scraping your entire website footer into every answer. - PDFs. - PDFs that are actually pictures of PDFs. - Keeping the content fresh. - Knowing when content changed. - Knowing when content disappeared. - Making the AI forget the pricing page from last year. - Conflicting answers across your docs, website, and past replies. - Deciding which one wins. - Chunking. - Embeddings. - Reindexing everything when you change embedding models. - Retrieval that finds the answer, not just something with similar words. - Web search tooling. - Knowing when to search. - Prompt injection hiding in a page you just scraped. - An agent confidently promising a feature you don’t have. - An agent confidently issuing a refund it shouldn’t. - Tool permissions. - Tool timeouts. - Tool retries that issue the refund twice. - Knowing when to hand off to a human. - Actually handing off to a human. - Not continuing to argue after handing off to a human. - Evaluating whether any of this works. - Evaluating it again after a model update. - Token budgets. - Context windows. - A customer pasting an entire novel into the chat. - WebSockets. - WebSocket authentication. - Reconnecting WebSockets. - Reconnecting 10,000 WebSockets at once after a restart. - A connection that looks alive but isn’t. - A phone switching from Wi-Fi to mobile data mid-message. - Messages that arrive once. - Messages that arrive in order. - Messages that arrive. - Syncing read states. - Unread badges. - Typing indicators that stop typing eventually. - A customer opening your widget in six tabs. - Anonymous users becoming logged-in users. - Logged-in users logging out on a shared computer. - The iPhone keyboard covering the message composer. - Safari. - Keyboard navigation. - A widget that must not slow down the actual product. - Explaining that “sent” and “delivered” are different things. - A help center. - An editor. - An editor that survives pasting from Google Docs. - Images. - Image resizing. - Broken images. - Article drafts. - Autosave. - Version history. - Restoring the version before someone deleted half the article. - Reordering nested categories without losing an afternoon. - Slugs. - 301 Redirects when slugs change. - Internal links that now point nowhere. - Working out which translations need updating after an edit. - Search that understands what customers mean. - Custom domains. - DNS verification. - SSL certificates. - Renewing SSL certificates. - Someone putting Cloudflare in front of your Cloudflare. - Mobile layouts. - Dark mode. - Code blocks. - Tables on small screens. - Sitemaps. - Canonical URLs. - Accidentally indexing draft content. - Accidentally deindexing published content. - Cache invalidation. - “I published it. Why does it still show the old version?” - Making sure your AI sees the new version too. - Spam. - Phishing. - Someone uploading malware as “a screenshot of the issue.” - Someone pasting their CC details into chat. - Someone asking you to delete every trace of that CC. - Logs that also contain the CC. - Backups that also contain the CC. - Backups. - Restoring backups. - Discovering those are two separate features. - An expired token. - A background job that quietly stopped on Thursday. - “Disk is full.” Sunday. 3 a.m. - Monitoring all of this. - Monitoring the monitoring. Now you have two jobs 🤷‍♂️
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how to eliminate UI slop in claude code and codex: > build first draft > install 0xdesigner MCP with one prompt > tell agent to give me the first draft > set thinking level (medium suggested) > grab a coffee, go for a walk > return and tell agent to implement my design 0xdesigner.com
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What if, for any scientific claim, you can search 100M+ papers to find the strongest evidence for and against it ⚡️in 1 second? That’s now possible with Evidence API! 🚀 paperclip.gxl.ai/evidence-ap… For example, does drinking coffee reduce diabetes risk?
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My agent stack: - @instinct - on-the-go purchases, form fill, local recs - @Muse - mini-apps that require reliable connectors (ex. "track my sleep and movement, send me a survey daily") - @tomo - motivation + goal tracking, also want to try their Interest Groups - @bot - X feed monitoring + alerts - Dots (@OpenAI) - deep, long-running projects...I'm currently making it start a business 👀 - @townai - everything work-related in email, Slack, docs - @Tabdotbot - outbound phone calls / appts
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i haven't opened my laptop in days. i'm fully phone agent pilled. i can do anything i want, and the UI is exactly what i want and need, and not more.
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Introducing Workers IO Agents are making it possible to turn ideas into software faster than ever. To keep up with that, we need better ways to understand how our software will behave in real-world. Workers IO runs your entire system through millions of simulated futures, exploring what happens when machines fail, networks slow down, and events arrive in the wrong order. It searches for the combinations that break your system before your customers encounter them. Every failure it encounters is perfectly reproducible, helping teams understand what happened, work on a fix, and verify against the same scenario. This ability changes what teams are willing to take on. Difficult engineering decisions become things that you can explore and verify. That’s the future we’re working toward: small teams building increasingly ambitious systems, with the evidence to stand behind. I can’t wait to see what you build with that confidence.
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🤣🤣it’s well.
My guy lost his job last month and his girlfriend just broke up with him over an argument they had in December 2025. Women. Lol.
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My guy lost his job last month and his girlfriend just broke up with him over an argument they had in December 2025. Women. Lol.
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We’re on a mission to build a billion AI models, not trained by us, but by you. Introducing @bryel_labs we help your company build its in-house AI lab and give you the software to make model development and continual improvement simpler. We are backed by @ycombinator and have trained models at Apple, Framer, and F500s. We’ve enabled companies to train: • Classification models that are 20x faster • Search models that cost 5x less. • Long horizon agent models that match the frontier at 5-8x lower cost. Are you interested in partnering with us? Reach out. bryel.ai/
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Every online file converter makes you upload your files to a random server Introducing convt Right-click any file, pick a format, done. - images, video, audio, PDFs and docs - macOS, Windows and Linux (soon) - runs 100% locally and it's open source 👀
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$ANET Andy Bechtolsheim says AI has made optics demand about 10 times bigger in five years and the industry is only at the "very beginning" "So I guess I don't need to tell you that AI has been driving this incredible increase in demand for high-speed optics, which is probably now 10 times bigger than it used to be five years ago..." "And what I want to talk to you today is that we're not at the end of this journey, but rather the very beginning. There's easily another order of magnitude increase in bits needed for the next generation kind of data centers." "So what I want to talk about first is what's happening at the data center level, and how we as an industry have to get together to solve these problems of this very rapid and high demand growth as fast as possible, since AI can't wait." ______ For full set of takeaways to Andy's AI Datacenter and Optics lecture: firesidealpha.substack.com/p…
$META Devansh Tandon reveals the tokens-in, engagement-out flywheel behind Meta's recommendation system, where better models lift Reels watch time 30% and the monetization pays for the next training run "These scaling curves aren't just academic research. They're driving real product impact at scale for some of the biggest consumer businesses in the world." "Here's a couple of examples I have from Meta's recent earnings reports. Instagram Reels had a strong quarter, 30% year on year watch time." "And the optimizations we made to improve the quality of recommendations included simplifying our ranking architecture to enable efficient model scaling and longer interaction histories to identify a person's interests." "We doubled the length of user interaction sequences used for training Instagram and increased the richness of each user interaction." "So these are direct parallels to the power law scaling curves for LLMs." "And I want to introduce this idea of a flywheel of tokens in engagement out, which is what's powering all of these recs models scaling." "You train a model, you then run inference on it, which is the tokens in, that recommendation model results in better content recommendations, it drives consumer engagement, daily active users' time spent, it translates to monetization and ads or subscription, which pays for the next model training run." "And so every step on the scaling curve is one loop around this flywheel, and a lot of consumer apps are spinning this core flywheel at the heart of their business. So we have a long way to scale these recommender systems." _______ For the full breakdown of the lecture on Meta's ads recommendation system: firesidealpha.substack.com/p…
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Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
$ANET Andy Bechtolsheim says AI has made optics demand about 10 times bigger in five years and the industry is only at the "very beginning" "So I guess I don't need to tell you that AI has been driving this incredible increase in demand for high-speed optics, which is probably now 10 times bigger than it used to be five years ago..." "And what I want to talk to you today is that we're not at the end of this journey, but rather the very beginning. There's easily another order of magnitude increase in bits needed for the next generation kind of data centers." "So what I want to talk about first is what's happening at the data center level, and how we as an industry have to get together to solve these problems of this very rapid and high demand growth as fast as possible, since AI can't wait." ______ For full set of takeaways to Andy's AI Datacenter and Optics lecture: firesidealpha.substack.com/p…
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An uncomfortable truth for a lot of people is that a lot of the most successful people in any industry are wicked smart. We apply stereotypes based on the loudest people, but its not representative of norms. Most are crazy smart and got to where they are because of it. I grew up in LA, one of my parents was a TV producer, my wife was an actor, many friends "in the industry." I've been constantly surrounded by it, and some of the stupidest seeming people (cause its their bit) are actually insanely smart and strategic in private. It sometimes is just beneficial for various reasons to... not show that side of you. My favorite anecdote was when a friend (a model) was dating a phD in physics and a very rude person made some off the cuff degrading comment to model friend about it without realizing model friend has their own phD in math lol. You wouldn't know from their instagram though! For the quoted video, I don't know Ben Affleck. I don't know how deep his knowledge goes. He's almost certainly not going to be more knowledgable than someone who professionally does this area of work full time, but he also to me on the surface sounds like someone who knows a LOT more than the average person and possibly even the average software engineer (on this topic). Anyways, this applies to tech too. I see it constantly.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
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Today we are open-sourcing 🥕Karotte, our framework for building RL environments. We've used it for the past year to build MLE RL environments for frontier labs, and it's been hardened through 1M+ evaluation runs and red-teaming.
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