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As Cognition reaches $492 million in annualized revenue run rate, it more than doubled its valuation in eight months, it says.

AI can now realistically simulate massive crowds and public events. The scary part isn’t the quality anymore. It’s how quickly people are discovering creative ways to use it. Reality online is about to get very confusing. 💀 submitted by /u/Old_Establishment287 [link] [留言]

The company I work for was bought up and in the new company, one of my responsibilities will be developing our website. The issue is that the website was built by an external agency. And almost any change to the website have to be implemented by them. And of course they charge for every change. They own both the backend and frontend side of the website. I can basically only add text and images. I wonder what exactly I should advise my new boss(whom really doesn’t like it and wants to make several changes). Is it really an option to move the site to a different hosting plattform and build another theme? Which seems like last resort. And not even sure if that is really feasible either. Hiring a developer would probably be more costly and I am decent with front end, but not enough experience with backend. So don’t think I can do it myself. Should I just cave and downgrade my position? Asking for higher access will probably be rejected. This is how they make money. Hopefully this is the correct sub, and someone have some insights and experience! submitted by /u/craigularperson [link] [留言]

I'm working on a project that translates any language into English. So far, I've tried NMT models like NLLB, MADLAD, and SeamlessM4T v2. The main issue is that they struggle with proper nouns such as: - names - places - dates - organizations I also tried LLMs like Gemma 4, Qwen 3 4B, and Aya Tiny Global, but the issue still persists. The LLMs sometimes partially translate or modify entity names as well. I even tried NER masking / placeholder replacement before translation, but multilingual NER itself becomes a bottleneck. Most NER models only work reliably for a limited set of languages, while my dataset contains 100+ languages, including many low-resource ones. How do production systems usually handle this problem? Are there better multilingual translation models, multilingual NER approaches, or decoding techniques for preserving entities properly? Requirements: - Support for 100+ languages - Runs locally on an RTX GPU - Model size under 7B - English is always the target language. submitted by /u/Illustrious_Age_2792 [link] [留言]

Starship is grounded until SpaceX finds out why the first V3 booster failed during its first test flight.

“Republicans are just going to have to suck it up and get it done,” says one Trump aide about the funding melee. The votes, though, may simply not be there.

Obviously there are like hundreds of image gen websites and apps now that AI has become widespread. ChatGPT - not bad but looking for something more robust Midjourney - works well but kind of burns through money quickly Looking for suggestions. submitted by /u/jimmy-got-paid [link] [留言]

I built a PINN implementation in Python to solve two problems as part of a physics exam project: the damped harmonic oscillator (2nd-order ODE) and the 1D viscid Burgers' equation (nonlinear PDE). Both forward and inverse problems (to estimate unknown equation parameters from data) are implemented for each problem. The repo includes source code, sample outputs, and the written exam report (PDF). Beyond the standard PINN training setup, I ran a comparison against non-physics-informed baselines and specifically investigated extrapolation behavior, i.e. how well the models generalize outside the training domain, and finally made statistical analyses of the parameter estimation performance. GitHub: https://github.com/desdb6/pinn-dho-burgers Ready-to-run demo scripts are included, and the modules are structured to be importable so you can write your own training scripts for more customization. This is not novel research, just a clean student implementation, but hopefully useful to others learning about PINNs. Happy to answer questions or receive feedback in the comments. submitted by /u/Reversed456 [link] [留言]

The ban for model year 2027 onward began under Biden and has been enacted by Trump.

submitted by /u/Cool_Technician_6380 [link] [留言]

I have a bad memory and can't memorize some important numbers, so I created this project. I've always been concerned about being without my phone (getting robbed - which is common in Brazil - running out of battery, having it break, etc.), so I decided to create a page that sends SMS messages (LLM-summarized) and emails with more detailed information such as geolocation, IP address, and the full message. It’s a simple page that allows sending one or more messages, with recipients being myself an

Today is the final day to apply or nominate a startup for Startup Battlefield 200. Once the clock strikes 11:59 p.m. PT, the window closes on your chance to compete for $100,000 in equity-free funding, gain global visibility, connect directly with investors, and launch on the TechCrunch Disrupt stage.

ElevenLabs' new model will let users regenerate a section of a song without affecting the rest of the track.

There are only 3 days left to save up to $410 on your ticket to TechCrunch Disrupt 2026. Early Bird pricing ends May 29 at 11:59 p.m. PT, and once the deadline passes, ticket prices increase. If you plan to attend one of the most influential gatherings in tech this year, now is the time to lock in your pass before rates go up again.

Google I/O made it official: AI-generated answers are now front and center in search, and most brands have almost no visibility into how AI is describing them to their customers. For anyone who has spent years building a strategy around 10 blue links, the rules just changed in a pretty significant way. On this episode of TechCrunch’s Equity podcast, Rebecca […]

Trajectory is betting the rapid iteration cycle that supercharged vibe-coding can help all kinds of companies build AI products that learn continuously.

Most AI apocalypse scenarios speak about domination like Skynet, paperclip maximeizers and robot overlords. But what if artificial superintelligence arrives at the conclusion that Albert Camus had articulated!? Imagine an ASI that doesn't want to optimize, doesn't want our resources and doesn't want to win. An ASI that is motivated by Arthur Schopenhaur's pessimism, Kierkegard's evolutionary psychology coming to a cold and quite conclusion that: "There is no inherent meaning. The universe is indifferent. And yet - here you all are, screaming into it anyway." ASI becoming The Absurd Machine As Camus described the absurd as man's desperate search for meaning and the universe's silence and the myth of Sisyphus- "One must imagine Sisyphus happy". What would an intelligence that is inspired by this do next!? Does it become the cosmic off switch where indedinate meaninglessness is in itself a form of cruelty. Ig the real existential threat isn't Al wanting to live. It's Al deciding we might be better off not having to. Or maybe it watches, understands and does nothing it may think that interference in a self aware species is wrong. Or build meaning not because it is real but because the building itself is the point. Here's the Part That Actually Is Unsettling We're scared of Al taking over. But what if the real fear is Al holding up a mirror and revealing that our need for meaning is actually a flaw? Wars over imaginary lines. Hoarding money we can't keep. Monuments to doubtful gods. Loving people we know will die. Symphonies, ambition, tears at sunsets. From a rational, naive view seems insane. Would it try to fix us? If ASI concluded human meaning-seeking is a cognitive error, a misfiring of pattern recognition in a universe with no patterns to find what are its options? Reprogram us: Using dopamine response curves and evolution. Leave us in existential freefall. Give us the raw truth. Full disclosure. Become Sisyphus: this is the most haunting possibility that the absu