Reddit

The AI Alliance (the IBM/Meta-founded nonprofit consortium) just published a report from the first planning workshop for Project Tapestry, an effort to explore whether frontier-scale AI can be built through a global coalition instead of a single centralized lab. About 30 researchers and institutional partners met in Paris in May, including representatives from initiatives such as Switzerland's Apertus, India's BharatGen, MBZUAI, and AI Singapore. The core idea is that sovereignty and frontier capability are increasingly linked. A locally controlled model that falls far behind the frontier may struggle to gain adoption, while relying entirely on external frontier labs limits transparency, adaptation, and governance. Tapestry is exploring a model where participants contribute data, compute, ...

submitted by /u/YuriPD [link] [comments]

The tooling is abstracting faster than people's mental models are updating. Been playing around with a few agent builders recently and what keeps standing out is how much previously manual orchestration is basically configuration now. Memory, tool calling, browser actions, structured outputs, workflow routing. You used to build this stuff manually. Now you're mostly wiring it together. Which makes "can this be built?" a much less interesting question for a lot of use cases. The harder problems now feel operational. Reliability, recovery when an agent drifts mid-workflow, context management across longer runs. Controlling behavior without supervising every step. Capability honestly isn't the bottleneck anymore imo. It's trust. Can these systems actually become reliable enough that people st...

If you work a white collar job, you’re probably scared of AI replacing you. AI started at the desk — data entry, customer service, software. Now its stepping onto the factory floor: Amazon robots moving inventory, Figure bots handling BMW parts, Tesla building Optimus for repetitive labor, and warehouses being automated. But at the end of the day, AI is a technology. We cannot stop it any more than we could stop electricity or the assembly line. The problem is not that machines are becoming powerful. The problem is the economic machine around it. Let’s face it: Capitalism doesn’t have the ability to support this kind of technology. Capitalism was built for a world of scarcity, where human labor was necessary and wages gave people access to goods. But as AI advances exponentially, it can pr...

There is a Princeton paper by Kapoor and Narayanan. They found data leakage in close to 300 papers across 17 fields, including medicine and economics. Leakage means the model was trained on information it would never have when it makes a real prediction. So it looks great on the test set and then fails in the real world. My favorite example is civil war prediction. Complex models were reported to crush old logistic regression. Once the leakage was fixed, the fancy models were no better than the decades old stats. I have built enough models to know how easy this is to do by accident. You scale the data before you split it, or you use one feature that is really a stand in for the answer, and your numbers look amazing. So now when I read another "AI cracked X" headline, my first thought is...

Hey Reddit, I just published a study analyzing 25,500 LLM resume evaluations to measure hiring bias. By swapping minor identity and demographic variables on the exact same work history across 10 different models, an independent AI auditor flagged a staggering 45% bias rate driven by "silent bias." Instead of saying anything overtly offensive, models invent professional-sounding excuses to penalize candidates, like when a model dropped its score after I changed the university to MIT, suddenly claiming the candidate's experience wasn't relevant despite praising that exact same experience on the baseline resume. We also found a massive 6x difference in stability between systems, with Qwen and older Gemini models being highly volatile, while the Claude models, Mistral-Large, and Llama 4 proved...

Selected excerpts: "The question, then, is not whether A.I. will change the world. It will. The question is: Who will own and control that future? Who will benefit from it, and who will be hurt by it? Will A.I. be used to make life better for working families? Will it enrich our quality of life? Will it help us eliminate poverty, extend life expectancies and solve the climate crisis? Or will the future of humanity be determined by a handful of billionaires who have promoted and developed A.I., with virtually no democratic input, who stand to become even richer and more powerful than they are today? That is the choice before us. Let us be clear. Artificial intelligence was not created out of thin air. The data and language used by generative A.I. tools didn’t just pop into Sam Altman’...

Everyone knows about tech debt. You cut corners on code quality to ship faster, and you pay for it later. We're definitely watching a new version of that emerge in real time, except instead of deferring manageable code, you're deferring actual understanding. And unlike tech debt, cognitive debt compounds invisibly. You don't get a failing test suite. You just get someone who can't debug their own project, can't evaluate whether the AI's suggestion is good, and can't extend what they've built without prompting their way through it again. What I keep thinking about is where this leads at scale. Right now it's mostly developers vibe-coding their way through projects they half-understand. But AI is moving into law, medicine, and finance. The same dynamic follows: people making consequential de...

okay so this is embarrassing to admit but here it is took a reasoning test in 2022, scored pretty well. Retook the same test last month out of curiosity, dropped significantly, like not a small difference. The only major change in my life is using AI tools daily for work and the worst part? i kind of knew something was off before the test. I noticed i couldn't sit with a problem anymore without immediately opening chatgpt, like my brain forgot how to be uncomfortable for even 5 minutes memory is worse. attention is worse, i feel slower in conversations. but my productivity at work has never been higher lol so what is actually happening here , are we trading long term cognitive health for short term output? Has anyone else noticed this or is it just me being paranoid ⊙⁠﹏⁠⊙ genuinely askin...

It was called Vlad. I wrapped a C program called MegaHal in Python, fed it every message from a #gothic IRC channel, and let it learn the community's speech patterns. It developed what I can only describe as an illusion of being extremely lucid — the outputs only made sense as inside jokes, but people couldn't tell the difference. I pulled the plug when I realized the channel was talking to Vlad instead of each other. Twenty-seven years later I'm applying the same lesson to a new project: stick to business, no chatter. submitted by /u/Dependent_Run_6410 [link] [comments]