@FrankieIsLost This diagram by @trychroma shows how accuracy crashes past ~5K tokens, dropping below 50/50. Let that sink in: you might need ~50 attempts to get the same result (if it exists). If not, you could be heading toward 100 tries with zero chance of success. https://t.co/qG2vWoAQBo https://t.co/OuSMrnUL3q

mlx-audio v0.4.0 is here 🚀 What's new: → Qwen3-TTS: fastest generation on Apple silicon and first batch support. > Sequential (<80 ms TTFB at 2.75x realtime) > Batch support (<210 ms TTFB at 4.12x for batch of 4-8) → Audio separation UI & server → nvfp4, mxfp4, mxfp8 quantization → Streaming /v1/audio/speech endpoint → Realtime STT streaming toggle New models: → Echo TTS → Voxtral Mini 4B, → MingOmni TTS (MoE + Dense) → KittenTTS → Parakeet v3 → MedASR → Spoken language identification (MMS-LID) → Sortformer diarization + Smart Turn v3 semantic (VAD) Plus fixes for Kokoro Chinese TTS, Pocket TTS, Whisper, Qwen3-ASR, and more. Thank you very much to @lllucas, @beshkenadze, @KarnikShreyas, @andimarafioti, @mnoukhov and welcome the 13 new contributors 🙌🏽 Get started today: > pip install -U mlx-audio Leave us a star ⭐ https://t.co/bQ5WBLR6FK

Even AI experts aren’t immune to the disruption they helped create. A machine learning engineer who thought his role was safe from automation was told AI could eventually replace much of his work. The lesson is becoming clear, no profession is entirely insulated from the technology it builds. https://t.co/Xlr7qqoB79 @futurism

New research on scaling agent memory for long-horizon tasks. One of the biggest challenges with AI agents is memory. As tasks get longer and more complex, agents lose track of what they've learned, what they've tried, and what worked. This paper, from Accenture, introduces Memex(RL), a system that gives agents indexed experience memory. Instead of relying on raw context windows, agents build a structured, searchable index of past experiences and retrieve relevant memories as needed. Long-horizon agent tasks like deep research, multi-step coding, and complex planning all require persistent memory. Memex(RL) shows how to scale this without blowing up context length. Paper: https://t.co/TWMF5HC6Qe Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

Do people become more conservative as they age? If they were born between 1940 and 1954, the answer is clearly "yes." Among people born from 1955 to 1979, there's really been no change. For those born in 1980 or later, it looks they are becoming more liberal as they age. https://t.co/cE3iJayMWH

New research from Databricks. It's about training enterprise search agents via RL. KARL introduces a multi-task RL approach where agents are trained across heterogeneous search behaviors, constraint-driven entity search, cross-document synthesis, and tabular reasoning. It generalizes substantially better than those optimized for any single benchmark. KARL is Pareto-optimal on both cost-quality and latency-quality trade-offs compared to Claude 4.6 and GPT 5.2. With sufficient test-time compute, it surpasses the strongest closed models while being more cost efficient. Paper: https://t.co/CToEmDU89J Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c

Block cut nearly half its workforce citing AI productivity gains. But current and former employees say the reality is more complicated, arguing many of their roles can’t simply be automated. The gap between AI expectations and operational reality is becoming a recurring theme in tech layoffs. https://t.co/YiM5Cxo6fl

If a fact or chart is surprising, it might be because it’s new information, or it might be something deeper — a sign that our mental model is wrong. Anthropic’s economic gap chart is the latter. https://t.co/c4vF9EetUk A big source of confusion in AI discourse is not recognizing that the speed of adoption follows its own logic that’s far slower than the speed of capability progress. I’m biased but I think AI as Normal Technology is still the best exposition of the many different speed limits to diffusion. Once we internalize this, the gap shown in the chart is what we should expect. How does this square with the “AI is the most rapidly adopted technology” narrative and all the graphs that are frequently shared to push that view? Unfortunately they lump together too many kinds of “AI use” to really tell us anything meaningful. On the one hand there are many marginal uses of AI (such as using chatbots instead of traditional search) that are being quickly adopted. But what will make a true economic impact are deeper changes to workflows that incorporate verification and accountability, manage the risk of deskilling, and are accompanied by organizational changes that take advantage of productivity improvements. Those changes happen at human timescales and are barely getting started. And that’s not even accounting for regulatory barriers. Finally, I’m also not sure how credible the “theoretical capability” estimates are. In particular, I don’t think they account for the capability-reliability gap, for which the AI community didn’t even have measurements until our work two weeks ago https://t.co/FI5kuBkdRZ

Farmers are turning to drones and AI to fight weeds more precisely. By identifying unwanted plants in real time, the systems can target herbicides exactly where needed. The result could mean lower chemical use, lower costs, and smarter agriculture. https://t.co/WITdTG6T8I @bbcnews

Recent media activity about the Abilene site are false and incorrect. First, Crusoe and Oracle are operating in lockstep to deliver one of the world's largest AI Data centers in Abilene at record-breaking pace. Two buildings are completely operational and the rest of the campus is on track. Second, Oracle has completed leasing for the additional 4.5GW to deliver on our commitments to OpenAI. We continuously evaluate sites around the world to meet the growing demand for OCI by working with great partners and customers all the time. https://t.co/rwuwL1QusC https://t.co/ZJbK257gAv

Introducing WorkBuddy, Tencent's AI native desktop agent for multi-type tasks. Handle non-technical tasks effortlessly using built-in skill templates for coding, documentation, research, data analysis, and automation. No projects setup required. One minutes to connect with IM like Wecom (WeChat for Work). Plan. Execute. Review. Deliver.

wow it's so cool that they added our favorite feature from the Claude Code CLI to the desktop app https://t.co/evcMJBWDf0

wow it's so cool that they added our favorite feature from the Claude Code CLI to the desktop app https://t.co/evcMJBWDf0

Someone built https://t.co/oipIfNWf2U a directory of 5,700+ failed YC startups with post mortems, deep analysis, and rebuild plans so you can revive dead ideas and turn them into new projects. https://t.co/C61yFfsVRu

Someone built https://t.co/oipIfNWf2U a directory of 5,700+ failed YC startups with post mortems, deep analysis, and rebuild plans so you can revive dead ideas and turn them into new projects. https://t.co/C61yFfsVRu

Traffic police… but in the sky. In Shenzhen, drones are now responding to traffic accidents in real time. Officers can analyze the scene remotely, generate a 3D reconstruction, and complete responsibility reports in about 5 minutes. https://t.co/hYefGavepK

@gokayfem thank you for the all the open sourcing 🤗 https://t.co/hhmff7iy2g

OpenClaw 2026.3.8 🦞 🔒 ACP provenance — your agent finally knows who's talking to it 💾 openclaw backup — because YOLO deploys need a safety net 📱 Telegram dupes killed 🛡️ 12+ security fixes We fixed more things than we broke. Progress. https://t.co/ahq26lABw3

we just wrote the ultimate beginner's guide to OpenClaw almost everyone @every has one now, and they have completely changed the way we work and live. we're using our claws to: - build product - answer customer service queries - book hard-to-get restaurant reservations - track our reading notes and much more this is the guide we wish we'd had at the start: https://t.co/66n3Wz6MT0

“The more laws, the less justice.” — Cicero https://t.co/hxnCa2vZWQ

Jim Cramer in 2010: “I’m not sure Tesla has a business plan that’s going to work, it’s not a smart investment” Inverse Cramer is so real https://t.co/dFRUzFczsb

Here are all the lighthouses of the Northern Seas, each light is the right color, each turns or pulses at the right frequency, and is scaled with its brightness. You can also see how far they are visible. I had Claude Code build this and upload it here: https://t.co/ZX6pyJhlr9 https://t.co/WZFewYGdUn

Created close reading notebooks for almost every lesson of @jeremyphoward's fastai deep learning course (it's more than a course) Close reading is a technique for reading out of text, not into. Use a LLM, and you're in flow state for longer–you ask right there, with all context. https://t.co/Wr1sWs40Tl