95% reliable is ~100% reliable if the hallucinations are uncorrelated across runs/systems/etc. It just means you spend a bit of extra effort on implementing a voting/etc layer and spend more on inference redundantly. This is almost boring.
AI
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Analyzing the nature of AI hallucinations for safety and reliability
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A related manner: there are many people who are quite worried that hallucinations will make AI unsafe or inappropriate for broad classes of problems. I very rarely hear those people explicitly try to reason whether hallucinations are a) random or b) persistent given request.
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Real-World Multi-Step Workflows Beyond Isolated Agent Benchmarks
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The agentic benchmarks are interesting but I want to see how it performs on real multi-step workflows not just isolated tasks
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The gap between technologists and society on LLM capabilities
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“And if you think that’s impressive, wait until someone puts it in a for loop.” a persistent source of why technologists and civil society have different POVs of the impact of various LLM capabilities improvements.
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Why Companies Pay Huge Money for AI Labelers
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Why Companies Are Paying Huge Money for AI Labelers Behind every powerful AI model is human input — companies are investing heavily in AI labelers to improve accuracy, reliability and performance. Read more https://
bernardmarr.com/why-companies-
are-paying-huge-money-for-ai-labelers/
… #AI #Data #FutureOfWork #BernardMarr -
Major News Sites Undercover Claude Mythos Release Coverage
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Think about it. None of the major newspapers have given Claude Mythos a prominent mention/Top Placement on their websites. We live in an AI ivory tower; 99% of people don't know what was published yesterday. They don't know what's coming. That's why our work is so important. Shakeel (@ShakeelHashim) The Anthropic Mythos release does not appear near the top of the homepage on any major news site today. The NYT is closest, but it's still pretty far down. The Guardian thinks a Vogue cover with Anna Wintour and Meryl Streep is more important. The Washington Post is prioritizing yet another "we tried to get into Berghain" story. The media is not adequately covering the insane moment we are in. — https://nitter.net/ShakeelHashim/status/2041829164894871584#m
→ View original post on X — @kimmonismus, 2026-04-08 14:04 UTC
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Universal Protocol Translator Unifies Factory Floor Industrial IoT
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Modbus. OPC UA. Siemens S7. Allen-Bradley. BACnet. 14+ protocols, one MQTT broker. No gateways needed. @corefluxiot built the universal translator for factory floors. #HM26 #coreflux_ai #OT pic.twitter.com/caC3PM5gtU
— Lucian Fogoros (@fogoros) 8 avril 2026Modbus. OPC UA. Siemens S7. Allen-Bradley. BACnet. 14+ protocols, one MQTT broker. No gateways needed. @corefluxiot built the universal translator for factory floors. #HM26 #coreflux_ai #OT
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Building Custom AI Agents with LangChain Deep Agents
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"Claude Code isn't magic. The harness layer is just software, and software is something any dev can shape to fit how they want to work." Check out @Hacubu’s practical guide to building a custom agent with @LangChain’s Deep Agents, LangSmith, and ACP. blog.jetbrains.com/ai/2026/0…
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Open Source Models Now Accessible on Local Hardware
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The fact that we're casually comparing open source models at this level is the real story. Two years ago this was a frontier model conversation. Now it's local hardware stuff.
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AI Model Power Consumption Explodes to City-Scale Levels
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Multiple gigawatts is an absurd number to read in a tweet. We went from 'how do we make the model smarter' to 'how do we power a small city' real fast