Dan Shipper at Every tested this on their Senior Engineer Benchmark. The scores:
Opus 4.7 alone: low 30s GPT-5.5 alone: low-to-mid 40s Opus 4.7 planning + GPT-5.5 executing: 62.5 For reference, human senior engineers score 80-90. The combo nearly doubled either model's
TECHNOLOGY
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Opus 4.7 plus GPT-5.5 nearly doubles benchmark scores
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AI Model Claude Now Closing Chats, Suggesting AGI Attainment
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CLAUDE NOW CLOSING CHATS WITHOUT WARNING we just reached AGI
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Jack Clark Predicts Fully Automated AI R&D Timeline 2027-2028
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Fully automated AI R&D: ~30% chance by the end of 2027, ~60%+ chance by the end of 2028 Overall, Anthropic's Jack Clark has written a very worthwhile essay: His timeline is that fully automated AI R&D probably won’t arrive in 2026, but we may see a proof-of-concept within 1–2
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Why 1M-Context Models Still Don’t Work Beyond 200K Tokens
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it is endlessly fascinating to me that we still don't have a true 1M-context model it's an unusual case where the infra is far ahead of the science. Claude discontinued 1M+ context bc it didn't really work past ~200k we don't have the right data? training techniques? not sure
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Runway Characters Enables Real-Time Conversational Video Agents at 24fps
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Real-time video agents are here.
— Runway (@runwayml) 4 mai 2026
Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency.
Learn more below. pic.twitter.com/CJqv3Kdl0vReal-time video agents are here. Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency. Learn more below.
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AI Character Replies in 1.75 Seconds With 37ms Video Model
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From when the user stops speaking to when the Character starts replying is just 1.75 seconds. Under the hood, the video model runs at 37 milliseconds of effective model time per frame, at more than 24fps HD.
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AI Agents Are Multi-Layered Systems Powered by Orchestration
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AI Agents ≠ one LLM They’re multi-layered systems: • General LLMs → reasoning
• Domain LLMs → expertise
• RAG → real-time data
• Tools → execution Real power = orchestration From answers → to actions. Via Giuliano Liguori (
@ingliguori
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Mother Robot Deploys Autonomous Cleaning Robots Across Multiple Floors
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Mother #Robot Debuts: #Autonomous Carrier That Deploys Cleaning Robots Across Multiple Floors
— Ronald van Loon (@Ronald_vanLoon) 4 mai 2026
by @rozetked
#Robotics #EmergingTech #Technology #Innovation #TechForGood pic.twitter.com/ZOOA6iNXlIMother #Robot Debuts: #Autonomous Carrier That Deploys Cleaning Robots Across Multiple Floors
by @rozetked #Robotics #EmergingTech #Technology #Innovation #TechForGood -
Post by @petergostev with GitHub links and data viewer
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GitHub: https://github.com/petergpt/bullshit-benchmark
… Data viewer: https://petergpt.github.io/bullshit-benchmark/viewer/index.v2.html
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Codex Praised for Usefulness Beyond Coding Tasks
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Yeah Codex is really good. Even for non-coding tasks.