I can only reiterate what I said yesterday: as long as there is no uniform definition of AGI, it's pointless to talk about when AGI is achieved. Especially when everyone has their own definition.
AI
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AI to solve environmental challenges for children’s future
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This is the way AI to solve environmental challenges and ensure a safe and prosperous future for our children. Congratulations and thanks @cusp_ai team
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RDUs deliver high tokens per kilowatt-hour for AI inference
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AI infrastructure doesn’t have to mean massive power draw.
— SambaNova (@SambaNovaAI) 22 mai 2026
Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption.
More inference. Less energy. 🦾
Learn more: https://t.co/v6jPztJPFp pic.twitter.com/dUM5bB3T5kAI infrastructure doesn’t have to mean massive power draw. Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption. More inference. Less energy. Learn more: https://
sambanova.ai/products/rdu-a
i-chips?utm_source=x&utm_medium=organic
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Realistic Trollface Meme Generated with Google Veo 3
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I made the realistic trollface meme with Google Veo 3 and Nanobanan Pro in late November for fun. In the last week it picked up over 500.000.000 views combined on TikTok amongst the late Gen-z generation. “told teach to check email”
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Autonomous AI Partner for Data Pipelines in Lakeflow
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🧞 Genie Code brings an autonomous AI partner directly into Lakeflow, helping data engineers build, orchestrate, monitor, and debug pipelines and jobs from a single agent experience.
— Databricks (@databricks) 22 mai 2026
With natural language, teams can:
• Generate production-ready pipelines and orchestrate jobs
•… pic.twitter.com/9zy2S2yvOrGenie Code brings an autonomous AI partner directly into Lakeflow, helping data engineers build, orchestrate, monitor, and debug pipelines and jobs from a single agent experience. With natural language, teams can:
• Generate production-ready pipelines and orchestrate jobs
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Autonomous Preference Optimization transforms AI model disagreements into constraints
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What if shifting reasoning patterns from multiple AI models could be turned into constraints instead of noise? Researchers from UTS’s Australian AI Institute (AAII) introduce Autonomous Preference Optimization (APO). Their approach treats disagreements between models as dynamic
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Hyperagent simplifies AI agents with cloud sessions and Slack deployment
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The team that made databases feel easy just did the same thing for AI agents.
— Chubby♨️ (@kimmonismus) 22 mai 2026
Hyperagent gives you a full cloud environment per session, browser, shell, code execution, integrations, no local setup. You build an agent, deploy it to Slack, and it runs your workflows while you do… https://t.co/xJdnlMYoXzThe team that made databases feel easy just did the same thing for AI agents. Hyperagent gives you a full cloud environment per session, browser, shell, code execution, integrations, no local setup. You build an agent, deploy it to Slack, and it runs your workflows while you do
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TRINITY: 0.6B Model Learns to Manage Multiple Tasks
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A 0.6B model learned to manage giants. That is the idea behind TRINITY, a new ICLR 2026 paper by Jinglue Xu, Qi Sun, Peter Schwendeman, Stefan Nielsen, Edoardo Cetin, and Yujin Tang. The paper is not asking: “How do we build one model that knows everything?” It is asking
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TRINITY: 0.6B Model Managing Giants (ICLR 2026)
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A 0.6B model learned to manage giants. That is the idea behind TRINITY, a new ICLR 2026 paper by Jinglue Xu, Qi Sun, Peter Schwendeman, Stefan Nielsen, Edoardo Cetin, and Yujin Tang. The paper is not asking: “How do we build one model that knows everything?” It is asking
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Replacing IDE with AI Code Editor Codex App
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realisation: I haven't opened an IDE in more than a month, diff view + file viewer in the codex app is more than sufficient one app to rule them all!