No, I am saying that this is the equivalent of TikTok brain rot for Local AI Longest prompt was 368 tons, longest output was 3k and some grifters out there are saying that this is great results of 45tok/s lol If you cannot see how this is performative slop / grifting then
AI
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Codex’s AI capabilities on macOS showcased
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Watching Codex use a Mac that’s fully locked feels slightly impossible the first time you see it. Apple built trusted foundations on macOS for this years ago. Codex is now shipping something magical on top of them!
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Sarcastic commentary on short prompt and costly hardware
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I mean, dude's longest prompt was 368 tokens and longest output was 4k He's literally crying next to that hardware and hoping to get enough engagement that elonbux can pay for his next month installment on those desk warmers
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Neer Jain on Model Ensembling for Improved Prediction Performance
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Neer Jain Explains Model Ensembling Strategies Used to Improve Prediction Performance in The Competition! #BigData #Analytics #AI #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux
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AI Enters the Kill Chain: Unity in Principle, Variation in Practice
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Unity In Principle, Variation In Practice: When AI Enters the Kill Chain! #BigData #Analytics #AI #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
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Matrix Factorization Explained for Recommendation Systems
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What's Matrix Factorization! #RecSy #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #Linux #Mathematics #Programming #Coding #100DaysofCode https://
geni.us/Matrix-RecSys -
Four Phases of AI in Academic Research: Core Principles
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First survey covering all 4 phases of AI in academic research. 5 Core Principles: > Structured tasks work. Judgment doesn't.
> Generation outpaces verification.
> AI assists humans, doesn't replace them.
> Explore. Execute. Verify.
> Disclosure beats detection. -
On-chain GANs: InChainPepeGAN, Concrete, and AAA improvements
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I stand corrected! There are at least two on-chain GANs that predate this, InChainPepeGAN (from 2023!) and Concrete by Higgs by @0xdiid
. So AAA is not first in that regard, although it's still innovative, as it generates clear subjects in high res, so it pushes fidelity forward -
Omni AI: Text Processing and Subject Tracking Workflow
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Omni is good at text and at tracking subjects. You can combine these things to make moving labels, etc. https://t.co/eo50cfiHYk
— fofr (@fofrAI) 22 mai 2026Omni is good at text and at tracking subjects. You can combine these things to make moving labels, etc.
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GPT 5.5 improving while Claude models worsening, no clear winner
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GPT 5.5 seems to be improving in that direction now, and Claude models are getting worse at it, so I don't think there's a clear winner now.