APPLE: "AFM Plus 150B Instruct" Apple Foundation Model has been spotted in the internal AFM Playground app. This app is being used internally by Apple employees to test Apple Foundation models. WWDC26 will be hot
LLMS
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IDEs Are Dead: Coding Models and the SaaS Apocalypse
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IDEs are dead.
— Replit ⠕ (@Replit) 30 avril 2026
When coding models plateau, the moat moves up the stack. @amasad sat down with @HarryStebbings on @twentyminutevc to talk about the SaaS apocalypse, why Cursor’s bet looks shakier by the week, and what it actually takes to stay 10 steps ahead.
Full conversation… pic.twitter.com/JVWmNDv03iIDEs are dead. When coding models plateau, the moat moves up the stack. @amasad sat down with @HarryStebbings on @twentyminutevc to talk about the SaaS apocalypse, why Cursor’s bet looks shakier by the week, and what it actually takes to stay 10 steps ahead. Full conversation
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LLMs Enable New Horizons Beyond Coding Acceleration
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Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights:
— Andrej Karpathy (@karpathy) 30 avril 2026
The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Three examples of new horizons:
1. menugen: an app that can be fully engulfed by… https://t.co/AJFgYC6SoNFireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights: The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Three examples of new horizons: 1. menugen: an app that can be fully engulfed by
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User Praises OpenAI GPT-5.5 as Impressive Model
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I do at the moment. Mostly because I like OpenAI models a bit better right now. GPT-5.5 is really damn good.
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Cursor AI Tests Harness for Models to Improve Speed and Efficiency
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Our agent harness makes models inside Cursor faster, smarter, and more token-efficient. Here's how we test improvements to the harness, monitor and repair degradations, and customize it for different models.
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Critique of GDPval-AA AI Benchmarking and Artificial Analysis Transparency
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i started writing about it in september, see my essay called Peak Bubble.
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Distillation Practice in AI Should Be Covered by Fair Use
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What people call "distillation" is a super common practice (you use other models to benchmark your model, to evaluate your inputs or to add a little bit to your datasets) that in my opinion should be covered by fair use (just like using public data is), especially when the
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Falkor’s Open-Source GraphRAG SDK Tops GraphRAG Benchmark
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Falkor's new GraphRAG SDK just took #1 on GraphRAG bench and yes it's open source
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Researcher Claims Priority on World Models Concept Since 2016
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I started using the concept in 2016 (e.g. in my NIPS 216 keynote, in which I called it a "world simulator"). I published papers on video prediction in 2016.
This was meant to be a key step to train world models.
Ha&Schmi appeared in 2018. The slide below is from a talk I gave -
AI Performance Is Now a Data Movement Problem Not Compute
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Everyone is scaling compute. That’s not the bottleneck anymore. AI performance is now a data movement problem. Every token =
read → fetch → compute → repeat And that loop is inefficient on traditional GPUs (like NVIDIA Blackwell B200). More FLOPs won’t fix it. Dataflow