245% faster is a massive claim, but dropping clunky step-by-step tool calls for full JS functions makes a lot of sense! Testing it rn, will report back 🙂
AI
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245% faster JS function execution: a promising new approach
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Claiming 245% faster completion is a big statement, but their approach of running full JS functions instead of step-by-step tool calls makes a lot of sense!
— Charly Wargnier (@DataChaz) 30 mai 2026
Going to have to try this 👀 https://t.co/TE7DdyHXN1Claiming 245% faster completion is a big statement, but their approach of running full JS functions instead of step-by-step tool calls makes a lot of sense! Going to have to try this
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AI founders for startup builders and community lists for researchers
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AI founders for startup builders.
AI community lists for researchers. https://
x.com/scobleizer/lis
ts
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Amazon plans to launch AI content marketplace
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Amazon plans to launch AI content marketplace
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @timnitgebru @oriolvinyalsml @ceobillionaire @soumithchintala @waitin4agi_ @sallyeaves @bernardmarr -
Unsolved productivity measurement makes AI ROI furiously difficult
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Plus the perennial challenge that measuring productivity of software teams (and knowledge workers in general) remains an unsolved problem, so calculating an "ROI" on your AI spend remains furiously difficult
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Token maxing leaderboards are a stupid idea for enterprise plans
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… and those "token maxing" leaderboards, which were clearly a stupid idea to begin with, are even more of a stupid idea if you're on an "enterprise" Anthropic/OpenAI plan where you get billed at full API token price, not consumer-subscriber discounts
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2025 AI budgets shocked by 2026 agent token surge
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I think the real story here is that anyone who set their AI budget in 2025 is going to get a shock in 2026 because agent tools that didn't work in 2025 are good enough in 2026 that their teams will be burning way more tokens than anticipated
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Abacus AI: Build Complex SaaS Apps & Automations with Agent Swarms & Top Models
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🚨 Agent Swarm – Build Complex SaaS Apps And Automations On The Abacus AI Super Computer!
— Abacus.AI (@abacusai) 30 mai 2026
Create multi-agent swarms using top models including Opus 4.8, Gemini 3.5 and GPT 5.5
Each agent excels at different tasks – coding, testing, mobile app, research and monitoring
Master… pic.twitter.com/wwLxfA3kVVAgent Swarm – Build Complex SaaS Apps And Automations On The Abacus AI Super Computer! Create multi-agent swarms using top models including Opus 4.8, Gemini 3.5 and GPT 5.5 Each agent excels at different tasks – coding, testing, mobile app, research and monitoring Master
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Latent prediction reduces sample complexity in hierarchical data learning
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"Learn from your own latents, not tokens: A Sample Complexity Theory" This paper explains why data2vec and JEPA can learn with much less data. They showed that when data has hidden hierarchy, token prediction becomes harder as the hierarchy gets deeper. But latent prediction
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Image comparison: unreleased model, Nano Banana Pro, GPT Image 2
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Which image do you like the most? One of them is from the unreleased model, one is Nano Banana Pro and one is GPT Image 2. Prompt below. Model reveal later today.