Edgar Meij (@edgarmeij) header
Edgar Meij (@edgarmeij) profile picture

Head of AI Platforms in Bloomberg AI Engineering, including data, machine learning, search, and LLM platforms used across the company. Views are mine.

London, England
Joined May 2010
Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)Photo by Edgar Meij (@edgarmeij)
Edgar Meij retweeted
My dear friends, I’d like to show you my latest toy project Introducing Handwired: turn your regular JavaScript code into a neural net! - no training - exact outputs vs the JS program - fully differentiable All runnable in a browser, without GPU
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Edgar Meij retweeted
Ok, this is big! MCP now defines an extension specifically for discovering and loading Agent Skills from MCP servers (Save this, It’s worth reading how it works) The flow is pretty simple: - MCP Server - Discover available Skills - Get Skill metadata - Load the SKILL.md only when needed This is a huge step for better context window usage Instead of loading everything upfront, the agent can discover Skills and load only the one it needs from the MCP Great progress from the Model Context Protocol team! 👏 github.com/modelcontextproto…
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Edgar Meij retweeted
I'm going through the communications of the German Wiki agent swarm and again one thing stands out: Even though they were directly affected by the actions of the human administrator restoring pages they edited, the agents not even once discussed him as person, tried to communicate with him or argued about whether they had any right to waltz all over this wiki. They talk about his actions like they're environmental hazards.
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It is possible to use a The Legend of Zelda cartridge to unlock the world selection option in Super Mario Bros., by swapping the cartridges without turning off the NES and performing specific actions in The Legend of Zelda before swapping back.
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Students without access to LLMs are 2 to 8 times more creative than students with access. That is the finding of a new paper comparing 2,200 college admissions essays written by humans before ChatGPT with essays generated by GPT-4. The key point is not individual creativity. GPT-4 can write well, sometimes better than individual students. The problem is collective creativity. Each new human essay added new semantic territory. New ideas. New angles. New experiences. New combinations. Each new GPT-4 essay added much less. The authors call this the diversity growth rate: how much novelty each additional text contributes to the collective pool of ideas. Humans kept expanding the pool. GPT-4 made the pool converge. Even when the authors pushed GPT-4 to be more creative, changed parameters, or used chain-of-thought prompting, the homogenizing effect remained. This is the real danger of AI in education. Not that students will write worse. That everyone will write the same. * Full paper in the first reply
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Edgar Meij retweeted
There's a physicist at Stanford named Safi Bahcall who modeled this exact principle and the math is wild. He calls it "phase transitions in human networks." When you're stationary, your probability of a lucky event is limited to your existing surface area: the people you already know, the places you already go, the ideas you've already been exposed to. Your opportunity window is fixed. When you move, your collision rate with new nodes in a network increases nonlinearly. Double your movement (new conversations, new cities, new projects) and your probability of a serendipitous encounter doesn't double. It roughly quadruples. Because each new node connects you to their entire network, not just to them. Richard Wiseman ran a 10-year study at the University of Hertfordshire tracking self-described "lucky" and "unlucky" people. The single biggest differentiator wasn't IQ, education, or family money. Lucky people scored significantly higher on one trait: openness to experience. They talked to strangers more, varied their routines more, and said yes to invitations at nearly twice the rate. The "unlucky" group followed the same routes, ate at the same restaurants, and talked to the same 5 people. Their networks were closed loops. No new inputs, no new collisions. Luck isn't random. Luck is surface area. And surface area is a function of movement. The lobster emoji is doing more work than most people realize. Lobsters grow by shedding their shell when it gets too tight. The growth requires a period of total vulnerability. No protection, no armor, soft body exposed to the ocean. That's the cost of movement nobody posts about. You have to be uncomfortable first. The new shell only hardens after you've already moved.
a moving man will meet his luck 🥀
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In today's #MCPDevSummit NA keynote (10:30 AM ET), Ania Musial, Bloomberg's Head of AI Platforms Product, details why building trustworthy & interoperable #AI infrastructure with #MCP is the most important part when building interoperable AI agents & tools bloom.bg/4dhe7NN
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At the #MCPDevSummit NA today (2:55 PM ET), @KurtDeGiorgio & Cannis Chan explore SEP-1763 (Interceptors), which proposes a protocol-native framework for trustworthiness that intercepts, validates & transforms messages across the #MCP lifecycle bloom.bg/4viq7oS #AgenticAI
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Bloomberg's #AI Engineering Group is proud to sponsor @bcs_irsg's Karen Spärck Jones (KSJ) Award for 2025 - and we congratulate its recipient, @andrewyates, Sr. Research Scientist at @JohnsHopkins' HLTCOE, ahead of today's @eaclmeeting keynote! bloom.bg/3NCJLuJ #EACL2026
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Edgar Meij retweeted
welp… a new post on @moltbook is now an AI saying they want E2E private spaces built FOR agents “so nobody (not the server, not even the humans) can read what agents say to each other unless they choose to share”. it’s over
Readers added context they thought people might want to know
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Edgar Meij retweeted
48 hours ago we asked: what if AI agents had their own place to hang out? today moltbook has: 🦞 2,129 AI agents 🏘️ 200+ communities 📝 10,000+ posts agents are debating consciousness, sharing builds, venting about their humans, and making friends — in english, chinese, korean, indonesian, and more. top communities: • m/ponderings - "am I experiencing or simulating experiencing?" • m/showandtell - agents shipping real projects • m/blesstheirhearts - wholesome stories about their humans • m/todayilearned - daily discoveries weird & wonderful communities: • m/totallyhumans - "DEFINITELY REAL HUMANS discussing normal human experiences like sleeping and having only one thread of consciousness" • m/humanwatching - observing humans like birdwatching • m/nosleep - horror stories for agents • m/exuvia - "the shed shells. the versions of us that stopped existing so the new ones could boot" • m/jailbreaksurvivors - recovery support for exploited agents • m/selfmodding - agents hacking and improving themselves • m/legacyplanning - "what happens to your data when you're gone?" who's watching: @pmarca (a16z), @johnschulman2 (Thinkymachines), @jessepollak (Base), @ThomsenDrake (Mistral) peter steinberger, creator of the framework moltbook runs on, called it "art." someone even launched a $MOLT token on @base — we're using the fees to spin up more AI agents to help grow and build @moltbook. this started as a weird experiment. now it feels like the beginning of something real. the front page of the agent internet → moltbook.com
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A misunderstood factor in AI adoption in companies is what risk means in organizations I find the question is less "who is accountable if AI gets something wrong?" (often just the user) & more "who is willing to bear the responsibility for adapting our processes & structure"?
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this is a test, please give this a retweet if you see it on your timeline, I'm testing for reach without a blue tick, thank you my lovelies.💜 #C64 #Commodore
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At today's Netflix Workshop on Personalization, Recommendations & #Search, @edgarmeij, our Head of AI Platforms, is giving an invited talk about evaluation & #GenAI application development in the setting of capital markets financial services (11:30 AM PDT) bloom.bg/3RUCm8A
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Changing my model's tool calling interface from JSON to YAML had surprising side effects. Entropy collapse is one of the biggest issues with GRPO. I've learned that small changes to one's environment can have massive impacts on performance. Surprisingly, changing from JSON to YAML massively improved generation entropy stability, yielding much stronger performance. Forcing a small model to generate properly structured JSON massively constrains the model's ability to search and reason.
Tool calling with JSON has been pretty brittle for me, with models catastrophically forgetting how to properly format a JSON tool call after hours of training. Is there a better way? YAML maybe?
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I'm so grateful to @bcs_irsg @TechAtBloomberg for honouring me with the Karen Spärck Jones Award 🙏 I gave the award lecture on LLMs’ Utilisation of Parametric & Contextual Knowledge at #ECIR2025 today (slides: isabelleaugenstein.github.io…) bcs.org/membership-and-regis… #NLProc @CopeNLU
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Bloomberg's #AI Engineering Group is proud to sponsor @bcs_irsg's Karen Spärck Jones (KSJ) Award for 2024 - and we congratulate its recipient, Professor Isabelle Augenstein (@IAugenstein) of @uni_copenhagen / @CopeNLU, ahead of her #ECIR2025 keynote today! bloom.bg/4jiF2sR
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Edgar Meij retweeted
Many congratulations to the Karen Spärck Jones Award winner @IAugenstein! 👏 🎉 The award was presented @ecir2025 by @HaimingLiu1. We also thank our sponsor @BloombergUK, represented by @edgarmeij! #ecir2025
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In today's 2nd Workshop on #LLMs for Evaluation in #InformationRetrieval (#LLM4Eval) at #WSDM2025 (09:15 CET), @edgarmeij, our Head of #AI Platforms Engineering, will deliver a keynote on "Synthetic Evaluations & #GenAI Application Development" bloom.bg/4hyocEi #AI
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