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Thibault Schrepel
@ProfSchrepel
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Associate Prof @VU_Law • Faculty Affiliate @CodeXStanford • Founder Stanford #ComputationalAntitrust project | @NetworkLawRev | Scaling Theory podcast • 🎾 🏃
#Antitrust #AI #Blockchain
Joined November 2012
🎙️ NEW PODCAST 🎙️ Where should I start? I am launching a new academic podcast called “Scaling Theory”. I am of course incredibly excited, but more importantly, I hope you’ll find it interesting. I want to explore the power laws behind the growth of businesses, technologies, legal systems, and living systems. The podcast will feature scholarly discussions with select guests (I’ve already recorded a couple, to be published very soon!!) and deep dives into the academic literature. Everything is explained in the introductory episode. ➝ Spotify: ➝ Apple: ➝ YouTube:
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@RobAtkinsonITIF @techreview 100%. I used to be a subscriber and recommended it to all my students. I stopped about two or three years ago when the new editor-in-chief arrived. Too bad—I liked it a lot.
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Very interesting strategy from @banditrunning: the more you scroll their website, the more 'distance' you accumulate. There is even a leaderboard. I could see how they might want to provide discounts or goodies if you pass specific distances...
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RT @ProfSchrepel: AI spending is going through the roof. Why? 1. Strong dynamic competition is at play. 2. The industry benefits from stron…
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“I think that there should be a constant effort among regulators and lawyers to work out the regulatory equivalence that would give the regulator what the regulator wants but in a context that permits or encourages open source development.” (@Lessig, @Harvard_Law). [link to the full conversation in the comment section]
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New episode of the Computational Antitrust podcast dropping next Monday! Our guest is Martijn Snoep, Chairman of the @AutoriteitCM. Here's a little snippet from a conversation I enjoyed very much! #computationalantitrust @CodeXStanford @groza_teodora
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Last week, my @VU_law students took their 'Foundations: Law & Technology & Economics' exam. The exam presented a set of facts (below), followed by questions on Article 102, the applicability of the DMA, computational antitrust, and a task requiring them to rewrite a portion of the DMA. Enjoy! PS: Wind is the fictive equivalent of @MistralAI; mistral being a cold northwesterly wind that blows through the Rhône Valley into the Mediterranean in France.
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The draft AI Act started with a definition of AI that pretty much covered all software in the world. The more it goes, the more the European Commission is reducing its scope…
🚨 BREAKING: The EU has just published guidelines on the EU AI Act's definition of AI. Many will be surprised to discover that the systems below are NOT COVERED [bookmark & download below]: 1. "machine learning-based models that approximate functions or parameters in optimization problems while maintaining performance. The systems aim to improve the efficiency of optimisation algorithms used in computational problems. For example, they help to speed up optimisation tasks by providing learned approximations, heuristics, or search strategies." 2. "satellite telecommunication system to optimize bandwidth allocation and resource management. In satellite communication, traditional optimization methods may struggle with real-time demands of network traffic, especially when adjusting for varying levels of user demand across different regions. Machine learning models, for instance, can be used to predict network traffic and optimize the allocation of resources like power and bandwidth to satellite transponders, having similar performance to established methods in the field." 3. "a chess program using a minimax algorithm with heuristic evaluation functions can assess board positions without requiring prior learning from data. While effective in many applications, heuristic methods may lack adaptability and generalization compared to AI systems that learn from experience." 4. "All machine-based systems whose performance can be achieved via a basic statistical learning rule, while technically may be classified as relying on machine learning approaches fall outside the scope of the AI system definition, due to its performance." 5. "Static estimation systems, such as customer support response time system that are based on static estimation to predict the mean resolution time from the past data and trivial predictors such as demand forecasting for a store to predict how many items of a product the store will sell each day are other examples, that help to establish a baseline or a benchmark, e.g. by predicting average or mean." 👉 Download & learn more below. 👉 NEVER MISS my AI regulation updates: join 51,500+ readers who subscribe to my weekly AI governance newsletter (link below)
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@Sherman1890 For my part, I now use ChatGPT more than Google for search purposes. And it seems that I am not the only one…
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@schmal_w Google "chatgpt compete google search" and limit to results published before the summer of 2024... :)
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