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"Noise" entsteht nicht nur in Daten - auch in Entscheidungen. Gleiche Situation, andere Entscheidung? Dann fehlt ein System.
📖 Basierend auf "Noise" von Daniel Kahneman
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Here’s to continuing the journey of building better, more effective teams! 💙
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Fascinating study on AI cooperation! Different LLMs show unique social behaviors - just like humans in teams 🤔
#AI #SoftwareTeams #DevCulture https://arxiv.org/abs/2412.10270
Large language models (LLMs) provide a compelling foundation for building generally-capable AI agents. These agents may soon be deployed at scale in the real world, representing the interests of individual humans (e.g., AI assistants) or groups of humans (e.g., AI-accelerated corporations). At present, relatively little is known about the dynamics of multiple LLM agents interacting over many generations of iterative deployment. In this paper, we examine whether a "society" of LLM agents can learn mutually beneficial social norms in the face of incentives to defect, a distinctive feature of human sociality that is arguably crucial to the success of civilization. In particular, we study the evolution of indirect reciprocity across generations of LLM agents playing a classic iterated Donor Game in which agents can observe the recent behavior of their peers. We find that the evolution of cooperation differs markedly across base models, with societies of Claude 3.5 Sonnet agents achieving significantly higher average scores than Gemini 1.5 Flash, which, in turn, outperforms GPT-4o. Further, Claude 3.5 Sonnet can make use of an additional mechanism for costly punishment to achieve yet higher scores, while Gemini 1.5 Flash and GPT-4o fail to do so. For each model class, we also observe variation in emergent behavior across random seeds, suggesting an understudied sensitive dependence on initial conditions. We suggest that our evaluation regime could inspire an inexpensive and informative new class of LLM benchmarks, focussed on the implications of LLM agent deployment for the cooperative infrastructure of society.
Software Development – Mob Programming, Pair Programming or Fly Solo? – by @chrisoldwood – ACCU 2024
Anneke Keller is de nieuwe CTO van PostNL, is commissaris bij BrandMR en zit in de raad van toezicht van het Wereld Natuur Fonds. In haar loopbaan bouwde ze driemaal bijna from scratch een softwareontwikkelteam op: bij TomTom, bij Coolblue en vervolgens bij Jumbo. Samen met Tim Meeuwissen schreef ze het managementboek The Cherry Model, over de ‘seizoenen’ die innovatieve teams doormaken en het belang van fasering daarin.
Software Development – Mob Programming, Pair Programming or Fly Solo? – by @chrisoldwood – ACCU 2024
Software Development – Mob Programming, Pair Programming or Fly Solo? – by @chrisoldwood – ACCU 2024
Software Development – Mob Programming, Pair Programming or Fly Solo? – by @chrisoldwood – ACCU 2024
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