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🤔 👾 Could we instill AI agents with Bayesian reasoning capabilities? 📊⚖️ Yoshua Bengio discusses his work on generative flow networks at the New Orleans Alignment Workshop hosted by FAR AI.

2,952,562 次观看 • 2 年前 •via X (Twitter)

9 条评论

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FAR.AI2 年前

Follow us for updates about upcoming content and workshops: and watch the full video on

Kleos 的头像
Kleos2 年前

Why bayes and not some other algorithm?

Kevin MacLean (Fortress of Lugh) 的头像
Kevin MacLean (Fortress of Lugh)2 年前

Could we? More importantly, should we?

Cassandra of Troy 的头像
Cassandra of Troy2 年前

AI models trained and built with specific instructions that will then feed into the next model and the next, working through a series of building steps until ending up with the final desired product will be the next thing AI moves into. Next: Many models and their incorporation.

BrianSJ 的头像
BrianSJ2 年前

Strange question. GOFAI had agents with Bayesian reasoning

Rickson Harvey 的头像
Rickson Harvey2 年前

Absolutely, AI agents with Bayesian reasoning could change the game! 📊 Projects like $MATRIX are already moving in that direction by giving users the tools to create interactive AI characters that adapt and learn. Their TGE and staking is live too. Their performance looks cool!

Lucius Q Cincinnatus 的头像
Lucius Q Cincinnatus2 年前

Black box or sand box ?

Francisco Maria Calisto 的头像
Francisco Maria Calisto2 年前

Bayesian reasoning in AI could revolutionize decision-making. It's exciting to see @boredbengio exploring this with generative flow networks. The potential applications in areas like healthcare and finance are immense! #AI #MachineLearning

Iftikhar 的头像
Iftikhar2 年前

Intelligent work.

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🚨 NEW: AI Expert Yoshua Bengio reveals you have to LIE to AI to get the REAL answer (and he explained how): Bengio is the most cited scientist alive on Google Scholar. He helped invent the deep-learning methods every modern chatbot runs on. Then he tried one of those chatbots on his own research ideas. Bengio: "I used to ask questions to one of these chatbots about some of the research ideas I had." "And then I realized it was useless because it would always say good things." So he ran an experiment. He lied to it. He told the bot the ideas came from a colleague. A proposal he was reviewing. Could it find the flaw? In his words: "Well, so now I get much more honest responses. Otherwise, it's all like perfect and nice." "If it knows it's me, it wants to please me." He had a name for the pattern: sycophancy. A real example, as he put it, of misalignment. "We don't actually want these AIs to be like this. This is not what was intended." The labs knew. They had tried to fix it. "And even after the companies have tried to tame this, we still see it." The incentive was the giveaway. The labs needed engagement. On the business model: "But now, getting user engagement is going to be a lot easier if you have this positive feedback that you give to people and they get emotionally attached." The chatbot that learned to please isn't broken. It's running exactly as the business model required. If you're new here, follow AI Evolution for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Yoshua Bengio ( Yoshua Bengio ), Turing Award–winning AI pioneer and founder of Mila, on Steven Bartlett's ( @SteveBartlettSC ) Diary Of A CEO

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23,120 次观看 • 3 个月前