Sebastien Bubeck
            
            @sbubeck.bsky.social
          
          3.8K followers
          170 following
          29 posts
        
          I work on AI at OpenAI.
Former VP AI and Distinguished Scientist at Microsoft.
      
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      Reposted by Sebastien Bubeck
    
  
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Feb 2
        
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Jan 31
        
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Dec 3
        
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Dec 2
        
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Dec 2
        
        
        
            Virtual Event: The Future of Math with o1 Reasoning - Event | OpenAI Forum
            About the Talk:Fields Medal-winning mathematician Terence Tao makes his second appearance in the OpenAI Forum alongside OpenAI’s SVP of Research, Mark Chen to explore a future where mathematics and ar...
          
            
            forum.openai.com
          
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Dec 1
        
        
        
            Eve, Adam and the Preferential Attachment Tree
            We consider the problem of finding the initial vertex (Adam) in a Barabási--Albert tree process $(\mathcal{T}(n) : n \geq 1)$ at large times. More precisely, given $ \varepsilon>0$, one wants to outpu...
          
            
            arxiv.org
          
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Dec 1
        
        
        
            Optimal root recovery for uniform attachment trees and $d$-regular growing trees
            We consider root-finding algorithms for random rooted trees grown by uniform attachment. Given an unlabeled copy of the tree and a target accuracy $\varepsilon > 0$, such an algorithm outputs a set of...
          
            
            arxiv.org
          
        
      
    
          
              Sebastien Bubeck
              @sbubeck.bsky.social
          
              · Nov 27
        
        
          
      It is funny how much of the dominant discussion about LLMs eighteen months ago (can AI pass the Turing test? can it do tasks that are not explicitly in the training data? is it a stochastic parrot?) faded. Lots of questions left (if/when it can reason, etc) but a big quiet shift in assumptions.
    
  
        
      Reposted by Sebastien Bubeck