[HN Gopher] Trustworthy AI Without Trusted Data
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       Trustworthy AI Without Trusted Data
        
       Author : gnabgib
       Score  : 17 points
       Date   : 2025-04-10 19:24 UTC (3 hours ago)
        
 (HTM) web link (actu.epfl.ch)
 (TXT) w3m dump (actu.epfl.ch)
        
       | dijksterhuis wrote:
       | Link to the python library (link in the article is broken atm):
       | https://byzfl.epfl.ch
       | 
       | > ByzFL is a Python library for Byzantine-resilient Federated
       | Learning. It is designed to be fully compatible with both PyTorch
       | tensors and NumPy arrays, making it versatile for a wide range of
       | machine learning workflows.
        
       | antonkar wrote:
       | Interesting, can be relevant: there is an idea for the unicorn AI
       | safety startup to get currently almost 100% unprotected (from AI
       | botnet) consumer GPUs into a cloud to get Google-level security
       | (each GPU can bring you $30-1500 in profits per month, you can
       | share it with the user, the user can play GPU game from any
       | device, use any free or paid AI model, everything really becomes
       | better, you can include a 5g modem), here's the full proposal
       | (the author is probably dyslexic)
       | https://melonusk.substack.com/p/notes-on-euto-principles-and...
        
       | SubiculumCode wrote:
       | I wonder, as AI becomes more and more complex and
       | incomprehensible, and the risk of loss of control becomes greater
       | and greater, that the solution will simply be two adversarial
       | AI's, one which generates, the other to detect
       | deception/misalignment, and that at some point, when things have
       | become so advanced beyond comprehension, we just have to trust
       | the ying yang balance of good vs evil AI gods. /s
        
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       (page generated 2025-04-10 23:00 UTC)