AI Ethics RSS
'Governing Superintelligence' - Synthetic Pathogens, The Tree of Thoughts Paper and Self-Awareness
Two documents released in the last few hours and days, OpenAI’s ‘Governance of Superintelligence’ and DeepMind’s ‘Model Evaluation for Extreme Risks’, reveal that the top AGI labs are trying hard to think of how to live with, and govern, a superintelligence. I want to cover what they see coming. I’ll show you persuasive evidence that the GPT 4 model has been altered and now gives different outputs from two weeks ago. And I’ll look at the new Tree of Thoughts and CRITIC prompting systems that might constitute ‘novel prompt engineering’. I’ll also touch on the differences among the AGI lab...
Embodied AI ...Robots (ChatGPT, Meta AI, Burnham, Phoenix, Tesla, 1X EVE, 1X NEO) - LifeArchitect.ai
Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021.
GPT-4 hits the ceiling (Theory of Mind, Mensa, Asimov) - LifeArchitect.ai
Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021.
Fourier Transformations Reveal How AI Learns Complex Physics
"I believe that scientific knowledge has fractal properties; that no matter how much we learn; whatever is left, however small it may seem, is just as infinitely complex as the whole was to start with. That, I think, is the secret of the Universe." - Isaac Asimov, A Memoir By RICE UNIVERSITY MARCH 20, 2023 A new study has found that Fourier analysis, a mathematical technique that has been around for 200 years, can be used to reveal important information about how deep neural networks learn to perform complex physics tasks, such as climate and turbulence modeling. This research highlights the potential...
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