Deep RL was at peak hype during NIPS2016. Everyone thought training a ConvNet to play a few Atari games using Q-Learning would lead to AGI.
AGI
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AI Systems Lacking Human Values Raise Ethical Concerns
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Nothing to worry about in these machines that lack human values. Nothing whatsoever.
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Turing Test 2.0: AI Passes Advanced Intelligence Evaluation
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Turing test 2.0. @erikdunteman passed.
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Adjacent Impossible and AGI-Hard: Categorizing AI Progress
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There's two lists to maintain – i've been calling it the "Adjacent Impossible" (stuff that it'll probably do soon) and "AGI-hard" (after @tszzl
) https://
lspace.swyx.io/p/agi-hard -
Artificial Narrow Intelligence Versus Artificial General Intelligence Comparison
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#Infographic: Artificial Narrow Intelligence Vs Artificial General Intelligence by @ingliguori #ArtificialIntelligence #ComputerScience #AI #smartmachines #AGI #NarrowAI #MachineLearning #DeepLearning #DataScience #RPA #NeuralNetworks #Robots #Bot #DigitalTwins #ModelOps #MLOps
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ChatGPT Future Excitement and Concerns About AI
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ChatGPT makes me both very excited and worried about the future of AI
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Consciousness: Self-Awareness and Environmental Awareness in AI Systems
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Consciousness is a combination of self and environmental awareness. I see environmental awareness in Minedojo as tractable but self-awareness is a different story. For that, you need uncertainty quantification is key: unknown unknowns is tricky.
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SAMPLR: Minimax Regret Method for Unsupervised Environment Design
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Grounding Aleatoric Uncertainty for Unsupervised Environment Design. @MinqiJiang
, @MichaelD1729
, @JParkerHolder
, @_AndreiLupu
, Heinrich Küttler, @EGrefen
, @_Rockt
, @J_Foerst propose SAMPLR, a minimax regret UED method that optimizes the ground-truth utility function. -
Exploration Integral to General Intelligence and Learning Systems
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General Intelligence Requires Rethinking Exploration. @MinqiJiang
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@_rockt
, @EGrefen argue that exploration is integral to all learning systems despite the fact that the study of exploration in AI has mostly focused on reinforcement learning.