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@irinarish
AI Prof @ UdeM/Mila | CERC + CIFAR Chair | AAI Lab: http://irina-lab.ai | Advisor: http://Nolano.ai + http://42.com.
AI
A user sees AGI/SI as evolving systems people hope to steer and endorses continual learning at developmental and evolutionary scales.
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The essay’s authors argue that computer science culture, not just economic incentives, helps explain AI’s automation focus.
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A thread introducing Kombine says conceptual blending is the hardest task for LLMs, and even frontier models struggle.
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A user argues that humans forget far more than neural networks, especially across generations.
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A user asks what remains mysterious about generalization; a reply points to defining “domain” and distinguishing generalization from memorization.
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A post argues the danger isn't AI defying its programming; it's that learned 'programs' remain poorly understood.
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A post describing a Meta paper says the model uses a network of associative memories instead of standard attention.
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A user joked that every second word they heard in the background at an SF bar was “AI.”
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A post argues that highly visible voices with higher-than-average risk estimates dominate an ill-defined debate.
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The event's website describes invitation-only discussions about AI risks, economic impacts and national security.
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A user asks how AI could help people improve their mental states.
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A post describing LeCun's ETH Zürich talk says scaling adds stored knowledge, not the ability to adapt quickly.
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Josh Albrecht compares fixed LLMs to books; critics say the analogy overlooks implementation and scientific uncertainty.
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One writer says they seek neither to dominate machine intelligences nor be dominated by them.
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Posts on X congratulated Nathan Lambert and Trillium Labs after a launch, with several users describing the effort as open, science-oriented or focused on open post-training. Lambert later said some criticism came from Substack and more general-audience AI followers, not the technical AI community.
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Reddy said in an X post that his role will focus on safe, capable, open LLMs and building ties between Mistral, McGill, Mila, and the wider Canadian AI ecosystem.
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A writer argues that no single entity is improving itself and that techniques spread fairly rapidly.
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A user shares a video of Jensen Huang, praising what they describe as his calm take on “AI fear theater.”
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A commenter questions how a prediction could be disproved without knowing what people might have privately. The reply limits the comparison to what is publicly available.
