All topics / AI modeling
Topic
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AI modeling
1
episodes
1
thinkers
2h
of conversation
11
books & papers
3
terms defined
The neighbourhood: AI modeling and the ideas it travels with. Drag to roam, click a star for the episode, click a neighbour to travel.
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From foundational to frontier
Climb the spectrum. The most accessible conversations come first.
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The lexicon
Every term the guests lean on, in plain language. Read one in full, or filter to find it.
What the corpus says
The throughline across every conversation that touches this idea.
Dilip George criticizes the Blue Brain project for simulating brain structures without understanding their functions, limiting its effectiveness.
Dilip George · Dileep George: Brain-Inspired AI
The Recursive Cortical Network (RCN) model achieved 95% accuracy on MNIST with minimal data, highlighting the power of feedback connections and recursive inference.
Dilip George · Dileep George: Brain-Inspired AI
Convolutional neural networks (CNNs) differ from the brain's visual cortex, which lacks translation invariance and relies on local receptive fields.
Dilip George · Dileep George: Brain-Inspired AI
GPT-3's lack of world models and feedback mechanisms limits its potential for achieving AGI, despite its 175 billion parameters.
Dilip George · Dileep George: Brain-Inspired AI
Connecting brains to machines could lead to intense experiences due to neuroplasticity and the brain's adaptation to new inputs.
Dilip George · Dileep George: Brain-Inspired AI
Voices on AI modeling
5 standout quotes from across the corpus.
Go read
11 books and papers cited across these episodes.
For the specialist
What experts find new
3 expert-level takeaways for a specialist reader.
At the frontier
Still unresolved
2 open questions flagged across these conversations.
The thinkers
Who takes this idea on, by how often they return to it.