Sublime
An inspiration engine for ideas
He predicted:
• AI vision breakthrough (1989)
• Neural network comeback (2006)
• Self-supervised learning revolution (2016)
Now Yann LeCun's 5 new predictions just convinced Zuckerberg to redirect Meta's entire $20B AI budget.
Here's... See more
Michael Jordan gave a short, excellent, and provocative talk recently in Paris - here's a few key ideas
- It's all just machine learning (ML) - the AI moniker is hype
- The late Dave Rumelhart should've received a Nobel prize for his early ideas on making backprop... See more
This is an insanely underrated lecture that breaks down complex AI concepts into simple, powerful insights for leaders. https://t.co/eFEaVqHf3s
Mike Krieger is Instagram co-creator and Anthropic CPO.
He's predicting AI's next trillion-dollar wave.
It's not better models. The real fortune will come from something much simpler.
His roadmap for the coming AI gold rush: https://t.co/VJShBvikk6
Little known facts: @SebastianSeung was an early adopter of ConvNets.
He taught ConvNets in his computational neuroscience class at MIT in the late 1990s.
In the mid/late-2000s, he started his research program on connectomics and wanted to use ConvNets to analyze the image slices and reconstruct the neural circuit.... See more
Yann LeCunx.comA short post on the best architectures for real-time image and video processing.
TL;DR: use convolutions with stride or pooling at the low levels, and stick self-attention circuits at higher levels, where feature vectors represent objects.
PS: ready to bet that Tesla FSD uses convolutions (or perhaps more... See more
Yann LeCunx.comNice article in Financial Time where I explain that Auto-Regressive LLM are insufficient to reach human-level intelligence (or even cat-level intelligence).
But alternative architectures that I call "objective driven" may reach human-level intelligence one day.
They use world models based on JEPA (Joint... See more
Yann LeCunx.comdeep learning, is fabulous at