I am looking to get up to speed with the latest things happening in AI, I use ChatGPT almost everyday and i last used the open AI api for 3.5 last year. I am looking for a tech blogs like HN to keep updated on things AI, I came across https://simonwillison.net/ but it appears fragmented
The poster's looking for articles, so this recommendation's a bit off the mark. I learned more from participating in a few Kaggle competitions (https://www.kaggle.com/competitions) than I did from reading about AI. Many folks in the community shared their homework, and by learning how to follow their explanations I developed a much more intuitive understanding of the technology. The first competition had a steep learning curve. I felt it was worth it. The application of having a specific goal and the provided datasets made the problem space more tractable.
I don't think it's a good idea to kepp up to date at a daily/weekly cadence, unless you somehow directly get paid for it. It's like checking stocks daily, it doesn't lead to good investment decisions.
It's better to do it more batchy, like once every 6-12 months or so.
So I'm currently using "OpenCV University"'s playlist on YouTube to get myself up to speed with computer vision, and this has lead into a spiraling staircase down into the depths of CNNs.
And after that, I've had some recent projects that I love to mess around with such as a better license plate detection API than what currently exists for U.K. plates, and once I completed those two courses I had a good enough baseline to work from where I'd encounter a repository and google around if I needed to learn something new.
Short, simple, not painful etc. and I don't have the advanced mathematical background (nor the background within the American mathematical notation) that I'd need to digest the MIT course set, so this learning path has been the best for me. I'm no expert whatsoever, though.
tikkun ·9 days ago
https://news.ycombinator.com/item?id=36195527 and
Hacker's Guide to LLMs by Jeremy from Fast.ai - https://www.youtube.com/watch?v=jkrNMKz9pWU
State of GPT by Karpathy - https://www.youtube.com/watch?v=bZQun8Y4L2A
LLMs by 3b1b - https://www.youtube.com/watch?v=LPZh9BOjkQs
Visualizing transformers by 3b1b - https://www.youtube.com/watch?v=KJtZARuO3JY
How ChatGPT trained - https://www.youtube.com/watch?v=VPRSBzXzavo
AI in a nutshell - https://www.youtube.com/watch?v=2IK3DFHRFfw
How Carlini uses LLMs - https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
For staying updated:
X/Twitter & Bluesky. Go and follow people that work at OpenAI, Anthropic, Google DeepMind, and xAI.
Podcasts: No Priors, Generally Intelligent, Dwarkesh Patel, Sequoia's "Training Data"
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pdevine ·10 days ago
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drcwpl ·10 days ago
For a general audience - https://www.ai-supremacy.com/?utm_source=substack&utm_medium...
Fromm inside the AI Labs - https://aligned.substack.com/
https://milesbrundage.substack.com/
for swe - https://artificialintelligencemadesimple.substack.com/
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Maro ·10 days ago
It's better to do it more batchy, like once every 6-12 months or so.
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explaingarlic ·9 days ago
Started off here: https://www.youtube.com/watch?v=hZWgEPOVnuM&list=PL6e-Bu0cqf...
Ended up here: https://www.youtube.com/watch?v=_5XYLA2HLmo&list=PL6e-Bu0cqf...
And after that, I've had some recent projects that I love to mess around with such as a better license plate detection API than what currently exists for U.K. plates, and once I completed those two courses I had a good enough baseline to work from where I'd encounter a repository and google around if I needed to learn something new.
Short, simple, not painful etc. and I don't have the advanced mathematical background (nor the background within the American mathematical notation) that I'd need to digest the MIT course set, so this learning path has been the best for me. I'm no expert whatsoever, though.