Philosophy B.S. learning about ML
Joined December 2025
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I created a project for math lecturing/demonstration. You can port your own handwriting recognition model in, utilize a Desmos-like 3D visualizer (optimized for linear algebra), as well as get in-depth views and explanations on many different NNs.
github.com/mrcal17/mathboard
Charlie Landau retweeted
Learn linear algebra. Learn to visualize matrices as spatial transformations. Learn to see calculus as the language of optimization. Learn vector spaces until neural networks stop looking like black magic and start looking like high-dimensional geometry. A deep understanding of math transforms you from an API-wrapper developer into an AI architect.
The Codex assistant has iMessage capability but Claude Duet does not, seems like a big mistake on Anthropic’s part to release without.
Notice that philosophy does not make the list!
Majors with the highest unemployment rates, per New York Fed.
1. Anthropology: 7.9%
2. Computer Engineering: 7.8%
3. Fine Arts: 7.7%
4. Computer Science: 7%
5. Performing Arts: 7%
6. Architecture: 6.8%
7. Art History: 6.7%
8. Early Childhood Education: 6.6%
9. Physics: 6.6%
10. Environmental Studies: 6.3%
Charlie Landau retweeted
We’re renaming our Max plans:
Max 5x → Max
Max 20x → Ultra
Max is still $100/month, and Ultra is still $200. If you’re a subscriber, there’s nothing you need to do.
We’re also removing the 5-hour limit for verified Ultra accounts, starting today with most existing subscribers. Newer accounts keep a temporary limit until they’re verified, which helps us prevent fraud and abuse. You'll get an email when it's removed.
Weekly limits remain unchanged. View our plans here: claude.com/pricing
Claude RC is back to this awful behavior where it turns off automatically for inactive sessions. I hate this back and forth (or if the app restarts overnight or ever it automatically disables). It was great for a couple weeks, don’t know what happened.
@bcherny I get card numbers, but DOB seems excessive. An assistant that can’t fill out a wide variety of forms?
4o ends up being the standard for all LLMs in the minds of people who are out of the know (because we keep on shoving the scary studies and news stories into peoples faces). Genpop and research are so far behind it’s not even funny.
Very hard to see AI assistants working out when they won’t enter passwords, create accounts, or solve CAPTCHAs. They’re these bizarre things that feel *almost* useful.
One thing I’m not seeing about You Can See Everything is how odd Holmes’ mother was acting. Her Dad seemed to be an active part while her mom was off on the sidelines. Maybe she wasn’t comfortable being an active participant, but it came off as very strange to me.
Charlie Landau retweeted
"three reasons why AI isn't conscious." really?
"consciousness is not intelligence": not a reason why AI isn't conscious, just rebuts a bad argument for AI consciousness (AI: intelligent therefore conscious).
"consciousness is substrate-dependent"/"noncomputational": would be a reason if true, but truth needs to be established.
more accurate title: "three reasons why AI might not be conscious".
teapawt.net/Nature/status/21121504…
LLMs can mimic thought and feeling with uncanny skill, but intelligence alone is not enough for subjective experience
go.nature.com/3VSXWQ4
Charlie Landau retweeted
The Research Papers section is now live at trentorch.com.
Explore 10 curated tracks featuring 360+ papers across neural network foundations, Transformers and LLMs, reinforcement learning, computer vision, inference, and more.
Go from first principles to implementation. Study the ideas behind each paper, then test your understanding by solving related questions and building the concepts yourself. Highlight key passages and add notes along the way to deepen your understanding.
Don’t just read research. Understand it, solve it, and implement it.
Charlie Landau retweeted
very cool
I created a project for math lecturing/demonstration. You can port your own handwriting recognition model in, utilize a Desmos-like 3D visualizer (optimized for linear algebra), as well as get in-depth views and explanations on many different NNs.
github.com/mrcal17/mathboard
I made this out of necessity for lectures I give to friends, because I felt no good tool existed that bundles these all in one. The NN viewer is incredibly powerful, and shows the Matrix math equivalent of the network on the side. You can even train models inside of it