t55

8 ms·

61.
by t55 2y ago
Disclaimer: I work on pyspur I'd recommend pyspur if you seek 1) More AI-native features eg. Evals, RAG, or even UI decisions like seeing outputs directly on the canvas when running on the agent 2) Truly open-source Apache license 3) P
62.
by t55 2y ago
what do you mean, the LLM abstracting things for us while we speak to it?
63.
by t55 2y ago
Agreed, Rashka's book is amazing and will probably become the seminal book on LLMs
64.
by t55 2y ago
IMO absolutely yes. I would start with the linked introduction and then ask myself if I enjoyed it. for a deeper dive, check out the sth like Georgia Tech’s CS 8803 O21: GPU Hardware and Software. To get into MLE/AI Data Engineering, I
65.
by t55 2y ago
I think that for at least for us dumb humans with limited memory, having good abstractions makes things much easier to understand
66.
by t55 2y ago
Related: https://sakana.ai/ai-cuda-engineer/ https://www.reddit.com/r/MachineLearning/comments/1itqrgl/p_...
67.
by t55 2y ago
They basically ditched CUDA and went straight to writing in PTX, which is like GPU assembly, letting them repurposing some cores for communication to squeeze out extra performance. I believe that with better AI models and tools like Cursor,
68.
Introduction to CUDA programming for Python developers(pyspur.dev)
365 points by t55 2y ago|95 comments
69.
Novelty Left on the Table(ansatz.blog)
2 points by t55 2y ago|0 comments
70.
Competitive Programming with Large Reasoning Models(arxiv.org)
16 points by t55 2y ago|1 comments
71.
The Differences Between Direct Alignment Algorithms Are a Blur(arxiv.org)
8 points by t55 2y ago|0 comments
72.
The Octalysis Framework for Gamification and Behavioral Design(yukaichou.com)
3 points by t55 2y ago|0 comments
73.
S1: Simple Test-Time Scaling(github.com)
40 points by t55 2y ago|3 comments
74.
A Malloc Tutorial [pdf](github.com)
1 points by t55 2y ago|0 comments
75.
by t55 2y ago
this is the most up-to-date summary i could find
76.
Reinforcement Learning: An Overview(arxiv.org)
82 points by t55 2y ago|12 comments
77.
What automated firms will look like(dwarkeshpatel.com)
2 points by t55 2y ago|0 comments
78.
Large Language Models for Mathematicians (2023)(arxiv.org)
89 points by t55 2y ago|28 comments
79.
Mathematics for Machine Learning(mml-book.github.io)
1 points by t55 2y ago|1 comments
80.
Propositional Interpretability in Artificial Intelligence(arxiv.org)
3 points by t55 2y ago|0 comments
81.
The Tensor Cookbook (2024)(tensorcookbook.com)
199 points by t55 2y ago|37 comments
82.
ArXiv LaTeX Cleaner: Clean the LaTeX code of your paper to submit to ArXiv(github.com)
103 points by t55 2y ago|42 comments
83.
Tesla Unveils Autonomous Cleaning Robot for Robotaxi(twitter.com)
2 points by t55 2y ago|1 comments
84.
O3-Mini vs. DeepSeek-R1: Which One Is Safer?(arxiv.org)
1 points by t55 2y ago|0 comments
85.
by t55 2y ago
https://github.com/PySpur-Dev/pyspur
86.
Qwen Chat – Another Chinese ChatGPT Rival(chat.qwenlm.ai)
4 points by t55 2y ago|0 comments
87.
Systemic Existential Risks from Incremental AI Development(gradual-disempowerment.ai)
6 points by t55 2y ago|0 comments
88.
by t55 2y ago
lmao i guess i'll be the last one scribbling i, j, k in my stone tablet
89.
by t55 2y ago
wow love the fact that you can interact with the videos
90.
The risk from prompt injection attacks on AI systems(security.googleblog.com)
1 points by t55 2y ago|0 comments

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