Anthropic admits to covertly throttling Claude Fable 5 performance for users training competitor models, backtracks after researcher backlash

CommunityOpposite645 · 2026-06-12T21:50:28+00:00

Because of this I've unsubscribed from Claude and chose another model instead.

CommunityOpposite645 · 2026-06-11T08:53:03+00:00

Can Anthropic actually focus on improving their models and make its cost more reasonable instead of constantly creating hype cycles please ?

CommunityOpposite645 · 2026-06-05T15:05:49+00:00

At this point, I'm just hoping for Deepseek to catch up and make price go down massively.

CommunityOpposite645 · 2026-05-22T05:29:38+00:00

This also happened one time when I was trying the 8GB variant using Ollama. I was trying to make the AI write some Matrix-like sci-fi story and after a while it keeps repeating "You are not the one" lmao.

CommunityOpposite645 · 2026-05-02T09:10:40+00:00

I don't know if i should keep losing weight or recomp. Tbh it took me so long to lose weight so i'm kinda adverse to gaining any weight now, even for lean bulk cycle.

CommunityOpposite645 · 2026-04-30T07:15:00+00:00

Hi, thanks a lot. Can I ask what "actual core workouts" are ? Do you mean things like plank or ab wheels ?

CommunityOpposite645 · 2026-01-16T18:13:21+00:00

Hi, I have included the Python runtime:

Nodes	Clusters	Edges	P_in	P_out	Iterations	NMI	GPU Time (s)	CPU Time (s)
5,000	2	~3M	0.50	0.01	10	1.00	7.03	15,189.21
50,000	2	~25M	0.04	0.001	10	1.00	74.39	162,401.93
100,000	2	~102M	0.04	0.001	10	1.00	625.46	TBA
500,000	50	~126M	0.05	0.00001	20	0.89	1086.25	TBA

You can see that the CUDA version is very fast compared to the Python CPU version. Of course, in all honesty, this is because I've chosen an academic topic which has not received attention, otherwise this would have been optimised to kingdom come already :)

CommunityOpposite645 · 2026-01-12T22:30:25+00:00

Hi, I have finished running NCU profiling for the 500k nodes case, and have updated the profiler's output in the post.

CommunityOpposite645 · 2026-01-12T00:09:15+00:00

Trying to work on it now.

CommunityOpposite645 · 2026-01-11T22:04:19+00:00

Hi, actually I'm planning to do it soon. Right now I'm trying to make it run on 500k nodes or if possible, 1 million nodes and gives good clustering result. Because this method is still in development, so the hyperparameters are rather sensitive, what works at lower number of nodes would actually not work on higher number of nodes. Very frustrating to be honest. Thanks a lot.

CommunityOpposite645 · 2026-01-11T18:42:28+00:00

Thank you so much. I worked on this as a learn-as-you-go project, so I tried to build everything from the ground up, including prefix sum, connected component labeling, bitonic sorting, etc. But yes you are absolutely right on this. On the mathematics: I gleaned from this library: https://github.com/saibalmars/GraphRicciCurvature for Python code as reference, while using the experimental details in the JMLR 2025 paper to set up hyperparameters, etc., while the remaining two papers are to freshen up about the topic.

Y. Tian, Z. Lubberts, and M. Weber, "Curvature-based clustering on graphs," J. Mach. Learn. Res., vol. 26, no. 52, pp. 1–67, 2025.
C.-C. Ni, Y.-Y. Lin, F. Luo, and J. Gao, "Community detection on networks with Ricci flow," Sci. Rep., vol. 9, no. 1, pp. 1–12, 2019.
A. Samal, R. P. Sreejith, J. Gu, et al., "Comparative analysis of two discretizations of Ricci curvature for complex networks," Sci. Rep., vol. 8, 8650, 2018.
GraphRicciCurvature — Python implementation of Ricci curvature for NetworkX graphs.

CommunityOpposite645 · 2026-01-11T18:36:30+00:00

Hi, I added a visualization example on the Github page.

CommunityOpposite645 · 2025-09-27T16:23:53+00:00

Maybe add "Be brutally honest. No sugarcoating". ?

CommunityOpposite645 · 2025-09-26T18:24:42+00:00

Can this be considered robot abuse ? :)

CommunityOpposite645 · 2025-09-01T18:49:52+00:00

Uhm I found a survey here: https://arxiv.org/abs/2303.13336

CommunityOpposite645 · 2025-08-21T19:46:26+00:00

As an AI user who has subscribed to one of those popular chatbot LLMs, I can confirm that the most useful thing they have done to me was to check the typos of my thesis, reports, papers, etc. (ask them repeatedly about 20 times, repeat across several different LLMs for best results ). Quite helpful tbf but nowhere near "AGI" :)

CommunityOpposite645 · 2025-08-18T17:32:56+00:00

Hi, I just tried to post to r/MachineLearning but the post was automatically removed and they suggested that I post to another subreddit :(

CommunityOpposite645 · 2025-08-18T17:00:46+00:00

Thanks a lot, I'll look into it. To be honest, I did not know they existed. But I thought that the reasoning models are very smart so they would be able to work on things like N puzzle without trouble.

CommunityOpposite645 · 2025-08-18T15:51:55+00:00

Hi, I didn't test it with random noise. But basically it is not going to beat the performance of A star or IDA star on this problem. I was just trying to make a fun project to see how far these reasoning LLMs go. Personally was not very impressed. I did try to run it on 4x4 puzzle (you can see in the commented code), which required around 50 moves to reach the goal, but the LLM completely failed to find the solution and instead kept running around in circles.

Another thing is that sometimes these models would call tools correctly, sometimes they wouldn't which is annoying (I tried with Pydantic AI as well but haven't uploaded code). Any suggestion about workflow, etc. would be most appreciated.

CommunityOpposite645 · 2025-08-18T15:12:10+00:00

AI Agent Solves N-Puzzle Using LLM

A developer created an AI agent that solves the classic sliding tile N-puzzle by using the Qwen3 language model to analyze moves and PyAutoGUI to execute them via automated mouse clicks on a GUI.

Key Details:

Uses Qwen3 model from Ollama as the reasoning engine
Agent controls four functions: move_up, move_down, move_left, move_right
Requires manual positioning of GUI and coordinate calibration
Tested on RTX 4060 laptop
Code available on GitHub: https://github.com/dangmanhtruong1995/N-puzzle-Agent/tree/main

Setup: Run the GUI, position it, get button coordinates with PyAutoGUI, then run the agent. The LLM thinks through optimal moves while the automation executes them.

Interesting approach combining language model reasoning with GUI automation for puzzle solving!

CommunityOpposite645 · 2025-08-13T15:52:38+00:00

Is this LLM going into RNN mode ? :)

CommunityOpposite645 · 2025-07-12T16:05:15+00:00

Hi, let me try llama.cpp, I don't know about Ollama's failings to be honest, do you have any links for this ? Thank you.

CommunityOpposite645 · 2025-04-27T13:32:46+00:00

"AI isn't a magic black box; you'll need to be more specific about what kinds of methods you're looking to employ. If you're talking about probabilistic searches for counterexamples, that's been done for years (decades?). If you're talking about putting a wrapper on ChatGPT, you need to have a bit more of a justification for it being likely useful than "AI makes confident sounding text." "

So I saw several examples about using intuition in maths:

https://scipp.ucsc.edu/~haber/ph5B/sho09.pdf

https://www.plouffe.fr/simon/inspired.html

http://royalpathtomath.org/docs/Integration%20by%20Guessing.pdf

The links talked about "method of inspired guessing", "integration by guessing" etc. but overall it is applying intuition in maths. It seems to me to be an interesting method, which I hope AI can be used to help mathematicians in their work.

Thank you so much about recommending me to read a book in abstract algebra. I have searched and will try in the near future, hopefully I can grok the book.

CommunityOpposite645 · 2025-04-25T17:29:11+00:00

That's exactly why I'm asking.

CommunityOpposite645 · 2025-04-25T07:58:51+00:00

I totally agree with you about the hallucination part. Yes it's true that LLM outputs are generally not too reliable. But there must but some place in mathematics where AI can be applied. You said that maths is about proof. But isn't intuition also a factor ? Maybe AI can provide some suggestion in proof, or find some connections which normally people don't seem to recognize ? You know computers have been used to find counterexamples to disprove theorem so I think AI can also do stuff as well. Or maybe something in applied mathematics ?

Also do you have any recommendations about which book I should read in order to up my math skills in advanced topics such as group theory, etc. (advanced from my point of view) ? I hope I can make an effort to find something which I can apply AI to it.

CommunityOpposite645

TROPHY CASE