xcodevn

5 ms·

1.
by xcodevn 5mo ago
Install the latest claude code to use opus 4.7: `claude install latest`
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by xcodevn 5mo ago
I have a strong feeling that this website was designed by Claude Code using the /frontend-design skill.
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by xcodevn 6mo ago
Example run: https://asciinema.org/a/udK1O06TS8f7kXNO
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Auto Research Engineer(github.com)
2 points by xcodevn 6mo ago|2 comments
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by xcodevn 6mo ago
A Claude Code setup that implements ML papers from arxiv. Give it a paper, it orchestrates a team of AI agents to read the paper, plan the implementation, write the code, verify correctness, optimize performance, train, and compare results
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by xcodevn 7mo ago
The official document from Anthropic: > Fast mode is not a different model. It uses the same Opus 4.6 with a different API configuration that prioritizes speed over cost efficiency. You get identical quality and capabilities, just faster
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by xcodevn 7mo ago
They failed to grasp the very fundamental point of batching, which is sharing model weights between requests. For more context, this wasn't just one person's mistake, several AI twitter personalities proposed this 'Claude Opu
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by xcodevn 8mo ago
I do think Claude Code as a tool gave Anthropic some advantages over others. They have plan mode, todolist, askUserQuestion tools, hooks, etc., which greatly extend Opus's capabilities. Agree that others (Codex, Cursor) also quickly co
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by xcodevn 8mo ago
I did something similar in Python, in case people want to see a slightly different perspective (I was aiming for a minimal agent library with built-in tools, similar to the Claude Agent SDK): https://github.com/NTT123/n
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by xcodevn 8mo ago
For one, these models should be able to understand the physical world via images, audio, and video. I do agree that current models are quite good at coding, but that's mainly because coding is entirely text-based and easily verifiable.
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by xcodevn 8mo ago
> we may have AI that is more capable than everyone in only 1-2 years There's no evidence this will be the case...
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by xcodevn 8mo ago
I'm not familiar with these open-source models. My bias is that they're heavily benchmaxxing and not really helpful in practice. Can someone with a lot of experience using these, as well as Claude Opus 4.5 or Codex 5.2 models, con
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by xcodevn 8mo ago
IIRC, the Claude Code creator mentioned that all the PRs are reviewed by humans, just like normal human PRs. So yes, humans still look at the code at the review stage. Though I still consider this to be level 3, but anyway, this is just a m
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by xcodevn 8mo ago
I believe Anthropic is already doing Level 3 vibe coding for >90% of their code.
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by xcodevn 8mo ago
My observation is that vibe-coded applications are significantly lower quality than traditional software. Anthropic software (which they claim to be 90% vibe coded) is extremely buggy, especially the UI.
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Nano agent: a minimalistic Python library for building AI agents using DAGs(github.com)
2 points by xcodevn 8mo ago|1 comments
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by xcodevn 8mo ago
Over the weekend, I wrote this small Python library to teach myself the core idea behind modern agentic systems. This kind of software sits at the core of Claude Code, Codex, etc. I wanted to see if I could build it from scratch, so this is
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by xcodevn 8mo ago
> only ~1/3 of sessions see at least a flicker. ...after many months, for such a visible bug, is such a crazy thing to say. In case the above comes across as too hostile, to balance this, I would say thank you to the claude code tea
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by xcodevn 8mo ago
I have a hypothesis: they haven't fixed this because they're using Claude Code to develop Claude Code. I'm a fan of Claude Code, but it isn't good enough to fix tricky issues like this. And because no one looks at the co
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by xcodevn 1y ago
Interesting, i can see this being very similar to Nvidia's CUTE DSL. This hints that we are converging to a (local) optimal design for Python-based DSL kernel programming.
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by xcodevn 1y ago
> Once the model is fully released, scientists will be able to adapt and fine-tune it on their own datasets to better tackle their unique research questions. This is in the press release, so they are going to release the weights.
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by xcodevn 1y ago
Author here: (1) We didn't remove the stddev term. (2) We use token-level loss (every token has the same weight), which is very similar to what Dr. GRPO does. However, we compute the mean gradient per token, while Dr. GRPO computes the
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Implementing DeepSeek R1's GRPO algorithm from scratch(github.com)
192 points by xcodevn 1y ago|3 comments
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by xcodevn 2y ago
On a very similar theme, here is the work from World Lab (founded by Fei-Fei Li, ImageNet dataset, et al.) about creating 3D worlds: https://www.worldlabs.ai/blog
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by xcodevn 2y ago
Who cares? If it brings benefits to the people who paid for the service, duh!
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The LLM pre-training data wall(substack.com)
2 points by xcodevn 2y ago|0 comments
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by xcodevn 2y ago
He plays an essential role as the model for NotebookLM. As Raiza Martin, the PM for NotebookLM, mentioned on a recent podcast, Steven is the product. The NotebookLM team essentially emulated his workflow, how he conducts research and comp
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by xcodevn 2y ago
For context , the author is Steven Johnson, one of the key people behind Google's latest hit, NotebookLM. For those who are curious, how can we technically support really long context window (like in the millions or even billions)?
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PodcastLM: An open-source AI podcast creator(github.com)
3 points by xcodevn 2y ago|0 comments
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by xcodevn 2y ago
During inference, it is not a matrix x matrix operation, but rather a weight matrix x input vector operation, as we are generating one token at a time. The bottleneck now is how fast we can load the weight matrix from memory to tensor cores

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