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easygenes
searching PlanetScale…
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6 ms
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31.
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by
easygenes
5mo ago
This has me pining for a future professional class CAS 3d graphing calculator. I'm thinking something that could be a major upgrade in spirit to the long-in-the-tooth (released a decade ago) Casio FX-CG500. Could use the soon to be rel
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by
easygenes
5mo ago
Very early in my career I made friends with the business’s sole Lotus Notes administrator, "the email server guy." He was pretty proud of what it could do, and I sometimes get nostalgic for the admin UI.
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by
easygenes
6mo ago
You could have it propose a spec or review a proposed spec to also get diagrams in a similar manner.
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by
easygenes
6mo ago
Claude tends to default to and do best with first making ASCII diagrams in markdown files, which you can then ask it to translate into Mermaid if appropriate. Prompts like, "Please write a comprehensive report on _____ to work with ___
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by
easygenes
6mo ago
Yeah, agree. This is the sort of thing you release to build brand awareness and either offer a hosted option as a bonus or integrate into a larger stack. It is not the product. Someone will just make a better OSS option if they don't d
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by
easygenes
6mo ago
Unless you're looking at something like a pass@100 benchmark, the benchmarks are confounded heavily by a likelihood of a "golden path" retrieval within their capabilities. This is on top of uncertainties like how well your ta
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easygenes
6mo ago
I was an original Thunderbird pre-1.0 (from 2003) user and prior to that, Netscape Mail, and am quite certain it has had bayesian spam filtering all this time, at least since the late ‘90s. That was a headline feature in the early days. My
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by
easygenes
6mo ago
While I understand why they used the METR data, a cleaner look would be against the current cost-optimal frontier of open models (e.g. GLM-5.1 and MiniMax-M2.7). That paints a very different picture. Comparing just the frontier models at
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by
easygenes
6mo ago
They are referring to Hermes Agent, not the Hermes model series. https://github.com/nousresearch/hermes-agent
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by
easygenes
6mo ago
LM Studio has been around longer. I’ve used it since three years ago. I’d also agree it is generally a better beginner choice then and now. Unsloth Studio is more featureful (well integrated tool calling, web search, and code execution bein
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by
easygenes
6mo ago
Why is ollama so many people’s go-to? Genuinely curious, I’ve tried it but it feels overly stripped down / dumbed down vs nearly everything else I’ve used. Lately I’ve been playing with Unsloth Studio and think that’s probably a much b
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easygenes
6mo ago
A full-module add-on in this power class is about $7 at 1,000 unit scale [0]. It would be around $3 with your own custom PCB design in terms of BoM addon at scale. That’s power only. Add another dollar or two for 10/100 PHY. The trick
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Show HN: Sixteen year trends in AI doom on HN
(hn.ai-doom.cc)
3 points
by
easygenes
6mo ago
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0 comments
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easygenes
6mo ago
The historic charts are at the bottom of the page, btw.
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Show HN: HN Remixed to only show AI Doom (or not)
(hn.ai-doom.cc)
2 points
by
easygenes
6mo ago
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1 comments
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by
easygenes
7mo ago
I never felt during this era that the information about these chips was hard to come by as the author claims. Retrospectively I appreciate that’s because I grew up living by a large, well funded library in a tech centric town, so they alway
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GPT from GPT: de novo microgpt
(github.com)
3 points
by
easygenes
7mo ago
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1 comments
48.
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by
easygenes
7mo ago
I started this project after watching Andrej Karpathy's recent interview on No Priors where he explained that he had to hand-write microgpt, a 200-line GPT implementation in Python which distills the essence of all the algorithms behin
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easygenes
7mo ago
The year is 2006 and Netvibes is hosting a huge party in San Francisco after raising in the Web 2.0 craze. They are yet to find out they will become a footnote in history to be rediscovered in 20 years’ time.
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by
easygenes
7mo ago
This is very similar to a project I created https://github.com/Entrpi/autonomy-golf and have been using as a gamified development process on active projects. The key insight was to not just handwave or guess at how muc
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easygenes
7mo ago
I liked this not because it's a good story. It is, but that's beside the point. I liked this because it's my story. Not literally so, but the shape of it is. He's struck a nerve at the heart of growing up eager and curio
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easygenes
7mo ago
Cool! I’ve been working on adding the same thing for Apple Silicon within my general “make autoresearch a serious tool” project here: https://github.com/Entrpi/autoresearch-everywhere
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easygenes
7mo ago
This is very much in line with what I found fascinating about optimizing microgpt for speed (0). Or rather, what I was able to do with it after doing so. It's so small and so fast to train, you can really dig deep into the optimization
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easygenes
7mo ago
Topical. My hobby project this week (0) has been hyper-optimizing microgpt for M5's CPU cores (and comparing to MLX performance). Wonder if anything changes under the regime I've been chasing with these new chips. 0: https:/
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EEmicroGPT: 19,000× faster microgpt training on a laptop CPU (loss vs. time)
(entrpi.github.io)
11 points
by
easygenes
7mo ago
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2 comments
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by
easygenes
7mo ago
At scale, teams don’t win by owning more FLOPs; they win by shrinking the distance between hypothesis and measurement. I learned that the expensive way: running large training pipelines where iteration speed was the difference between “we
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by
easygenes
7mo ago
Inspiring. Definitely got nerd sniped by this. Now you can train it in under a second on one CPU core with no dependencies: https://github.com/Entrpi/eemicrogpt Detailed optimizing journey in the readme too.
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Training microgpt in milliseconds
(github.com)
2 points
by
easygenes
7mo ago
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1 comments
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by
easygenes
7mo ago
Heavily optimized single C file that can train the same model as Karpathy's microgpt to lower loss in under a second on a single Mac core.
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by
easygenes
7mo ago
It did before, link was changed.
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