computerex

3 ms·

1.
by computerex 10d ago
How ironic for you to say that to me. Maybe you can use ai to help explain it to you.
2.
by computerex 12d ago
What an incredibly useless comment. You state a conclusion as fact without any supportive reasoning/evidence. Prove that human intellect is different and that we solve problems using fundamentally different processes. I’m waiting.
3.
by computerex 12d ago
Why don’t you solve such problems?Being “not impressed” sounds more like a knowledge gap on your part than an informed opinion.
4.
Show HN: Your Home, Reallocated(55percent.org)
1 points by computerex 17d ago|0 comments
5.
Show HN: Slavesofaipac.org(slavesofaipac.org)
2 points by computerex 22d ago|0 comments
6.
by computerex 22d ago
Do you know the probability of all these companies being down at precisely the same time?
7.
by computerex 25d ago
Wow that got dark real quick, mind sharing any links/evidence? Never would have thought NZ has a CSAM problem.
8.
by computerex 1mo ago
You should look at some literature around it. I don't have time to pull it up now but it's been shown that much smaller small million parameters JEPA model outperforms much bigger LLMS in some applications. Keep in mind JEPA is ar
9.
Show HN: Z, minimal agentic harness for engineers that just works(github.com)
3 points by computerex 1mo ago|0 comments
10.
Show HN: Memorial for Athena Strand. She will always be remembered(athena-strand.org)
2 points by computerex 1mo ago|1 comments
11.
by computerex 1mo ago
I disagree totally. DeepSeek raised prices because they couldn’t serve the demand. But there are tons of American vendors ready to fulfill it. Many enterprises, including the one I work for, are swapping to open weights. Why wouldn’t you?
12.
by computerex 1mo ago
Didn't OpenCode CTO state they could replicate deepseek pricing on rented hardware?
13.
by computerex 1mo ago
You heard of JEPA? LLM's have all sorts of garbage they have memorized. Reasoning in latent space instead of in text significantly reduces the number of needed parameters.
14.
by computerex 1mo ago
I use my own harness: https://github.com/computerex/z Have been using it as my primary harness for personal work for I'd say 6 months. I recommend everyone create their own harness at least to learn. There are a l
15.
by computerex 1mo ago
Do you know how much traffic luna was getting vs Ox Alpha?
16.
by computerex 1mo ago
Gemini 3.7 has been trash in my testing. So is its pricing.
17.
by computerex 1mo ago
Casual consumers are using American models because their usage is low. As usage scales, the economics heavily favor open weight models. The API pricing from American companies is absurd. This is particularly true in an enterprise setting.
18.
by computerex 1mo ago
How is that vastly different from any other non-enterprise facing provider? I do believe Anthropic bans accounts without even a human in the loop with no recourse left to those banned.
19.
by computerex 1mo ago
You'll find that hard to prove objectively and conclusively.
20.
by computerex 1mo ago
The LLM is the core model, but the harness has the prompts/tool definitions, guidance/recovery/correction code. The harness itself is the agent, because same model may perform vastly differently on different harnesses. Agent
21.
by computerex 1mo ago
The harness is the agent. LLM's can be asked to output things in JSON for example. The LLM then literally asks for things like "execute this cmd" or search/replace this string. The LLM outputs text, but in a determinis
22.
by computerex 1mo ago
Yes, and the reason why pass@k exists is because of self-consistency. There is no guarantee for right answer to be selected or for the LLM to correct itself. While I agree pass@1 is a useful metric, I'd be more interested to know pass@
23.
by computerex 2mo ago
An agent doing a task even with multiple back to back calls like normal without an example is zero shot. An agent doing a task with 1 example is one shot. An agent doing a task with a few examples is few shot. I don't think you are cor
24.
by computerex 2mo ago
They are causal autoregressive models, the output is sensitive even to the implementation nuances in inference. Even 1 token that's badly selected could throw off the entire answer.
25.
by computerex 2mo ago
Repeat the test like 5 times for each model and see the results.
26.
by computerex 2mo ago
While I agree with need more and better gun control, American police officers are abhorrent for a very simple reason: lack of basic training, discipline, and practically zero screening/qualification process. Anyone can become a cop in
27.
by computerex 2mo ago
Absolutely. Although DeepSeek started announcing "Peak valley" pricing which started making me nervous. I have spent $50 usd in July on deepseek and for that much spend I got SO MUCH mileage. I feel perfectly content in using pay
28.
by computerex 2mo ago
Not really. I test the output thoroughly, I examine the thinking process, I go through the diff to see if anything jumps out but I my thinking process/the way I work has changed. Low level programming thinking has gotten atrophied it s
29.
by computerex 2mo ago
I think it's because python is far more approachable/ubiquitous than go/rust. It's the entry level language for many people from all disciplines of life. Scientific community uses it, data science uses it. Golang/ru
30.
by computerex 2mo ago
People know it’s happening. What do you expect an average consumer to do about it? Pay more out of pocket due to the potential national security risks?

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