sinuhe69
sinuhe69 on Hacker News
I wish the author has written about the motives behind the language and why someone should choose Copper. We have in fact more programming languages than we actually can use.
In some cases, it can certainly help. However, it isn't helpful for deep thoughts or when innovative, creative ideas are needed.
I have found that speaking the steps out loud helps, especially with new, confusing working steps. For example, it helps when tying a complex knot or following the steps/work of others without explicit instructions. In such situations, speaking out loud helps me to remember the steps much faster (simple repetition through multiple pathways) and also helps me to detect and correct spatial and sequential mistakes. It also helps enormously when working with or teaching someone else.
I have a funny memory from my youth: one time, I had to solve a particularly difficult maths problem on the blackboard. I don't remember exactly why, but while I talked out loud about solution A, I wrote a slightly different step (B) on the board. Looking back, I realised I had made mechanical mistakes, so I had to correct them to get the final valid solution. My teacher laughed and joked, 'A sign of genius is to write A, say B, but only C is the true solution.' :) (no, he was just too kind).
I have often experienced my handwriting being much slower than my speaking, so sometimes they don't sync and funny mistakes are made (one line contains the words of the next line). But I fondly remember that particular moment.
I wonder whether the guy who wrote the order understood how LLM works and how an open source model running in an US data center could pose a "threat"?
On Openrouter at least, all Mino models are painfully slow. TTFT is many seconds and the models spend a lot of time on its CoT, making effective output per second many times slower than DS Flash. On Flash 4.1, I constantly get ~180 tok/s and the real work got done fast, too. So even when the Mimo 2.6 are smart models, I use them much less recently. Not to mention their costs are also higher than DS.
For me, the DeepSeek 4.1 models are currently the ultimate cost-effective model the rest have to match with, especially if you are not on a subscription plan with heavy discount.
GPT Sol 6.1 is however, for me the most efficient model, both in terms of time to finish and token usage.
It sounds pretty nice on paper. But I tested the huggingface.co/mradermacher/hybridagent-8b-agentic-gguf:IQ4_XS with a simple question: "Who is the pope?" and it got stuck in a thinking loop forever and simply could not finish the task.
```
Okay, the user is asking who the pope is. The pope is the leader of the Catholic Church. The current pope is Pope Francis, who became pope in 2013 after Pope Benedict XVI resigned. There's no indication of a change since then, so the answer is Pope Francis.
Okay, the user is asking who the pope is. The pope is the leader of the Catholic Church. The current pope is Pope Francis, who became pope in 2013 after Pope Benedict XVI resigned. There's no indication of a change since then, so the answer is Pope Francis.
Okay, the user is asking who the pope is. The pope is the leader of the Catholic Church. The current pope is Pope Francis, who became pope in 2013 after Pope Benedict XVI resigned. There's no indication of a change since then, so the answer is Pope Francis.
```
Then I also gave it the counterfeit ball problem, but it could not solve it either. But to be fair, no 8B model seem to be able to solve it.
```
I have 9 balls that look exactly the same. But I know one ball is different. I only have a scale. Call scale(b1,b2)={-1;0;1} will tell me whether the left object b1 is heavier, same weight or lighter than the right object b2. How many times at minimum do we have to apply scale to find the different ball? Explain how we can achieve this.
```
What does “verified” mean here? Someone has formalized verified the kernels or just different kernels cross check each others?
So, basically they created the recent situation in math where a great deals of top mathematicians criticized their methods, even called to boycott their dumped results. And the answer of the AI labs is buying these poor academic souls with 15$ millions? Most of them even as AI tokens? Why do I see a macabre irony here?!
For me, it coincidentally connects well with Tao's essay (Math 2.0). Even if a field of practice such as oral care requires understanding rather than just results, why would someone think that we will not need to understand maths or science if AI can deliver results?
A story about dentists is not just about dentists. I like that!
I see it like this: because greenfield coding is strong with AI, but improving/large rewriting an existing codebase is getting progressively harder and worse, if you don't get the architecture right in the first try, improve them in later rounds will be very hard,if not futile. Thus the poor performance is not a typical day 1 problem as with human coding, but a pestilence.
Not to mention a sudden ebb of bot traffic all over the world!
The zooming is pretty bad: yanking and uncontrollable.
Yeah. It’s expected from a vibe coding project, especially if they care more about the optics than functionality.
I heard from another Photoshop clone that they spent almost a year to polish the software, using AI nonetheless. The hardest part they told me is the getting the color management part right.
That for one app. A full suit with a “written in Rust” tag sounds today almost like a clickbait.
How much polluted is the water after cooling? Can they not be reused?
As long as they don’t pollute, I don’t see much a problem with this amount of water usage. And the water doesn’t need to be disinfected either, only cleaned and filtered. So any natural renewable source would do.
From my perspective, having high resolution scans or even 3D scans could undermine the role of the museums. Their role is to provide the best environment to view, to experience and
to appreciate the works of the artists. A casual viewing at home, from a computer cannot provide that optimal experience and almost certainly will reduce the wish to visit the museum in person. Much like a recording of a concert or an opera cannot replace a in-person experience but (unfortunately?) is the default way for pop music. Much of that experience is how we mentally, emotionally and physically prepared ourselves for the experience.
Museums want to prevent that and also ensure their own existence.
PS: in this specific case, the museum has to worry about counterfeit copies of Rodin works as well. But I don’t want to succulents on that as I don’t know the details.
What if automating AI R&D triggers an intelligence explosion?
No title editing please
Philippines has a very similar game called Game of the Generals.
Did the author really believe the LLM made the compiler by itself and not distilled (copied) from other compilers?
More like the healthcare providers found a way to milk the insurance. The most important aspect that is amiss is the outcome of the patient's treatment. But if the practice of background mining to upgrade the claims is correct, I don't see how it can help the patients.
2021. Please remember the rule of HN to add the year if it’s not actual.
Because it will never change if you not try.
In daily decisions perhaps not, and certainly not when we were in the cave. But from time to time, we will face fundamental questions that need addressing clearly and decisively, and I believe it’s the case with AI. The more advances we make, the more frequent such questions will arise. That is also one of the main reasons why we don’t see any alien civilization. It’s getting harder and harder to keep the entropy low as we gain more knowledges and cognitive power.
Because it’s high time to rethink the incentives and rewards structures to nurture the next generations of mathematicians when corporate money and automated AI systems are mining the pool of limited interesting problems without giving back or enhance our understanding.
The problem they care about is not just “AI replaces human mathematicians” but rather the society thinks mathematicians can be replaced by AI.
As I understand you referred to Elon Musk. But this is Poh Shen Loh talking. If you don’t know who he is, look up or at least read his articles.
Irregular again! The single company that was responsible for the sloppy configurations and the hacks by OpenAI, Anthropic and now Google. This company and their partners should be held accountable for the crimes.
You use the low cost Mimo-V2.5 and not its big brother Mimo-V2.5 Pro? I also made good experience with Mimi-V2.5 when used in conjunction with prewalk mode. But then other models got so cheap and perform better, so I only use Mimo for background tasks.
The availability of Mimo over Openrouter got however, much worse recently.
If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves? Certainly they understand their problems better than you and they can adapt to rising issues faster if their in-house team does it themselves. And certainly what kind of AI you can access, they can too and perhaps even more. So what will remain your value propositions?
I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly. Or work on the backend when constraints are not strictly enforced (for various historical reasons). Sometimes additional chunking and detailed planning/instructions suffice. But other time, humans are still the best vehicles to code.
Absolutely! I’ve never lied to anybody and any work we copied was purely accidental.
Snap is designed to be more expressive and powerful than Scratch. But I find debugging them is very painful. Changing the name of a variable or block for example, could create “holes” in the calling sites but the system can or cannot report an error and fails silently. Snap is IMO more flaky and the team seems more eager to add features than polish the existing ones or make the system mor robust and stable.
"OpenRouter runs per-provider benchmarks on the same model: GPQA Diamond and TAU-Bench Airline (a tool-calling task)." why I haven't never seen it? Click on the link brings nothing! Benchmark is only for the model. Per provider is a performance matrix (latency, throughput)
What did I miss?
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Update: oh, that is the AutoExacto Benchmarks! Now I see it.