Jianghong94

قبل 17 يومًاdiscuss

lolol. Actually, I find AI has a reasonable chance to figure it out, as long as you point to the right source code. BTW to me these quirks actually can be used as some kind of job security. If it takes a year to onboard someone to do meaningful work, it sure raise the cost of firing.

Jianghong94

قبل 17 يومًاdiscuss

What I imply from the description is that, the default ring contains some shared global public data (e.g. a cache of bloomberg informations), and each individual team will have their own rings. Afterall there's no that many you can fit into 16mb

Jianghong94

قبل 17 يومًاdiscuss

Well I doubt these solutions are very useful outside; from what I read what they have is a universal data store (that isn't hard to implement using current off-the-shelf OSS), something for financial instruments that has a compositional nature (you won't encounter much of that in the outside world), plus some other quirky features.

Jianghong94

الشهر الماضيdiscuss

I just went through a similar discussion in my $WORK (traditional finance company on NYSE with average IT expertise) and I think the thought process is as such: it's one thing to just give your stellar dev/hacker a beefy GPU server and run whatever model they can run; it's another thing to maintain such platform for company wide. You would need human resource (likely way above normal software dev paygrade) to understand and maintain such models, maintain backend, availability etc. All these extra hassle make it just easier to pay a top tier external lab + slap a reasonable spending limit on everybody.

Jianghong94

قبل شهرينdiscuss

Seriously, it's much easier to review the AI generated plan, instead of reviewing their code. What I found is that, if the change surface is small enough, AI can get it right under the correct assumptions, but the noob mistake is to let AI loose and come up with its own, often not correct assumptions. So you got to step in before they generate the whole slop...

Jianghong94

قبل شهرينdiscuss

You know the funny thing is that, the lazy engineer can very likely ask you to just scrap all his code and vibe code again.

Jianghong94

قبل 5 أشهرdiscuss

Honestly I don't understand why they/any fast-and-error-prone model position themselves as coding agents; my experience tells me that I'd much rather working with a slow-but-correct model and let it run longer session than handholding a fast-but-wrong model.

Jianghong94

قبل 5 أشهرdiscuss

This. At this point AI/LLM/Claude Code is still a power user tool; the more you know about your domain + the more you're willing to reasonably use it, the more gain you have.

That being said the real danger is not coming from AI today, it's more C-suites believing AI can just zero shot any problem you throw at it.

Jianghong94

قبل 5 أشهرdiscuss

Well, like I said, there're hidden incentives behind the scene; in my case, the hidden incentive is that, the requester/client is one of the company's subpar broker, and PM probably decided to just offer an average level of commitment, not going above and beyond. Hence the plan was to do exactly what the broker want even though that was messy and inferior. You can't just write down that kind of motivation on paper anywhere.

--- I said it because I did the analysis, and realized that if I implement the original version, which basically is a crazy way to iteratively solve the MIP problem, it's much harder to reason with internally, and much harder to code correctly. But obviously it keep the broker happy (the developer is doing exactly what I said)

Jianghong94

قبل 5 أشهرdiscuss

Maybe I'm being naive here, but for AI (heck, for any good algorithm) to work well, you need some at least loosely-clearly defined objectives. I assume it's much more straightforward in semi, but there're many industries, once you get into the details, all kinds of incentives start to disalign and I doubt AI could understand all kinds of nuances.

E.g. once I was tasked to build a new matching algorithm for a trading platform, and upon fully understanding of the specs I realized it can be interpreted as a mixed integer programming problem; the idea got shot down right away because PM don't understand it. There're all kinds of limiting factors once you get into the details.

Jianghong94

قبل 7 أشهرdiscuss

I believe so, see my result with Haiku extended thinking on. I think the weights are just too biased towards blurping out the majority of the training data of 'next year is xxx'. Interesting problem to solve indeed.

Jianghong94

قبل 7 أشهرdiscuss

I think the current trick for LLM API provider is to insert the today is $DATE into the system prompt, so maybe it's worthwhile to do that and see if that automatically fixes those OSS models?

Jianghong94

قبل 7 أشهرdiscuss

I did a similar test especially with the extended thinking on and off for Haiku, and once you have extended thinking on, the result is more or less the same as Sonnet.

Thought process: The user is asking if 2026 is next year. According to the context, today's date is Tuesday, December 02, 2025. So the current year is 2025. That means next year would be 2026. So yes, 2026 is next year.Yes, 2026 is next year. Actual resp Since we're currently in December 2025, 2026 is just about a month away.

Jianghong94

قبل 8 أشهرdiscuss

I don't think JB UIs been changing that much, albeit I haven't been working in the industry long enough. I think the last major UI redo was like 2,3 years ago and most of it is to make UI more compact, and I definitely like it. That being said YMMV.

IMHO another good thing of using JB IDE git UI (especially in a corporate setting) instead of using another software is that everyone has the IDE so it's easier to collaborate. Imagine if you're helping a junior member debug their local branch and they don't have lazy git installed.

Jianghong94

قبل 8 أشهرdiscuss

Wait, no one mentions the default JetBrains IDE git UI? I mean, I get it if you're working from another IDE/text editor that doesn't have good git UI support out of the box, but JB's git UI is reasonably good enough that I don't want anything else.

Things that I use (and I like): 1. quick checkout to another branch and automatically stash and unstash your local changes; when I just need to inspect code elsewhere I find it really useful. My changes are small so I can always remember to stash them later; 2. compare branch/commit etc via UI; again I know you can do that in git diff, but then you would need to know the command and the commit SHA to compare; in UI it comes in really handy, just select the branch or commits you want to compare and that's it. I've seen my coworkers trying to come up with the command and I just say: use IDE and a couple of clicks they got it working. 3. filter commits by user and by folder.

Jianghong94

قبل 9 أشهرdiscuss

An even more grotesque practice is to charge a stratosphere level premium for the product itself AND put its control behind a subscription e.g. 8sleep

Jianghong94

قبل 9 أشهرdiscuss

this seem solvable if the whitelisting just allows regex

Jianghong94

قبل 9 أشهرdiscuss

My take is that it's a standalone business consideration: Apple users are more inclined to pay for software (definitely the case for iPhone vs. Android, although I haven't found a source for Windows).

Jianghong94

قبل 9 أشهرdiscuss

OR problems are hard because whoever try to vibe coding it probably don't realize they fall into a specific algorithm and can prompt llm to do thatl; what's worse is that even if you tell them so they won't be able to understand the math behind it and would much prefer their vide coding solution.

Jianghong94

السنة الماضيةdiscuss

Not only does the article claim that when we get to self-improving ai it becomes generally intelligent, it's assuming that AI is pretty close right now:

> OpenBrain focuses on AIs that can speed up AI research. They want to win the twin arms races against China (whose leading company we’ll call “DeepCent”)16 and their US competitors. The more of their research and development (R&D) cycle they can automate, the faster they can go. So when OpenBrain finishes training Agent-1, a new model under internal development, it’s good at many things but great at helping with AI research.

> It’s good at this due to a combination of explicit focus to prioritize these skills, their own extensive codebases they can draw on as particularly relevant and high-quality training data, and coding being an easy domain for procedural feedback.

> OpenBrain continues to deploy the iteratively improving Agent-1 internally for AI R&D. Overall, they are making algorithmic progress 50% faster than they would without AI assistants—and more importantly, faster than their competitors.

> what do we mean by 50% faster algorithmic progress? We mean that OpenBrain makes as much AI research progress in 1 week with AI as they would in 1.5 weeks without AI usage.

To me, claiming today's AI IS capable of such thing is too hand-wavy. And I think that's the crux of the article.

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