KurSix

12 ms·

211.
by KurSix 11mo ago
It's a very bold move to open-source a system that claims to generate alpha. In the world of quantitative finance, any real market edge disappears the moment enough people know about it
212.
by KurSix 11mo ago
Of all the features listed, the ""self-learning architecture that updates behaviour without manual retraining"" is the most interesting and simultaneously the most dangerous. Anyone who has run ML systems in production k
213.
by KurSix 11mo ago
Exactly. And the author seems to have missed that media generation is arguably the purest demonstration of agentic potential outside of coding. Modern tools like Krea or Magnific are no longer just "enter prompt, get image", it&#
214.
by KurSix 11mo ago
Grammarly and DeepL are great examples of successful AI products, I agree. What's most interesting is that they became successful long before the LLM hype. They didn't try to be "universal intelligence", they just wanted
215.
by KurSix 11mo ago
To me, this classification overlooks the largest and arguably most profitable class of AI products: models that aren't the interface but are embedded deep within existing systems as infrastructure components, for example: - Anti-fraud
216.
by KurSix 11mo ago
The key will be whether they treat experienced users like adults after the initial opt-in
217.
by KurSix 11mo ago
You're right: if the logic is that low-install apps are the most dangerous (because they can fly under the radar), then making it easier for unverified apps to reach a "small" audience doesn't really solve the problem
218.
by KurSix 11mo ago
I'm not sure it's entirely fair to say this is just Google flexing control
219.
by KurSix 11mo ago
The tension here is classic: governments want accountability, Google wants plausible deniability, and users want control
220.
by KurSix 11mo ago
Tying app distribution to a verified identity definitely raises the cost for scammers. But the devil's in the implementation. If "verification" ends up being too bureaucratic or expensive, it risks pushing legit indie devs an
221.
by KurSix 1y ago
This is the perfect product description for how a tool like this should actually work. Not git-rewrite-history, but something like git-explain-commit <hash>. It would take the diff, run it through an LLM at request time, and give you
222.
by KurSix 1y ago
AI-generated commits are useful, as long as they act as a post-processor rather than the author. If the history is already a mess, the tool can structure it chronologically, restore the connections between changes, and describe what they me
223.
by KurSix 1y ago
LLMs like Chat GPT don't actually understand text the way a person does. They don't have concepts or any life experience. When you type something, the model turns your text into a bunch of numbers (called a "vector"). Ev
224.
by KurSix 1y ago
Yeah, it's easy to jump to the collusion theory, especially with this industry's, let's say, history. But honestly, I think it's less of an evil conspiracy and more just good old-fashioned fear mixed with inertia. These
225.
by KurSix 1y ago
You're right. And it's not just about parameter count. Efficiency is a full-stack problem: from the architecture (like MoE instead of dense transformers), to the inference techniques (speculative decoding), to the data formats (qu
226.
by KurSix 1y ago
Even if the hype around LLMs dies down, the demand for AI compute won't disappear. It will just shift from giant language models to more specialized areas: computer vision, scientific computing (like AlphaFold), drug discovery. All of
227.
by KurSix 1y ago
This shortage is the best thing that could have happened for R&D in model efficiency. The "who has more parameters" race is about to hit the physical wall of hardware availability. Now the real race for efficiency begins: quan
228.
by KurSix 1y ago
This approach is perfect for mature projects with a well-established architecture. But it could be counterproductive in the early R&D stages when the architecture is still fluid and the team is constantly experimenting. The rigid constr
229.
by KurSix 1y ago
This is poetic and painfully accurate
230.
by KurSix 1y ago
Yeah, when the punishment for thousands of images and videos is just four months, it really puts the whole "we need mass surveillance to protect kids" narrative under a harsh light
231.
by KurSix 1y ago
Definitely feels like something to keep watching closely
232.
by KurSix 1y ago
It's like surveillance logic eats itself in the end. What really gets me is how often these proposals skip over the part where we ask whether they actually work
233.
by KurSix 1y ago
Protecting children is critically important, but turning every citizen into a potential suspect by default? That's not justice, that’s just lazy policy design. Honestly, this feels like one of those rare moments where political pressur
234.
by KurSix 1y ago
You can take the git idea even further. Instead of just committing more often, make the agent write commits following the conventional commits spec (feat:, fix:, refactor:) and reference a specific item from your plan.md in the commit body.
235.
by KurSix 1y ago
Linters are great at catching specific pattern violations, but they’re useless against bad decomposition or a poorly chosen abstraction. An LLM can generate code that passes all 100 linters and still ends up being a logical mess - with busi
236.
by KurSix 1y ago
This whole situation painfully reminds me of the low-code/no-code boom from like 5–10 years ago. Back then everyone was saying developers would become obsolete and business analysts would just “click together” enterprise solutions. In
237.
by KurSix 1y ago
That's a fascinating bit of rail history
238.
by KurSix 1y ago
You board a train in Milan and wake up in Sicily without ever having to drag your luggage across terminals, onto buses, or through port checkpoints. Especially for night trains, that seamlessness adds a kind of magic
239.
by KurSix 1y ago
Feels like no one really wants a solution
240.
by KurSix 1y ago
What you described reminds me that travel isn't just about the destination, it is the time in between

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