https://openrouter.ai/deepseek/deepseek-v4-pro?sort=throughp...
4,193 karma · joined May 26, 2013
My current venture is Semi-Decent, a software consultancy that helps businesses grow through intensely pragmatic software. https://www.semi-decent.com/
I also run a side business making bespoke, sustainable craft cocktails for events: https://www.theminimalmixologist.com/
Please get in touch! I'd love to chat.
sasha+hn@chedygov.com
https://openrouter.ai/deepseek/deepseek-v4-pro?sort=throughp...
Can you expand on this?
Note: Alibaba Cloud is the only company that currently offers Qwen 3.7 models (they haven't released any open weight versions yet), and according to OpenRouter, they retain prompts for an unknown period. So they might not explicitly use your data for training, but they do store it indefinitely on their servers and can potentially[0] use it for all sorts of other purposes.
[0]: Disclaimer: I haven't read their privacy policy. Just pointing out that it's not so simple.
I think AI is going to force most software engineers to pick up this skill in some form. Building is easy; knowing what to build is the hard part.
I disagree. The models are going to become commodities (we're already almost there), but the tooling and integrations will be the moat. Reproducing everything Anthropic has already built with Claude Code, Cowork, and all their connectors would be nontrivial, and they're just getting started.
Anyone can implement an AI chatbot. But few will be able to provide AI that's deeply integrated into our daily lives.
No, my understanding is that AI generated content can't be copyrighted by the AI. A human can still copyright it, however.
My wife currently has an old MacBook with 8GB of memory, and she hits the memory limit somewhat regularly just from web browsing and light productivity work. But whether more breathing room in terms of memory is worth almost double the price...
If Composer 2 is as big a leap as they claim, I might start using it exclusively for anything that's not terribly complicated, including planning. The speed and cost effectiveness are just hard to beat.
The more likely reason is that there simply hasn't been that big a push for it. Ruby was dog slow before the JIT and Rails was very popular, so there was a lot of demand and room for improvement. PHP was the primary language used by Facebook for a long time, and they had deep pockets. JS powers the web, so there's a huge incentive for companies like Google to make it faster. Python never really had that same level of investment, at least from a performance standpoint.
To your point, though, the C API has made certain types of optimizations extremely difficult, as the PyPy team has figured out.
I know it's a nit-pick, but I hate that this always gets brought up when it's not actually true. Public corporations face pressure from investors to maximize returns, sure, but there is no law stating that they have to maximize profits at all costs. Public companies can (and often do) act against the interest of immediate profits for some other gain. The only real leverage that investors have is the board's ability to fire executives, but that assumes that they have the necessary votes to do so. As a counter-example, Mark Zuckerberg still controls the majority of voting power at Meta, so he can effectively do whatever he wants with the company without major consequence (assuming you don't consider stock price fluctuations "major").
But I say this not to take away from your broader point, which I agree with: the short-term profit-maximizing culture is indeed the default when it comes to publicly traded corporations. It just isn't something inherent in being publicly traded, and in the inverse, private companies often have the same kind of culture, so that's not a silver bullet either.