The credibility point is the most interesting part of this. In semiconductors, having a good design seems secondary to convincing customers that you'll still be around to support it years later. RISC-V lowers the barrier to building a CPU, but i'm not sure it lowers the trust barrier nearly as much.
I'm not so sure of that. Don't companies often buy a million of a chip and then that's it? Famously the MacBook Neo was created to get rid of some stockpile of old chips Apple was sitting on.
It depends on the industry. High-volume consumer electronics is often like this (they're making this year's product, they roughly know the demand, they'll be redesigning it in a year or two), but industrial electronics generally wants to know that they will still be able to buy the parts in 10 years, at least (a design or even a single unit can be in active use for decades).
I think this story is the exception. The supply chain time for hardware is so long, designers are picking their chips out months and years in advance. So you really do have to trust that the supplier will be around to support the hardware in a few months or a few years.
numerically, most companies are not in cutting edge rapid product cycle consumer gear like apple, they instead want to buy 1000/year of the same part for a decade (or maybe gradually better, compatible equivalents)
Separately from my other comment, European companies seem to have a credibility problem no matter what they do or how well they do it, just because they're outside of the good old boy's club that is Silicon Valley. When's the last time you heard some praise for OVH or IONOS Cloud?
Not really. It's a capitalist economy, they can only regulate what exists, not bring things into existence. The best they can do is offer grants to those who apply for them.
Has anyone looked closely at the security of all these Lovable-generated apps? There have been reports of serious security issues in apps built with Lovable, especially around backend/database configurations. Curious how Lovable plans to address this
I find it interesting how much adoption seems to be influenced by momentum. Some of these Chinese models are surprisingly capable, but developers often default to the models that are already established as the “industry standard
Well things may change soon. I've been testing Coding fulltime with Deepseek Flash this week to evaluate an eventual shift for the whole company away from anthropic. It has been quite positive and I can't wait to try pro tomorrow. If our data has to be used by either US or China, we might as well go the cheaper and unwalled garden. If only it supported image input ...
Hacker News is very Bay Area/US tech centric where spending a few hundred a month on AI is just pocket change. The weaker AI models with more questionable data retention policies are popular in developing countries. I think the new Facebook muse model will be similarly popular.
Well, one reason is that we always have to work with the quirks of each model. So, a know model is often preferred over a new/unknown one because we have to be vigilant again. (Negative) surprises are mentally exhausting in the long run.
IMO, you can work much better when you know the model.
In an enterprise setting Chinese models are often discouraged due to political risk. They don't want to need to remove a model that's deeply embedded in their stack. And it's entirely feasible that the US gov bans federal contractors from using them in the next 6 months for example, or that EU AI safety rules effectively ban them too.
Based on what the political climate looks like nowadays it's entirely possible the US bans federal contractors from associating with any company that uses the models themselves, regardless of data provenance or where they are hosted. Or they create AI safety rules that make it impossible to release open source models (for example, making it so that closed-source models can be evaluated with a harness but open-source models need to pass the benchmark with the weights alone, which isn't really possible). Or they just declare Chinese models a security risk like TikTok (claiming that the model would be trained to respect Chinese interests).
It may not be likely but it's definitely possible enough to be something people worry about.
There's just no place for models that are neither SoTA nor truly crazy cheap in today's public mental health climate.
If it's 500x cheaper than US models for similar ballpark performance just because it's hosted in China, sure whatever. If it's name brand like Anthropic/OpenAI/Google, that's kinda fine too.
If it's neither, like merely 50% cheaper than latest OpenAI whatever, however massive loss that pricing may be incurring to its provider, it wpuld be considered not worth any attention.
Most of my model usage comes from my work’s model selection (which is now down to just Claude models)
I’ll try out the latest models, but mainly stick with Claude only because I’m most used to its quirks and how to work around them. I imagine this is part of these hyperscalers playbook.
I will say though, I miss Sol model at work. It with Codex was amazing at first-shot understanding. Claude i need to scope out where to look otherwise a large portion of my token budget is eaten up
While I do agree it's tiring and agree with your point I think the issue is finding the exact point to draw the line. It's easy to differentiate the two ends.
I think the operative difference here is that in the case of the little league photography, the cameras are not fixed in place, are temporary, and are not set up with the intent to capture the identity and actions of everyone in the background. Fixed-installation cameras are permanent, do attempt to capture all possible subjects in its frame, and have an alternate, obvious intent to identify them all. I don't think a Private investigator, paparazzi, or parked police cruiser on a stakeout represent anywhere near the same practical or legal problems as fixed, always-on surveillance cameras. As such, this seems to me like a good place to draw the line.
I don't really care about the fixed vs mobile distinction. Police could just use a drone swarm that automatically charges if it were ruled fixed installs were illegal.
That is already the manual model: the parent creates a separate shelf for each child and adds videos based on that child’s interests. There is intentionally no automated personalization or recommendation system deciding what to add next.