It's really cool and interesting to see the kind of engineering that goes into Xiaomi (and Deepseeks) inference optimizations. Z.ai has also published some interesting papers although I haven't had a chance to go through them yet.
It does inspire hope that the Chinese labs seem to be so open although the sceptic in me does wonder what their end game is.
Surely, from a purely economic perspective it would be wiser to keep this proprietary and benefit from the increased API traffic?
While I mostly agree with your statement there's evidence that testosterone is linked to social status and mental well being.
A 50% drop most likely has a multifactorial explanation, being told that some traditional male traits are bad (and thus lower well being or social status) or medicated away (see e.g the rise in ADHD and Autism diagnosis) might have some effect.
I'm not nearly knowledgable enough to give any reasonable estimate but it would not surprise me if it was higher than 0%.
Short-term, follow the steps on the website and contact your political representative to explain to them why it's such a bad idea.
Long-term, switch to another messenger app that's opensource and truly E2E encrypted.
That also shows why this is such a foolish proposal.
The truly scary people are not on the "consumer" chat apps anyway and most certainly will be the first ones to switch to another communication channel if this passes. If this will have any effect it'll be that some, "dumb" criminals will be caught.
I remember looking into SDR when I was a student, really amazing what you can pull down for the price of a dinner these days.
I know that you can get the same pictures from the internet but building something like this and seeing how all the pieces fit together is extremely cool.
Also an extremely cool project to do with kids, the output is visual but it's such a cool combination of hardware, software, some light math (to design the attena) and crafting (to build it).
I'm not an expert but I think the SBB is already pretty good at handling this. I think they already run measuring wagons (Oberbaumesswagen) with grond penetrating reader and ultrasonic measurement and use flow sensors to monitor drainage.
I would expect that the solar panels impact the efficiency at least somewhat but apparently not enough to cause real and enough issues for the SBB or perhaps they see ways to improve this in the future.
I imagine that the cost to install is fairly low since train tracks require regular monitoring and maintenance so it's fairly cheap to add the installation and maintenance on top of the existing schedule.
The manufacturer claims that durability should not be an issue. Time will tell.
They might be sending some user requests to Anthropic to gather trading data for their own models. If they do so, perhaps they need to add some tracer to request that they prefer to hide.
I've gained and lost 10kg twice in my life. Maintaining the weight loss isn't that hard once you've a rhythm dialed in.
In my case I just weight myself daily, track the weight and scale my food consumption with the current trend. If I'm gaining weight I'll skip a meal.
It takes a while to figure out what works for you but I can tell you that making small lifestyle changes to maintain your weight is fairly easy compared to figuring out how to lose 10 kg.
GLM 5.2 is great but it heavily detoriates once the context window gets past 200k tokens.
I've had more success with creating a plan first and then implementing it in (short-lived) sub-agents.
Ironically good software architecture patterns (small functions, single responsibility) heavily impact the performance of these models as well. They do surprisingly well in well architectured codebases.
They do very poorly in anything that's a mess where Opus and GPT 5.5 still get reasonable performance.
6bn seems excessive but despite GPT 5.5 arguably being better than Claude I don't see a lot of adoption of Codex yet.
Some of my coworkers even use Sonnet (the default in Claude Code for the 20 USD subscription) and see no reason to change even though that model is definitely "outdated" compared to current SOTA.
This is too little, too late. Europe really need to start focussing.
All these tiny niche models are perhaps fun as an academic exercise or great for the researchers resume but I highly doubt that they'll add any value or will be used for anything serious.
Even if this becomes a somewhat decent model with a fantastic understanding of "gezellig", "kring verjaardag" or "pannenkoeken", how many people will interact with it before the limits of it will drive them back to a frontier model?
Even if the purpose of this is government & other regulated industries, do we really want our government to use a poor model? Either do it right or don't do it at all.
Thanks for pointing that out! I'm not in the US and I guess it's not illegal in China (given that Deepseek was more than happy to do it).
That does raise an interesting question, what kind of laws should LLMs (attempt to) follow? It's easy enough to spoof the country in the system prompt. I wonder how ChatGPT would respond if I told it I was located in a developing country without any piracy laws.
> And compared to other countries, I think Xenophobia is low
I would agree and also suggest that initiatives like this play a large role in doing so. While there's a lot of bullshit arguments coming from the "yes" camp they do make some reasonable points and it's important that we discuss them to show what the trade-offs are.
I cannot speak for all Swiss but knowing that it was a democratic decision to continue with some, high skilled, immigration makes it far easier to accept than if some government employee in Bern would've made that decision single handed.
Based on my first impressions it's about 6 months behind the frontier labs. So very similar to Opus in January.
That is, pretty damn impressive and very useable. When it comes to architecture or complex problems it does noticeable worse but I don't think anyone expected anything else.
One particular interesting strong point seems to be design and user interfaces. It does seem to punch above it's weight there but that might just be personal preference.
While it seems reasonable to comment about how we're using water it also seems like a complex topic.
What happens to the (slightly warmer) water after it has been used? Is there a way we could return it in a way to minimise impact? I.e if we extract ground water should we inject it back into the ground? Would that even matter?
In the end I have a feeling that the most efficient solution will most likely be to just increase the price of water during a drought. People will complain but it won't be long before the big consumers will happily adjust their consumption or move to an area with abundant water.
I'm not nearly as knowledgeable about chips as I would like to be but I'm seeing lots of hype around the new Huawei Ascend 910C-Chips. These are in no way competitive with Nvidia for training but they're cheap for inference and seems to be winning market share inside China.
China doesn't access to any of the latest chips technology but Huawei seems to have a roadmap to work around this by focussing on "3D chips" (vertical stacked). It's unclear if they can pull this off but if they can it might be a huge boost and allow them to further drive down inference prices.
It does inspire hope that the Chinese labs seem to be so open although the sceptic in me does wonder what their end game is.
Surely, from a purely economic perspective it would be wiser to keep this proprietary and benefit from the increased API traffic?