They definitely have some. They handle the basic test scenarios where multiple people alter some state without the knowlege of the other. Most models seem to handle tracking differing knowledge between entities.
Some of the simple bench tests show how thin that can be.
Things like two lifelong friends had a fight when they were 8 years old because A broke B's favourite toy. They are now 25 and B sees A drowning, Will B try and save A?
Models tend to place massively undue influence on facts just because they have been mentioned. If every part of the text is accurate and relevant, then this helps immensely. Many fine tuning examples are precisely on topic. That leads to a bias against ignoring trivia.
Fine tuning has gotten a lot better now that the value of nuance in training examples is better known.
No, it's not. You generally want to ventilate an office when you reach 1000ppm, but then the IKEA will often warn you already at 700ppm. 700ppm is fine.
"Generally" is a vibe measurement to begin with. You won't notice any difference at all between 700ppm and 1000ppm. It's once you start hitting 2000ppm you are getting noticeable brain fog.
Had bad ventilation in my old apartment (built 1888) so got a co2 monitor. Started feeling the effect at 1100-1300ppm, so would open it in home assistant and check, never below and never above really. During winter when it was -10 so couldn't keep the window open all the time.
I disagree. I feel a very steady and progressive deterioration starting at 600 ppm. It becomes significant at 800 ppm. The studies back up the latter threshold.
You're not wrong, but indoor CO2 at these sub-1000 levels is a useful proxy metric for bioeffluent VOCs which are an objectively tiring subset of total VOCs. Ventilation lowers both. This explains the observation better than nocebo theory. See https://www.aivc.org/resource/effects-carbon-dioxide-and-wit...
You would not notice a difference if you weren’t checking the CO2 ppm. You primed your brain to ‘feel’ the effects of higher CO2 by reading a study and are experiencing the nocebo effect.
If it makes you feel better I don’t see a problem with it.
Indoor CO2 is likely overrated here at these sub-1000 levels but it's a useful proxy metric for bioeffluent VOCs which are a tiring subset of total VOCs. Ventilation lowers both. This explains the observation better than nocebo theory. See https://www.aivc.org/resource/effects-carbon-dioxide-and-wit...
Interesting study, thanks for sharing! I am starting to see more space temp/CO2 combo sensors in commercial office conference spaces, if the CO2 rises above the setpoint, the VAV opens to let air in to reduce CO2 (and bioeffluent VOCs, according to this study.)
Have you looked at the prices of meeting room furniture? A $200 meter is not a significant cost measured against what it costs to furnish the room in the first place. It only becomes significant is you treat it as a line item disconnected from the room it's in
There are good $50 Euro meters. Besides that, I am not sure if that is true, at my wife's workplace, they put high-end CO2 meters in every larger room where multiple people meet. Admittedly, this was during COVID, so a lot of organizations were using CO2 levels as a proxy for finding whether a room was properly ventilated.
Presumably there is still the need to ventilate. So the concentration can also be measured more centrally. That is how the mechanical ventilation unit in my house works. For both humidity and CO2.
Do they dupe VC into enormous datacentre and capacity build-out investment? Why yes, actual money going to the AI hypester pick-axe vendors (and early equity dumpers) in that sense, absolutely yes it does.
Is Big AI on track to pay that back with profit from any foreseeable and defensible business model? Different question. I sincerely doubt it.
I think one of the more sober analysis that focused on danish firms exclusively predicted the overall growth impact on GDP to be a bit less than half a percent. Now, well that doesn’t sound very large, considering nominal GDP for the world is nearly $60 trillion, that is a big deal. I don’t know if that justifies trillion dollar evaluations for the providers, but even a small improvement over a large base is meaningful.
Conservative estimates in the United States puts it at $300,000 to raise a child from 0-18, including the cost of birth in the healthcare system. It goes up to $1 million for a HCOL area though.
This seems wrong to me on multiple different levels.
One, this conversation is about economy side of things.
And two, calling comparison between humans and LLMs disgusting when LLMs are borderline GAIs sounds very xenophobic. Did you see the thread about LLM-written fiction contest the other day? https://news.ycombinator.com/item?id=48782890
Big AI labs aren't making money. They're buying revenue. Sure, the product is amazing, but it wouldn't be as amazing if offered at cost - which is exactly where "good enough" smaller and specialized models will survive.
And yet, they are highly unprofitable. Yes, people pay for the API because it's a frontier model, but it's a frontier model because of billions of capex that are (so far) not getting recouped. And if they stopped the capex on new frontier models, that API revenue would walk off to whoever else does. If, at some point, the entire industry decides to stop burning money and start squeezing customers, that will be the test of which business models actually survive, and in that scenario I am bullish on scrappier shops that can't possible compete on all fronts now.
That’s by choice. Spend more than you make and you can claim no profit. They could become profitable overnight by cutting spending, though that would also be akin to switching from a run to a walk in the AI race.
They are selling api tokens at good margins. Of course they then reinvest all of it in research for new models and for continued growth. But the api inference is profitable.
a CPU is a rock about as much as much as an airplane is a rock (aluminium ore), "look, we are able to make rocks fly on their own power, isn't that awesome?"
people using it think they are impressing the normies, but it just shows them being condescending "of course I dont believe rocks calculate, but I assume you are so stupid and know so little that you might actually believe me and be impressed by my people"
Hi, I understand your point. But my intention was just to create a sense of wonder that we have manipulated an inanimate thing to do useful things for us. I have only used it in the intro. In the rest of the article, i am only talking about actual ideas and concepts.
I would agree its a cliche but the intention here definitely isn't to be condescending. There's literally an image of the actual cpu below it - the rock thing is more of a metaphor and as any good metaphors, they can get tiring if you hear them a lot as you might do as someone working in the domain.
Actually, CPUs are made from highly purified silicon, which is commonly produced from silica found in quartz-rich sand; that silica ultimately comes from rocks.
You've completely missed the point of how silicon chips are organized rock, and have completely invented and projected a condescending view that no one actually intends.
Nuclear has been in maintenance mode for so long that there are doubts about if anyone could right now detonate one without shitting their pants on account if it would even go off.
