I'm not so sure -- I live in Southern California in a very liberal area, and there are a huge number new teslas that would have been bought after Musk's political adventures, far more than any other EV brand. A fair number of cyber trucks too, but much less than other tesla models.
I also wouldn't take southern cali as representative of the US though. It is one of the most expensive places in the nation with a very high income where most people can completely ignore politics and the world around them because of the higher wealth floor. Im sure you can also find tons of people with $1500 phones and 5090s just for their gaming PC, but elsewhere in the nation you won't see so many.
The median wage in S.Cali is literally double the median wage of the midwest, but they don't pay twice as much for their cars or consumer goods.
Even in Southern Cali you’ll get voting at 40% red normally. I’ve only seen pockets go lower. Even at 20% that’s still two out of every ten folks on the road.
Interesting, this has not been my experience at all. I have an M5 machine and I'm not even aware of what AI features have been added, and it's streets ahead of my old M1 Pro in speed.
peep the comment I just made to the adjacent commenter, that has been my experience. I basically have to run my fans at full speed all day while working now in order to type on my computer (when I'm not using my magic keyboard). It is like a huge problem, not even just a small one but like something that is affecting me negatively every single day, increasingly making me want to break this machine in half and disappear into the woods.
skills and agent.md are very portable though? I figure at most, as the models get better, the only maintenance you need to do is pare them down to remove unnecessary context.
I mean, I wouldn't know how portable they are between models because I don't use them. I don't use them because, well, I don't need them. I mainly use LLMs as a StackOverflow replacement via the Web chatbots.
I only use CC or Codex for a quick MVP once every few months or so.
That study cites that 45% of vendors had hallucinations, likely vendors using smaller or cheaper models. So 55% of vendors had no known hallucinations.
Provenance is part of the work. If a roomful of monkeys banged out something that looked like anything, I'd absolutely hang it on my wall. I would not say the same for 99% of AI generated art.
I remember this! Sorry again for the frustration >_< We made our Stripe API requests a little more robust after this happened.
We do get a fair number of disputes like the author where customers will cancel after getting billed, and then dispute it, even though we always give refunds to people who email and ask for one. It also feels like there's been a significant up-tick in recent months of disputes like these, maybe a reflection of the current economic climate. Hard to blame the customer though, for all the reasons listed by the top comment -- sometimes it's just easier to do it through the bank than figure out how to cancel through an app you forgot you even subscribed to.
Haha, I'm amused you remember. I went back in my emails and it happened back in 2018. I was a not-so-eloquent college student back then. I appreciated that you both handled it with grace and kindness - sorry if I sounded irate at the time, and hope you're doing well these days. :)
This isn’t a given since there’s still a way to give them money directly for cosmetics (which makes them a ton of money). Many freemium business models give away a lot product for free with the goal of convincing a minority of users to pay and subsidize the rest.
Wow, I have been following the Chris Krebs saga quite closely AND been an avid consumer of Krebs on Security and for whatever reason always assumed they were one and the same. I even know his name is Brian Krebs!
It's humbling when you're confronted with your blinders and stupidity, and they are the same as those you rail against for being so blindly stupid...
This is neat. I've spent a lot of time thinking about implementing something similar for my company Eat This Much, but end up pushing it off in favor of focusing on our core meal planning features.
When something doesn't have a reference listed, and just says "sourced from a publicly available first-party datasource", what does that mean? Crawled from other sources and you'd prefer not to say? The wording does feel a little sketchy when contrasted with entries that do list sources.
When something does list references that don't seem super close to the actual food, what is the process like there for interpreting those values? Example, this Chicken Salad inheriting from Chicken Spread: https://www.opennutrition.app/search/chicken-salad-37mAX17YX...
The quality of the data might feel rough now, but I can see this being valuable for our users even if it's just an opt-in "show estimated micronutrients" or something. Would require labeling values as not being directly from a source of truth.
One thing that a lot of people are missing is that there is already a lot of inaccurate nutrition data out there. Even on information directly from the manufacturer, sometimes there are errors, or just old versions of the product that never get scrubbed from the internet (I imagine the latter case would be tricky for an LLM to deal with too). Just logging your dietary intake in any form will get you 80% of the benefit of tracking via some self awareness of your intake. Of course, it's an easy argument to point out that if you had the choice between verified data and fuzzy LLM data, you should go for the human verified data (for now).
> When something doesn't have a reference listed, and just says "sourced from a publicly available first-party datasource", what does that mean?
It depends, and the degree to which it depends is why the citation is ambiguous (although it is true, if imprecise). My goal is to individually cite the individual nutrients but it was simply too costly and time-consuming at the stage of the project at which I did this work.
> what is the process like there for interpreting those values?
Because the degree to which something in the database might be related to those values is so varied, it depends. The reasoning agent had access to those database entires, which is helpful because they tend to contain micronutrient data. It also had access to web data, as well as its own world knowledge, and considers sources in that order. Ultimately it was left up to the agent to decide what the most reasonable fit for each food was, thinking through what an average user likely meant by that entry (e.g. a typical user probably assumes a 'Tomato' is raw), and then to choose the best sources from there. For the chicken salad, it used approximate micronutrient values from the listed references to inform its answer, but adapted the end values for how the dish is described in the description.
> if you had the choice between verified data and fuzzy LLM data, you should go for the human verified data (for now)
Human verification isn't free, and that means it is not available to a lot of people who can't or don't want to pay for something. But if that's something that someone values, I would certainly not diss the human effort!
I was under the impression that Tesla has put a lot of effort into building out support infrastructure? My perception is a bit clouded by the fact that I live a few miles from a service center.
Try to get spare parts for teslas. Or fix them at a non-Tesla owned shop. Both are 100x more complex and expensive than any other mass produced car made in the last decade 20 years. And it is like that by design: it was never a priority for them.
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