In Italy several cities lowered the maximum speed from 50 to 30 km/h.
There was a huge fight over it, car drivers in those cities were mad. Plenty of politicians opposed it.
One year later stats were super clear: streets got way safer and the number of fatal accidents dropped to near 0. Time to traverse cities didn't change much, as it was already limited mostly by traffic and lights.
I think this ignores the argument the high speed limit people make which basically boils down to "sure some people will die or get injured but its worth it because driving faster is fun"
Autonomous vehicles following proper signalling before lane changes can be safe at arbitrary speeds (see Autobahns working at all). Humans, we should limit passing speed to roughly ~5 mph delta between adjacent lanes and leave it at that.
Humans with adequate following distance in the entire lane can probably manage 10 mph delta. I routinely travel dozens of miles very safely at ~80 with the flow of traffic (including the cops), and been stressed out at 55 in the carpool lane through stop and go traffic in the right-hand lanes due to on ramps/offramps.
I think 75 is memorable and roughly in the region where the tradeoff between increased kinetic energy and decreased time to arrival per additional unit of velocity becomes untenable.
It's easy but it's not cheap. Well, price is relative but capturing video is certainly cheaper.
Also, I am not sure how heavy LIDAR units are, but remember that the heavier the payload the more the flight time is reduced. Some drones can only have a single payload, so if you also want to capture (high-res) video/imgs you need to fly again.
The most available lidar is found on your iPhone, but the results are orders of magnitude less detailed than that derived from photogrammetry. How ever an advantage is that lidar is not confused by reflections.
Huh? LIDAR absolutely is confused by reflections. Not always the reflections you can see (because often it’s using IR wavelengths) but nonetheless, reflections.
This is just marketing nonsense. You don't have to train models to not retain personal information. They simply have no memory. In order to have a chat with an LLM, every time the whole conversation history gets reprocessed - it is not just the last answer / question gets send to the LLM but all preceding back and forth.
But what they do is exfiltrate facts and emotions from your chats to create a profile of you and feed it back into future conversations to make it more engaging and give it a personal feeling. This is intentionally programmed.
I think they mean that they trained the tool-calling capabilities to skip personal information in tool call arguments (for RAG), or something like that. You need to intentionally train it to skip certain data.
>every time the whole conversation history gets reprocessed
Unless they're talking about the memory feature, which is some kind of RAG that remembers information between conversations.
> In order to have a chat with an LLM, every time the whole conversation history gets reprocessed - it is not just the last answer / question gets send to the LLM but all preceding back and forth.
Btw, context caching can overcome this, e.g. https://ai.google.dev/gemini-api/docs/caching . However, this means it needs to persist the (large) state in the server side, so it may have costs associated to it.
I used to work in healthtech. Information that can be used to identify a person is regulated in America under the Health Insurance Portability and Accountability Act (HIPAA). These regulations are much stricter than the free-for-all that constitutes usage of information in companies that are dependent on ad networks. These regulations are strict and enforceable, so a healthcare company would be fined for failing to protect HIPAA data. OpenAI isn't a healthcare provider yet, but I'm guessing this is the framework they're basing their data retention and protection around for this new app.
I didn't wanna cite the Fortune article I got it from because it cited research from a group called "Whop" that didn't have the full data available. But here's the article I read
I do vaguely recall a more serious study showing a vast majority of kids thinking "influencer" was a viable career path and a very large portion beleiving it was the only viable career path for them. It also found that these percentages were higher in boys than in girls. That's the study I was trying to find but failed and found this instead
Consider a prompt like this to a Deep Research agent if you are interested:
How have youth career aspirations toward entertainment/fame-oriented careers changed over time (1960s-present), and does the rise of "influencer" represent a genuine shift or category substitution?
\"Specific sub-questions\":
1. What longitudinal or repeated cross-sectional surveys have asked children/teens about career aspirations with consistent methodology?
2. What were the historical rates for "actor/entertainer/movie star" type responses in surveys from 1970-2000?
3. How do current "influencer/YouTuber" rates compare when aggregated with traditional entertainment categories?
4. Are there international comparison studies showing different rates by country?
5. Is there evidence for changing perceived accessibility of fame careers (kids thinking it's actually achievable vs. fantasy)?
\"Priority sources\": Academic journals (Journal of Career Development, Journal of Vocational Behavior), Gallup historical archives, Pew Research, YouGov archives, OECD education reports, Harris polls historical data.
\"Methodological notes\": Flag when studies use different age ranges, different question framings (open-ended vs. multiple choice), and whether "entertainment" categories were offered or emerged organically.
I ran this for you and got some really interesting results[0] (TLDR: Young people have traded the stability of the "Company Man" for the autonomy of the "Personal Brand" in response to a labor market that no longer guarantees security.
I also wish we were attracting industries that weren't going to significantly push up electricity consumption on windless days, which will have an outsized effect on electricity prices everyone else pays. At least this says the datacentres will be up north, hopefully not exacerbating transmission issues.
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