Coopr8

There are free clinics in some areas specifically serving these communities for this reason. Disproportionately impacted by thr disease, and more likely to be unable to pay due to economic disadvantage.

The simple answer is always antigravity aka magic. You could calculate the force of gravity acting on them and say that amount of antigravity plus the force required to accelerate them at the rate they accelerate including wind resistanceat the elivation they are flying, but you would need their mass and dimensions.

There should be a Magic Eye community! This is awesome.

worked for me, the smaller it is the harder it can be to focus right though.

So beautiful!

It's what I was thinking about in the shower 🤷‍♀️

Don't get LLMs confused with specialized ML algorithms. Hallucination is an LLM problem, algorithms like gait recognition have been honing in accuracy since way before LLMs started development. Where LLMs come into the picture is that they can act as agents, processing queries and then selecting the best fit specialized algorithm to process the data and then cross reference results from different queries to compile a correlated multidomain dataset. Done properly, this will yield not just a single answer but a list of potential answers with their relative degree of certainty.

Look at the Harvard facial recognition glasses as a proof of concept of this kind of approach: https://specialconcentrations.fas.harvard.edu/news/heres-looking-you

That's why I said gait recognition, not facial recognition. Last year GaitNet hit over 99% recognition accuracy, given another year of training the error rate will have gone down and the recognition window will have gone up. https://pmc.ncbi.nlm.nih.gov/articles/PMC11323174/#%3A%7E%3Atext=Diverse+neural+network-based+gait%2Cresearch+direction+is+also+assessed.

Yes, and of course wifi is just one frequency band. That kind of technique could also be used with other frequency bands, I wonder what the resolution of 5G is for that kind of telemetry.

See below. The post wasn't about data acquisition, it was about data sorting.

But the point wasn't about the tracking, it was about sorting the data. The data acquisition has existed for years, but was never useful because it could never be processed in an accessible manner. Now AI can sort through the hours of traffick camera footage, identify your gate, and show every location you appeared on camera in the past 24 hours. It can also check cell tower records and record every cell phone that stood by the hotdog stand for more than 60 seconds, and crossreference the hardware IDs and Sim cards on those phones against carrier databases to match the walking gates of the people on camera to their name, address, SSN via credit check, and bank information.