It's what I was thinking about in the shower ๐คทโโ๏ธ
Coopr8
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.
Yes, by the traffick camera on the corner tracking your gate up to the hotdog stand, and your phone showing your location by the hotdog stand and how long you stood there. Not to mention, you just wrote that transaction down here in public.
You can inspect my comment history. An LLM agent with the proper scraping tools and integrations could answer the question "identify all accounts on lemmy which have expressed a negative view of (insert government), search those accounts for any personally identifying information including photographs and accounts on other websites which they link to more than three times, and create a database of these accounts" in a tiny fraction of the time it would take a human to perform this same task.