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Path: ...!news.mixmin.net!news.swapon.de!fu-berlin.de!uni-berlin.de!individual.net!not-for-mail From: rbowman <bowman@montana.com> Newsgroups: comp.os.linux.advocacy Subject: Re: A Godfather of AI Just Won a Nobel. He Has Been Warning the Machines Could Take Over the World. Date: 19 Oct 2024 02:30:55 GMT Lines: 21 Message-ID: <lngjuuFs9nrU5@mid.individual.net> References: <n3djgjhqqqf3hh9o0ua7lirdt8pel916uc@4ax.com> <547d7042-b50e-d5fd-51f6-e6aff7bbac7e@ichigo.kinoko.kuri> <slrnvgkr5p.j02.rotflol2@geidiprime.bvh> <e11b49e7-801f-8988-6d09-c1701268ff62@ichigo.kinoko.kuri> <slrnvgpr80.mr5.rotflol2@geidiprime.bvh> <vek7s3$1cf26$1@dont-email.me> <RniPO.55917$vtH3.13939@fx07.iad> <vel2mo$1k0kk$1@dont-email.me> <cOtPO.213884$1m96.102822@fx15.iad> <veo8gp$282p1$3@dont-email.me> <cLOPO.380388$FzW1.308377@fx14.iad> <veqatt$2levu$2@dont-email.me> <VQ7QO.226118$1m96.76357@fx15.iad> <ver3u3$2opnq$1@dont-email.me> <WV8QO.382401$FzW1.75425@fx14.iad> <verb10$2opnq$4@dont-email.me> <6712b6f2$0$29713$426a74cc@news.free.fr> Mime-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit X-Trace: individual.net Z0+ukdYopNSENrO8s8JsCwd908N6enTwluoCi8DefVgBLJdC2F Cancel-Lock: sha1:U3KVuYiGKnZv3JUd23lYJjmf4ok= sha256:t5VF0JpXZR46MIVLD5IYA+sbDDm2q6e0yQ38LfS1/00= User-Agent: Pan/0.149 (Bellevue; 4c157ba) Bytes: 2587 On 18 Oct 2024 19:28:50 GMT, Stéphane CARPENTIER wrote: > <https://www.reuters.com/technology/tesla-workers-shared-sensitive- images-recorded-by-customer-cars-2023-04-06/> I don't remember the crime show but none of the surveillance cameras picked up the plate on a car they were trying to identify. However the camera did show a Tesla parked behind the vehicle of interest. That one they could identify and got the footage from the owner. I'd never thought about yet another invasion of privacy. "Since about 2016, Tesla has employed hundreds of people in Africa and later the United States to label images to help its cars learn how to recognize pedestrians, street signs, construction vehicles, garage doors and other objects encountered on the road or at customers’ houses. To accomplish that, data labelers were given access to thousands of videos or images recorded by car cameras that they would view and identify objects." I'd mentioned in another post that image recognition requires a huge amount of labeled images for training. Nothing like outsourcing it to Africa. I wonder if an Kenyan princes were able to exploit the data?