Lol he was nothing more than middle class. He also was telling the story from the perspective of “I understand how easy it was for me”. He was a really cool guy.

I remember talking to an older fella about his experience becoming a programmer back in the 60s (I think). He told me that he decided it was time to start a career so he went to a nearby IBM office and asked for a job. They gave him an aptitude test and then hired him the same day. He wrote code for their mainframes until he retired.

It sounds like the model is overfitting the training data. They say it scored 100% on the testing set of data which almost always indicates that the model has learned how to ace the training set but flops in the real world.

I think we shouldn’t put much weight behind this news article. This is just more overblown hype for the sake of clicks.

Do you have any proof? Apple claims they’ve fixed these issues in iOS 17.1 which would again suggest that this is just soft image retention that that they weren’t accounting for well enough.

Yes, it is but this isn’t it. I guarantee these displays are not permanently damaged so soon after launch. It usually takes thousands of hours of displaying the same image with max brightness to actually burn in a modern OLED panel.

My understanding is that a lot of “burn in” with OLED screens isn’t permanent. The quote accurately calls it “image retention” because the image is temporarily retained but the screen will go back to normal. It also points out that this type of thing happens under niche circumstances. Almost like people are trying to make this happen.

YouTube is not a news source my friend. A lot of the “experts” you’ll find on there have zero credibility.