The conventional wisdom is that Kevin Bacon is the allencompassing center of Hollywood, so prolific that the game is a lot easier than if it were called the “Six Degrees of John Doe.”
However, Kevin Bacon is not the center of Hollywood. In fact, he never has been, and almost certainly never will be.
This is a wonderful showcase of data analysis and visualization. I didn’t guess who the real “Kevin Bacon” was, though I did guess the person who ranks third. And Lacey’s projections about who will become the supreme movie connector of the future are fascinating, too.
The Cambridge Analytica scandal has come back to haunt Meta after a New Mexico judge ordered it to pay $25 billion in penalties for more than 43 million violations of the state's unfair practices law. The ruling marks the biggest legal hit Meta has taken this year, even as it's faced several other losses or settlements.
A New Mexico jury ruled in September that Meta misled consumers over how it protected their data and prevented misinformation and hate speech on its platforms. The case stemmed from a 2021 complaint in the wake of the revelations a few years earlier that UK political consultancy Cambridge Analytica harvested data from millio …
Programming turned into one of the greatest jobs you could imagine. You got paid to work on tricky little logic puzzles. The trickier the puzzle, the more you got paid. But even pretty simple puzzles were worth a lot of money because regular people just couldn't do it! No, they needed us. They would give us a problem and we would solve it the way we wanted. We set the strategy, we made the timeline, we defined what was and was not possible.
If you're a programmer who thrives on building working systems and doesn't care too deeply about the problems solved along the way, LLMs are the gift that keeps on giving.
If directly solving those problems was a big part of your enjoyment, the loss is very real.
Via lobste.rs
Tags: programming, careers, ai, generative-ai, llms, coding-agents, deep-blue
Mathematicians are facing the sudden shift with grief, anger, and a desperate search for fresh ideas.
I've always been kind of into computers since I was young. And then when film started to move from analog film to digital, I became more interested in that aspect of it. And the visual effects workflow for many years has included machine learning.
So I can write like pretty shitty Python scripts and stuff like that because with convolutional neural networks, which were the sort of precursors to what the transformer can do, which is just much more computation simultaneously, you would do things like look at what's called a tensor, which is just the numerical translation of a visual image in numbers — like the batch number, the frame number, the red, green, and blue values of each pixel in each frame.
And a tensor, you use a convolutional neural network to identify patterns in that that would reveal what's called edge detection or feature extraction, which is just identifying patterns enough to know like this is where the window ledge is, so we can more easily take the green screen image out and replace it with something.
— Ben Affleck, Pythonista
Tags: machine-learning, python