A judge in Washington state has blocked video evidence that’s been “AI-enhanced” from being submitted in a triple murder trial. And that’s a good thing, given the fact that too many people seem to think applying an AI filter can give them access to secret visual data.
Whenever people say things like this, I wonder why that person thinks they’re so much better than everyone else.
Tangentially related: the more people seem to support AI all the things the less it turns out they understand it.
I work in the field. I had to explain to a CIO that his beloved “ChatPPT” was just autocomplete. He become enraged. We implemented a 2015 chatbot instead, he got his bonus.
We have reached the winter of my discontent. Modern life is rubbish.
Normie, layman… as you’ve pointed out, it’s difficult to use these words without sounding condescending (which I didn’t mean to be). The media using words like “hallucinate” to describe linear algebra is necessary because most people just don’t know enough math to understand the fundamentals of deep learning - which is completely fine, people can’t know everything and everyone has their own specialties. But any time you simplify science so that it can be digestible by the masses, you lose critical information in the process, which can sometimes be harmfully misleading.
LLMs (the models that “hallucinate” is most often used in conjunction with) are not Deep Learning normie.
https://en.m.wikipedia.org/wiki/Large_language_model
https://en.m.wikipedia.org/wiki/Neural_network_(machine_learning)
I’m not going to bother arguing with you but for anyone reading this: the poster above is making a bad faith semantic argument.
In the strictest technical terms AI, ML and Deep Learning are district, and they have specific applications.
This insufferable asshat is arguing that since they all use fuel, fire and air they are all engines. Which’s isn’t wrong but it’s also not the argument we are having.
@OP good day.
When you want to cite sources like me instead of making personal attacks, I’ll be here 🙂
I said good day.
Ok but before you go, just want to make sure you know that this statement of yours is incorrect:
Actually, they are not the distinct, mutually exclusive fields you claim they are. ML is a subset of AI, and Deep Learning is a subset of ML. AI is a very broad term for programs that emulate human perception and learning. As you can see in the last intro paragraph of the AI wikipedia page (whoa, another source! aren’t these cool?), some examples of AI tools are listed:
Some of these - mathematical optimization, formal logic, statistics, and artificial neural networks - comprise the field known as machine learning. If you’ll remember from my earlier citation about artificial neural networks, “deep learning” is when artificial neural networks have more than one hidden layer. Thus, DL is a subset of ML is a subset of AI (wow, sources are even cooler when there’s multiple of them that you can logically chain together! knowledge is fun).
Anyways, good day :)