Yeah, not sure I would listen to this guy. Setting up a venv for each project is about a bare minimum for all the teams I’ve worked on.

That being said python env can be GBs in size (especially when doing data science).

The download feature is always in some state of broken, but it has gotten a lot better over the past couple of years. If you haven’t tried it in a year or so, you may have better luck now.

Fair point then about the arguement around safety. For me the bigger issue is control. Cars with kill switches and conditions to use is a slippery slope. Just look at what’s happened with software and media. Don’t want to have to pirate my car or load custom firmware so I can use it as I want.

I don’t think there is a car where the seat belt is tied to anything besides a little notification beep. Seems like a different situation if the “safety” feature dictates how the car is used.

Do you still use WASM? I’ve been exploring the space and wasn’t sure what the best tools are for developing in that space.

This is just the estimates to train the model, so it’s not accounting for the cost to develop the system for training, collecting the data, etc. This is just pure processing cost, which is staggeringly large numbers.

LLMs do suck at math, if you look into it, the o1 models actually escape the LLM output and write a python function to calculate the output, I’ve been able to break their math functions by asking for functions that use math not in the standard Python library.

I know someone also wrote a wolfram integration to help solve LLMs math problems.

Not sure if you’re serious, but they were making a joke because Intel, who makes chips, is a competitor to TMSC the chip manufacturer from the article.

So they played on that relationship by treating the word Intel in your “thanks for the Intel” comment as meaning the company.

All the evolution in AI right now is just trying different model designs and/or data. It’s not one model that is being continuous refined or modified. Each iteration is just a new set of static weights/numbers that defines it’s calculations.

If the models were changing/updating through experience maybe what you’re writing would make sense, but that’s not the state of AI/ML development.

This approach has been around for a while and there are a number of applications/systems that were using the approach. The thing is that it’s not a different model, it’s just a different use case.

Its the same way OpenAI handle math, they recognize it’s asking for a math solution and actually have it produce a python solution and run it. You can’t integrate it into the model because they’re engineering solutions to make up for the models limitations.

I mean I can list a lot of things AI (and I’ll limit it to Transformers, the advancement that drives LLMs) has enabled:

• Audio Transcription
• Greatly improved language translation
• Improved computer vision, in some situations
• Combined with diffusion models has enabled targeted image generation, which we already know is being used in media and ads.

AI isn’t a scam, but it’s being oversold and it’s limitations are being purposefully hidden. That being said, it is changing how things are done and that’s not going to stop. We’re still seeing impacts from CNNs, one of the major AI/ML breakthroughs from over a decade ago, make impacts.

What was so obvious in that instance was the board members trying to push him out were calling out the lack of openness OpenAI was trending towards. They were literally calling him out for not upholding the vision of why the company was founded.

All the engineers clearly saw their payday slipping away and revolted for that reason. Can’t say I blame them, but it was a scenario where the board was actually doing the right thing and everyone turned on them for profit.

Originally all their work was supposed to be published and shared with the world, hence the “open” in OpenAI. However somewhere along the way they made a for-profit break off of the original company and started pulling everything in that direction.

Microsoft actually ported their keyboard to android, called “Microsoft SwiftKey” or similar. It’s a great keyboard, but apparently now has copilot ಠ_ಠ

Yeah I read another article on this and it’s very unclear what was illegal. If I had to guess they’re getting him on the technicalities of the process rather than on the actual streaming.

Edit: so I looked it up and realized wire fraud is “electronic” fraud, not bank wiring - Online definition

Which given the way the guy did it definitely seems to meet that definition.

One solution that’s been proposed is to cryptographic ally sign content. This way someone can prove they “made” the content. It doesn’t prove the content is real, but means you can verify the originator.

However, at the end of the day, you’re still stuck with needing to decide who you trust.

I was responding to an above comment. The guy who was arrested in op’s article was posting clips from movies (so not deep fakes).

That being said, for deepfakes, you’d need the original video to prove it was deepfaked. Additionally, you’d then probably need to prove they used a real person to make the deep fake. Nowadays it’s easy to make “fake” people using AI. Not sure where the law sits on creating deepfakes of fake people who resemble other people.

Why do you not know how to feel about it?

To me it’s just clip collection, you could have a collection of all death scenes or car cashes. They’re all just clips from videos people agreed to make for public consumption.

It’s messy legislation all around. When does it become porn vs art vs just erotic or satirical? How do you prove it was a deep fake and not a lookalike? If I use a porn actress to make a deep fake is that also illegal or is it about how the original source content was intended to be used/consumed?

I’m not saying that we should just ignore these issues, but I don’t think any of this will be handled well by any government.

The study is still valuable, this is a math class not a technology class, so understanding it’s impact is important.