The issue is it’s going to be trained only on places people go. My understanding is that most geolocating systems are more focused on the uncommon or less traveled locations. Maybe I’m wrong, but I guess they’re probably tested it out before announcing it.
Maybe I’m not aware of similar configurations you can do, but it’s only sorta it’s own container. VSCode can actually directly connect to it automatically so you can develop in host os but run directly against the container. Additionally this means some visualization/gui interfaces can be visible on the host side (this is a gift and a curse).
So you basically have system integrated containers/vms. It’s not perfect, but it is definitely leagues better than what windows development was prior and may have some advantages over Linux only deployments (not sure if the system integrations are feasible in Linux hosts).
I totally agree, really took me out of the movie too.
I find it funny in a world with a billionaire dressing up as a bat, the most ridiculous thing is how they commit white collar crime. I think largely it seemed to easy and also soo stupid that batman wouldn’t have a diversified portfolio with things not all tied up in the stock market.
That’s sad to hear, cause it really is a great game.
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.
To be fair casting for both Tilda Swinton as The Ancient One and Johnny Depps as Tonto were both criticized when the movies were released. Probably not to the level Halle Baileys casting was, or by the same people, but both were definitely seen as whitewashing.
Its also likely The Ancient Ones casting got as much attention as it did due to the political nature of the change (seen as to appease China over its history regarding Tibet).
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.
Yeah, not everything in science is super cool, but it is valuable to show why testing things out matters. Although it’s not like the scientific community has been great about doing peer reviews anyways.
That’s why I did “watching paint dry” as an actual science fair experiment. Tried putting paint in different environments to see how conditions actually effected the speed in which it dried.
Requires experimentation to backup a hypothesis with empirical data. Yeah it sounds boring, but had some fun with it regarding the different “environments” (like under heat lamp, with a fan, etc.)
Yeah another way to interpret it is “oh damn were doing something wrong and need better leadership”.
Not saying that’s actually the case, but would better align with the graphic.
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:
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.
It definitely has applications in defense/Intel spaces. Knowing where a photo was taken can be really useful info.