ignirtoq

I would honestly like to see a cut of just about any TV show or movie that uses stunt doubles where the doubles do both the lines and the action. I would like to see how different a director would shoot a scene if they weren't constrained to choosing angles and lighting to make it look like two different people were the same person.

At least it was better than Indiana Jones and the Kingdom of the Crystal Skull.

I don't follow Mexican politics closely, but this could be part of an effort to curb obesity. I've heard they introduced taxes on sugary drinks for this, so this might be another avenue.

If people are wanting cheap snacks, and private companies are only making unhealthy ones, you can introduce regulations to micromanage what they can produce, or you can introduce a complex taxation process to disincentivize sugar snacks. Or you can introduce your own product that meets a perceived unmet demand in an underserved market.

Part of the reason that this jailbreak worked is that the Windows keys, a mix of Home, Pro, and Enterprise keys, had been trained into the model, Figueroa told The Register.

Isn't that the whole point? They're using prompting tricks to tease out the training data. This has been done several times with copyrighted written works. That's the only reasonable way ChatGPT could produce valid Windows keys. What would be the alternative? ChatGPT somehow reverse engineered the algorithm for generating valid Windows product keys?

The thing is it's been like that forever. Good products made by small- to medium-sized businesses have always attracted buyouts where the new owner basically converts the good reputation of the original into money through cutting corners, laying off critical workers, and other strategies that slowly (or quickly) make the product worse. Eventually the formerly good product gets bad enough there's space in the market for an entrepreneur to introduce a new good product, and the cycle repeats.

I think what's different now is, since this has gone on unabated for 70+ years, economic inequality means the people with good ideas for products can't afford to become entrepreneurs anymore. The market openings are there, but the people that made everything so bad now have all the money. So the cycle is broken not by good products staying good, but by bad products having no replacements.

The technological progress LLMs represent has come to completion. They're a technological dead end. They have no practical application because of hallucinations, and hallucinations are baked into the very core of how they work. Any further progress will come from experts learning from the successes and failures of LLMs, abandoning them, and building entirely new AI systems.

AI as a general field is not a dread end, and it will continue to improve. But we're nowhere near the AGI that tech CEOs are promising LLMs are so close to.

I don't know. I feel like if I lived 150 years ago and was very lucky, I might have been one of those people who invented a ketchup of ketchups. If I had more free time, I would probably experiment a lot more in the kitchen.

Oppenheimer was already really long, and I feel like it portrayed the complexity of the moral struggle Oppenheimer faced pretty well, as well as showing him as the very fallible human being he was. You can't make a movie that talks about every aspect of such an historical event as the development and use of the first atomic bombs. There's just too much. It would have to be a documentary, and even then it would be days long. Just because it wasn't the story James Cameron considers the most compelling/important about the development of the atomic bomb doesn't mean it's not a compelling/important story.

The first statement is not even wholly true. While training does take more, executing the model (called "inference") takes much, much more power than non-AI search algorithms, or really any traditional computational algorithm besides bogosort.

Big Tech weren't doing the best they possibly could transitioning to green energy, but they were making substantial progress before LLMs exploded on the scene because the value proposition was there: traditional algorithms were efficient enough that the PR gain from doing the green energy transition offset the cost.

Now Big Tech have for some reason decided that LLMs represent the biggest game of gambling ever. The first to find the breakthrough to AGI will win it all and completely take over all IT markets, so they need to consume as much as they can get away with to maximize the probability that that breakthrough happens by their engineers.

There was a crazy amount of variety in at least American recipes and cuisine until the turn of the 20th century when modern grocery store practices replaced older ways of managing a food store and food distribution. Innovations in canning, refrigeration, and other food preservation technologies allowed for the creation of larger, centralized factories that could mass produce products that could be shipped further away. Food prices and meal preparation times dropped, but so did variety and unique food cultures across most home kitchens.

They keep tasking these LLMs with things that traditional programming solved a long time ago. There are already vending machines run by computers. They work just fine without AI.

Honestly the computer controlled vending machines are already over-engineered since many of them play ads when you walk up. The last customer-focused feature added was credit card support, and that just needs a credit card reader and a minimal IoT integration. They really shouldn't even have screens.

Why are they... why are they having autocomplete recommend medical treatment? There are specialized AI algorithms that already exist for that purpose that do it far better (though still not well enough to even assist real doctors, much less replace them).