Imagine it's ten years from now, and for $199 anyone can buy an in-home UPS from Home Depot with enough capacity to keep their lights on and their ice cream frozen for 48 hours. Once most houses have one of those, most power outages become more of a minor nuisance than a significant problem.
"No. It is not copyright infringement"
Go ahead, prompt for that story and publish your own 'moonlit princess". It is not a court case you'd win; the details taken from the Disney version are beyond excessive.
" and there's no reason to hold copyright so sacred anyway. Are you seriously wanting to protect hundred year old fairy tails from being retold?"
That's an entirely separate discussion. Legally it is infringement. Whether it should be is completely separate question, or how long it should be are separate questions.
FWIW, I don't agree with copyright being 100 years.
Who is they? And what database are you referring to?
Dictionaries often contain quotes from original source material, or references to where it was first used, or first used a certain way.
Dictionary publishers have never been accused of downloading massive torrents of pirated copies of books and processing them.
Google on the other hand HAS been accused of that, and the decade of litigation related to that ultimately rules that the limited things google was doing with it was fair use. The dictionary companies are likely paying for enhanced access to that google data now.
The AI companies are singing the same fair use tune, but its really quite different. Google was doing it (at the time) to allow for search so you could enter phrase or quote and find the book it was from and the page it was on, and to collect other meta data - word count, word frequency, analyze sentence complexity, etc... all factual information.
AI companies are using the content of that digitized corpus and everything else they can get their hands on to generate new content, much of which non-factual in nature, and often very arguably explicitly creatively derivative.
prompt: "Make a story like sleeping beauty"
The kingdom celebrated for seven days and seven nights. At the grand naming feast, three magical guardians arrived, each bringing a special gift.
The first guardian said, "May Lyra always have a kind heart."
The second smiled and whispered, "May she be wise enough to guide her people with fairness."
The third raised her glowing staff. "May hope follow her wherever she goes."
But before she could finish, a shadow swept across the hall.
It was the sorceress Vespera, who had been forgotten when the invitations were sent.
"You celebrate without me?" she cried. "Then hear my gift! On her sixteenth birthday, Princess Lyra will touch the thorn of the Moon Rose and fall into an endless sleep."
You seriously telling me this is NOT copyright infringement? Even if you wanted to argue that sleeping beauty is a classic fairytale from the 17th century and not under copyright, the prose above is a pretty blatant Disney ripoff.
Exactly. But you have to keep the original BSD license intact. You can modify the files, but you have to acknowledge, that you got them from FreeBSD. That's why many commercial companies like to base their systems on FreeBSD.
You're missing the point. Commercial companies can usurp the code without sharing back to the project that made their business possible. It's quite likely that a commercial company's version can dominate the market, thus strangling the original free version. In fact, this has happened many times. The GPL prevents that from happening.
Realistically, open source software that has a decent number of maintainers means that the quality is good and bugs get fixed, including security bugs. But what that also means is that when problems get fixed in the open source repo, those changes have to be pulled into the source code that companies are building into their products. The more they diverge from the open source version, the harder that becomes. So while a company theoretically could do what you are describing, the reality tends to be tht companies contribute the vast majority of their changes, keeping private only the parts that are specific to their custom integrations with their product.
For example, LLVM is under a permissive license, and some of the biggest contributors are companies like Apple. They use it in their proprietary products (Xcode). But they are basically using it as a library and giving back their changes. What they're not doing is giving back the tools that they wrap around it. But the original core functionality is still out there, still open, and still being maintained.
The GPL doesn't actually prevent that from happening. It just means that the code gets rewritten instead of being copied. It makes the closed-source app ever so slightly more expensive to develop and ever so slightly later to hit the market. If the closed-source app is better than the Free Software app, it will still dominate the market unless someone is prepared to throw resources into making the Free Software app equally capable, and the market will still determine the winners and losers.
Yeah, there's two main problems:
1) People entering the wrong fields. For example, medicine really needs workers, at all levels, but not enough people are going into it.
2) Certain manual labour fields, like field work and home construction, because... well, I think we all know why there's a shortage of workers in those fields.
Part of it may be a dysfunctional corporate culture, but a lot of it is a consequence of Microsoft's business decision to maintain backwards compatibility at all costs. When you're committed to retaining every design mistake, forever, the complexity of the codebase just keeps rising, which means that less and less of it can fit into anyone's mind at one time, which means more mistakes are made going forward, and the technical debt just keeps compounding.
We can bust on Microsoft all day and all night, and they deserve it, but the fact that their ability to find and fix these problems has greatly increased is a good thing. Software is incredibly complex, and no software more complicated than "10 GOTO 10" is free from the potential of security problems. Microsoft's QA has gone downhill in recent years, but now it's getting better apparently (even if it's after the fact). They are not going away, so this makes all our lives better.
OpenAI envisions the device anticipating needs, surfacing information proactively and serving as an expert on its user, they said.
Will it have a Genuine People Personality? Perhaps a cheerful and sunny disposition?
Good question. Their POWER series of CPUs were not insignificant in capability, their chip designers were clearly technically sophisticated, and GPUs are just specialised vector processors with a few extra bells and whistles - stuff IBM is extremely familiar with.
It would not have been difficult to release a GPU or other LLM-specific processor to go along with the POWER11. They'd been working on the POWER11 for 4 years, they knew in 2020 that LLMs had a strong potential to be significant for Big Data processing - an area you use big iron for, they're not rank amateurs, they have plenty of reserve, they could have assembled an emergency team to build a vector processor that was custom-designed for just LLM work, and released an LLM processor card that could run circles around nVidia.
They didn't. Because, as has happened before, their management is simply too stupid and too slow.
I wrote a file searching utility in C++ about 30 years ago. About 15 years ago I ported it to Python and found it to be faster than using the Windows directory enumeration APIs, and I've been using that ever since. It just searches filenames, but that's all I need.
"NOTE: Experiences vary by region." says to me that Microsoft doesn't even know what their changes will do.
Or let's put this another way. Show of hands - how many of you "spicy autocorrect" / "stochastic parrot" people had "AI will start mass-solving Erdos problems" on your forecast list a couple years back? Huh, none of you? Fascinating!
Take some time to reassess your priors. And while you do so, understand that, yes, they are doing logic / reasoning.
They weren't discovered by an LLM. They were known conjectures that were proven by an automated solving language that was linked to an LLM.
I'll take "Things That Didn't Happen For $200", Alex.
Only a handful of meaningful proofs have ever been done by automated formal theorem solvers (the Four Colour Theorem being the most noteworthy example - but its proof is so long that humans can't verify it). By contrast, AI tools have been solving Erdos problems en masse. The majority of them just bog-standard commercial models. In case you need help, the only ones on that list that were hybrid (AI / non-AI) in the actual solving phase are:
1) AlphaProof / DeepMind Prover Agent / AlphaProof Nexus
2) Aristotle (Harmonic)
3) Seed Prover / Seed Prover 1.5 (ByteDance)
4) AxiomProver (Axiom Math)
In each of the above, LLMs come up with the lemmas / strategies but then use Monte Carlo search ("brute force") or likewise to investigate what they came up with. These are a minority. In the "AI Standalone" category, these "hybrid" tools made up only ~20% of attempts and successful proofs. Hybrid tools actually made more of a contribution in the "AI Alongside Literature" (related literature found afterward) and even more of the "AI Building On Literature" (related literature known beforehand) categories, which is the opposite of what people like you expect.
And even with the hybrid tools, it's still the AI doing the heavy lifting when it comes to strategy. Non-AI theorem solvers, again, don't have a spectacular record for churning out novel proofs to unsolved problems. Tools like Lean are more about mathematical rigour - a passive environment that requires a driver (a human or AI) to feed it actual strategies, lemmas, and proof steps. And no, you cannot brute force "strategy" in the vast majority of cases, which is, again, why automated theorem solvers don't have much of a track record with unsolved mathematical problems.
Let's take a random example: the disproof of the unit distance conjecture. It was solved purely by a general purpose commercial GPT model, not custom-trained to mathematics, with no external tools. Read what the various mathematicians reviewing / commenting on it have to say (sections #3 and onward). Seriously, don't skip reading them, actually read them. This was one of Erdos's favourite problems. He mentioned it commonly in his lectures. Essentially every mathematician working in complex geometry has thought about this problem. The approach that the model came up with was highly novel approach, based on CM-fields and class field towers.
I know you don't want to accept this reality, but it is the reality, so you better improve your ability to accept it,. The field of mathematics is already doing so.
Dang, link didn't post.
Interchangeable parts won't.
