What does self referential have to do with anything? These LLMs have proven they can "talk about themselves".
> an individual act or product of thinking
Emphasis on "product of thinking". Though you'll probably get all upset by the use of the word "thinking". However, people have applied the word "thinking" to computers for decades. When a computer is busy or loading, they might say "it's thinking."
> a developed intention or plan
You could certainly ask this model to write up a plan for something.
> reasoning power
Whether you like it or not, these LLMs do have some limited ability to reason. Far from human level reasoning, and they VERY frequently make mistakes/hallucinations and misunderstand, but these models have proven they can reason about things they weren't specifically trained on. For example, I remember seeing one person made up a new programming language, never existed before, and they were able to discuss it with an LLM.
No, they're not conscious. No, they don't have minds. But we need to rethink what it means for something to be "intelligent", or what it means for something to "reason", that doesn't require a conscious mind.
For the record, I find LLM technology fascinating, but I also see how flawed it is, how over hyped it is, that it is mostly a stochastic parrot, and that currently it's greatest use is as a grand scale bullshit misinformation generator. I use chatgpt sparingly, only when I'm confident it may actually give me an accurate answer. I'm not here to praise chatbots or anything, but I also don't have a blind hatred for the technology, nor do I immediately reject everything labeled as "AI".
Self driving cars aren't fully autonomous yet. They occasionally require human intervention to make decisions, which I would guess makes it difficult to steal these cars without being detected. They're constantly cloud connected and so they know where the car is at all times. I imagine these factors may deter theft of self driving cars for a while longer.
Repossessing a self driving car, on the other hand...
Fascinating stuff! It reminds me a little of chaos theory. The average person probably wouldn't expect to find structure in chaos, but that's exactly what we have.
I know the experiment you're referring to. It's been a long time since I've seen it, no idea how to find it now, but you're definitely misremembering some details. Dogs do have a sense of time, but in that experiment, it actually had to do with scent. As their owner was away, their scent would gradually dissipate throughout the day. At a certain point, the scent was weak enough that the dog knew it was about time for their owner to be home.
In the experiment, then they did everything they could to remove their owners scent from their home. The dog's owner came home at the usual time, but the dog wasn't expecting it this time because they had removed the owner's scent earlier, so the dog was clearly surprised and confused.
Dogs have a very strong sense of smell which we humans often fail to appreciate. It's not like dogs can smell their owner coming home from miles away, that's a little preposterous. But they can use their sense of smell in other ways, which are not so obvious to us, such as to maintain a sense of time.
Acquisitions/mergers are one of the great evils of capitalism which only serve to consolidate power into mega corporations. Governments are far too permissive of them. The vast majority should be flat out rejected.
The sad truth is, most people simply don't care about anything that doesn't affect them. Yes, there are people who do care, like many of us here on Hacker News, but we are very much in the minority. And even among those who do care, very few are really willing to do anything about it, far from enough to bring about any meaningful change.
Why does the title mention specifically duckdb and postgres? It sounds like it supports multiple embedded and remote databases, and I don't see anything special in the README specifically about this pairing...
Grep is nice, but I would much prefer better tools for searching through code. Something that knows how to parse multiple languages and can infer the types of things. Not to mention indexing, for large code bases, grep'ing through possibly millions of lines of code can be awfully slow.
IDEs do a decent job but are typically lacking compared to the raw power of grep.
I've noticed Windows is buggier when I disable certain features or tweak certain configurations. I'm not suggesting it's deliberate, but maybe just not well tested by Microsoft. For example, using the registry to disable copilot features, or disabling bing search in the start menu, are scenarios which are not going to be as well tested as the default configuration.
So maybe windows will still boot after "uninstalling" recall, but it could have other consequences that make the operating system less stable.
> Apple has stated that Bing does not match Google’s search result quality, and they are unwilling to compromise on user experience by offering subpar results.
I wouldn't take this statement at face value. This is most likely a BS PR excuse for Apple to maintain their current deal with Google. I wouldn't expect anything less from any large corporation looking to protect $20 billion in annual revenue.
Only if you use the decompiled code. But if one team uses decompiled code to write up a spec, then another team writes an implementation based on that spec, then that could be considered clean room design. In this case, the decompiler would merely be a tool for reverse engineering.
I think there's actually some potential here, considering LLMs are already very good at translating text between human languages. I don't think LLMs on their own would be very good, but a specially trained AI model perhaps, such as those trained for protein folding. I think what an LLM could do best is generate better decompiled code, giving better names to symbols, and generating code in a style a human is more likely to write.
I usually crap on things like chatgpt for being unreliable and hallucinating a lot. But in this particular case, decompilers already usually generate inaccurate code, and it takes a lot of work to fix the decompiled code to make it correct (I speak from experience). So introducing AI here may not be such a huge stretch. Just don't expect an AI/LLM to generate perfectly correct decompiled code and we're good (wishful thinking).
> an individual act or product of thinking
Emphasis on "product of thinking". Though you'll probably get all upset by the use of the word "thinking". However, people have applied the word "thinking" to computers for decades. When a computer is busy or loading, they might say "it's thinking."
> a developed intention or plan
You could certainly ask this model to write up a plan for something.
> reasoning power
Whether you like it or not, these LLMs do have some limited ability to reason. Far from human level reasoning, and they VERY frequently make mistakes/hallucinations and misunderstand, but these models have proven they can reason about things they weren't specifically trained on. For example, I remember seeing one person made up a new programming language, never existed before, and they were able to discuss it with an LLM.
No, they're not conscious. No, they don't have minds. But we need to rethink what it means for something to be "intelligent", or what it means for something to "reason", that doesn't require a conscious mind.
For the record, I find LLM technology fascinating, but I also see how flawed it is, how over hyped it is, that it is mostly a stochastic parrot, and that currently it's greatest use is as a grand scale bullshit misinformation generator. I use chatgpt sparingly, only when I'm confident it may actually give me an accurate answer. I'm not here to praise chatbots or anything, but I also don't have a blind hatred for the technology, nor do I immediately reject everything labeled as "AI".