I mean, obviously they're going to be related. Even in a perfectly competitive environment, if everyone's costs increase then so will the going price. The operative question is whether these increased costs will be passed onto the consumer in their entirety, and that much isn't necessarily clear. If they do pass those costs on 100%, then it's a tacit admission that they weren't pricing in a profit-maximizing way before the cost increase.
It's nice of you to clearly state what reasonable persons should believe violates the law. Alas, your contention about what reasonable people believe about the law isn't actually the law.
How can no one see what we have today? You only need six instances of an LLM running at the same time, with a system to coordinate between them, and then you have to verify the results manually anyway. Sign me up!
What does it mean to get something right? If I ask GPT-4o (or any model, really) whether it's usually hot in Topeka during the summer, it will give me the correct answer. The model may or may not understand what it means for Topeka to be hot during the summer, but it has generated text with a single reasonable interpretation which happens to include a factually correct statement. I'm comfortable saying that GPT-4o "got it right" in that case regardless of what we believe about its understanding.
Important is pronounced not with two hard t sounds, but with a glottal stop: Impor[glottal stop]ant. That's not laziness, that's my actual dialect of English spoken by actual adult people.
I wouldn't say speaking is mostly for short exchanges of information. Sometimes it's the opposite: my wife will text me for simple comments or requests, but for anything complicated she'll put the phone to her ear and call me. Or coworkers often want to set up a meeting rather than exchange a series of asynchronous emails -- iteration, brainstorming, Q&A, and the like can be more agile with voice than it can with text.
Prompt injecting their own article would indeed be an incredible show of incompetence by the New York Times. I'm confident that they're not so dumb that they put their article in their prompt and were astonished when the reply could reproduce the prompt.
Rather, the actual culprit is almost certainly overfitting. The articles in question were pasted many times on different websites, showing up in the training data repeatedly. Enough of this leads to memorization.
I'll agree that "interesting thoughts" may be up to interpretation, but imma fight you on the charisma thing. I looked up "flat affect" in the dictionary and there were no words, only a full-page headshot of Lex Fridman.
I haven't listened to Dwarkesh, but I take the complaint to mean that he doesn't probe his guests in interesting ways, not so much that he doesn't criticize his guests. If you aren't guiding the conversation into interesting corners then that seems like a problem.
I don't know Dwarkesh but I despise Lex Fridman. I don't know how a man that lacks the barest modicum of charisma has propelled himself to helming a high-profile, successful podcast. It's not like he tends to express interesting or original thoughts to make up for his paucity of presence. It's bizarre.
Maybe I'll check out Dwarkesh, but even seeing him mentioned him in the same breath as Fridman gives me pause ...
Well, they're not AI companies, necessarily, or at least not only AI companies, but the big hardware firms tend to have engineers at the helm. That includes Nvidia, AMD, and Intel. (Counterpoint: Apple)
Or how it took Google ages to address the scam "You Win!" YouTube comments disguised as if coming from the videos' posters. How hard could that be, exactly?
It depends on your expectations. I'm used to the idea that I have to drive everywhere and it never occurs to me that I would prefer walking or bicycling. In my current suburban home I'm a three minute drive from a relatively big supermarket, and an eight minute drive to a somewhat wider array of shopping. I rarely feel like I'm too far removed from any particular item or service that I need.
That said, I hate driving to work; it's a half hour drive to and from downtown Cincinnati if I keep crazy hours (I work 6-2:30 just to avoid any hint of stopped traffic, otherwise my daily total commute time shoots to 2-2.5h). I envy those of my coworkers -- generally the younger ones -- who live two minutes by foot from the building, but my dogs would have to give up their big backyard, so ... not happening.
I think you have the mistaken impression that I was arguing with you (certainly my comment makes it clear that I don't feel that LLMs are a panacea). I merely thought that you might be curious how GPT-4 would respond.
> My guess is that this was generated using GPT4?
This is a good guess, since I stated outright that I used GPT-4, and then mentioned GPT-4 later on in the comment.
You can't not include native libraries, at least if you want your benchmark to be realistic. Almost every Python library where performance matters is written (at least partially) in a compiled language.
I'm a Python-slinging data scientist so C++ isn't my jam (to say the least), but I changed the prompt to the following and asked it to GPT-4:
> Write me an algorithm in C++ which finds the begin and end iterator of a sequence where leading and trailing whitespace is stripped. Please write secure code that handles any possible edge cases.
I'm not sure what other edge cases there might be, however. This only covers one of them.
In general, I've found LLMs to be marginally helpful. Like, I can't ever remember how to get matplotlib to give me the plot I want, and 9 times out of 10 GPT-4 easily gives me the code I want. Anything even slightly off the beaten path, though, and it quickly becomes absolutely useless.
Python on 2024 hardware vs C++ on 2004 hardware ... I don't think it's obvious that C++ always wins here, though it would depend on the use case, how much of the Python is underpinned by native libraries, and the specific hardware in question.
I'm a data scientist and I agree that work meant to last should be in a source-controlled project coded via a text editor or IDE. But sometimes it's extremely useful to get -- and iterate on -- immediate results. There's no good way to do that without either notebooks or at least a REPL.
> The exact definition of a word has nothing to do with it.
It has something to do with it. There will be scenarios where the definition of "copyrighted material" does matter, even if they come up relatively infrequently for Databricks' intended use cases. If I ask DBRX directly whether it was trained on copyrighted material, it's quite likely to (falsely) tell me that it was not. This seems suboptimal to me (though perhaps they A/B tested different prompts and this was indeed the best).
Are you alleging that Nancy Pelosi invested in Databricks, a private company without a fluctuating share price, because she learned that they would soon release a small, fairly middling LLM that probably won't move the needle in any meaningful way?
Agreed. I only played Cyberpunk on the Deck for a few hours, but I was impressed how well it ran. 40fps worked fine for long stretches, and the text size wasn't an issue in the slightest.
With the OLED model the lowest you'll get is maybe 1.5h on heavy games. That seems .. okay to me. It's not super great, but it's more than enough to play a more demanding game during a break or something.
I played nontrivial portions of the Dead Space and Resident Evil IV remakes on the Deck over the past year and I didn't mind it, once I got used to the low frame rates, anyway. BG3 was similarly fine until act 3, though it admittedly falls apart then.