Most of the time (with many notable exceptions), Hacker news comments are interesting and insightful, clearly written by intelligent and thinking people. However, in a number of AI threads, it seems like so many commenters are wearing the hype goggles when it comes to this technology.
Large language models have their uses, but calling them AI, or thinking of them as AGI, seems like a mistake. I'm no expert, but insofar as I can tell, these things are just complex stochastic parrots; pattern matching algorithms at a massive scale. They really don't seem that useful outside of more narrow use cases, like language translation and other forms of data analytics.
Just playing around with GPT/Bing chat for a while makes this obvious. The LLMs can't reason and have no actual awareness of the information they are regurgitating. A moments consideration of the output from these things shows them to be vapid and useless; a glorified parlor trick for the VC-funded tech industry to build hype around and make money. It's the next block chain/ crypto / NFT.
There are great uses for block chain tech, same with machine learning / AI. But the scope of the claims made about these technologies in their hype cycles is just insane. Crypto is not going to replace fiat currency anytime soon. NFTs are stupid. LLMs are useless stochastic parrots. Maybe people are just wising up to that fact, now. Good on them.
As a preemptive rebuttal:
I don't think LLMs are useful for coding either. If you want lots of sloppy, poorly written code, sure they're useful. But to write good software, you have to think carefully about what you're doing and have a thorough mental model of what's going on. Relying on AI to generate that code prevents that from happening from the outset.
However, in a number of AI threads, it seems like so many commenters are wearing the hype goggles when it comes to this technology.
You should have seen the crypto threads about five years ago.
People — especially people on HN — want to believe that technology can solve humanity's problems. It can't at this time. And it won't in our lifetimes.
Really good info, thanks. I'll add the dividend cut metric to my list. Not sure what you mean by yield vs history. I do have a chart comparing the yield to the stock price over time, but the window is only 4 years back. I'll try and expand that window, too.
I may not be the best source on yield vs history, cause I learned about it by looking at stocks I bought that did not pan out. But yeah basically for a company with stable, decade(s) long payout, if yield looks low vs the long-term, the price may be too high. Of course, it can depend on future prospects, market conditions, etc. But in general all other things being equal it seems to hold for boring stocks.
Appreciate the feedback grounded in personal experience, thanks!
I was just looking into Adsense, and it does seem like a poor option for the reasons you mentioned: too much effort for too little return, not to mention the ugliness.
I'm glad you see some value in this! Based on the feedback I'm getting here, I have plans for some short-term wins that I can execute within the week, and beyond. I'm hopeful they can bare some fruit, or just add more value.
For now in the middle term, a few carefully positioned affiliate marketing links may be the way.
Awesome, thanks for the feedback!
That filter seems like a good idea--I'll work on implementing it. An expansion at larger view sizes should be doable!
Good points, especially for value investing. It also seems likely that this logic holds whenever analyzing a traditional company. Once again, I'd ask whether the same logic holds for the ETFs and leveraged funds that encompass most of the stocks on this site?
There may be other reasons not to invest in such a stock, but I seem to keep seeing value investors trying to compare apples to oranges.
Looking at your point regarding that earning call, it seems you're looking at this in light of a more traditional company and not an ETF/REIT/Leveraged fund. Forgive me if I'm wrong in that assumption. For conventional value investing, this is probably true, I'm no expert.
It does seem to me that there is room for a stock like this in one's portfolio though, as part of a larger strategy. Maybe a high yield leveraged fund is only a small portion of your stock, or you need to convert some of your assets to income for a few years.
I think the parent comment was talking about the companies. Instead of re-investing profits into the company -- long-term thinking -- they just pass them over to the investors -- short-term wins.
Large language models have their uses, but calling them AI, or thinking of them as AGI, seems like a mistake. I'm no expert, but insofar as I can tell, these things are just complex stochastic parrots; pattern matching algorithms at a massive scale. They really don't seem that useful outside of more narrow use cases, like language translation and other forms of data analytics.
Just playing around with GPT/Bing chat for a while makes this obvious. The LLMs can't reason and have no actual awareness of the information they are regurgitating. A moments consideration of the output from these things shows them to be vapid and useless; a glorified parlor trick for the VC-funded tech industry to build hype around and make money. It's the next block chain/ crypto / NFT.
There are great uses for block chain tech, same with machine learning / AI. But the scope of the claims made about these technologies in their hype cycles is just insane. Crypto is not going to replace fiat currency anytime soon. NFTs are stupid. LLMs are useless stochastic parrots. Maybe people are just wising up to that fact, now. Good on them.
As a preemptive rebuttal: I don't think LLMs are useful for coding either. If you want lots of sloppy, poorly written code, sure they're useful. But to write good software, you have to think carefully about what you're doing and have a thorough mental model of what's going on. Relying on AI to generate that code prevents that from happening from the outset.