But if we look at the 90’s, the lesson is not that companies wasted time on internet strategies they didn’t need. The lesson is that companies that had good internet strategies thrived (Netflix) and those that had bad internet strategies died (Blockbuster).
Agree there’s a lot of FOMO, but unlike your patsies, these companies would not be better served by staying away and ignoring the temptation.
There are examples of where LLMs are useful for information retrieval in that they can take vague queries and produce good summaries, but they're just as likely to produce reasonable-sounding nonsense that needs to be carefully verified.
I've also seen examples where LLMs can produce code that implements well-defined toy problems but when used on a real software system with millions of lines of context they do not produce code that can remain coherent with the system.
From what I've seen LLMs have yet to graduate from "impressive demo" and everyone characterizing them as being a revolution are still describing some potential future state with no real evidence that we'll get there with this technology or any time soon.
I think so much of the hype is about potential larger scale applications but the models just don’t seem reliable enough yet for that.
Bailey:" AI can replace your entire human labor (the most expensive cost of business) by scraping the content made by laborers on the internet without compensation"
Unfortunately, businesses are being sold the Bailey. And the sad part is that some companies aren't even pretending to hide behind the motte. I'm sure some, many businesses won't fall for the hype, but many others will and it will take a huge toll on the workers as a result.
Before this I was building a matching engine for online retail which used (then) state of the art multimodal models to decide which products would match your query to the lowest priced item. The dirty secret here is that we've solved search, it just costs too much to provide it for free. I think we'll soon see an online Costco show up which can provide this service to members and filter all the bullshit dropshippers.
So far this year the main thing slowing down development for us has been the SEC seizing our development boxes for insider trading once a month or so. Which given that each cost $50,000 has been something of a sore point.
What an interesting comment. So, your thesis is that a few players that come out ahead will be worth substantially more than the biggest players now and they will all be using LLMs? What's driving the consolidation? High barrier to entry for making a foundation model for finance?
so are you saying that you are okay with LLM hallucinations causing your company to make possible huge losses, even if rarely ?
I should mention that I am an LLM newbie, or rather a zerobie. all I have is a very high level sketchy overview of the field. but I am a dev with many years background in many areas, though not AI at all, except for reading a little bit now and then about it.
feel free to blast me, but preferably with data-backed statements.
But take a look at GitHub’s Copilot Workspaces for ideas of how transformative AI will be.
I don’t have all the pieces (if I did, I’d be rich, right?), but I think AI will deliver mass customization of goods, software, and content by reducing up front costs to near zero. So if I were looking for good strategies, I’d start with companies that currently spend a lot of money on software or content creation and who are investing in automating that.
This doesn't mean that the human is no longer required, but for certain tasks a company can save a lot of time/money.
So I don't know if they dream to drop a dept of 50 people and replace it with a single machine, but there are some tasks that cannot be outsourced to machines (e.g. decisions impacting the lives cannot be made by automation)
"the existence of automated decision-making, including profiling, referred to in Article 22(1) and (4) and, at least in those cases, meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing for the data subject."
So good luck 'convincing' the regulator that an LLM can replace mortgage-decisions makers (it is considered a significant activity in a person's life).
That said, I know someone who almost took a job writing the actual text of laws, and they were excited about it because, while they didn’t control the laws in general, comma placement allowed them to subtly change the law’s meaning.
I currently would‘t trust an LLM to understand subtle comma placement.
I can't see any evidences that those aren't really important or useful given your comment, do you have any data to support your argument?
AI (in the general sense) is also obviously useful, but the jury's still out on whether LLMs are the way to get there. Right now their best use-case seems to be cannibalizing the search market. It's not clear whether they can fully displace search engines though, given their stubborn propensity for confabulation.
AI will transform production , distribution, and consumption at least as much as the Internet did.
AI isn't at that level yet, and I don't know when it will be. When it does get that good, the meaning of wealth changes at least as much as it did in the Industrial Revolution when land took a second seat to capital, and I have no idea what our societies will do any more than Adam Smith could have imagined Communism.
There is a finite number of hours, dollars, and willpower within an org. Companies are pivoting into becoming AI companies without any understanding of what that means.
It's not that companies shouldn't be wondering if and how LLMs will change their industry, but there's a very real possibility that the answer for the next 20 years is "A bit, but not enough for us to need to drop everything yet. Let's keep watching and see how this pans out."
[0] http://web.archive.org/web/20001109045300/http://www.petco.c...
They failed to do either one.
People said the same things about blockchain—that it would be the foundational tech that would power a new iteration of the Internet, a web3.
Not that LLMs are in the same category, they certainly seem to have more utility in certain contexts than I ever saw in blockchain, but OP is correct that not every hyped technology turns into the next internet.
So many people have been following the hype of foolish tech trends that they can no longer differentiate them from actual ground shifting technology.
It's sad what blockchain hype has done to a supposed tech audience. To this day all nobody can describe an actual large impactuf use for blockchains other than get rich quick. Even with the tech there it does nothing for day to day life.
Duplicating portions of human intelligence has tremendous practical use in every facet of society. The tech just needs to get there.
It's pet rocks vs electricity.
That last part is the only part that skeptics are skeptical of.
GPT-4 is amazing in a lot of ways and shouldn't be discounted, but the grandest predictions of AI's impact depend on the exponential growth we saw in 2022-2023 continuing. What we've seen this year (GPT-4o, increasing cries from the established players for governments to build them a moat) suggests that that's not happening. We seem to have hit a cap on capabilities and have started just making it smaller and faster.
This is great and will be useful, but GPT-4-level tech isn't going to revolutionize everything the way that the hype suggests. We need something more.
And yet practically every big company was falling over itself to have a ‘blockchain strategy’ (remember IBM’s thing?) Sound familiar?
> Duplicating portions of human intelligence has tremendous practical use in every facet of society. The tech just needs to get there.
Trouble is, that’s a _huge_ ‘just’.
There are real use cases and value from blockchain, but it is far more niche than the crypto and NFT folks wanted to believe. IMO there was a lot of horse-cart thinking. “Blockchain is so amazing any product built on it will be successful!”
Which I guess gets back to AI. But AI is so much more general purpose than secure public ledgers. One is a screwdriver, the other is a million pound press.
The LLM stuff is an even bigger pot of gold potentially, a workable semantic embedding for semantic queries or other things is another thing that a million improvements can be shaken out of.
it’s actually bizarre to me how much people stand on the “no commercial value!!!” thing, and I have to view some of it as just being the next round of histrionics from the same people who are mad their deviantart got scraped etc.
That's a great example. You could also include systemic events like the introduction of the microcomputer, smartphone, and even "Web 2.0." AI looks like it will be a systemic change, we just don't know what that change is yet. Companies that find the winning formula will have a competitive advantage. Companies that ignore it will start a downward spiral that will be difficult to survive.