Google is winning on every AI front

As an Ex-OpenAI employee I agree with this. Most of the top ML talent at OpenAI already have left to either do their own thing or join other startups. A few are still there but I doubt if they'll be around in a year. The main successful product from OpenAI is the ChatGPT app, but there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free and ads would become the main option to make money out of chatbots. The whole time that I was at OpenAI until now GOOG has been the only individual stock that I've been holding. Despite the threat to their search business I think they'll bounce back because they have a lot of cards to play. OpenAI is an annoyance for Google, because they are willing to burn money to get users. Google can't as easily burn money, since they already have billions of users, but also they are a public company and have to answer to investors. But I doubt if OpenAI investors would sign up to give more money to be burned in a year. Google just needs to ease off on the red tape and make their innovations available to users as fast as they can. (And don't let me get started with Sam Altman.)

> I think soon people expect this service to be provided for free and ads would become the main option to make money out of chatbots.

I also think adtech corrupting AI as well is inevitable, but I dread for that future. Chatbots are much more personal than websites, and users are expected to give them deeply personal data. Their output containing ads would be far more effective at psychological manipulation than traditional ads are. It would also be far more profitable, so I'm sure that marketers are salivating at this opportunity, and adtech masterminds are hard at work to make this a reality already.

The repercussions of this will be much greater than we can imagine. I would love to be wrong, so I'm open to being convinced otherwise.

You're assuming ads would be subtly worked into the answers. There's no reason it has to be done that way. You can also have a classic text ads system that's matching on the contents of the discussions, or which triggers only for clearly commercial queries "chatgpt I want to eat out tonight, recommend me somewhere", and which emits visually distinct ads. Most advertisers wouldn't want LLMs to make fake recommendations anyway, they want to control the way their ad appears and what ad copy is used.

There's lots of ways to do that which don't hurt trust. Over time Google lost it as they got addicted to reporting massively quarterly growth, but for many years they were able to mix in ads with search results without people being unhappy or distrusting organic results, and also having a very successful business model. Even today Google's biggest trust problem by far is with conservatives, and that's due to explicit censorship of the right: corruption for ideological not commercial reasons.

So there seems to be a lot of ways in which LLM companies can do this.

Main issue is that building an ad network is really hard. You need lots of inventory to make it worthwhile.

> You're assuming ads would be subtly worked into the answers. There's no reason it has to be done that way.

I highly doubt advertisers will settle for a solution that's less profitable. That would be like settling for plain-text ads without profiling data and microtargeting. Google tried that in the "don't be evil" days, and look how that turned out.

Besides, astroturfing and influencer-driven campaigns are very popular. The modern playbook is to make advertising blend in with the content as much as possible, so that the victim is not aware that they're being advertised to. This is what the majority of ads on social media look like. The natural extension of this is for ads to be subtly embedded in chatbot output.

"You don't sound well, Dave. How about a nice slice of Astroturf pizza to cheer you up?"

And political propaganda can be even more subtle than that...

There's no reason why having an LLM be sly or misleading would be more profitable. Too many people try to make advertising a moral issue when it's not, and it sounds like you're falling into that trap.

An ideal answer for a query like "Where can I take my wife for a date this weekend?" would be something like,

> Here are some events I found ... <ad unit one> <ad unit two> <ad unit three>. Based on our prior conversations, sounds like the third might be the best fit, want me to book it for you?

To get that you need ads. If you ask ChatGPT such a question currently it'll either search the web (and thus see ads anyway) or it'll give boring generic text that's found in its training set. You really want to see images, prices, locations and so on for such a query not, "maybe she'd like the movies". And there are no good ranking signals for many kinds of commercial query: LLM training will give a long-since stale or hallucinated answer at worst, some semi-random answer at best, and algorithms like PageRank hardly work for most commercial queries.

HN has always been very naive about this topic but briefly: people like advertising done well and targeted ads are even better. One of Google's longest running experiments was a holdback where some small percentage of users never saw ads, and they used Google less than users who did. The ad-free search gave worse answers overall.

Wouldn't fewer searches indicate better answers? A search engine is productivity software. Productivity software is worse when it requires more user interaction.

Also you don't need ads to answer what to do, just knowledge of the events. Even a poor ranking algorithm is better than "how much someone paid for me to say this" as the ranking. That is possibly the very worst possible ranking.

Google knows how to avoid mistakes like not bucketing by session. Holdback users just did fewer unique search sessions overall, because whilst for most people Google was a great way to book vacations, hotel stays, to find games to buy and so on, for holdback users it was limited to informational research only. That's an important use case but probably over-represented amongst HN users, some kinds of people use search engines primarily to buy things.

How much a click is worth to a business is a very good ranking signal, albeit not the only one. Google ranks by bid but also quality score and many other factors. If users click your ad, then return to the results page and click something else, that hurts the advertiser's quality score and the amount of money needed to continue ranking goes up so such ads are pushed out of the results or only show up when there's less competition.

The reason auction bids work well as a ranking signal is that it rewards accurate targeting. The ad click is worth more to companies that are only showing ads to people who are likely to buy something. Spamming irrelevant ads is very bad for users. You can try to attack that problem indirectly by having some convoluted process to decide if an ad is relevant to a query, but the ground truth is "did the click lead to a purchase?" and the best way to assess that is to just let advertisers bid against each other in an auction. It also interacts well with general supply management - if users are being annoyed by too many irrelevant ads, you can just restrict slot supply and due to the auction the least relevant ads are automatically pushed out by market economics.