Thanks for yet another great piece, Alberto! As someone working with SEO and content, I've been wondering how ongoing AI trends will affect the field, especially if we get to a point where search engines can reliably consolidate and deliver answers across multiple sources.
What will that mean for the entire "thought leadership" approach where companies try to become knowledge hubs for topics and keywords related to their products and services. Today, the reward is "free" organic traffic...but what if people no longer have the incentive to click through to the company site because LM+SE combo becomes much better at delivering thorough, accurate, and neutral answers?
Very interesting analysis. The problem that I keep coming back to is that search ads constitute something like 80% of Google's revenue (and a smaller, albeit still large, percentage of Alphabet's as a whole). This means that MSFT, if it wanted to, would only have to bleed off a small amount of Google's search revenue to seriously harm Google's ability to generate revenue and so finance its operations. On the other hand, Google (and its parent, Alphabet) has a strong balance sheet, so it could finance a war of attrition with MSFT for a while. But its stock would tank, and so its ability to recruit and retain employees would decline. MSFT, on the other hand, has a more diversified revenue stream, and if it decides that it's willing to finance losses on Bing for a while, it won't be as harmed by that decision. Of course, I am looking at this through a financial, not technological, lens. But I very much see this as an Innovator's Dilemma kind of problem, as articulated by Clayton Christensen in his book of the same name.
I agree with your points about how the search space might play out and the risks to each side of this equation - Microsoft vs. Google
One question that's been troubling me though - if we look outside of the Search market. Say for any other product - do you think Google and Microsoft (+Open AI) will be the only two major owners of LLMs?
How easy or difficult is it for any other player (say Amazon) to build an LLM that can compete with ChatGPT and add it to their own products? (Say to power the search experience, etc.)?
A thought: If virtual assistants like Siri finally start to work as intended in the near future on the back of LMs, couldn't search quickly be performed by them exclusively - without any human involvent? Synthesis could be done equally well by a system the user has paid for directly to provide other high value services as well.
Especially if concerns about privacy and trust/alignment pervail, individually fine tuned assistants might become the norm.
This could keep the need for a search or at least a catalogization supplier more or less intact, but would bring upheaval to the "free", ad financed business model as well.
The companies best able to provide such assistants might be those already monetizing through hardware sales or software subscriptions, like Apple or (surprise) Microsoft.
Why can't Google offer two search engines, one optimized for authoritative resources and another LM based one ... then users can make an informed choice ... I personally can see myself using both depending on the question I have.
Great piece Alberto! I liked particularly the way you describe the incentives and dilemmas of the tech giants.
One detail I'd add is to consider Google's Knowledge Graph (KG). As you know, the KG is instrumental to getting direct answers in Google search (the snippets on top of the search results in some searches). For instance, if you search for "who was Nero's mother?" you get, additionally to a ton of links, the answer itself: "Agrippina the Younger." This is done using the KG and some undisclosed algorithms.
Now, I think the combination of LLM with search will need to use the KM, both because it's the current question answering used by Google and also because it's factually guaranteed. It seems to me that there should be a way of using LLMs to develop more elaborated answers compatible with the KG. The use of the KG will also finish the "hallucinations" so common in Generative AI systems.
The deep issue is the impact of LLMs on the search business model. Today's Google Search Business litters the results page with garbage, irrelevant and misleading content (and some potentially valuable pointers) scattered about. LLMs force a rethinking of how better to inform USERS. Look at YOU.COM for examples. USERS don't need dozens of pages of crap. They will flock to generative results that are enriched by older search tools. That will kill the current "litter the results with crap" model that funds Google. Google won't die, of course, but this is going to force EVERYONE to pay more attention to user needs FIRST.
Thanks for yet another great piece, Alberto! As someone working with SEO and content, I've been wondering how ongoing AI trends will affect the field, especially if we get to a point where search engines can reliably consolidate and deliver answers across multiple sources.
What will that mean for the entire "thought leadership" approach where companies try to become knowledge hubs for topics and keywords related to their products and services. Today, the reward is "free" organic traffic...but what if people no longer have the incentive to click through to the company site because LM+SE combo becomes much better at delivering thorough, accurate, and neutral answers?
I'm very curious to see how this plays out.
Very interesting analysis. The problem that I keep coming back to is that search ads constitute something like 80% of Google's revenue (and a smaller, albeit still large, percentage of Alphabet's as a whole). This means that MSFT, if it wanted to, would only have to bleed off a small amount of Google's search revenue to seriously harm Google's ability to generate revenue and so finance its operations. On the other hand, Google (and its parent, Alphabet) has a strong balance sheet, so it could finance a war of attrition with MSFT for a while. But its stock would tank, and so its ability to recruit and retain employees would decline. MSFT, on the other hand, has a more diversified revenue stream, and if it decides that it's willing to finance losses on Bing for a while, it won't be as harmed by that decision. Of course, I am looking at this through a financial, not technological, lens. But I very much see this as an Innovator's Dilemma kind of problem, as articulated by Clayton Christensen in his book of the same name.
Thank you for this insightful piece Alberto!
I agree with your points about how the search space might play out and the risks to each side of this equation - Microsoft vs. Google
One question that's been troubling me though - if we look outside of the Search market. Say for any other product - do you think Google and Microsoft (+Open AI) will be the only two major owners of LLMs?
How easy or difficult is it for any other player (say Amazon) to build an LLM that can compete with ChatGPT and add it to their own products? (Say to power the search experience, etc.)?
Would appreciate your thoughts!
Amazing article, thanks a lot!
A thought: If virtual assistants like Siri finally start to work as intended in the near future on the back of LMs, couldn't search quickly be performed by them exclusively - without any human involvent? Synthesis could be done equally well by a system the user has paid for directly to provide other high value services as well.
Especially if concerns about privacy and trust/alignment pervail, individually fine tuned assistants might become the norm.
This could keep the need for a search or at least a catalogization supplier more or less intact, but would bring upheaval to the "free", ad financed business model as well.
The companies best able to provide such assistants might be those already monetizing through hardware sales or software subscriptions, like Apple or (surprise) Microsoft.
Why can't Google offer two search engines, one optimized for authoritative resources and another LM based one ... then users can make an informed choice ... I personally can see myself using both depending on the question I have.
Great piece Alberto! I liked particularly the way you describe the incentives and dilemmas of the tech giants.
One detail I'd add is to consider Google's Knowledge Graph (KG). As you know, the KG is instrumental to getting direct answers in Google search (the snippets on top of the search results in some searches). For instance, if you search for "who was Nero's mother?" you get, additionally to a ton of links, the answer itself: "Agrippina the Younger." This is done using the KG and some undisclosed algorithms.
Now, I think the combination of LLM with search will need to use the KM, both because it's the current question answering used by Google and also because it's factually guaranteed. It seems to me that there should be a way of using LLMs to develop more elaborated answers compatible with the KG. The use of the KG will also finish the "hallucinations" so common in Generative AI systems.
What do you think?
Great read! Esp the tweet by François Collet is very memorable/decisive. I wrote a related piece on knowledge retrieval (including Deepmind's RETRO) btw: https://scalingknowledge.substack.com/p/knowledge-retrieval-transformers
The deep issue is the impact of LLMs on the search business model. Today's Google Search Business litters the results page with garbage, irrelevant and misleading content (and some potentially valuable pointers) scattered about. LLMs force a rethinking of how better to inform USERS. Look at YOU.COM for examples. USERS don't need dozens of pages of crap. They will flock to generative results that are enriched by older search tools. That will kill the current "litter the results with crap" model that funds Google. Google won't die, of course, but this is going to force EVERYONE to pay more attention to user needs FIRST.