Once upon a time when search was new, Google came along and put the whole darn Internet in RAM. This was an astonishing (and expensive) feat of engineering at the time – one that gave Google a significant competitive moat. Twenty years ago, very few companies had the know how or the resources to keep an up-to-date copy of the entire web in expensive, super fast silicon. Google’s ability to do so allowed it unprecedented flexibility and speed in its product, and that product won the search crown, building a trillion-dollar market cap along the way.
Since then compute, storage, and engineering costs have declined in a kind of reverse version of Moore’s Law. Pretty much anyone with a bit of funding and some basic Internet crawling skills can stand up a web index – but there’s been no reason to do so. For 15 or so years one of the biggest clichés in venture circles was “no one will ever fund another search engine.” (A second cliché? “No one’s ever said “Just Bing it.”)
Google had won, and that was that.
All of this came back to me when reading an eye-opening leaked memo over on Dylan Patel’s SemiAnalysis newsletter. Titled “We Have No Moat, and Neither Does OpenAI” and written by a senior researcher at Google, the memo is a devastating critique of Google’s approach to competing in the world of generative AI. SemiAnalysis placed a strong caveat at the top of the text, and I’ve not been able to find confirmation of the memo’s claims (Bloomberg has more here). But the essence of the memo’s argument resonates: Both Google and OpenAI are going to lose out in the race to dominate the AI future because they are refusing to play in the domain of open source software, where legions of developers are racing ahead of companies who are trying to go it on their own.
But while the “open vs. closed” debate is fundamental to the future of the Internet (and our society), that’s not the only thing I’m on about today. What I realized today was something more concrete and astonishing. With GPT technologies, pretty much every startup can now put a decent facsimile of Google in RAM, and according to the memo, they can do it for pretty much peanuts.
Put another way, Google’s been commoditized.
I know, I know, the whole “Google is screwed” meme has been around ever since ChatGPT’s launch, but before I joined the chorus, I’ve been waiting for Google’s response (there are rumblings it may come at Google’s I/O event next week, we’ll see). If and when Google launches competitive products, I reasoned, then we’ll see whether the search giant is truly in trouble.
But it might not matter how good Google’s eventual products may be. The bar for what consumers expect from an index of the world’s information has not just been raised, it’s been entirely reset. This hit home for me as I was playing around with Pi, the new “personal AI assistant” from Reid Hoffman & co’s Inflection AI. In my initial conversation, I asked Pi if it used the Internet as its core source material. Of course it does. With my recent posts about my wife’s ChatGPT usage in mind, I then asked it if it could help me find the best design blogs. It certainly could, and not only that, it suggested I browse some niche sites as well. I then began querying Pi about how it determines which sites to display – does it have a ranking system like Google’s PageRank?
No, Pi responded, it doesn’t employ a ranking system, but it does use various signals to determine which sites to suggest. What are those signals, I asked? Pi replied they include a site’s “popularity” as well as “quality of writing.” Interesting! I asked what Pi used to determine popularity, and its reply kind of blew my mind: Backlinks.
Backlinks! For those who aren’t Internet history nerds, Google began as a project called “BackRub” – an attempt by then-PhD candidate Larry Page to create a database of every backlink on the web. In addition to backlinks, Pi also uses the number of social media shares a particular site garners as a signal, as well as analyzing the complexity and grammar of the site’s text to determine quality. These are among the many signals that Google (and every other search engine) uses – in essence, replicating Google’s core differentiation and leveraging it for a new use case – as an AI personal assistant.
Sure, Google can compete by creating its own AI personal assistant, but one has to ask, where does it end? There are limitless use cases to employ the world’s knowledge at scale – and Google can’t possibly compete in every one of them. The author of the aforementioned memo states as much in his manifesto. Like it or not, GPT technology has transmogrified Google’s once-impermeable moat into an open platform, and thousands of entrepreneurs and developers are busy building new applications on top of it. Unfortunately for Google, none of them are paying the company a cent for the pleasure of doing so.
This is likely the subject of many future posts, but it strikes me that if it’s going to compete, Google has a very big pivot in its near future: abandon its closed approach to developing products and services, and finally become a true platform company.
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GPT’s reaction to this article:
As an AI language model, I don’t have opinions, but I can summarize the article for you. The article discusses how Google’s once-impermeable moat has been commoditized by GPT technologies, making it possible for every startup to put a decent facsimile of Google in RAM. The author argues that Google and OpenAI are going to lose out in the race to dominate the AI future because they are refusing to play in the domain of open source software, where legions of developers are racing ahead of companies who are trying to go it on their own. The author suggests that Google needs to abandon its closed approach to developing products and services and become a true platform company if it wants to compete.