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.”)
On Sunday The New York Times reported that Google is furiously working to incorporate conversational AI into its core search products – not exactly news, but there was a larger takeaway: Google has got to get some killer AI products out the door, and fast, or it risks losing its core users for good. And if my own family is any indication, the company is already imperiled. More on that below, but first, a bit more on the Times piece.
The article led with big news: Samsung may decamp from Google and partner with Microsoft’s Bing instead. This would be a major blow both financially as well as optically – Samsung’s commitment to Android is a key reason Google’s mobile platform towers over Apple’s iOS in terms of worldwide market share.
Would you pay $200 a month for generative AI services? It may sound crazy, but I think it’s entirely possible, particularly if the tech and media industries don’t repeat the mistakes of the past.
Think back to the last time you decided to fork over a substantial monthly fee for a new technology or media service. For most of us, it was probably the recent shift to streaming services. If you use more than a few, that bill can add up to nearly $100 a month. But streaming is a (not particularly good) replacement for cable – it’s not a technological marvel that changes how we live, work, and play. To find a new service that rises to that level, we have to go back to the introduction of the smart phone – a device we were willing to spend hundreds of dollars to obtain and an average of $127 a month to keep.
Of all the structural problems “Web 2” has brought into the world – and there are too many to list – one of the most vexing is what I call the “meta-services” problem. Today’s commercial internet encourages businesses and services to create silos of our data – silos that can not and will not connect to each other. Because of business model constraints (most big services are “free,” revenues come from advertising and/or data sales), it’s next to impossible for anyone – from an individual consumer to a Fortune 50 enterprise – to create lasting value across all those silos. Want to compare your Amazon purchase history to prices for the same goods at Walmart? Good luck! Want to compare the marketing performance of your million-dollar campaigns between Facebook and Netflix? LOL!
For the past 15 or so years, I’ve written about a new class of “meta-services” that would work across individual sites, apps, and platforms. Working on our behalf, these meta-services would collect, condition, protect, and share our information, allowing a new ecosystem of services and value to be unlocked. OpenAI’s recent announcement of plugins, along with their already robust APIs, has brought the meta-service fantasy tantalizingly close to reality. But it’s more likely that, just as with the “open internet,” the fantasy will remain just that. Internet business models have been built to collect short term rent. Truly open systems rarely win over time – regardless of whether the company uses the word “open” in its name.
Once again, Google and Microsoft are battling for the AI spotlight – this time with news around their offerings for developers and the enterprise*. These are decidedly less sexy markets – you won’t find breathless reports about the death of Google search this time around – but they’re far more consequential, given their potential reach across the entire technology ecosystem.
Highlighting that consequence is Casey Newton’s recent scoop detailing layoffs impacting Microsoft’s “entire ethics and society team within the artificial intelligence organization.” This team was responsible for thinking independently about how Microsoft’s use of AI might create unintended negative consequences in the world. While the company continues to tout its investment in responsible AI** (as does every firm looking to make a profit in the field), Casey’s reporting raises serious questions, particularly given the Valley’s history of ignoring inconvenient truths.
I’ve written a long-ish post attempting to answer that question over at P&G’s Signal360 publication, please head there (and sign up for their newsletter!) if you’d like to read the whole thing. Below is a teaser for those of you who aren’t sure you want to click the link (so few of us do these days!).
Last week I asked if Google was f*cked, and since then quite a few of you have reached out asking what I think the company could do to … un-f*ck itself. “Easy enough to declare the company is too big, too stuck in the mud, too cautious, too dependent on its cash cow,” you told me. “Much harder to advise them on what to do about it.” One of you just sighed to me on the phone, then said “it’s always been this way. No large company can escape the innovator’s dilemma.”
Well, maybe so, but wouldn’t it be fun to try? I’ve been in touch with various Googlers over the past few weeks, as I’m still working on a “What should the ads look like” piece around ChatGPT and AI-driven search (promise, it’ll be done soon). While folks at Google are polite and engaged, they’ve also given me the extended play version of “No comment” – stating it’s too early to declare the business model for conversational search. In short, they’re waiting for the market to reveal itself a bit more before making any public statements or declaring themselves all in on tech’s next big trend.
Do generative AI innovations like OpenAI’s ChatGPT and Google’s LaMDA represent a new and foundational technology platform like Microsoft Windows, Apple iOS or the Internet? Or are they just fun and/or useful new products that millions will eventually use, like Google Docs or Instagram? I think the answer can and should be “both” – but to get there, the Valley is going to have to forego the walled garden destination model it’s employed these past 15 or so years.
The question of OpenAI’s ultimate business model has dominated nearly every conversation I’ve had this week, whether it’s with reporters from the Economist and the Journal, senior executives at large-scale public companies, or CEOs of ad-tech and data startups. Everyone wants to know: What’s the impact of generative AI on the technology industry? Will OpenAI be the next Google or Apple? Who wins, and who will lose?
What’s the hardest thing you could do as a tech-driven startup? I’ve been asked that question a few times over the years, and my immediate answer is always the same: Trying to beat Google in search. A few have tried – DuckDuckGo has built itself a sizable niche business, and there’s always Bing, thought it’s stuck at less than ten percent of Google’s market (and Microsoft isn’t exactly a startup.) But it’s damn hard to find venture money for a company whose mission is to disrupt the multi-hundred billion dollar search market – and for good reason. Google is just too damn well positioned, and if Microsoft can’t unseat them, how the hell could a small team of upstarts?
I’ve used the image above for many years, mainly because I love how surprised the guy looks as he gazes into the crystal ball. Or maybe he’s just sat on something unpleasant. In any case, it pretty much sums up my approach to this, my 20th edition of annual predictions. I sit down, I might have an adult beverage on hand, and I just write until I feel like I’m done.
While reviewing my ’22 predictions (I did pretty well!) I promised to do something new: One post per predictions, ten posts total. But as I began that promised work, I realized it would test the limits of even my most dedicated readers (I see you, kids). So instead I wrote three long form posts, each with three or four predictions apiece. The first focused on AI, the second on advertising, and the third on markets, with a bonus call related to the ’24 election. Having now written all of them, I’m going to summarize them briefly in this “master post.” Grab your own favorite beverage, have a wonderful New Year, and read on!