Wow. Jeff and Sanjay both departing. Truly end of a golden era.
There is an entire cohort of work-optional very senior engineers for whom one of the last reasons for hanging on was "at least Jeff and Sanjay are around".
This just shows that the "great minds" of AI in these companies are not able to come up with anything that radically differentiates their AI than the others. Wether it is gemini or openAI or grok - meh they all are similar and at this point one can interchange one with the other , excep that Google sits right at the edge with almost every browser search query hitting the google search engine AKA Gemini on the backend and one can switch easily into chat mode right from the search page. I dare say that the google CEO has done his job and set up the cash printing machine but from the AI masterminds in Google, not a groundbreaking progress has been made.
Once upon a time it would've been unthinkable for Google search to become awful and nearly worthless due, in large part, by Google's discretionary choices.
Related - interns these days don't seem to have any particular preference for using Google for finding information...
I think it's a bit inflated to label Gmail a "great tech for consumers". Maps certainly, YouTube mostly, Chrome & Android for loyalists, but Gmail hasn't been "great tech" for well over a decade.
Additionally these are all old products - even the company's more recent products such as Gemini feel stale and on unsteady ground.
Their entire business is predicated on search dominance, which is now on much shakier footing. Agreed that those comments were ridiculous pre-ChatGPT, but now they have a genuine challenger.
This take only makes sense if you don’t know what people use Google search for. If you’re looking for your local Ford dealership, or to book a Carnival cruise, or need a disability lawyer, or to refinance your credit card debt, you’re searching for an ad. You’re not using Chat-GPT for that. You’re asking Chat-GPT about a research project. It’s stealing away all the hard to monetize searches and leaving the incredibly lucrative searches.
Your narrative depressed Google’s stock price for years, and bears finally gave up since they kept coming out with huge earnings beats.
I actually use Claude for finding stuff and recommendations. like "Find me a decent shoe with blah blah conditions" this query now goes to LLM Chat instead of google search. I use google search to find the url of something that i know exists like find the website of a company or finding address of a store.
The issue is Claude is losing money serving you that, and while Google makes money serving you the same result. On top of that, you are paying Claude to get that same result.
Unless Claude adds ads, it isnt going to be sustainable for both Anthropic or you - and congrats, you've invented Google Search.
Google and ChatGPT are both running LLMs on free user queries. If Google is doing it more profitably, it’s because they have a much more mature ad business, and/or they are running a cheaper LLM. There’s no fundamental difference in the business model in that specific product line.
Regarding Claude, it’s true they must be losing money on free users since they promised they won’t put ads there.
Speculatively, I think people are overestimating the cost of inference for the consumer free tier chatbots. I suspect it’s effectively a marketing cost. The primary expenses are compute to train the next model, stock compensation, and heavy-duty enterprise inference (which pays for itself).
I agree. But then again you and I are contrbuting to that. We invest our money into S&P 500 hoping it'd grow (and that greed / need is what is contributing to companies trying to make a profit).
It isnt Netflix deciding, sure I'll make money, it is more shareholders are demanding profits .. and Netflx is forced to act.
So if Ads are a disease, and we (you + me + anyone with a stake in the US economy's growth) are the virus.
> But that’s it. I never use Google outside of that. It’s just ads, and most of the web is just ads or AI slop.
Funnily enough, their core revenue driver (Google Ads) is very broken too. I'm trying to run some ads, but for a week they haven't been showing due to some invisible combination of flags when the campaign was created. There's no way of knowing they're not showing from the dashboard, it only becomes apparent when you try and preview the ads with one of your search terms.
I know everyone is long Google but that experience seriously makes me question how valuable their ad business will stay in the future.
Someone deleted a reply to this comment “And where does ChatGPT get the data for those answers?” they wrote and I think the question is important: LLM chatbots can crawl the web just as well as Google.
Nah, just another startup that’ll get acquired or a similar fate. Building the capability is a superior option imho, if you’re at Anthropic or OpenAI scale. Cut out the middleman.
Indeed, but what is the difference between crawl data and model data but decay rate? Models are trained on previous crawl data, but if an LLM provider engages a search engine to get "live data," that data isn't live but previously crawled as well (and perhaps not yet integrated into models as crawl data).
So, why would you use Google as a tool or search target when you can, in some combination, go direct to the website (or whatever the target data endpoint is) yourself as an LLM provider to retrieve the most recent data or rely on your own "hot cache" of that data that was crawled recently but said data is not stale enough warranting a live web crawl to retrieve and present to the user or AI agent? Is this capability to perform retrieval from a data source in real time not similar to an AI agent?
Broadly speaking, I'm just spitballing on the concept of "You must use a search engine for an LLM to return 'live-ish' results" as I think we're directionally headed to where that isn't the case.
> but if an LLM provider engages a search engine to get "live data," that data isn't live but previously crawled as well
I'm not sure frontier labs do it, but imo fetching live data requires fetching both the search engine (1) and the website/page (2). The search engine gives you search results + content snippets (potentially stale), the website/page gives you the actual content fresh from the source.
The tradeoff I see here is between liveness/staleness and cost (hitting an index if of course cheaper and faster than querying live websites again).
You clearly haven't spent much time around young adults. I work with college students a fair amount and they use chatbots for 100% of their questions, including the ones you listed. And much like google got a rich data trove from user's searches, OpenAI is getting an even richer trove from chatbot chats.
I would actually recommend using a LLM over normal search for that sort of thing, because SEO has ruined those high intent phrases. The AI equivalent of SEO is also a problem there, but it's so much less prevalent.
"google it" has a stain on it. And that's not said in jest. In my social circle, it has grown a boomer-tint. Like it or not; it's just how it is.
I personally like google over asking an AI. Esp. since something like google is a substrate without which an AI would be far more prone to hallucinations.
That’s over half of their business, but they do have some diversification with YouTube, Play Store, and cloud services.
Some of their newer efforts like Waymo and AI hosting for Apple could turn into large businesses to make up for any lost search revenue.
They also have significant costs to maintain their search revenue, such as $20B a year to Apple alone to make Google the default search engine in Safari.
If search becomes less lucrative, they would presumably pay less for such deals.
So yeah, definitely a time of disruption for Google and they need to keep moving fast on many fronts, but they are still well positioned in multiple markets to be successful.
Curious to see how long that lasts - YouTube and Google Maps were fairly mainstay apps for iPhones for a while, and eventually Apple cut the Maps cord to do their own thing. I don’t know if that’s from an existential concern of “we need to eventually move Maps in-house”, but given the Google of it all I wouldn’t be surprised if Apple is already at least planning on how to do the same with AI once the bulk of the usage evens out i.e. let someone else worry about it now while also getting a read on what rolling their own would feasibly require.
A model serves a different purpose from a web crawler.
I'd prefer to be able to find source material over steering a model I have no control over while managing hallucinated outputs without the ability to fact check.
Just because it sourced some materials using RAG doesn't make its outputs valid, accurate, or factual.
Is it though? As far as I can tell they continue to maintain total domination of web search, and LLMs do not replace search engines, they work on top of them.
People have been saying that for over a decade now, and their business is still going.
So is IBM.
There was a pretty interesting article in the Wall Street Journal a few weeks back about how IBM is flying under the radar, and doing well by not taking the hype bait.
It noted that 70% of all credit card transactions on the planet go through an IBM system.
It ought to be extremely easy now to use LLMs to transpile cobol and do the necessary reverse engineering to migrate off mainframes and aix servers.
I think IBM will lose many customers.
It ought to be extremely easy now to use LLMs to transpile cobol and do the necessary reverse engineering to migrate off mainframes and aix servers. I think IBM will lose many customers.
The problem is that those COBOL systems have to be absolutely provably correct, for both financial and regulatory reasons. LLMs can't do that. They're designed to be variable.
You can't vibe code a bank transaction system. "Close enough" isn't good enough in some fields. A minor glitch in a video game may result in screen artifacts. A minor glitch in a banking system can crash the economy.
Not so much hardware these days, about half of IBM's revenue comes from software (Red Hat related stuff alone probably brings in a ton), and about 20% comes from consulting
IBM had something of a downward blip last quarter, partly because of mainframe cycles. But it's actually done generally well the past few years and pays a pretty good dividend. $10B in net income for 2025 isn't shabby.
I dunno about going strong. $1,000 in Microsoft stock in 1990 would have made you a multi-millionaire today. $1,000 in IBM stock in 1990 would make you a ten-thousandaire today.
For reference, IBM was founded in 1911. At the time "computer" was a profession, not a machine, and the majority of US households had no electricity or telephone service
There is an entire cohort of work-optional very senior engineers for whom one of the last reasons for hanging on was "at least Jeff and Sanjay are around".