I attended a presentation in the early 2000s where an IBM executive was trying to explain to us how big software-as-a-service was going to be and how IBM was investing hundreds of millions into it. IBM was right, but it just wasn't IBM's software that people ended up buying.
Google falls somewhere in the middle. They have great R&D but just can’t make products. It took OpenAI to show them how to do it, and the managed to catch up fast.
Is this just something you repeat without thinking? It seems to be a popular sentiment here on Hacker News, but really makes no sense if you think about it.
Products: Search, Gmail, Chrome, Android, Maps, Youtube, Workspace (Drive, Docs, Sheets, Calendar, Meet), Photos, Play Store, Chromebook, Pixel ... not to mention Cloud, Waymo, and Gemini ...
So many widely adopted products. How many other companies can say the same?
What am I missing?
It took OpenAI for Google to finally understand make a product out of their years if not decades of AI research.
YouTube and Maps are both acquisitions indeed.
A phrasing I've heard is "Google regularly kills billion-dollar businesses because that doesn't move the needle compared to an extra 1% of revenue on ads."
And, to be super pedantic about it, Android and YouTube were not products that Google built but acquired.
But I reckon part of the sentiment stems from many of the more famous Google products being acquisitions orignally (Android, YouTube, Maps, Docs, Sheets, DeepMind) or originally built by individual contributors internally (Gmail).
Then here were also several times where Google came out with multiple different products with similar names replacing each other. Like when they had I don't know how many variants of chat and meeting apps replacing each other in a short period of time. And now the same thing with all the different confusing Gemini offerings. Which leads to the impression that they don't know what they are doing product wise.
Look at Microsoft - Powerpoint was an acquisition. They bought most of the team that designed and built Windows NT from DEC. Frontpage was an acquisition, Azure came after AWS and was led by a series of people brought in in acquisitions (Ray Ozzie, Mark Russinovich, etc.). It's how things happen when you're that big.
That's not like Google buying Android when they already had a functioning (albeit not at all polished) smartphone OS.
Many of those are acquisitions. In-house developed ones tend to be the most marginal on that list, and many of their most visibly high-effort in-house products have been dramatic failures (e.g. Google+, Glass, Fiber).
Honestly, I still don't really know how Google managed to mess that up.
Even with gemini in lead, its only till they extinguish or make chatgpt unviable for openai as business. OpenAI may loose the talent war and cease to be leader in this domain against google (or Facebook) , but in longer term their incentive to break fresh aligns with average user requirements . With Chinese AI just behind, may be google/microsoft have no choice either
Well, I mean, WebSphere was pretty big at the time; and IBM VisualAge became Eclipse.
And I know there were a bunch of LoB applications built on AS/400 (now called "System i") that had "real" web-frontends (though in practice, they were only suitable for LAN and VPN access, not public web; and were absolutely horrible on the inside, e.g. Progress OpenEdge).
...had IBM kept up the pretense of investment, and offered a real migration path to Java instead of a rewrite, then perhaps today might be slightly different?
And while I’m writing this I just finished up today’s advent of code using vim instead of a “real IDE” haha
Once we have sufficient VRAM and speed, we're going to fly - not run - to a whole new class of applications. Things that just don't work in the cloud for one reason or another.
- The true power of a "World Model" like Genie 2 will never happen with latency. That will have to run locally. We want local AI game engines [1] we can step into like holodecks.
- Nobody is going to want to call OpenAI or Grok with personal matters. People want a local AI "girlfriend" or whatever. That shit needs to stay private for people.
- Image and video gen is a never ending cycle of "Our Content Filters Have Detected Harmful Prompts". You can't make totally safe for work images or videos of kids, men in atypical roles (men with their children = abuse!), women in atypical roles (woman in danger = abuse!), LGBT relationships, world leaders, celebs, popular IPs, etc. Everyone I interact with constantly brings these issues up.
- Robots will have to be local. You can't solve 6+DOF, dance routines, cutting food, etc. with 500ms latency.
- The RIAA is going door to door taking down each major music AI service. Suno just recently had two Billboard chart-topping songs? Congrats - now the RIAA lawyers have sued them and reached a settlement. Suno now won't let you download the music you create. They're going to remove the existing models and replace them with "officially licensed" musicians like Katy Perry® and Travis Scott™. You won't retain rights to anything you mix. This totally sucks and music models need to be 100% local and outside of their reach.
[1] Also, you have to see this mind-blowing interactive browser demo from 2022. It still makes my jaw drop: https://madebyoll.in/posts/game_emulation_via_dnn/
Hopefully it's just network propagation that creates that latency, otherwise local models will never beat the fanout in a massive datacenter.
What hardware did the users of this service use to connect to the service?
But anyways, my question to you is, was there any software that IBM charged money for as opposed to providing the software at no additional cost with the purchase or rental of a computer?
I do know that no one sold software software (i.e., commercial off-the-shelf software) in the 1960s: the legal framework that allowed software owners to bring lawsuits for copyright violations appeared in the early 1980s.
There was an organization named SHARE composed of customers of IBM whereby one customer could obtain software written by other other customers (much like the open-source ecosystem) but I don't recall money ever changing hands for any of this software except a very minimal fee (orders of magnitude lower than the rental or purchase price of a System/360, which started at about $660,000 in 2025 dollars).
Also, IIUC most owners or renters of a System/360 had to employ programmers to adapt the software IBM provided. There is software with that quality these days, too (.e.g, ERP software for large enterprises) but no one calls that a software as a service.
>except a very minimal fee
the fee would be for membership SHARE. The fee (if it even existed) would not have been passed on to the entity that paid to create the software.
I spent days, weeks arguing against it and ended up having to dedicate resources to build a PoC just to show it didn’t work, which could have been used elsewhere.
If you assume the napkin math is correct on the $800bn yearly needed to service interest rates on these CAPEX loans, then you’d need the collective revenue of the major players (OpenAI, Google, Anthropic, etc) to pull in as much revenue in a year as Apple, Alphabet, and Samsung combined.
Let’s assume OpenAI is responsible for much of this bill, say, $400bn. They’d need a very generous conversion rate of 24% for their monthly users (700m) to the Pro plan for an entire year to cover that bill, for one year. That’s a conversion rate better than anyone else in the XaaS world who markets to consumers and enterprises alike, and paints a picture of just how huge the spend from enterprises would need to be to subsidize consumer free usage.
And all of this is just for existing infrastructure. As a number of CEBros have pointed out recently (and us detractors have screamed about from the beginning), the current CAPEX on hardware is really only good for three to five years before it has to be replaced with newer kit at a larger cost. Nevermind the realities of shifting datacenter designs to capitalize on better power and cooling technologies to increase density that would require substantial facility refurbishment to support them in a potential future.
The math just doesn’t make sense if you’re the least bit skeptical.
Maybe that will turn out to be a good decision and Microsoft/Google/etc. will be crushed under the weight of hundreds of billions of dollars in write-offs in a few years. But that doesn’t mean they did it intentionally, or for the right reasons.
What is more convincing is when someone invests heavily (and is involved heavily) and then decides to stop sending good money after bad (in their estimation). Not that they’re automatically right, but is at least pay attention to their rationales. You learn very little about the real world by listening to the most motivated reasoner’s nearly fact-free bloviation.
But Watson doesn't count?
Or they recognize that you may get an ROI on a (e.g.) $10M CapEx expenditure but not on a $100M or $1000M/$1B expenditure.
One big ones used heavily is Watson AIOps. I think we started moving to it before the big LLM boom. My usage is very tangential, to the point where I don’t even know what the AI features are.
I think the dilemma I see with building so much data centers so fast is exactly like whether I should buy latest iPhone now or should wait few years when the specs or form factor improves later on. The thing is we have proven tech with current AI models so waiting for better tech to develop on small scale before scaling up is a bad strategy.
Taking a look at IBM's Watson page, https://www.ibm.com/watson, it appears to me that they basically started over with "watsonx" in 2023 (after ChatGPT was released) and what's there now is basically just a hat tip to their previous branding.
Does it matter? It’s still a scam.
but when I look at their stock, its at all time highs lol
no idea
IBM doesn’t majorly market themselves to consumers. The overwhelming majority of devs just aren’t part of the demographic IBM intends to capture.
It’s no surprise people don’t know what they do. To be honest it does surprise me they’re such a strongly successful company, as little as I’ve knowingly encountered them over my career.