Artificial Intelligence: the next Metaverse?
A few days ago on Facebook I made a joke about “Microsoft circling the AI drain”, and someone emailed to ask what I meant about it.
It’s simple: I wonder if generative intelligence and OpenAI will be to Microsoft what the Metaverse was to Facebook.
If you’re not familiar with the Metaverse (and why should you be, seeing how it vanished into obscurity), it was Facebook’s big idea for virtual reality back in 2020-2021. That was right around peak COVID, and it seems that Facebook’s leadership had the idea that the distancing requirements would be more or less permanent, that COVID had caused permanent change in the ordering of society. So it was time to go all-in on virtual reality headsets and software, since that would be the next major computing paradigm, in much the same way that first the Blackberry and then the iPhone had driven the mobile computing revolution.
This was a disastrous failure. Facebook ended up losing about two-thirds of its value, and its stock price dropped below $100 for a while for the first time in years. The company has since more or less recovered thanks to political ad spending on its platform, but not without a lot of layoffs along the way. If Mark Zuckerberg hadn’t set up Facebook so that it was nearly impossible to get rid of him, he probably would have been fired and a new CEO installed.
The three big problems with the Metaverse were 1.) no one wanted to use it, 2.) it didn’t make any money, and 3.) it cost enormous amounts of money to create and develop. Having something that costs a ton of money and doesn’t bring in any money is a big problem for any business in both the short term and the long term.
Generative AI doesn’t have the first problem – a lot of people want to use it for a variety of things – but it does have the second two problems in enormous spades. It doesn’t make a lot of money, if any, and it is enormously expensive to run the cloud computing infrastructure to maintain it.
Like, no one has really answered the question – how do you actually make money using generative AI? The hype around it seems to follow the usual tech investment bubble:
1.) Exponential user growth.
2.) ???
3.) Profit!
But tech entrepreneurs have a bad habit of ignoring step number two, which is unfortunate because it turns out step two is quite important.
(Midjourney is allegedly profitable since it offers subscription plans, though I wonder how much of the “profit” comes from outside investment.)
You can’t copyright anything AI puts out, which means you can’t use it in any business model that relies upon intellectual property rights, like publishing. Because hallucinations and mistakes are so common, you can’t use it for anything where you’ll get in trouble if it’s wrong. There was a famous recent case where a lawyer used ChatGPT to write a court filing, and ChatGPT cited six nonexistent cases. The judge was not pleased, and if you know anything about the American legal system, you know that having a federal judge mad at you because of your gross incompetence is not a good place to be. ChatGPT can generate code, but if you’re going to use that code for anything important, you really need an actual human to review it so you don’t get sued when something inevitably goes horribly wrong. So if you’re thinking to save money on developers by using ChatGPT, you still need to pay actual humans to check the code.
It’s very difficult to make money from generative AI, and the other side of the coin is the cost. Generative AI requires enormous quantities of computing power, and all that requires big data centers and lots of electricity. All of that is extremely expensive.
(As an aside, in a darkly amusing way, it is possible to make a lot of money using AI, or at least machine learning. YouTube’s and Facebook’s recommendation algorithms run off machine learning, and they’re so good at it that they caused a significant amount of global civic and social disorder over the last yen years.)
So on the one hand you have a product that doesn’t make much or maybe any money, and on the other hand is costs titanic amounts of money to produce.
How is this going to affect Microsoft?
On the surface (sorry, bad pun), Microsoft looks like a corporate empire in robust health. It’s consistently one of the world’s most valuable companies, and the stock price keeps going up. But if you pay close attention to Microsoft and its products, you can see the cracks starting to form. The company keeps having layoffs across all its divisions. The price for Xbox Game Pass just went up for the first time in a while. The much-touted Windows Recall feature was a security disaster and had to be, well, recalled, and that messed up the launch of its much-vaunted Copilot PCs. Windows 11 seems to keep getting worse and laden with more ads and bundled crapware. Speaking of security, Microsoft has been in trouble with the US government because of all the data breaches on Azure services. And speaking of Azure, “Azure is down” is something you hear more and more from people who work at companies that rely on Microsoft cloud services.
What I suspect is happening is that Microsoft’s leadership is throwing piles of money at AI projects since it helps drive the stock price up, but AI isn’t actually making any money, and the strain is starting to show across the rest of the company. So everything that actually makes money like Windows and Azure and gaming is getting cut to the bone so they can keep throwing money at AI since that’s what is currently driving up the stock price. But AI isn’t making any money, and eventually the whole thing is going to go bust.
This is all speculative on my part. And I don’t think Microsoft will go out of business or collapse when generative AI tanks, since the company has a lot of revenue streams, even if it is ignoring those revenue streams in favor of AI. I do think generative AI will do significant harm to Microsoft the way the Metaverse did to Facebook, but I could be wrong.
Nevertheless, in the last few years, we’ve seen a lot of speculative bubbles around what turned out to be totally useless and even destructive technology – crypto, NFTs, the Metaverse, and so forth – and a lot of the fervor around generative AI seems to be following a suspiciously similar trajectory.
-JM
I decided to ask ChatGPT to comment on (an excerpt of) your post. Here is its response (which I agree with):
The argument … raises some valid points and concerns, but there are several counterarguments and additional considerations to take into account when evaluating the potential of generative AI from a business perspective:
1. Revenue Generation Potential:
* Unlike the Metaverse, which struggled to find a broad user base and monetization strategy, generative AI has already demonstrated various applications across industries. For instance, it can be used in content creation, customer service, software development, and more. Companies like OpenAI have started to monetize their models through subscription services, licensing, and partnerships.
* Many businesses are integrating generative AI to enhance their operations, reduce costs, and innovate their products and services. This integration can lead to indirect revenue growth and efficiency improvements.
2. Cost of Development and Maintenance:
* While it is true that generative AI requires significant computational resources, advances in hardware and software optimization are continually reducing these costs. Moreover, the economies of scale can further mitigate expenses as the technology becomes more widespread.
* Cloud providers, including Microsoft Azure, offer AI services as part of their broader cloud ecosystems, spreading the cost across a wide range of services and customers.
3. Adoption and User Base:
* The adoption rate of generative AI tools has been rapid, with many industries finding practical uses for them. This is a significant difference from the Metaverse, which struggled to find a compelling use case for the average consumer.
* The versatility of generative AI means it can be tailored to a wide range of needs, increasing its potential user base compared to a more niche technology like the Metaverse.
4. Competitive Edge and Innovation:
* Companies that effectively leverage generative AI can gain a significant competitive edge by automating tasks, generating insights from data, and creating new products and services. This potential for innovation can drive long-term business success.
* The technology is still evolving, and new breakthroughs can lead to unforeseen applications and opportunities, expanding its value proposition over time.
5. Market Trends and Investments:
* The investment landscape for AI is robust, with venture capital and large corporations pouring funds into AI startups and research. This indicates a strong belief in the long-term viability and profitability of AI technologies.
* Regulatory developments and standards are also emerging to support the responsible use of AI, which can help mitigate some of the risks and uncertainties associated with the technology.
While it is important to be cautious and realistic about the challenges and costs associated with generative AI, dismissing it as a potential failure like the Metaverse may be premature. The key difference lies in the current adoption, practical applications, and the continuous improvements in the field, suggesting a more promising outlook for generative AI from a business perspective.
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Could I improve on ChatGPT’s response? Sure, but it took 10 seconds to paste your post and get this initial response.
Have you not noticed that Generative AI is improving? I’m not convinced your arguments are good even against the current state of Generative AI (as discussed in ChatGPT’s response), but against much improved AIs in the future? We’ll have to see, but from where I sit, small improvement from here will yield access to ever larger markets.
Have you not noticed that humans aren’t perfect either? That fairly often they’re not even honest and make stuff up (how is that better than ChatGPT hallucinating?)? That legal filings by humans are error free? That code written by a journeyman (or even expert) programmer still has to be carefully checked and tested, especially if it’s mission critical?
To me, it seems like you’re heavily leaning on the current negatives of Generative AI while ignoring the generally poor performance of humans and the positives of Generative AI.
The simple model across a wide variety of applications is to have Generative AI generate initial content with people taking that content and massaging until it’s right. There’s a huge productivity boost in that alone and that will ultimately translate into revenue and profit.
What does ChatGPT say when you tell it that OpenAI lost 5 billion dollars this year?
First it says the statement isn’t accurate. It’s estimated that OpenAI COULD lose $5 billion during the FULL year, not that it HAS lost $5 billion already this year.
When I tell it to ignore that rather significant detail, here is its response…
If someone claims that “OpenAI lost 5 billion dollars this year,” it’s important to consider several aspects before drawing any conclusions about the viability and future of OpenAI or generative AI as a whole. Here are key points to respond within the context of this discussion:
1. Financial Context and Investment:
Losses in high-growth tech companies, particularly in the AI sector, can be part of a strategic investment phase. Companies like OpenAI, which are at the forefront of technological innovation, often incur significant expenses for research, development, and infrastructure before achieving profitability.
Losses might reflect substantial investments in developing new technologies, expanding computational resources, hiring top talent, and scaling operations. This is common in industries with high upfront costs and potential for long-term gains.
2. Revenue and Monetization Strategies:
OpenAI has started monetizing its technologies through products like the GPT-3 API, available via OpenAI’s platform and integrated into Microsoft Azure. These monetization efforts are likely to grow as AI adoption increases.
The partnership with Microsoft includes not only a financial investment but also opportunities for joint development and integration, potentially leading to future revenue streams.
3. Market Potential and Adoption:
Generative AI has seen widespread interest and adoption across various sectors, including healthcare, education, customer service, and content creation. This broad applicability suggests a strong potential for revenue generation as these technologies mature.
The rapid adoption and integration of AI tools into business processes indicate a high demand, which can lead to significant revenue growth over time.
4. Comparative Analysis:
Comparing OpenAI’s situation to Facebook’s Metaverse might not be entirely appropriate. While the Metaverse faced challenges in finding a user base and viable applications, generative AI is already being used effectively in numerous practical applications, demonstrating its value and potential.
5. Long-term Vision and Impact:
OpenAI’s mission to develop AGI that benefits all of humanity involves long-term research and development. Short-term financial losses may be part of a larger strategy aimed at achieving breakthroughs that can lead to substantial long-term benefits, both financially and socially.
The potential impact of AGI on various industries and everyday life could be transformative, justifying significant investments and temporary losses.
6. Economic Climate:
The broader economic climate, including the tech sector’s performance, can also influence financial outcomes. Factors such as market volatility, changes in investment patterns, and economic downturns can impact financial statements but don’t necessarily reflect the underlying value or potential of the technology.
In summary, while a substantial financial loss might seem alarming at first glance, it’s crucial to consider the broader context of investment, development, and long-term potential. OpenAI’s investments in generative AI represent a commitment to advancing cutting-edge technology that could yield significant returns and societal benefits in the future.
I have some of my own comments.
$5 billion isn’t that much money. Consider that Musk bought Twitter on what looked to me like a whim for somewhere around $50 billion. Consider that pharmaceutical companies often lose billions on developing drugs that turn out to be duds.
Sure, OpenAI could run out of money and go bankrupt. My guess is if that happens it will be because competitors get ahead of it. For example, the latest revision of Llama (which is open source) is comparable to ChatGPT so perhaps funders will jump ship to that platform.
I believe the exact details have not been released but Microsoft Azure gets paid for the computing resources required for training and deployment of OpenAI projects. So a perhaps substantial portion of that $5 billion is just recycled back into Microsoft.
People are paying Microsoft $$$ for subscriptions to AI and cloud services. You can check out their quarterly earnings. Generative AI is a terrific money maker compared to the metaverse.
Due to this, Microsoft has mostly reduced the focus on their core software – OS and products.
If anyone knows how to make a lot of money from bad technology, it’s definitely Microsoft.
Interesting post. Thanks for the info about the Metaverse! Had been wondering why it randomly vanished out of existence.
Interesting post. Thanks for the info about the Metaverse! Had been wondering why it randomly vanished into non-existence.