ChatGPT is the latest artificial intelligence product to take Silicon Valley’s breath away (and venture capital investments), but it’s yet another AI advancement that hasn’t proven its ability to sustain a large valuation.
Projects like ChatGPT can be amazing because they try to test the limits of technology and push it further. However, excitement for technological promises does not always lead to great financial returns.
As an example, take Watson. IBM Corp., IBM,
natural-language computer became a household name more than a decade ago by two people on the game show “Jeopardy”, Big Blue leads to make a big bet on the technology. IBM opened a business unit with IBM Watson offices on both the East and West coasts, focusing on healthcare as the largest business opportunity.
This opportunity did not lead to riches for IBM. The health push was disappointing, and while the company was streamlining some of its operations earlier this year, it sold the Watson Health assets to a private equity firm for an undisclosed sum. The rest of Watson still exists within IBM’s $25 billion software business as a suite of AI tools and apps, but IBM has never disclosed how much revenue those products produce; Revenue in IBM’s data/AI segment fell 1% year over year in the third quarter. IBM stock is down 8.6% since Watson won “Jeopardy” in February 2011, while the S&P 500 index SPX,
rose 189.5% in that time, according to FactSet data.
This lesson did not stop the fascination with AI developments. Forrester Research analyst Rowan Curran told MarketWatch that ChatGPT was an “iPhone moment for AI,” referring to Apple Inc.’s AAPL.
reinvention of consumer electronics in 2007. Paul Saffo, a Silicon Valley forecaster and consulting associate professor at Stanford University, said “This is a big deal,” adding that this is where technology is going.
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While OpenAI is private and therefore does not disclose revenue, it has experienced a rapid increase in valuation and investment. The San Francisco company was founded in 2015 as a nonprofit, and its first press release at the time mentioned “donations” totaling $1 billion from Silicon Valley investors like Peter Thiel and Reid Hoffman, as well as Amazon.com Inc.’s AMZN. ,
Amazon Web Services, to name a few, without publishing a review. Elon Musk was also co-chairman, along with Sam Altman, who remains chief executive today (Musk resigned in 2018, citing possible conflicts of interest with Tesla Inc.’s TSLA,
A lot has changed since – OpenAI received $1 billion in funding just from Microsoft Corp. in 2019 MSFT,
and Microsoft is looking to pour more funds into the “capped profit” company, which was recently valued at about $20 billion in a stock sale. According to a Reuters report, in a recent pitch to investors, Open AI executives said they expect revenue to reach around $200 million next year and $1 billion by 2024.
OpenAI currently offers GPT-3—the major language model that serves as the basis for ChatGPT—as a paid application programming interface (API) service so companies can build apps around it. Reuters reports that OpenAI costs about a penny or a little more for a text-based query and two cents for an image result.
IDC analyst Ritu Jyoti said some of ChatGPT’s customers include DoNotPay, a startup company whose chatbot negotiation — powered by GPT-3 — helps consumers cancel subscriptions, appeal parking lots and generally fight big companies. Another customer is Jasper, which uses GPT-3 to power its AI-based copywriting and content writing software.
For more: What is ChatGPT? Well, you can ask yourself.
OpenAI officials did not respond to a request for an interview, so MarketWatch turned to the free version of ChatGPT on the Internet. When MarketWatch ChatGPT asked “who are some customers of GPT-3,” it said, “It is not unusual for businesses and organizations to use GPT-3 as a tool to build natural language processing applications.” It then listed several clients, including eBay Inc. eBay,
which it said used GPT-3 to improve the accuracy of product categorization and search; Goldman Sachs Group Inc. GS,
which it uses to analyze large volumes of unstructured data; and The Guardian, which uses it to generate news.
These answers may not be the most accurate, however, which kind of fit into the current state of ChatGPT despite the excitement. For example, while eBay said at an AI hardware summit last year that it uses machine learning and other AI techniques to infer information from text, and Goldman Sachs is part of a GPT-3 demo, the Guardian only used GPT-3 to write a few nonsensical paragraphs of an article about AI earlier this year, not exactly something that leads to long-term revenue.
“It’s unimaginable what things can be done,” Jyoti said, adding that she was “excited and impressed” with OpenAI’s ChatGPT demo. “But because I live and breathe in this space… I want to be careful that it has a lot of inaccuracies, doesn’t tell you the source of the data, and it can be very misleading.”
OpenAI CEO Altman noted the chatbot’s limitations:
“ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical responses,” OpenAI also says in a blog post about the release.
Saffo said he wasn’t overly concerned about the chatbot’s propensity for error. “Surely it’s more accurate than your average conspiracy theorist,” he half-joked. “This is a technical demonstration, it is the first of what is to follow.”
One confirmed customer that MarketWatch spoke to is Smartling, a cloud-based, smart translation service company. Smartling uses GPT-3 to improve the source text of a translation in the post-editing process, before the text is passed to the translator.
“In my opinion, it’s kind of inventing machine translation,” said Olga Beregovaya, vice president of AI and machine translation at Smartling.
“Even if you’re generating coherent nonsense, it doesn’t mean the content is useless,” said Curran of Forrester. “ChatGPT is a really good model. It’s generally good to tell you why it can’t do certain things… If you use ChatGPT for some internal customer service reps, the questions that are asked by that rep will be much more narrow in scope, the training data will be announced.”
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However, the very narrow use cases will also narrow the opportunity for revenue, and there isn’t much of that for AI to go around yet. IDC said that global spending on AI, including software, hardware and services for AI-centric systems will reach nearly $118 billion in 2022 and exceed $300 billion in 2026, but the market research firm does not break down the market for AI software into its own And considering how much more expensive top-of-the-line hardware is for AI, it’s possible that software is a small percentage of that total.
So it’s tricky to get any kind of sense of how big or small these AI software companies are right now and what the future holds. As many analysts have noted, it is definitely still early days. But even if it is, Saffo noted that “this is where we’re going.” He also said that the whole tech demo and the excitement around ChatGPT showed how humans always want to believe that inanimate objects have intelligence.
“The relentless pace of Moore’s Law means these things are progressing at 18- to 20-month doubling periods,” he said. “People look back on ChatGPT and say ‘that was so basic and boring’.”
The same could be said about Watson a decade after it made a big splash. And we can also say that its ability to make money was even more disappointing than its staying power as a technology. Will we say the same of ChatGPT in the next decade?