ChatGPT is the latest in artificial intelligence to breathe (and venture capital investment into) Silicon Valley, but it’s also an advance in AI that hasn’t proven its ability to live up to the hype.
Projects like ChatGPT can be amazing because they test the limits of technology and try to push it further. However, the anticipation of technological possibilities does not always lead to great financial gains.
Take Watson as an example. IBM of IBM,
Natural language computers became famous over a decade ago when they defeated two humans on the game show Jeopardy, prompting Big Blue to bet big on the technology. IBM has opened a business unit with his IBM Watson offices on both the East and West Coasts, focusing on healthcare as the biggest business opportunity.
That opportunity did not lead to IBM’s wealth. Healthcare’s push has disappointing, and when the company streamlined some of its operations earlier this year, it sold Watson Health assets to a private equity firm for an undisclosed amount. is a suite of AI tools and apps in its $25 billion software business, but IBM doesn’t disclose how much revenue these products generate. IBM’s data/AI segment revenue declined 1% year-over-year in the third quarter. Since Watson won “Jeopardy” in February 2011, IBM’s stock has fallen 8.6% and the S&P 500 index SPX has
According to FactSet data, it increased by 189.5% during this time.
That lesson hasn’t stopped the fascination with AI development. Forrester Research analyst Rowan Curran told his MarketWatch that ChatGPT is “the AI moment for the iPhone,” referring to his AAPL for Apple Inc.
“This is a big deal,” said Paul Saffo, a Silicon Valley forecaster and consulting associate professor at Stanford University, adding that this is where the technology is headed.
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OpenAI is private and does not disclose earnings, but valuations and investments are rising rapidly. The San Francisco company was founded as a nonprofit in 2015, and an initial press release at the time said it had raised a total of 10 shares from Silicon Valley investors such as Peter Thiel and Reid Hoffman, as well as his AMZN at Amazon.com Inc. A billion dollar “donation” was mentioned. ,
Without disclosing valuations, Amazon Web Services, to name a few. Elon Musk, along with Sam Altman, co-chaired and remains chief executive officer (Musk resigned in 2018, citing Tesla’s potential conflict of interest with his TSLA.
AI work).
A lot has changed since then — OpenAI raised $1 billion in funding alone from Microsoft Corp. at 2019 MSFT.
Microsoft is reportedly looking to pour more money into the “marginal margin” company, which was valued at about $20 billion in a recent stock sale. In a recent pitch to investors, an OpenAI executive said he expects revenue to be around $200 million next year, and he expects to hit $1 billion by 2024, according to a Reuters report. .
OpenAI now offers ChatGPT’s underlying multilingual model, GPT-3, as a paid application programming interface (API) service, so businesses can build apps on top of it. Reuters reported that OpenAI charges around 1 cent or more for text-based queries and 2 cents for image results.
According to IDC analyst Ritu Jyoti, ChatGPT customers have seen the rise of GPT-3-powered chatbot negotiators to help consumers cancel subscriptions, appeal parking tickets, and fight big corporations in general. The company’s DoNotPay is said to be included. He has one customer, Jasper, who uses GPT-3 to power his AI-based copywriting and content creation software.
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OpenAI officials did not respond to requests for interviews, so MarketWatch turned to the free version of ChatGPT available on the web. When MarketWatch asked ChatGPT, “Who are some of GPT-3’s customers,” it said, “It’s not uncommon for companies and organizations to use his GPT-3 as a tool to build natural language processing applications. ‘ said. Then eBay Inc. EBAY,
It says it will use GPT-3 to improve product classification and search accuracy. Goldman Sachs Group Inc. GS,
Use it to analyze large amounts of unstructured data. The Guardian uses it to generate news articles.
However, these answers may not be the most accurate, but they fit the current state of ChatGPT despite the excitement. Goldman Sachs was part of the GPT-3 demo, stating that it uses machine learning and other AI techniques to infer information, while Guardian only wrote using GPT-3. A few pointless paragraphs in an AI article earlier this year that won’t lead to long-term revenue.
“It’s incredible what can be done,” said Jyoti, adding that he was “thrilled and impressed” by OpenAI’s ChatGPT demo. “But I live and breathe in this space… so I want to be aware that there are a lot of inaccuracies, they don’t tell you the source of the data, and they can be very misleading.”
OpenAI CEO Altman said of the limitations of chatbots:
“ChatGPT may produce plausible-sounding but inaccurate or nonsensical answers,” OpenAI said in a blog post about the release.
Saffo said he isn’t too concerned about the chatbot’s propensity for errors. “Certainly more accurate than your average conspiracy theorist,” he half-joked.
One of the confirmed customers MarketWatch spoke with is Smartling, a cloud-based smart translation service company. Smartling uses her GPT-3 to improve the source text for translation in a post-editing process before the text is passed to translation.
Olga Beregovaya, Vice President of AI and Machine Translation at Smartling, said:
Forrester’s Curran said: “ChatGPT is a really good model. In general, it’s great at explaining why you can’t do certain things…if you’re using his ChatGPT for an internal customer service representative, that representative A much narrower range of questions can be asked of a person whose training data is known.”
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However, the use cases are so narrow that it also narrows the revenue potential, but there is not much about AI yet. 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, according to IDC. , market research firms have not pioneered the market for AI software. Unique. And given how expensive top-of-the-line hardware for AI is, software is likely a small percentage of the total.
So it’s hard to know just how big or small these AI software companies are today, and what the future holds. As many analysts have pointed out, it’s definitely still early days. But even so, Sappo said, “This is where we’re going.” He also said the excitement surrounding tech demos throughout and his ChatGPT shows that humans always want to believe that inanimate objects have intelligence.
“The relentless pace of Moore’s Law means that these things go on in 18- to 20-month doubling periods,” he said. “People will look back at ChatGPT and say, ‘It was so basic and boring.'”
The same can be said for Watson ten years later, which made a big splash. And I would say that the ability to make money was even more disappointing than its endurance as a technology. Will he be able to say the same about ChatGPT in his next decade?