Generative AI has been predicted to add trillions to the global economy in a productivity boost never seen before in history (if it doesn’t wipe out humanity first).
But what if it isn’t?
A growing number of skeptics, including some prominent AI scientists, wonder whether the technology will fail to deliver on its promises to boost the global economy.
Goldman Sachs predicted that generative AI would bring about “radical changes” to the global economy, driving a $7 trillion increase in global GDP and lifting productivity growth by 1.5 percent this decade.
Professor Gary Marcus of New York University wrote about Substack that “we are starting to see signs” that generative AI could be a “flop.”
Among the warning signs was a Wall Street Journal report suggesting that customers found the $30-a-month price of Microsoft’s new AI-powered Copilot software too expensive.
Sam Altman of OpenAI has become a figurehead of artificial intelligence
Professor Gary Marcus is a leading skeptic about the benefits of generative AI
Marcus wrote in his Substack: ‘Putting large language models (like ChatGPT) into production is difficult; most of the work to date has been preliminary.
‘Companies are beginning to moderate their expectations. Many initial expectations were unrealistic.’
Marcus notes that progress in making money with large language models has been slow and that after OpenAI released GPT-4 in 2023, no one has released a model that is decisively more powerful.
We could be reaching a plateau in terms of absolute capacity. No one has been able to defeat him decisively. Places like Google and Anthropic have invested a lot of money in trying this. None were successful; instead, there tentatively appears to be convergence in GPT-4 levels.
Marcus says there has been “progress” toward finding possible uses for large language models, but so far the technology is often used to commit crimes.
He said: “Bad actors, who may have lower standards of trustworthiness, appear to be using them for cybercrime and disinformation.”
Retired Professor Jeffrey Funk
Retired professor Jeffrey Funk points out that AI has spent enormous amounts of money trying to combat “hallucinations” – where AI systems “invent” facts – but has not solved the problem.
He wrote on LinkedIn: “Revenue has not arrived yet and may never arrive.” Valuations anticipate trillion-dollar markets, but actual current revenues from generative AI are rumored to be in the hundreds of millions. That revenue could actually grow 1,000 times, but that’s highly speculative. We shouldn’t just assume it.
Funk also warns that the pace of innovation in generative AI appears to be slowing.
He said, ‘Think about PCs or the iPhone.’ There were large improvements in system performance during the early years that declined over time despite 40 percent annual improvements in the performance-to-price ratio of memory and processor chips.
‘Given that Moore’s Law has slowed considerably in the last 5 to 10 years, (Sam) Altman of OpenAI cannot expect much more from Moore’s Law and those concerned about the large energy appetite of generative AI are bound to put pressure on it to be regulated.
Could returns from software like ChatGPT be lower than expected? (AFP)
Speaking to The Information, Todd Lohr, director of consulting firm KPMG, which resells Microsoft products, was lukewarm about the benefits of Microsoft’s CoPilot AI products.
Lohr said: ‘Word is fine, Powerpoint is not particularly useful unless you train it with specific (instructions) because it just creates a Powerpoint that is very basic.
“Excel isn’t there yet; you have to spend a lot of time quickly engineering it to do something for you, which takes a lot more time than just writing Excel formulas yourself.”
Bank of America investment strategist Michael Hartnett has previously suggested that AI could be a bubble, comparing it to the dotcom crisis of 2000.
Amazon CEO Andy Jassy said during an earnings call in February that near-term revenue from AI is “relatively small.”
Speaking to DailyMail.com, Dom Couldwell, head of field engineering at DataStax, said we are still in the “unknown unknowns” phase of generative AI.
Couldwell said: “This area has received so much publicity that it is growing in public: it took Netflix three years to reach a million users, but ChatGPT only took five days.”
“There are also companies that see this as the next get-rich-quick scheme after cryptocurrencies.”
The companies Coudwell works with are still trying to find where generative AI can deliver results, he said.
He said: “I don’t want to get too technical, but the challenge is how companies get their own data and intellectual property to work for them, rather than just leveraging OpenAI or Google technology.”
‘Simply trying to get value from GenAI from off-the-shelf solutions or replacing staff will not work; You should use it as a multiplier to make your employees more productive, deliver more value to customers, and differentiate yourself from the competition. and paste the chatbot.’