ChatGPT and generative AI are booming, but the costs can be extraordinary
OpenAI CEO Sam Altman speaks during a keynote address announcing ChatGPT integration for Bing at Microsoft in Redmond, Washington, on February 7, 2023.
Jason Redmond | AFP | Getty Images
Before OpenAI’s ChatGPT emerged and captured the world’s attention for its ability to create compelling sentences, a small startup called Latitude was wowing consumers with its AI Dungeon game that let them use artificial intelligence to create fantastical tales based on their prompts.
But as AI Dungeon became more popular, Latitude CEO Nick Walton recalled that the cost to maintain the text-based role-playing game began to skyrocket. AI Dungeon’s text-generation software was powered by the GPT language technology offered by the Microsoft-backed AI research lab OpenAI. The more people played AI Dungeon, the bigger the bill Latitude had to pay OpenAI.
Compounding the predicament was that Walton also discovered content marketers were using AI Dungeon to generate promotional copy, a use for AI Dungeon that his team never foresaw, but that ended up adding to the company’s AI bill.
At its peak in 2021, Walton estimates Latitude was spending nearly $200,000 a month on OpenAI’s so-called generative AI software and Amazon Web Services in order to keep up with the millions of user queries it needed to process each day.
“We joked that we had human employees and we had AI employees, and we spent about as much on each of them,” Walton said. “We spent hundreds of thousands of dollars a month on AI and we are not a big startup, so it was a very massive cost.”
By the end of 2021, Latitude switched from using OpenAI’s GPT software to a cheaper but still capable language software offered by startup AI21 Labs, Walton said, adding that the startup also incorporated open source and free language models into its service to lower the cost. Latitude’s generative AI bills have dropped to under $100,000 a month, Walton said, and the startup charges players a monthly subscription for more advanced AI features to help reduce the cost.
Latitude’s pricey AI bills underscore an unpleasant truth behind the recent boom in generative AI technologies: The cost to develop and maintain the software can be extraordinarily high, both for the firms that develop the underlying technologies, generally referred to as a large language or foundation models, and those that use the AI to power their own software.
The high cost of machine learning is an uncomfortable reality in the industry as venture capitalists eye companies that could potentially be worth trillions, and big companies such as Microsoft, Meta, and Google use their considerable capital to develop a lead in the technology that smaller challengers can’t catch up to.
But if the margin for AI applications is permanently smaller than previous software-as-a-service margins, because of the high cost of computing, it could put a damper on the current boom.
The high cost of training and “inference” — actually running — large language models is a structural cost that differs from previous computing booms. Even when the software is built, or trained, it still requires a huge amount of computing power to run large language models because they do billions of calculations every time they return a response to a prompt. By comparison, serving web apps or pages requires much less calculation.
These calculations also require specialized hardware. While traditional computer processors can run machine learning models, they’re slow. Most training and inference now takes place on graphics processors, or GPUs, which were initially intended for 3D gaming, but have become the standard for AI applications because they can do many simple calculations simultaneously.
Nvidia makes most of the GPUs for the AI industry, and its primary data center workhorse chip costs $10,000. Scientists that build these models often joke that they “melt GPUs.”
Training models
Nvidia A100 processor
Nvidia
Analysts and technologists estimate that the critical process of training a large language model such as OpenAI’s GPT-3 could cost more than $4 million. More advanced language models could cost over “the high-single-digit millions” to train, said Rowan Curran, a Forrester analyst who focuses on AI and machine learning.
Meta’s largest LLaMA model released last month, for example, used 2,048 Nvidia A100 GPUs to train on 1.4 trillion tokens (750 words is about 1,000 tokens), taking about 21 days, the company said when it released the model last month.
It took about 1 million GPU hours to train. With dedicated prices from AWS, that would cost over $2.4 million. And at 65 billion parameters, it’s smaller than the current GPT models at OpenAI, like ChatGPT-3, which has 175 billion parameters.
Clement Delangue, the CEO of AI startup Hugging Face, said the process of training the company’s Bloom large language model took more than two-and-a-half months and required access to a supercomputer that was “something like the equivalent of 500 GPUs.”
Organizations that build large language models must be cautious when they retrain the software, which helps improve its abilities, because it costs so much, he said.
“It’s important to realize that these models are not trained all the time, like every day,” Delangue said, noting that’s why some models, such as ChatGPT, don’t have knowledge of recent events. ChatGPT’s knowledge stops in 2021, he said.
“We are actually doing a training right now for the version two of Bloom and it’s gonna cost no more than $10 million to retrain,” Delangue said. “So that’s the kind of thing that we don’t want to do every week.”
Inference and who pays for it
Bing with Chat
Jordan Novet | CNBC
To use a trained machine learning model to make predictions or generate text, engineers use the model in a process called “inference,” which can be much more expensive than training because it might need to run millions of times for a popular product.
For a product as popular as ChatGPT — which investment firm UBS estimates to have reached 100 million monthly active users in January — Curran believes that it could have cost OpenAI $40 million to process the millions of prompts people fed into the software that month.
Costs skyrocket when these tools are used billions of times a day. Financial analysts estimate Microsoft’s Bing AI chatbot, which is powered by an OpenAI ChatGPT model, needs at least $4 billion of infrastructure to serve responses to all Bing users.
In the case of Latitude, for instance, while the startup didn’t have to pay to train the underlying OpenAI language model it was accessing, it had to account for the inferencing costs that were something akin to “half-a-cent per call” on “a couple million requests per day,” a Latitude spokesperson said.
“And I was being relatively conservative,” Curran said of his calculations.
In order to sow the seeds of the current AI boom, venture capitalists and tech giants have been investing billions of dollars into startups that specialize in generative AI technologies. Microsoft, for instance, invested as much as $10 billion into GPT’s overseer OpenAI, according to media reports in January. Salesforce‘s venture capital arm, Salesforce Ventures, recently debuted a $250 million fund that caters to generative AI startups.
As investor Semil Shah of the VC firms Haystack and Lightspeed Venture Partners described on Twitter, “VC dollars shifted from subsidizing your taxi ride and burrito delivery to LLMs and generative AI compute.”
Many entrepreneurs see risks in relying on potentially subsidized AI models that they don’t control and merely pay for on a per-use basis.
“When I talk to my AI friends at the startup conferences, this is what I tell them: Do not solely depend on OpenAI, ChatGPT or any other large language models,” said Suman Kanuganti, founder of personal.ai, a chatbot currently in beta mode. “Because businesses shift, they are all owned by big tech companies, right? If they cut access, you’re gone.”
Companies such as enterprise tech firm Conversica are exploring how they can use the tech through Microsoft’s Azure cloud service at its currently discounted price.
While Conversica CEO Jim Kaskade declined to comment about how much the startup is paying, he conceded that the subsidized cost is welcome as it explores how language models can be used effectively.
“If they were truly trying to break even, they’d be charging a hell of a lot more,” Kaskade said.
How it could change
It’s unclear if AI computation will stay expensive as the industry develops. Companies making the foundation models, semiconductor makers and startups all see business opportunities in reducing the price of running AI software.
Nvidia, which has about 95% of the market for AI chips, continues to develop more powerful versions designed specifically for machine learning, but improvements in total chip power across the industry have slowed in recent years.
Still, Nvidia CEO Jensen Huang believes that in 10 years, AI will be “a million times” more efficient because of improvements not only in chips, but also in software and other computer parts.
“Moore’s Law, in its best days, would have delivered 100x in a decade,” Huang said last month on an earnings call. “By coming up with new processors, new systems, new interconnects, new frameworks and algorithms, and working with data scientists, AI researchers on new models, across that entire span, we’ve made large language model processing a million times faster.”
Some startups have focused on the high cost of AI as a business opportunity.
“Nobody was saying ‘You should build something that was purpose-built for inference.’ What would that look like?” said Sid Sheth, founder of D-Matrix, a startup building a system to save money on inference by doing more processing in the computer’s memory, as opposed to on a GPU.
“People are using GPUs today, NVIDIA GPUs, to do most of their inference. They buy the DGX systems that NVIDIA sells that cost a ton of money. The problem with inference is if the workload spikes very rapidly, which is what happened to ChatGPT, it went to like a million users in five days. There is no way your GPU capacity can keep up with that because it was not built for that. It was built for training, for graphics acceleration,” he said.
Delangue, the HuggingFace CEO, believes more companies would be better served focusing on smaller, specific models that are cheaper to train and run, instead of the large language models that are garnering most of the attention.
Meanwhile, OpenAI announced last month that it’s lowering the cost for companies to access its GPT models. It now charges one-fifth of one cent for about 750 words of output.
OpenAI’s lower prices have caught the attention of AI Dungeon-maker Latitude.
“I think it’s fair to say that it’s definitely a huge change we’re excited to see happen in the industry and we’re constantly evaluating how we can deliver the best experience to users,” a Latitude spokesperson said. “Latitude is going to continue to evaluate all AI models to be sure we have the best game out there.”
Watch: AI’s “iPhone Moment” – Separating ChatGPT Hype and Reality
Technology
Amazon warehouse workers lose jobs after Trump’s immigration crackdown: ‘We have done everything legally’
A worker prepares orders at an Amazon.com Inc. fulfillment center.
Jason Alden | Bloomberg | Getty Images
Daphnee Poteau, a Haitian who came to the U.S in 2023, began working for Amazon last year at a returns center in Indianapolis. While packing up boxes, she met her husband Kristopher Vincent, who’s been at the site, known as IND8, since 2013.
Last month, Poteau was contacted by the Department of Homeland Security, after the Trump administration canceled humanitarian immigration programs that allowed participants to live and work legally in the U.S. for two years while applying for permanent status.
A notice from DHS told Poteau that her parole program was being terminated. Her last day at Amazon was June 28. She’s among a group of warehouse workers whose jobs have been eliminated since DHS revoked the parole program that was created during the Biden administration.
While Poteau tries to secure a spousal visa, her future in the U.S. is uncertain. She and Vincent, who’s from Indiana, said they’re concerned about being able to afford rent and costly immigration fees.
“We’re taking it one day at a time, but it does leave me stressed that they’re going to come and try to get her, even though she does have an asylum case pending in court,” Vincent said in an interview.
“Everything we’ve seen in the news shows they flagrantly no longer care what the laws say,” Vincent said.
Poteau and her terminated co-workers had been protected under programs that provided Haitians, Cubans, Nicaraguans and Venezuelans with temporary legal status in the U.S. Many of the employees at IND8 are Haitian, a large enough contingent that some of the morning staff meetings are translated into Creole, Vincent said.
Daphnee Poteau met her husband Kristopher Vincent while working at an Amazon warehouse in Indianapolis.
Kristopher Vincent
Amazon last month began asking staffers who came to the U.S. under the Biden-era program to provide updated work permits within a certain timeframe or they would be put on unpaid leave, according to documents viewed by CNBC.
Several workers who spoke to CNBC said they were dismissed by Amazon in late June after they couldn’t get new work authorizations.
Amazon declined to say how many employees were let go following the changes in immigration policy, but spokesperson Richard Rocha said the company prepared for potential staffing impacts due to changes in work authorization programs, and made adjustments to be in compliance with the law.
“We’re supporting employees impacted by the government’s recent changes in immigration policy,” Rocha said in a statement. “Over the past few months, we’ve been in regular communication with these employees about the changes and are ensuring they’re aware of all available resources.”
The company has provided impacted employees with information about where to find free or low-cost legal services, access to counseling support and other resources, Rocha said.
A DHS spokesperson pointed to the agency’s announcement terminating the humanitarian parole program.
Fired before Prime Day
As part of the Trump administration’s broad immigration crackdown, DHS has eliminated not just the humanitarian parole program. It’s also ended separate programs that provided temporary protected status to Venezuelans, Haitians, Nicaraguans and Hondurans seeking refuge from their native countries, which have suffered from armed conflict and humanitarian crises. Last week, a federal judge ruled the Trump administration can’t revoke the temporary protected status, or TPS, of Haitian migrants. The White House said it will appeal the ruling.
Amazon is far from alone. Other companies including Walmart and Disney have been forced to fire employees or put them on leave in order to comply with shifting federal policies.
Among private employers in the U.S., only Walmart has a bigger workforce than Amazon. Most of the e-commerce giant’s 1.56 million employees globally are concentrated in its warehouse operations.
The terminations started just as Amazon was gearing up for its annual Prime Day discount blitz, which began on Tuesday and lasts four days. The event is typically one of the busiest periods of the year for Amazon warehouse and delivery employees, alongside the holiday shopping season.
Amazon has counted on immigrants to meet a big part of its staffing needs. In 2022, the company set a goal to hire 5,000 refugees and other forcibly displaced individuals by the end of 2024.
While Trump’s policies create a challenge for large employers like Amazon, the real devastation is being felt by the immigrant workers. Those who now find themselves unemployed and lacking documentation are at a higher risk of being targeted for deportation unless they can secure an alternative form of legal status.
Christopher Lubin, an Amazon warehouse worker in Delaware, lost his job at the company on June 27, a day before Poteau received her notice.
“We have done everything legally in this country,” said Lubin, 24, who is also from Haiti. “We haven’t committed fraud. We go to school, we work, and we pay taxes.”
DHS said it was revoking protections for Haitian nationals after a review by Secretary Kristi Noem determined “country conditions have improved to the point where Haitians can return home in safety.”
The U.S. granted TPS for Haitian nationals following a catastrophic earthquake in 2008 that destroyed much of the nation’s infrastructure. In 2024, the TPS designation was extended through February 2026, as the country faced “rapidly deteriorating security, human rights and humanitarian” conditions, according to the United Nations Human Rights Council.
Armed gangs control the majority of Port-au-Prince and violence has spread beyond the capital in recent months. About 10 individuals from Haiti lost their jobs at an Amazon warehouse in Spokane, Washington, after DHS revoked the TPS program, said Katia Jasmin, executive director of Creole Resources, which provides support to Haitian immigrants in the region.
Serge, who asked to have his full name withheld out of fear of being targeted for deportation, came to the U.S. from Haiti nearly two years ago and secured a job at the Spokane warehouse as a packer. The situation in Haiti was dire when he left and it remains unsafe today, Serge said.
“I witnessed violence and trauma, including the loss of family members who were killed,” Serge said. “Others were displaced from their homes and are now homeless. I genuinely feared for my life.”
In desperation, he said he sought a safer future and secured a sponsor that allowed him to come to the U.S. legally. It’s “unjust” that Haitians are now being ordered to return to their home country when it’s plagued with violence, Serge said.
“We’re not just recipients of economic support,” he said. “We’re also contributors who help drive the economy.”
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