Companies are caught in an expensive AI 'arms race'

John Collins says there's no doubt we're in the middle of an AI arms race.

He has worked in the IT industry for 35 years in various roles including software programmer, systems manager and chief technology officer.

He is currently an industry analyst at research firm Gigaom.

Collins says the current arms race has been fuelled by the launch of ChatGPT at the end of 2022.

Since then, many such generative AI systems have emerged, and millions of people use them every day to create artwork, text, and video.

For business leaders, the stakes are high: generative AI systems are incredibly powerful tools, able to process more data in minutes than a human could process in a lifetime.

Collins explained that business leaders were suddenly realizing what AI could accomplish for their companies and their competitors.

“Fear and greed are what drive it,” he says, “and that creates an avalanche of momentum.”

With proper training, customized AI systems can help companies stay ahead of competitors with research breakthroughs and reduce costs by automating tasks currently performed by humans.

In the pharmaceutical industry, companies are customizing AI to help discover new compounds to treat diseases, but this is a costly process.

“You need data scientists and model engineers,” Collins explains.

Scientists and engineers need to have at least some understanding of the area of ​​medicine the AI ​​will be addressing.

And that's not all: “We also need infrastructure engineers who can build the AI ​​platform,” he continues.

Finding these highly skilled workers is not easy.

There is a shortage of people “who understand how to build these systems, how to make them work in the wild, and how to solve some of the challenges that lie ahead,” said Andrew Rogojski, innovation director at the Surrey Human-Centred AI Institute at the University of Surrey.

He added that salaries for people who can tackle these challenges are reaching “ridiculous” levels because they are so important.

“If we had the capacity, we could produce hundreds of AI PhDs, because people would give them jobs.”

Not only is there a skills shortage, but simply accessing the physical infrastructure needed for large-scale AI can be a challenge.

The kind of computer system needed to run AI for cancer drug research would typically require 2,000 to 3,000 of the latest computer chips.

The cost of this computer hardware alone could easily exceed $60m (£48m), before other essential costs such as data storage and networking.

Part of the problem for businesses is that this kind of AI has arrived fairly suddenly – previous technologies, such as the advent of the internet, were built up much more slowly.

A large bank, pharmaceutical company, or manufacturing company may have the resources to purchase the technology needed to take advantage of the latest AI, but what about smaller businesses?

Italian start-up Restworld is a job website for catering staff with a database of 100,000 workers.

Chief Technology Officer Edoardo Conte was interested in whether AI could benefit the business.

The company explored building an AI-driven chatbot to communicate with users of its service.

But Conte said that with thousands of users, “the costs would increase significantly.”

Instead, they focused on a narrower issue: that candidates weren't always presenting their experiences in the best way possible.

For example, an applicant might not list their skills as a waiter, but Conte's algorithm can help surface additional information, such as whether the candidate has previously applied for and been hired as a waiter.

“The AI ​​can infer that they might be a waiter or be interested in other waiter jobs,” he says.

One of the hurdles in recruiting in the hospitality industry is getting candidates through to the interview stage.

So Conte's next step is to use AI to automate and customize the interview process for candidates.

AI can also “talk” to candidates and create summaries to give to recruiters.

This would speed up the entire process, which currently takes several days, potentially allowing waiters and chefs to find other work.

Meanwhile, large companies will continue to pour money into AI projects, even if it's not always clear what they'll accomplish.

As Rogojski says, the adoption of AI is in a “Darwinian experiment” and it's difficult to predict what the outcome will be.

“That's the funny part. But I think we have to go along with it,” he said, adding, “I don't know if we have a choice.”