Is the artificial intelligence (AI) bubble set to burst soon?
It will likely happen in the next year, Yanev Suissa, the founder of venture capital firm SineWave Ventures, told Seeking Alpha in an interview published Saturday (Oct. 14). Still, that doesn’t mean the technology isn’t worthwhile, he added.
“AI is the next revolution in tech, but it’s also been around forever,” Suissa said. “It’s one of those things that’s going to pop and it’ll be a huge pop. And then it’ll sort itself out, right?”
He described a scenario in which a generative AI chatbot will put forth something inappropriate dealing with race, or with the 2024 U.S. presidential election, uprooting the AI industry. Suissa predicted that AI could end up like blockchain, a tool that businesses use to boost efficiency but not its own thing.
Suissa also told Seeking Alpha that he’s interested in investing in proprietary data security.
“Security is a key part of any solution,” he said. “You cannot provide anything today in the tech world without security as part of it. You need to be able to integrate for proprietary data without it thinking it, knowing it’s secure and also being able to tailor it to your own business.”
His company has backed companies like data analytics firm Databricks. Suissa said the industry’s next phase will see the incorporation of AI, something Databricks undertook when it purchased MosaicML earlier this year.
“They’re going to own this space,” Suissa said, adding that the company was due to reach $2 billion in revenue in the quarters ahead.
Overall, however, AI is “entering the end of its first full year of commercialization without having cracked the profitability nut,” PYMNTS wrote last week.
The steep cost of AI, fueled mainly by the computing power an AI model requires — which grows alongside the number of customers using the product — “is an uncomfortable and expensive reality” that businesses need to adapt to stay competitive, the report said.
Just one AI query can cost almost 1,000 times that of the same question asked of a standard Google search, making the margins for AI applications smaller than other software-as-a-service (SaaS) solutions.
“Even when they aren’t being used by customers, AI models need to be constantly retrained and fine-tuned to stay relevant and safe, a computationally heavy process that isn’t necessarily easy on a firm’s war chest,” PYMNTS wrote.
All the same, the generative AI industry itself is projected to reach $1.3 trillion by 2032.