AI Becomes Silicon Valley’s Next Buzzy Bandwagon as Crypto Boom Fizzles

Even tech workers who weren’t casualties of the recent rounds of layoffs that have rocked Silicon Valley are jumping on the AI bandwagon. Among them are refugees from the most recent tech-industry boom to flame out: the crypto craze.

Some AI veterans worry that “artificial intelligence” is in danger of becoming the latest in a string of empty tech buzzwords.

“The people talking about generative AI right now were the people talking about Web3 and blockchain until recently—the Venn diagram is a circle,” says Ben Waber, chief executive of Humanyze, a company that uses AI and other tools to analyze work behavior. “People have just rebranded themselves.”

Of course, the same investors and founders in the AI industry who voice these concerns believe in their own AI tech, and in any application of AI they think can have an impact in the real world. Despite the dangers of AI becoming another hype-fueled bubble, it’s apparent that the shift of talent and funding from tech giants, dead-end Web3 startups, and SPAC-fueled flights of fancy could be exactly the refocusing the tech industry needs.

At the same time, with AI tools more accessible than ever, turning your startup into an “AI” one is as simple as writing a little code to tap into existing services. Those include Google’s BERT or OpenAI’s GPT-3, which Microsoft has embraced to try to beef up its Bing search engine—with notably mixed results.

There’s every incentive for startups to toss a little AI into their pitches, considering that the field is a rare bright spot in a generally poor investment environment for tech startups. Investors last year poured $2.6 billion into 110 generative AI-focused startups in the U.S., according to CB Insights. This year looks to be comparable, says Matt Moberg, a senior vice president at Franklin Templeton Investments.

Even investors who are keen on AI are concerned that the amount of interest in it might lead to the launch of many low-quality startups.

“A lot of investors are saying, ‘I might actually sit out this trend, because if all these companies are going to be built on top of ChatGPT, then it’s harder to find a winner,’ ” says Brianne Kimmel, founder of Worklife Ventures, which invests in early-stage tech companies.

As with the crypto bubble, for every investor who is cautious, there are plenty who are more afraid of missing out on the next Google—or at least the next OpenAI. OpenAI was founded as a nonprofit in 2015 before transforming into a for-profit company in 2019. In January it was in talks for investments that would have valued it at $29 billion despite generating little revenue. Then the company announced it had signed a deal with Microsoft for a multiyear, multibillion-dollar investment.

“It reminds me of pretty much everything else that goes up and down the hype cycle,” says Mr. Moberg. “With this launch of OpenAI we are at peak hype. It was metaverse before that, cannabis before that. Five years ago it was 3-D printing.” 

Founders and employees are responding to this demand from investors, who are creating bubbles as often as they are following trends. Mr. Waber, of Humanyze, says that despite hiring freezes in other areas of tech, many of his customers at large firms are continuing to hire those with skills in data science, which is key to gathering and preparing the data fed into AI models.

Ashley Chang is an example of midcareer switchers who are eager to launch companies. She spent three years at Carta, a company that helps startup employees track and manage their equity stakes in the companies they work for. In September, she left Carta to explore startups in Web3—a catchall phrase for next-generation, distributed-internet technologies like blockchain—but in December decided to launch an AI startup instead. 

Part of what drew her to AI, she says, was that AI could enable her to solve “real-life problems I’ve been working on for a long time.” Her startup, Altitude, makes an AI customer-support tool for e-commerce companies.

This shift is also apparent among more senior engineers, who in some cases are starting the AI companies doing the hiring. In the past year, for example, veterans of both

Meta Platforms

and Google left their roles in those companies’ augmented- and virtual-reality divisions to start their own AI companies.

To be fair to this fresh crop of AI companies and budding machine-learning engineers, AI still lacks what often seemed like the naive or cynical business models common to some corners of the crypto industry. Many of those movements and startups resembled multilevel marketing schemes fueled entirely by their own hype.

And many existing companies in this space have been quietly building AI-based solutions to problems for years, and are beginning to establish a record of success.

Mike Tung, chief executive of AI-enabled, business-focused search startup Diffbot, which was founded in 2008, says that one telling sign of the attention focused on AI is that he is seeing many more job candidates reach out to his company than in the past.

Shiv Rao is a cardiologist who is primarily occupied with building his generative AI-powered medical startup Abridge, which records, transcribes and summarizes doctor-patient visits. It’s intended to reduce the amount of after-hours paperwork doctors have to do, and to help patients remember doctors’ instructions.

Abridge was founded in 2018, well before the current hype for generative AI. But the company is benefiting—in terms of investment and interest from potential users—from all the attention focused on AI now, says Zachary Lipton, its chief AI scientist and a Carnegie Mellon University professor.

Part of what’s going on with the talent migration to AI is that layoffs and a refocusing on efficiency at big tech companies are liberating more senior engineers and executives to strike out on their own—aided by generous severance packages. Big tech companies have basically been hoarding talent for the past decade or more, says Mr. Tung, who is hearing from senior employees at these companies who are starting their own companies.

“I’ve had quite a lot of recent meetings with quite a number of high level people at big tech companies who have been frustrated for over a decade by not being able to launch new things,” says Mr. Tung. “But now they are free agents.”

It’s unclear how many of tech’s newly liberated engineers and founders will find a home building AI systems. Startups in this space remain small, and can’t possibly absorb more than a fraction of the tech workers being laid off, says Amit Taylor, founder of TrueUp, a site that tracks tech job postings.

But it’s also likely that, as in technological shifts since time immemorial, many will make transitions into roles that do not exist yet, but are enabled by this new technology. One such job, says Ms. Kimmel, is “prompt engineer.” That’s the person who enters text into a generative AI to get it to create an image, or more text, or just about any other kind of content. Hot new AI startup Anthropic, for example, is currently advertising an opening for a prompt engineer in San Francisco. Starting salary: $250,000.

For more WSJ Technology analysis, reviews, advice and headlines, sign up for our weekly newsletter.

Write to Christopher Mims at christopher.mims@wsj.com

Even tech workers who weren’t casualties of the recent rounds of layoffs that have rocked Silicon Valley are jumping on the AI bandwagon. Among them are refugees from the most recent tech-industry boom to flame out: the crypto craze.

Some AI veterans worry that “artificial intelligence” is in danger of becoming the latest in a string of empty tech buzzwords.

“The people talking about generative AI right now were the people talking about Web3 and blockchain until recently—the Venn diagram is a circle,” says Ben Waber, chief executive of Humanyze, a company that uses AI and other tools to analyze work behavior. “People have just rebranded themselves.”

Of course, the same investors and founders in the AI industry who voice these concerns believe in their own AI tech, and in any application of AI they think can have an impact in the real world. Despite the dangers of AI becoming another hype-fueled bubble, it’s apparent that the shift of talent and funding from tech giants, dead-end Web3 startups, and SPAC-fueled flights of fancy could be exactly the refocusing the tech industry needs.

At the same time, with AI tools more accessible than ever, turning your startup into an “AI” one is as simple as writing a little code to tap into existing services. Those include Google’s BERT or OpenAI’s GPT-3, which Microsoft has embraced to try to beef up its Bing search engine—with notably mixed results.

There’s every incentive for startups to toss a little AI into their pitches, considering that the field is a rare bright spot in a generally poor investment environment for tech startups. Investors last year poured $2.6 billion into 110 generative AI-focused startups in the U.S., according to CB Insights. This year looks to be comparable, says Matt Moberg, a senior vice president at Franklin Templeton Investments.

Even investors who are keen on AI are concerned that the amount of interest in it might lead to the launch of many low-quality startups.

“A lot of investors are saying, ‘I might actually sit out this trend, because if all these companies are going to be built on top of ChatGPT, then it’s harder to find a winner,’ ” says Brianne Kimmel, founder of Worklife Ventures, which invests in early-stage tech companies.

As with the crypto bubble, for every investor who is cautious, there are plenty who are more afraid of missing out on the next Google—or at least the next OpenAI. OpenAI was founded as a nonprofit in 2015 before transforming into a for-profit company in 2019. In January it was in talks for investments that would have valued it at $29 billion despite generating little revenue. Then the company announced it had signed a deal with Microsoft for a multiyear, multibillion-dollar investment.

“It reminds me of pretty much everything else that goes up and down the hype cycle,” says Mr. Moberg. “With this launch of OpenAI we are at peak hype. It was metaverse before that, cannabis before that. Five years ago it was 3-D printing.” 

Founders and employees are responding to this demand from investors, who are creating bubbles as often as they are following trends. Mr. Waber, of Humanyze, says that despite hiring freezes in other areas of tech, many of his customers at large firms are continuing to hire those with skills in data science, which is key to gathering and preparing the data fed into AI models.

Ashley Chang is an example of midcareer switchers who are eager to launch companies. She spent three years at Carta, a company that helps startup employees track and manage their equity stakes in the companies they work for. In September, she left Carta to explore startups in Web3—a catchall phrase for next-generation, distributed-internet technologies like blockchain—but in December decided to launch an AI startup instead. 

Part of what drew her to AI, she says, was that AI could enable her to solve “real-life problems I’ve been working on for a long time.” Her startup, Altitude, makes an AI customer-support tool for e-commerce companies.

This shift is also apparent among more senior engineers, who in some cases are starting the AI companies doing the hiring. In the past year, for example, veterans of both

Meta Platforms

and Google left their roles in those companies’ augmented- and virtual-reality divisions to start their own AI companies.

To be fair to this fresh crop of AI companies and budding machine-learning engineers, AI still lacks what often seemed like the naive or cynical business models common to some corners of the crypto industry. Many of those movements and startups resembled multilevel marketing schemes fueled entirely by their own hype.

And many existing companies in this space have been quietly building AI-based solutions to problems for years, and are beginning to establish a record of success.

Mike Tung, chief executive of AI-enabled, business-focused search startup Diffbot, which was founded in 2008, says that one telling sign of the attention focused on AI is that he is seeing many more job candidates reach out to his company than in the past.

Shiv Rao is a cardiologist who is primarily occupied with building his generative AI-powered medical startup Abridge, which records, transcribes and summarizes doctor-patient visits. It’s intended to reduce the amount of after-hours paperwork doctors have to do, and to help patients remember doctors’ instructions.

Abridge was founded in 2018, well before the current hype for generative AI. But the company is benefiting—in terms of investment and interest from potential users—from all the attention focused on AI now, says Zachary Lipton, its chief AI scientist and a Carnegie Mellon University professor.

Part of what’s going on with the talent migration to AI is that layoffs and a refocusing on efficiency at big tech companies are liberating more senior engineers and executives to strike out on their own—aided by generous severance packages. Big tech companies have basically been hoarding talent for the past decade or more, says Mr. Tung, who is hearing from senior employees at these companies who are starting their own companies.

“I’ve had quite a lot of recent meetings with quite a number of high level people at big tech companies who have been frustrated for over a decade by not being able to launch new things,” says Mr. Tung. “But now they are free agents.”

It’s unclear how many of tech’s newly liberated engineers and founders will find a home building AI systems. Startups in this space remain small, and can’t possibly absorb more than a fraction of the tech workers being laid off, says Amit Taylor, founder of TrueUp, a site that tracks tech job postings.

But it’s also likely that, as in technological shifts since time immemorial, many will make transitions into roles that do not exist yet, but are enabled by this new technology. One such job, says Ms. Kimmel, is “prompt engineer.” That’s the person who enters text into a generative AI to get it to create an image, or more text, or just about any other kind of content. Hot new AI startup Anthropic, for example, is currently advertising an opening for a prompt engineer in San Francisco. Starting salary: $250,000.

For more WSJ Technology analysis, reviews, advice and headlines, sign up for our weekly newsletter.

Write to Christopher Mims at christopher.mims@wsj.com