According to a CNBC report, some AI specialists from big tech companies like Amazon, Google, and Microsoft, as well as from start-ups, are feeling enormous pressure to deliver AI tools at a breakneck pace.
This pressure is now driving their work, sometimes forcing them to work on "nonsense" projects just to impress investors or managers, without solving real problems.
Ethical concerns, testing, and accuracy are being pushed aside in the race to compete with OpenAI, the report says.
Burnout is becoming an increasingly common problem as employers pursue projects without considering the technology's potential real-world impact on issues such as climate change and surveillance.
Developers report accelerated timelines, a rush to keep up with competitors' announcements, and a general lack of interest from superiors in the actual benefits and implications of generative AI - all in the name of speed.
One Amazon engineer told CNBC about having to write thousands of lines of code for new AI features in an environment with no testing, which can lead to buggy code and middle-of-the-night phone calls to fix pieces of AI software.
Amazon told CNBC that this was the opinion of a single employee and not representative of everyone's experience at the company. But the news outlet claims to have identified a general industry trend through conversations with numerous sources and experts in the field.
One Microsoft AI engineer spoke of an "AI rat race" in which the company is compromising ethics and safety in favor of speed, leading to hasty rollouts without sufficient consideration of the consequences.
Another Microsoft representative said that many tasks serve only to generate "AI hype" without any practical benefit, with non-AI solutions being sidelined in favor of less efficient, more expensive, and slower LLM approaches.
An AI specialist at Google also complained about increasing pressure, workload, and speed despite staff reductions. Microsoft and Google declined to comment on the CNBC story.
A software engineer at a large Internet company described much of the current work in generative AI as "extreme amount of vaporware and hype," with major changes in direction every two weeks but everyone ultimately building the same thing.
Demos are put together in a matter of weeks for management and investors, and then never touched again. "It's a big pile of nonsense," the engineer said.
