Artificial intelligence engineers at top tech companies told CNBC that the pressure to roll out AI tools at breakneck speed has come to define their jobs.
There went the weekend. The AI engineer bailed on his friends, who had traveled from the East Coast to the Seattle area. Instead, he worked day and night to finish the job. A common feeling they described is burnout from immense pressure, long hours and mandates that are constantly changing. Many said their employers are looking past, AI's effect on the climate and other potential harms, all in the name of speed. Some said they or their colleagues were looking for other jobs or switching out of AI departments, due to an untenable pace.
In an emailed statement to CNBC, an Amazon spokesperson said, the company is "focused on building and deploying useful, reliable, and secure generative AI innovations that reinvent and enhance customers' experiences," and that Amazon is supporting its employees to "deliver those innovations." "It boils down to the pace at which it felt like you had to ship and perform," said Gu, who left Apple a year ago to join AI startup Imbue, where he said he can work on equally ambitious projects but at a more measured pace.Microsoft CEO Satya Nadella speaks as OpenAI CEO Sam Altman looks on during the OpenAI DevDay event in San Francisco on Nov. 6, 2023.An AI engineer at Microsoft said the company is engaged in an "AI rat race.
There's also the conference schedule. AI teams had to prepare for the Google I/O developer event in May 2023, followed by Cloud Next in August and then another Cloud Next conference in April 2024. That's a significantly shorter gap between events than normal, and created a crunch for a team that was "beholden to conference timelines" for shipping features, the Google engineer said.The sentiment in AI is not limited to the biggest companies.
A software engineer at a major internet company, which the person asked to keep unnamed due to his group's small size, said the new team he works on dedicated to AI advancement is doing large language model research "because that's what's hot right now."
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