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Wes Streeting has been accused of taking a “chaotic and incoherent approach” to reforming the NHS which makes it unlikely the government will hit its own targets, according to a damning report by the Institute for Government (IfG).
The report praises elements of how the health secretary has managed the health service in his first year in office, including improving performance and staff retention in hospitals. Thepay settlement he reached with resident doctors last year avoided a winter plagued by NHS strikes
It’s not too late to break into AI — and it doesn’t really matter where you’re coming from.
That’s what Business Insider learned while speaking to dozens of people working in AI, from recent college graduates to mid-career job switchers to those on the cusp of building their own AI companies.
Their stories took us from India and Singapore to Silicon Valley and Sydney, and demonstrate that there are myriad paths into this booming space.
We broke the routes of entry into four categories — graduating, transitioning, pivoting, and DIYing your way into AI — and asked people to share candid advice, fears, challenges, and takeaways they’ve learned about working with this emerging technology. Below are 16 of their tales to help you chart your own AI career path.
Have your own story to share? Fill in this quick form to share more about your journey with Business Insider readers.
Graduate into AI
Ready to land a job in AI right out of college? We’ve got you covered — we spoke to four people who landed their first AI jobs either while they were still students or immediately after graduation.
Transition into AI
Not every job change has to be a drastic one. We spoke to four people who transitioned into AI roles from jobs in tech or after dipping their toes into finance.
Make the pivot of a lifetime
Then again, some career pivots are the pivot of a lifetime. We spoke to people who gave up music careers, medical careers, and walked away from other industries after years of work, all to get into AI.
Build it yourself
Not inspired by any company out there? Go ahead — build it yourself. We spoke to four people who have founded their own AI companies.
Alex Broadway/Sportsfile for Web Summit via Getty Images
Alex Schultz, Meta’s CMO, says the AI spending boom is “aggressive, but not crazy.”
Meta’s AI investments have driven billions in revenue and enhanced its content ranking systems.
Schultz said the AI wave has prompted productive conversations about energy.
Meteoric levels of investment in AI infrastructure have sparked concerns that Big Tech’s latest boom is veering into bubble territory. So, is Meta, along with the rest of Silicon Valley, overspending on AI?
“Clearly no Meta executive would ever answer that question with a ‘yes,'” Alex Schultz, Meta’s CMO and VP of analytics, said in an interview with Business Insider at the Web Summit tech conference in Lisbon this week.
Meta plans to spend up to $72 billion this year on AI infrastructure, and has said spending will climb higher next year. CEO Mark Zuckerberg said this year that he’d rather risk “misspending a couple of hundred billion dollars” than be late to the development of superintelligence. Amazon, Google, Microsoft, and privately held AI companies like OpenAI are logging record-breaking capital expenditures on all things AI. That includes chips and data centers, as well as big salaries to attract and retain top AI research and engineering talent.
There are eyewatering sums of money at play, but Schultz said that, compared to historical bubbles, the current trend is not huge as a percentage of the sector’s market capitalization or revenue. Compared to the US railroad bubble of the late 19th century, “it seems aggressive, but not crazy,” said Schultz of the current AI boom.
In an October research note, Goldman Sachs analysts estimated that AI-related investment in the US is under 1% of GDP, compared with the 2% to 5% of GDP reached during earlier technology booms, including the railroad expansion.
Schultz said Meta’s AI investments are already translating into billions of dollars in revenue for the company, as they improve its advertising tools and content ranking algorithms. Meta is expected to ring in around $200 billion in revenue this year and is trading at a market cap of about $1.5 trillion.
Schultz said the biggest AI-powered revolution for Meta has been its more sophisticated content recommendation system. He said this was necessary because the majority of time spent on Facebook and Instagram now is people looking at “unconnected content” — content that isn’t from a friend, or from a page or group you actively follow.
“If we hadn’t made that pivot, how much smaller would we be as a company today?” Schultz said. “We managed a massive disruption without becoming irrelevant, and it is incremental to our business.”
Schultz said the Meta AI app’s newly released Vibes feed — a feed of short-form, purely AI-generated video content — represents “probably a large chunk of the future” for the company and has demonstrated “good retention” of users so far once they use it. (Vibes has been panned by many online as “AI slop.”)
Video-generation models require more computing power than text or image ones, creating huge energy demands that have the potential to strain power grids and water supplies. The popularity of apps like OpenAI’s Sora has sparked questions about whether the entertainment value is worth it for the environmental trade-offs.
“Vibes isn’t that big — it’s not draining lakes or using multiple nuclear power stations,” Schultz said. He added that it’s one of many experiments the company is working on to train and learn from its AI models.
“There’s sort of this Western European Calvinist streak to society that’s like, doing nice things that are fun is not what life’s about,” Schultz said. “And life is about doing nice things that are fun, and we do all the other stuff so that we can do nice things that are fun.”
The AI wave has prompted what Schultz described as productive conversations about the safety of nuclear power stations and the use of desalination plants to produce freshwater from seawater.
“In general, humanity has the ability to have a lot more abundance than it does,” Schultz said.
The “Wolverine” star was spotted in Muncie, Indiana on Friday outside the Delaware County Sheriff’s station, where a memorial was set up for fallen Corporal Blake Reynolds.
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Eli Lilly CEO David Ricks says AI helps him stay up to date on the latest science.
Ricks said OpenAI’s ChatGPT is “too verbal” for those types of queries.
He wants something that is “more terse” and more reliable with its references.
Eli Lilly CEO David Ricks says he uses AI in every meeting he attends.
“I read a lot of medical journals. I go to conferences where data is presented,” Ricks told Stripe cofounder John Collison during a recent episode of Collison’s “Cheeky Pint” podcast. “I spend time with our scientists to stay curious. Yeah, now I have at least one or two AIs running every minute of every meeting I’m in, and I just am asking science questions.”
Ricks said he doesn’t like OpenAI’s ChatGPT for science-related questions — “It’s too verbal,” he said. Instead, he prefers Anthropic’s Claude and xAI’s Grok. Still, he has to be careful to watch for halcunications, an issue the frontier model companies are still trying to tamp down.
“I find it more terse and the references actually check out more often,” he said. “Sometimes the AIs produce references, and they’re actually not the thing that it said, and that takes too much work to go cross-reference.”
xAI CEO Elon Musk quickly took notice of the praise.
“Cool that David Ricks uses @Grok as his daily AI advisor,” Musk wrote on X.
Ricks is just the latest big-name CEO to reveal his AI diet. Microsoft’s Satya Nadella said he uses Copilot to summarize his Outlook and Teams messages after reaching Microsoft’s Washington headquarters. Nvidia CEO Jensen Huang said he uses AI as a tutor.
Lily has been on a tear this past year, with shares up roughly 31%. The drugmaker has capitalized on sales of its GLP-1 weight-loss drug Zepbound and diabetes treatment Mounjaro.
AI still has a way to go when it comes to helping drug development, Ricks said.
“Probably we need to create the equivalent of what got created with human language, which is a more complete repository of biological knowledge to train against before the machines get a lot better,” he said. “And today, I don’t know, I would estimate we might know 10 to 15% of human biology, so the machine is not going to be good at all until we get way above 50%.”
To even reach that point, Ricks said there would need to be a significant investment in robotics to create the training data needed to teach AI.
“That probably requires robotic 24/7 experiments just to create training data sets and this kind of big lift effort, the kind of thing actually NIH should be doing right now, I would think,” he said. “But that effort’s not ongoing, at least in our country.”
