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As 2022 winds down, some might say mercifully, VentureBeat readers are clearly thinking ahead. Whether you’re hiring to fill skills gaps or looking to find your next opportunity, you flocked to Drew Robb’s look at the hottest IT skills 2023, which dominated the top 5 list, garnering twice as many visits as the other four top stories combined. Robb not only includes the skills that are in demand, but adds the certifications that verify those skills.

Is there an artificial intelligence (AI) divide? That is, are only large enterprises positioned to take advantage of the insights and innovations offered by AI? Maybe. Once. But the emergence of AI-as-a-service (AIaaS) is making the technology accessible to smaller companies without requiring them to build their own systems from scratch.

Looking ahead again to 2023, our third most-read story this week is Sharon Goldman’s look at 23 AI predications for the coming year, ranging from “generative AI will transform enterprise applications” to “AI will empower more efficient devops.” Be sure to check out the other 21.

Ashleigh Hollowell notes that 2022 was a big year for AI in healthcare, citing specific advances by GE Healthcare and Siemens. So why, she asks, do 50% of U.S. adults say they haven’t seen or experienced improvements in their own care as a result of medical AI advancements?

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Holding down the 5th spot is Ben Dickson’s look at why 2022 was an eye-opening year for AI and deep learning.

Here are the top five stories for the week of December 26th.

The hottest IT skills for 2023 – even in a recession

For many of the hundreds of thousands who’ve been laid off by tech companies recently, this might well be considered, to borrow the words of Charles Dickens,  the worst of times — especially with a recession looming. Yet there are plenty among them, and others in the workforce, who could consider this the best of times.

Why? Because they possess the most in-demand skillsets and certifications. Despite the layoffs, cutbacks, tightening purse strings, and general doom and gloom presented in the media, these IT professionals can look forward to higher pay, plenty of offers, perpetual headhunting inquiries and even the occasional bidding war for their talents.

AI-as-a-service makes artificial intelligence and data analytics more accessible and cost effective

AIaaS is becoming an ideal option for anyone who wants access to AI without needing to establish an ultra-expensive infrastructure for themselves. With such a cost-effective solution available for anyone, it’s no surprise that AIaaS is starting to become a standard in most industries. An analysis by Research and Markets estimated that the global market for AIaaS is expected to grow by around $11.6 billion by 2024.

23 AI predictions for the enterprise in 2023

It’s that time of year again when AI leaders, consultants and vendors look at enterprise trends and make their predictions. After a whirlwind 2022, it’s no easy task this time around.

You may not agree with every one of these — but in honor of 2023, these are 23 top AI and ML predictions experts think will be spot-on for the coming year.

Healthcare AI is advancing rapidly, so why aren’t Americans noticing the progress?           

There’s no doubt that AI in healthcare had a very successful year. Back in October, the FDA added 178 AI-enabled devices to its list of 500+ AI technologies that are approved for medical use. Topping the list for most approved devices were two massive players in the healthcare technology space: GE Healthcare, with 42 authorized AI devices, and Siemens, with 29. 

However, despite the leaps and bounds made in the field thanks to these two giants, a recent survey from medical intelligence company, Bluesight, found that regardless of actual advancements made, around 50% of U.S. adults say they have not seen or experienced improvements in their own care as a result of medical AI advancements

What we learned about AI and deep learning in 2022

It’s as good a time as any to discuss the implications of advances in AI. 2022 saw interesting progress in deep learning, especially in generative models. However, as the capabilities of deep learning models increase, so does the confusion surrounding them. On the one hand, advanced models such as ChatGPT and DALL-E are displaying fascinating results and the impression of thinking and reasoning. On the other hand, they often make errors that prove they lack some of the basic elements of intelligence that humans have.

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