Название: Upskilling AI Professionals: Defining Skills and Identifying PitfallsАвтор: Thomas Nield
Издательство: O’Reilly Media, Inc.
Год: 2024-07-10
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB
The world of Artificial Intelligence (AI) is in constant flux. Amid this barrage of rapidly evolving information, today's professionals often find it challenging to identify crucial skills and prioritize their learning. To thrive, you need clear, actionable guidance that cuts through the clutter, enabling you to effectively upskill in the AI landscape.
In this indispensable report, author Thomas Nield offers vital tools for any AI professional looking to make informed decisions about their skill development. It delivers strategic insights into selecting impactful projects and skills, ensuring that your learning translates into real-world solutions.
Artificial intelligence is a unique opportunity for businesses. Never have we had so much data at our disposal thanks to the events following the dot-com boom, the rise of mobile and connected devices, and the scalability of computing and storage. All this has created a renaissance in the AI space. Neural networks, researched as early as the 1950s, came back into the limelight with this availability of data and computing hardware. Breakthroughs in computer vision happened shortly after, in 2014, and then large language models (LLMs) and generative AI after 2020.
However, the availability of these new tools has put business leaders in a potentially awkward position. There is opportunity, and indeed pressure, to develop AI talent and continue to upskill these employees to add value to the business. The great news is that plenty of tools and resources are readily available, so anyone can become an expert with enough commitment. But undertaking this journey is easier said than done. There are many types of AI products and services for sale, and they all require different skills and serve different talent roles. Discerning these differences allows us to avoid many pitfalls and fallacies in developing talent. After all, an “AI expert” can be anyone from a deep learning researcher to a prompt engineer—or even an operations research specialist who never touches a neural network.
This report is written for business and technology professionals looking to upskill for the artificial intelligence boom, as well as executives seeking to upskill their teams. From reading this report, you will learn how to frame skill objectives toward specific outcomes and how upskilling is best started with a problem definition. We will also talk about different areas that translate to different skills needs and what specialties you might want to lean into.
By the end of this report, you'll:
Discover strategic approaches to AI skill acquisition
Understand the realistic capabilities and limitations of AI
Learn to identify and sidestep common pitfalls in AI projects
Find effective methods for keeping pace with rapid technological advancements
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