Skills with artificial intelligence, machine learning, and large language models are very much in demand across a variety of industries.
No, AI isn’t going to take your job. Not yet anyway. As I’ve written, the best uses of artificial intelligence and machine learning (AI/ML) complement human creativity rather than supplant it. Ironically, the best large language models, or LLMs, are trained, perhaps not always legally, using the copyrighted products of human creativity. People and robots are going to peacefully coexist for the foreseeable future.
Even so, some industries are more aggressively embracing AI than others, as revealed in the newest 2022 AI Index Report from Stanford’s Institute for Human-Centered Artificial Intelligence. During the past year, virtually every industry has increased its investments in AI-savvy people, with even higher AI-centric job postings from companies in the following industries: information (5.3%); professional, scientific, and technical services (4.1%); and finance and insurance (3.3%). If you’re worried about your job or simply want to capitalize on this trend, I have one word for you: Python.
Business leads the way
Until 2014, academia was the center of the ML universe. No more. Big business has led the AI/ML charge since 2014, and in 2022, businesses released 32 ML models while academia released just three. Academic institutions can’t keep pace with the data, CPU cycles, and money that industry brings.
[ When the robots come: ChatGPT and the ethics of AI ]
How much money? Well, while an LLM like GPT-2 cost $50,000 to train back in 2019, PaLM cost roughly $8 million to train, with 360 times more parameters than GPT-2 (which, of course, was cutting edge for its time). Governments could afford this kind of investment, but governments have mostly been concerned with trying (unsuccessfully) to regulate LLMs, so industry has filled the void.
Python’s impact on data science shouldn’t be a surprise. As I wrote back in 2021, “the language most likely to dominate [data science] is the one that is most accessible to the broadest population within the enterprise.” A year later, this was still true: “As organizations look to a more diverse group to help with data science, Python’s mass appeal makes for an easy on-ramp.” More and more, Python is the lingua franca for experts and novices alike as they dive into data science.
