If you want a career in AI, learn Python

No, AI will not take your job. Not yet. As I wrote, making the most of artificial intelligence and machine learning (AI/ML) complements, rather than replaces, human creativity. Ironically, the best large-scale language models (LLMs) are probably not necessarily legally trained using copyrighted products of human creativity. In the near future, humans and robots will be able to coexist peacefully.

Still, some industries are adopting AI more aggressively than others, as revealed by the latest 2022 AI Index report from Stanford University’s Human-Centered Artificial Intelligence Lab. Over the past year, virtually every industry has increased investment in AI-savvy talent, with AI-centric job postings from companies in the following industries even higher: Information (5.3%). Professional, scientific and technical services (4.1%). Finance and Insurance (3.3%). If you’re worried about your job, or just want to take advantage of this trend, I have one word for you: Python.

business leads

Until 2014, academia was at the center of the ML universe. no more. Since 2014, a large company has taken the lead in AI/ML, and by 2022, the company has released 32 of his ML models, while academia has released only 3 of his. bottom. Academic institutions can’t keep up with the data, CPU cycles, and money the industry brings.

How much is it? His LLM like GPT-2 cost him $50,000 to train in 2019, while PaLM cost him about $8 million to train and used 360 times the parameters of his GPT-2 (Of course, it was cutting edge at the time). The government could afford to make this type of investment, but the government was primarily concerned with trying (and failing) to regulate LLMs, so the industry filled the void.

In doing so, corporate appetite for AI/ML talent is increasing in nearly every American industrial sector. On average, AI/ML-related job postings surged from 1.7% in 2021 to 1.9% in 2022. all US job listings. Approaching 2% is huge considering AI/ML is unproven in most companies. As mentioned earlier, some industries have a much higher posting rate for jobs that require AI/ML expertise.

Stanford Institute for Human-Centered Artificial Intelligence

Of course, employment is not the only measure of investment, and when it comes to cash, medical and healthcare will lead with $6.1 billion in AI investment in 2022. Fintech ($5.5 billion) is next. These industries make sense given how AI funding is being used. According to the report, companies are using AI in a variety of ways, but the main areas are robotic process automation (39%), computer vision (34%), natural language text understanding (33%), and virtual agents (33%). In terms of use cases, the main adoption in 2022 was optimizing service operations (24%). Other popular ones were creating new AI-based products (20%), customer segmentation (19%), customer service analytics (19%), and enhancing new AI-based products (19%).

what does this mean your work? According to another study conducted by researchers at the University of Pennsylvania and funded by OpenAI, “almost 80% of the U.S. workforce could be affected by the introduction of LLMs on at least 10% of their work tasks. , about 19% of workers may be affected.Make sure at least 50% of their tasks are affected.” Who is at risk? Accountants, mathematicians, interpreters, creative writers, and more. Who is it? More manual labor focused, such as cooks, machinists, and oil and gas factories. (However, electric vehicles may appear in the latter group.)

Of course, this news doesn’t have to be bad. As seen in software development, AI can remove the tedium of certain jobs and free up employees (developers in this case) to focus on higher-value tasks. For those looking to advance their potential in this AI-driven future, the Stanford report singles out one technology over the other. It’s Python.

The Holy Grail of Python and AI

The impact of Python on data science should come as no surprise. As I wrote in 2021, “The most dominant language is [data science] It is the one that is most accessible to the widest range of people within the enterprise. ’ A year later, this was still true. “As organizations look to more diverse groups to help with data science, Python’s appeal to the masses will be an easy entry point.” is becoming increasingly common language among

In the Stanford report, Python stands out for both its relative and absolute growth compared to other required skills.

Stanford Institute for Human-Centric AI

There are several reasons why Python continues to reign supreme in data science in general and AI/ML in particular. Python helps reduce the complexity inherent in AI/ML by providing a powerful set of libraries that simplify development. It’s also simple, consistent, and has a clear, human-readable syntax that lowers the learning curve. Python also comes with a broadly welcoming community that allows developers to be productive faster and run on almost any platform they want to use.

Yes, given the ability of machines to do things more efficiently than humans, AI may make some of your jobs obsolete. There should be plenty of opportunities to embrace and extend it to meet your (and your employer’s) needs using Python and other tools.