Tech professionals want to go further with AI

25% of software developers want to improve their AI and machine learning capabilities, but hurdles to achieving this remain.

  • 4 months ago Posted in

Research from STX Next, Europe’s largest software development company specialising in the Python programming language, has found that 29% of developers have completed courses in AI and machine learning (ML), making it the third-most popular area for training behind web development (67%) and software development (65%).

Despite this, only 6% expect to see more AI or ML tools and functionality in future versions of Python, underlining how more needs to be done to support software developers in their current and future AI and ML projects.

The findings were taken from STX Next’s 2023 Python Tech Radar report, which collected insights from a range of Python developers. Other key figures include:

•17% of respondents see AI, ML, data engineering and data science as the next big things in Python, ranking higher than any other area, including performance (15%)

•36% are undecided on what the next big things in Python will be, but are curious to find out

•25% want to enhance their AI and ML skills, only ranking behind more established areas such as software architecture (76%), software development (52%) and leadership (28%)

Ronald Binkofski, CEO at STX Next, said: “Stories about AI are dominating the news schedule at the moment, with much of the debate focusing on the future of the technology and whether regulation is needed to keep its progress under control.

“In any case, AI and ML are here to stay; there is a strong appetite among software developers for building and growing their skills in this area, and they recognise its potential in helping them complete more innovative and ambitious projects.

“However, there is still some ground to make up to ensure that developers have the tools at their disposal to elevate their skills to a new level. Despite Python’s status as the go-to programming language for AI research and the practical application of ML and data science, it still has room for improvement in terms of functionality.”

“To meet this demand, future updates to Python – and other popular programming languages – should focus on implementing improved AI and ML tools as a matter of course. Updates to other areas such as performance and security are always crucial, but making it easier to carry out AI-related projects has to be a priority from now on as well.”

Binkofski concluded: “On a more general level, it’s also vital that developers are given the training they need to deepen their AI and ML skills, outside of the programming process itself. If organisations emphasise holistic training for their employees in this area – covering everything from wider AI-related concepts, all the way through to the intricacies of coding for AI – they will set themselves up for a successful future.”

Dataiku has unveiled at its Everyday AI Conference in New York, the LLM Mesh, addressing the critical need for an effective, scalable, and secure platform for integrating Large Language Models (LLMs) in the enterprise. In addition, Dataiku is joined in this announcement by its LLM Mesh Launch Partners Snowflake, Pinecone, and AI21 Labs.
First-of-its kind GPU Stack with public and private Container Registry provides full AI application lifecycle management from anywhere in the world.
Report indicates a complex tech environment for R&D and IT, key barriers to address, and investment priorities for next 12 months.
IT leaders report a significant impact to customer value, employees’ well-being, and enterprises’ return on AI investments.
Leading intellectual property firm reveals soaring AI patent applications across Europe as use cases for AI increase in the physical economy.
The report also reveals the impact of poor Digital Employee Experience on workers, 57% report serious friction with work tech at least weekly and 61% say negative experiences with work tech impacts morale.
Together, Cisco and Splunk will help move organizations from threat detection and response to threat prediction and prevention.
Intel presents a software-defined, silicon-accelerated approach built on a foundation of openness, choice, trust and security.