By late 2024, AI was generating roughly 29% of programming functions in the US in the GitHub repositories the researchers analysed.

There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.

Stefan Panourgias, the Managing Director of Composite Consult, delves into the common types of claims in the construction ...

Discover how Singapore's national service work-learn schemes are training young specialists for crucial roles in cyber ...

Anthropic research shows developers using AI assistance scored 17% lower on comprehension tests when learning new coding ...

As his polytechnic peers use their final year to complete internship programmes, Third Sergeant (3SG) Khaimelruzzaman Kamaruzzaman is gearing up to support the national fight against ...

Get the scoop on the most recent ranking from the Tiobe programming language index, learn a no-fuss way to distribute DIY tooling across Python projects, and take a peek at ComfyUI: interactive, ...

While Anthropic’s Claude Code grabbed headlines, IBM has been deploying its own generative AI solution, Watsonx Code Assistant for Z, designed to modernize the very mainframes it built. Unlike general ...

There’s a common assumption that if someone starts learning a language when they are very young, they will quickly become fluent. Many people also assume that it will become much harder to learn a ...

Familiarity with basic networking concepts, configurations, and Python is helpful, but no prior AI or advanced programming ...

NLP offers powerful opportunities to support the UN Sustainable Development Goals (SDGs)—including SDG2 (Zero Hunger). In the ...