TinyML: Bringing machine learning to the edge

'Harness engineering' is one of the most significant terms to emerge in software engineering in 2026. Broadly referring to the work done to control unpredictable AI agents and coding assistants, its use signals growing attention on what needs to be done to make agents reliable an ...  Show more

Anthropic Mythos garnered significant attention when it was launched in mid-April 2026. Yet despite it apparently presenting an unprecedented threat to global software, you don't have to look to closely to see that this was an effective product launch as much as a story about the ...  Show more

In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fa ...  Show more

In this episode, we take a closer look at Elon Musk's AI research company, Grok, and its latest development: the addition of an image generation capability called FLUX to its AI model. We discuss the potential implications of this advancement, which combines text and image genera ...  Show more

Catherine Nelson, author of the new O'Reilly book, Software Engineering for Data Scientists, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ...

Jimmy Secretan, CTO of JustWin, explores the latest innovations in privacy-preserving neural networks, and explains how JustWin is leveraging AI to help small businesses win government contracts. He also explores the future directions of AI, and the impact of AI on user autonomy ...  Show more