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Large Language Models (LLMs) are now essential to modern artificial intelligence (AI), enabling machines to understand and generate human language. Their impact is evident across various industries, with estimates suggesting that by 2025, 750 million apps will integrate LLMs. From enhancing customer service with intelligent chatbots to advancing medical research, LLMs are driving efficiency in business operations.

Generative AI has revolutionized the way we approach creativity, allowing anyone with a computer to bring ideas to life through images, music, and more. At the forefront of this revolution is Stable Diffusion, a model that has captured the imagination of developers, artists, and hobbyists alike.

In the dynamic world of IT, change is the only constant. What used to be manual, repetitive, and slow has now become quick, automated workflows that run faster than ever before. IT process automation, previously known as “runbook automation,” has evolved significantly. It started as a simple concept and has become essential in modern IT operations. But how did this transformation happen, and why is real-time automation now imperative for businesses to thrive?

I always find the Olympics to be an unusual experience. I’m hardly an athletics fanatic, yet I can’t help but get swept up in the spirit of the competition. When the Olympics took place in Paris last summer, I suddenly began rooting for my country in sports I barely knew existed. I would spend random Thursday nights glued to the TV, cheering on athletes as they skillfully let fly arrows, disks, hammers and so on.

In the wake of EU drafted legislation and US executive orders, a software bill of materials (SBOM) has gone from a nice-to-have to a fundamental piece of software documentation. In this article, we’ll examine what an SBOM is, what information it must include, and the approaches that developers and manufacturers alike should consider as they start building their SBOM.

Mike Hoy, CTO, Pulsant looks ahead to the next 12 months, identifying some of the challenges organisations are likely to face in delivering AI projects, and highlighting the importance of a resilient, connected infrastructure in meeting these. As AI proofs of concept evolve over the next 12–18 months, they will lay the groundwork for advances in technology.

Kubernetes (K8s) has transformed cloud-native infrastructure, enabling enterprises to build scalable, agile environments. Yet, alongside its benefits, Kubernetes introduces a significant blind spot —a rapidly growing part of cloud budgets that has become more and more difficult to optimize. Excess spend is common, and is caused by incorrectly specified container resources, stranding tremendous amounts of resources while at the same time introducing significant operational risk.

2025 will continue the theme of powerful business and technological transformation under a never-ending barrage of cyber threats that are spawning faster and evolving in more complex ways than ever. To ward off an increasingly sophisticated community of threat actors, we’ll need to innovate faster than the speed of the threat landscape — but how?

From simplifying AI integration and automation to network virtualization and cybersecurity, re:Invent 2024 left us with plenty to think about going into 2025. AWS re:Invent 2024 was a whirlwind. TechRadar reported an estimated 60,000 in-person attendees, and with over 2,000 learning sessions there was no shortage of opportunities to collaborate. Our Megaport booth was buzzing, and we loved connecting with you.