I’ve spent the past few months experimenting and researching here and there with tiny and small language models, e.g. running log analysis on edge devices, processing audio in remote locations where connectivity is spotty, power is low and the environment harsh. They’re fast, efficient, and honestly? Pretty fun to work with and research. But lately, I’ve caught myself asking: Am I actually solving a problem here – or just doing something because it’s technically interesting? If you’re working with AI in any capacity, you’ve probably felt this tension too (and to be honest, sometimes because something is technically interesting, that can be a good enough reason for personal research).
Tag: #BusinessStrategy
Stay Focused: You’re Solving a Business Problem, Not Chasing the Next AI Trend
Being immersed in the world of AI can feel like being caught in a whirlwind, every week brings a new model, a fresh feature, or a must-try tool and the pace is not slowing down – it’s easy to get swept up in it all. That’s why I always value conversations with businesses that bring things back to what really matters, solving real problems. GenAI isn’t just the latest shiny object, it’s a powerful tool to unlock capacity and drive real value, when focused on a business problem.
Canada’s AI Legislative Landscape: Navigating the Future.
As artificial intelligence continues to reshape industries globally, Canada finds itself at a critical point in AI regulation. With the recent appointment of Evan Solomon as Canada’s first-ever Minister of Artificial Intelligence and Digital Innovation, we are seem to be charting a new course that prioritises economic growth while maintaining responsible oversight. Where does this leave organisations that are eager for clarity and direction in an increasingly complex global and asymmetrical regulatory environment?
GenAI’s Hidden Risk: Doing the Same Work Faster and Falling Behind – Move from the To-Do list to the Should-do list.
I’ve seen it in so many organisations, that growing pile of Should-Do projects gathering dust while teams scramble through endless To-Do lists under the pressure of everyday work. The story is always the same: “We’d love to explore that new product”, “We should really improve our staff on-boarding”, “We could really improve our end-user experience if only we …..”. The constraint? Never enough time, budget, or human intellectual capital.
Generative AI is about to hand you back some of that capacity (and capability) – what you do with it will determine whether you’re leading your market in the future or wondering what happened to your competitive edge.
Why Deep Research AI Models Are the New Power Tool for Business Professionals
I wrote about Deep research models back in February and since then I have been actively integrating them into my business processes (both ChatGPT and Gemini version) and I thought the subject was worth revisiting in more depth. For me they have made a huge difference in everything from developing strategic plans to pre-meeting research.
Is Your Data ‘Good Enough’ for Generative AI decision making? Spoiler: It Might Be!
Generative AI (GenAI) is promising to reshape how we work and innovate. Yet, many organisations hesitate, wondering, “Is our data perfect enough?” However, perfection often isn’t the prerequisite you think it is.