AI feels like it’s everywhere right now, dominating headlines, conversations, and virtually every startup pitch. But attending WebSummit Vancouver last week provided me with a quiet yet impactful moment that made me reconsider what I truly understand about AI, and more importantly, what might still be hidden beneath the surface.
One thing became clear. AI might be everywhere, but genuine understanding of its practical use (and its limitations) is still evolving. Many pitches claim revolutionary AI solutions that are just improved workflows.
Beyond the hype, three critical conversations stood out at WebSummit. Call them the three S’s—security, scalability, and semantic understanding.
The first two are familiar challenges, but semantics is the one that’s quietly becoming essential. AI tools today still struggle to grasp the real-world context and the nuanced meaning that humans intuitively understand. That context gap means AI isn't yet ready to handle complex projects independently.
This gap echoed clearly during our recent BitBakery AI hackathon. We experimented with a variety of new tools that helped us quickly build usable prototypes.
We also discovered firsthand that AI requires skilled human developers and designers who have a deep understanding of users and their context. AI might generate great ideas and initial frameworks, but it takes human insight to turn them into genuinely impactful solutions.
AI is rapidly advancing, but real breakthroughs will depend on how well we bridge the semantic gap. I'm excited to keep exploring this balance at BitBakery and to share what we learn with you.
What gaps or opportunities are you overlooking in your AI journey? Let's talk.
- Wes
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