If l have been blinded side it’s not my intention But the value of community is key And conversations of sharing Finding your feet Help with teaching and understanding of complexities Setting up clones Experts at Hand Dean/ Tony and the many many more in our community Learning a new language connections in and out Makes every day a better one from the last YOU ALL ROCK

One nuance we ran into with food recognition specifically is that ingredients rarely appear in a clean, “textbook” state. In the real world, ingredients are sliced, diced, mashed, squeezed, crushed, cooked, or partially combined. That meant we had to train the model to recognise ingredients across many different forms and states, not just whole items. The biggest challenge wasn’t the concept, it was volume and variety: a lot of ingredients, in a lot of conditions, across a lot of images. It reinforced how important real-world data is versus idealised datasets when you want recognition to actually work day-to-day. Curious how others handling vision models deal with highly variable inputs like this.

Thank you, Tony, Dean, and Igor, for such high-quality training. The idea of creating a clone, much less actually doing it, has been mind-blowing. I even asked my clone the "what do you know about me" question that Igor discussed. The information opened up content-creation ideas I would never have thought of on my own. Your training and heart are classy, high-quality, and so user-friendly! I thank God I chose to participate in the AI Advantage! I have so much to learn, and I'm so grateful I can go back to the replays and keep trying.