Maybe there is a misconception about what his blog is about. You should treat it more like a YouTuber reporting, not an expert evaluation, more like an enthusiast testing different models and reiterating some points about them, but not giving the opinions of an expert or ML professional. His comment history on this topic in this forum clearly shows this.
It’s reasonable that he might be a little hyped about things because of his feelings about them and the methodology he uses to evaluate models. I assume good faith, as the HN guidelines propose, and this is the strongest plausible interpretation of what I see in his blog.
It probably depends on the definition of "expert" here. Based on my definition, experts are people who write the LLM papers I read (some of them are my colleagues), people who implement them, people that push the field forward and PhD researchers blogs that go into depth and show understanding of how attention and transformers work, including underlying math and theory. Based on my own knowledge, experience (I'm working on LLMs in the field) and my discussions with people I consider experts in my day job I wouldn't add you to this category, at least not yet.
Based on my reading of some of your blogs and reading your discussions with others on this site, you still lack technical depth and understanding of the underlying mechanisms at what I would call an expert level. I hope this doesn't sound insulting, maybe you have a different definition of "expert". I also do not say you lack the capacity to become an expert someday. I just want to explain why, while you consider yourself an expert, some people could not see you as an expert. But as I said, maybe it's just different definitions. But your blogs still have value, a lot of people read them and find them valuable, so your work is definitely worthwhile. Keep up the good work!
Yup, I have a different definition of expert. I'm not an expert in training models - I'm an expert in applications of those models, and how to explain those applications to other people.
AI engineering, not ML engineering, is one way of framing that.
I don't write papers (I don't have the patience for that), but my work does get cited in papers from time to time. One of my blog posts was the foundation of the work described in the CaMeL paper from DeepMind for example: https://arxiv.org/abs/2503.18813
If you dont mind answering, is there any implication of not getting preview access if you are negative or critical? Asking because other companies have had such dynamics with people who write about their products
It’s reasonable that he might be a little hyped about things because of his feelings about them and the methodology he uses to evaluate models. I assume good faith, as the HN guidelines propose, and this is the strongest plausible interpretation of what I see in his blog.