https://huyenchip.com//2025/01/16/ai-engineering-pitfalls.html Common pitfalls when building generative AI applicationsChip HuyenJan 16, 2025 “As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This
What I Read: AI, HCI
https://ianarawjo.medium.com/what-ai-engineers-can-learn-from-qualitative-research-methods-in-hci-5b29b9b7465a What AI engineers can learn from qualitative research methods in HCIIan ArawjoJan 9, 2025 “Meet inductive coding and grounded theory, the new bread-and-butter of LLMOps”
What I Read: impossible languages
https://www.quantamagazine.org/can-ai-models-show-us-how-people-learn-impossible-languages-point-a-way-20250113/ Can AI Models Show Us How People Learn? Impossible Languages Point a Way.Ben Brubaker1/13/25 11:00 AM “Certain grammatical rules never appear in any known language. By constructing artificial languages
What I Read: transfer learning
https://lunar-joke-35b.notion.site/Transfer-Learning-101-133ba4b6a3fa800e8cede11ee3f1c1cd Transfer Learning 101Himanshu DubeyNov 5, 2024 “Let’s understand Transfer Learning in greater detail.”
What I Read: Model Merging
https://planetbanatt.net/articles/modelmerging.html Model Merging and YouEryk BanattAugust 2024 “Model Merging is a weird and experimental technique which lets you take two models and combine them together to get a new model.”
What I Read: optimizing softmax
https://maharshi.bearblog.dev/optimizing-softmax-cuda Learning CUDA by optimizing softmax: A worklogMaharshi Pandya04 Jan, 2025 “Optimizing softmax, especially in the context of GPU programming with CUDA, presents many opportunities for learning.”