Group 1 - The core viewpoint is that large language models (LLMs) are not a universal solution, and the future will see more customized and specialized models that address specific problems [1][2] - The current focus and funding are heavily concentrated on the idea of building a "universal model" using vast computational resources, but the reality is that smaller, specialized models will emerge to effectively solve different issues [2] - The potential bursting of the LLM bubble may have limited impact on the company, as the AI industry is large and diversified, meaning that even if the sector is overvalued, it will not significantly affect the overall industry or its business [3] Group 2 - Hugging Face has adopted a cautious spending strategy, with half of the $400 million raised still in the bank, contrasting sharply with the "burn rate" of other AI companies, particularly in the large language model space [3] - The company aims to build a "long-term, sustainable, and globally impactful" business, learning from past industry cycles where many practitioners are eager for quick results and act with a short-term perspective [3]