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In a Training Loop 🔄

NJX-njx PRO

NJX-njx

AI & ML interests

AI infra, large model architecture, intelligent agent,evaluation

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posted an update about 1 hour ago
Recently, I've come across some practices in the community where skills empower intelligent agents, and I'd like to share my thoughts on the future of agents inspired by these practices. https://huggingface.co/blog/custom-cuda-kernels-agent-skills Hugging Face (hf) recently created a skill related to kernels and achieved good results in two tests. We know that AI infrastructure is actually a relatively high-threshold task that requires considering many variables and pursuing ultimate performance. However, when we internalize the skills in this field into a single skill, it truly brings about tremendous changes. Perhaps we need to refocus our attention on this function. Currently, many of our AI products spend a lot of effort on redundant tasks such as prompt engineering and workflow building. But when these AI products are being developed, they fail to consider that the essential capabilities of large models (context, memory, collaboration, logical reasoning) are actually constantly improving. We don't really need these complex tasks. I believe that "great truths are simple" is the only solution. Currently, most tasks can be accomplished with a command-line tool, a skill, and one or more large models. There's no need for any other complex logic—just bash. Maybe there aren't that many things we need to do right now. Find a sufficiently vertical field, internalize the knowledge within that field into a skill (which can also take other forms), create interfaces for any channels you can think of in the form of command lines, and allow AI to thrive in as many tasks as possible. Then leave everything to AI. The power of bash is beyond your imagination. @AdinaY@burtenshaw@clem@evalstate
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