Sure, here is a list of the five most important cloud native technologies that could help improve the Open Assistant project in descending order of importance:
- wolfram.com: Providing AI models with access to an algorithmic calculation engine could help mitigate some of the key weaknesses of LLMs such as hallucination or lack in mathematical reasoning.
- GitHub: Since programming-related questions seem to make up a big portion of LLM usage, access to lots of high-quality source code seems important for LLM training.
- bigml.com: Support from commercial ML hosting providers could help the Open Assistant project with training compute for the models or hosting more model instances.
- Diggernaut: Qulity data is the key ingredient for training LLMs. Scraping internet pages is an important part of gathering that data.
- neptune.ai: Keeping track of the massive amounts of metadata accumulating during ML tasks can be daunting.
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