The Hottest 3 Letters in Generative AI Right Now Are Not LLM
How to take generative AI prompts to the next level with retrieval augmented generation, or RAG.
How to take generative AI prompts to the next level with retrieval augmented generation, or RAG.
Off-the-shelf LLMs pull in data from all over the internet. That can be a good thing, except when it’s not.
Generative AI is laying the foundation for a new kind of app: super intelligent assistants that can do the work of hundreds — or even thousands — of individual applications based on a simple prompt.
Using existing interaction patterns and focusing on accessibility and inclusion are key.
AI and generative AI are helping create a variety of new careers, from prompt engineer to AI trainer. Here are 12 new and upcoming roles, and tips for how to prepare for them.
Data is your most important strategic asset; don’t let your team stumble with improper prep.
Large language models are the foundation for today’s groundbreaking AI applications. Instead of training an LLM on a massive dataset, save time by using an existing model with smart prompts grounded in your data. Here’s how.
Most companies will not build their own LLM. We’re sharing the universal challenges of off-the-shelf LLMs and how to address them.
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