Our books: https://www.nownextlater.ai/aibooks Our Insights: https://www.nownextlater.ai/Insights/ Our AI Academy: https://www.nownextlater.ai/AIAcademy 01:16 Search 02:07 Conversational Aid 03:45 Summarization 03:55 Background Knowledge 05:22 Education 07:19 Coding 09:10 Brainstorming 09:26 Writing Aids 10:25 Fiction Writing 13:13 Defining Your Use Case

Hey there! It's Inês here. I work with businesses on generative AI. Here's something I've observed: - Some leaders are very enthusiastic, seeing huge potential for productivity gains with AI . - Others are cautious, concerned about issues like "the bots hallucinate" and prefer to wait. It's crucial to strike a balance. I recently hosted a webinar where I discuss the real workings of these AI models, what they can and can't do, and how best to approach them. Simple, but informed insights. ⁠ http://www.nownextlater.ai⁠

There are many variables to consider when defining our Generative AI strategy. Having a clear understanding of the use case/business problem is crucial. However, a good understanding of benchmarks and metrics helps business leaders connect with this new world and its potential.

So whether you are intending to: 

• select a pretrained foundation LLM (like OpenAI's GPT-4) to connect via API to your project, 
• select a base open-source LLM (like Meta's Llama 2) to train and customize, 
• or looking to evaluate the performance of your LLM 

the available benchmarks are crucial and useful in this task. In this video we will explore a few examples.