The AI race is heating up, my friends. It’s not just about being the first anymore, it’s about knowing how to actually use this powerful technology in an effective way. And let me tell you, some companies are really stepping up their game when it comes to deploying AI correctly.
One interesting development I’ve seen is the creation of prompt libraries. Take Johnson & Johnson, for example. They’ve created a whole library of prompts that their staff can use to improve the quality of AI output. And Starbucks is getting in on the action too, creating their own in-house models. It’s all about finding ways to make AI work better, folks.
Now, let’s talk about prompts. These are basically instructions you give to the AI to tell it what to do. You gotta be specific and descriptive, my friends. But here’s the thing, some prompts work better than others. It’s all about finding that sweet spot. Believe it or not, even grandma-style instructions like “think carefully about it” can have a positive impact. Who would’ve thought, right?
Prompt libraries can be a lifesaver, people. They’re like a collection of conversation starters that reduce friction for employees using AI chatbots. Johnson & Johnson is using their chatbot to summarize documents and ask questions. So, they created a whole library of thought-starters to help their employees in different areas of the business. It’s all about making things easier and more efficient.
But that’s not all, my friends. We’ve also got prompts aiming to minimize the risk of AI hallucinating. Yeah, you heard me right. Sometimes AI can produce facts that sound legit but are actually pure fiction. So, companies are creating different libraries for different use cases and expected outputs. It’s all about tweaking those keywords to get the results you want.
Now, don’t be fooled. Sometimes those undesired outputs happen because the AI just doesn’t have the right knowledge. Like, imagine asking an AI why John got hit by a car when it knows nothing about John or the accident. It’s gonna make stuff up, my friends. That’s where prompt engineers come in. They craft the perfect prompt by providing tons of context, tweaking those keywords, and being super specific about what they want. It’s an art, my friends.
But here’s the kicker, even the perfect prompt might not be enough sometimes. Those large language models are trained in a very generic way. That’s where companies like Ernst & Young come in. They’ve created their own in-house AI platform called EY.ai. They work with Microsoft to fine-tune their system and make it secure. It’s all about customization, my friends.
Fine-tuning is a whole different ball game, folks. It requires someone with machine learning experience. You gotta shrink the dataset and make the model focus on a specific function. It’s all about getting those desired outcomes, my friends. And Ernst & Young takes it to the next level by creating a library of embeddings. These are like extra datasets that make the model hyper-specific. They connect the dots, my friends. The tax knowledge, the regulations, the sector knowledge, it all comes together in a beautiful dance of data.
And let me tell you, the future is looking bright. Personalized AI models are gonna be the way to go. Customized in-house models and embedding libraries will be crucial for companies using AI. And as AI gets smarter, the importance of prompts might decrease. But don’t worry, there will always be a place for engineered prompts, like when you need to write a killer job advertisement. It’s a mixed bag, my friends.
So, buckle up because we’re in for an exciting ride. The AI revolution is just getting started, and it’s gonna change the game. Whether it’s prompt libraries, fine-tuning, or customized models, companies are finding ways to make AI work for them. It’s an evolving journey, but I’m confident that we’re heading in the right direction. Stay curious, my friends.
