The Wall Street Journal’s Post

🔧 AI isn't just hype – it's a game-changer for the industrial sector. However, to leverage the potential of AI and avoid projects ending up as mere proof-of-concepts, with investments failing to pay off, businesses need a clear understanding of how AI can create value in their organisation. My colleagues at Zühlke share practical insights and real-life use cases of how AI is driving efficiency and cost savings. From enhancing R&D documentation to enabling predictive maintenance, discover how these applications can benefit your projects. Dive into the blog post and let's discuss how we can integrate these innovative solutions into your work. #AI #LLM #industry #ChatGPT

This week on Explain Yourself we will ask ChatGPT to tell us about the most common applications of AI in each sector.

I just read an insightful article discussing the future of AI and the rise of smaller, specialized LLMs. As we witness the incredible capabilities of models like ChatGPT and Gemini, it's important to recognize that their limitations and potential for "hallucinations" have sparked a shift towards more precise LLMs. Specialized LLMs offer several advantages over their general-purpose counterparts. They require fewer hardware resources, making them more efficient and cost-effective. Companies can build their own models with focused datasets, reducing the barrier to entry and enabling tailored solutions for specific tasks. Check out this article and see for yourself! Let's embrace the future of AI with these smaller, specialized LLMs that empower us to achieve remarkable results. #GenerativeAI #LLMs #Deployment

The difference between the open ai chat completion api and the assistant api: You can use the assistant api to create a model where you can tell it how to behave and what its purpose is. You can give it knowledge through files that you want the ai to use (can be proprietary company knoledge). You can call functions to retrieve data that the ai will use when calculating its response. Assistant api also utilizes thread history of your users as they use the ai. The chat completion ai is a general knowledge model. It is simpler to use but you dont have as much control over how it behaves.

AI is getting insane you can build an AI chat bot in seconds that knows your business how is this possible!?!?! Try it yourself https://lnkd.in/dgSTK5be

It's time for AI This Month! 🥳 April saw no signs of slowing down in the world of AI. 😅 The tech continues to roll out new capabilities, allowing for even more innovative ways to work, learn, and do business. 🤖 Discover how orgs are using AI and get the 411 on emerging AI security challenges, new product releases, and more.📈 Watch the full recap now >> https://lnkd.in/egHF7twi

I just read an insightful article discussing the future of AI and the rise of smaller, specialized LLMs. As we witness the incredible capabilities of models like ChatGPT and Gemini, it's important to recognize that their limitations and potential for "hallucinations" have sparked a shift towards more precise LLMs. Specialized LLMs offer several advantages over their general-purpose counterparts. They require fewer hardware resources, making them more efficient and cost-effective. Companies can build their own models with focused datasets, reducing the barrier to entry and enabling tailored solutions for specific tasks. Check out this article and see for yourself! Let's embrace the future of AI with these smaller, specialized LLMs that empower us to achieve remarkable results. #GenerativeAI #LLMs #Deployment

Great read on the future of AI!

I just read an insightful article discussing the future of AI and the rise of smaller, specialized LLMs. As we witness the incredible capabilities of models like ChatGPT and Gemini, it's important to recognize that their limitations and potential for "hallucinations" have sparked a shift towards more precise LLMs. Specialized LLMs offer several advantages over their general-purpose counterparts. They require fewer hardware resources, making them more efficient and cost-effective. Companies can build their own models with focused datasets, reducing the barrier to entry and enabling tailored solutions for specific tasks. Check out this article and see for yourself! Let's embrace the future of AI with these smaller, specialized LLMs that empower us to achieve remarkable results. #GenerativeAI #LLMs #Deployment

What if GenAI is a balloon just waiting for the first one to poke it? Don't get me wrong; AI is definitely a big thing, and there are already a lot of industries, where AI-like solutions are deployed, contributing and helping generate value. But there is also a HUGE element of hype, lack of understanding of what the present opportunities within AI are, and what the limitations for deploying AI in a meaningful way to generate value are. Expectations of AI are at an all time high. And historically that's when people asking thoughtful, serious and maybe even logical questions can end up being the ones holding the needles and getting a little too close to the balloon. I find this thought experiment somewhat fascinating, and I think we need to prepare ourselves for all scenarios. Including the 'this is a bubble' one. It just seems prudent. What do you think? #ai #hype #bubble https://lnkd.in/dQjjwWSN