Insights, updates, and thought leadership on conversational AI, enterprise automation, and the future of customer experience
Large Language Models are reshaping how organizations interact with information, customers, and services. Blits.ai participates in the EU-funded LLMs4EU initiative focused on strengthening Europe's position in large-scale language technology.
In my previous article about AI, I mentioned how everyone suddenly seems to be an AI expert and how that creates a lot of noise. In this post, I'll break down one of the most important topics: how (and why) you should add your company's data to large language models.
Let's be honest: I think it's great that technology is so embedded in our daily lives. It helps us get knowledge faster, complete tasks more efficiently, gives us inspiration, and occasionally scares the hell out of us. But after spending a ridiculous amount of time with these technologies, I feel it's time to reflect on what I really hate about AI.
In the world of AI, where innovation moves at breakneck speed, being the CTO of a fast-growing scale-up is an exhilarating job—but not for the faint of heart. Our company specializes in large language models, chatbots, digital humans, and voicebots.
Someone once told me, stupid questions don't exist. This might be true, but people are still afraid to look stupid by asking questions that are assumed to be general knowledge. In this article, my goal is to get everyone up-to-speed on the basics of AI.
Over 5 years ago I started a chatbot (ad)venture called Blits.ai because I believed the way we as humans interact with data will change to a more conversation-based approach. With the current ChatGPT hype, more and more people are coming to the same conclusion.
We're happy to announce that Blits.ai now supports GPT-4, supercharging the potential of GPT-4 in chatbots like never before. As one of the world's most advanced language models, GPT-4 brings unprecedented capabilities to conversational AI.
Chatbot technology is improving every day. Artificial Intelligence (AI) underlaying chatbots has caused a better understanding of the intentions of users, and better replies without human intervention.
In this article we will explore how practical GPT-3 is for Conversational AI chatbots and voicebots, and what you need to know about it. First, let's understand the capabilities and limitations.
At Blits.ai we're introducing a new method that reshapes how chatbots work. From the beginning, our company has been focusing on building a chatbot ecosystem that gives companies access to 40+ cognitive AI services.
Bot building and conversation design is not easy, but good software is the starting point to help you build better bots that your users love. Here are 15 advanced features that can transform your chatbot from basic to brilliant.
You are considering building a chatbot. If you decide to build an artificial intelligence (AI) powered chatbot you will undoubtingly question yourself the following: which NLU engine should I use?
Get the latest insights on conversational AI, enterprise automation, and customer experience delivered to your inbox
No spam, unsubscribe at any time