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An AI engine acts as a versatile toolkit, enabling businesses to automate tasks previously requiring human intellect. It transforms messy data into structured, actionable insights, streamlining business processes and enhancing decision-making speed.

OpenAI just dropped a bunch of new features and improvements to their service. These are bound to be real productivity boosters!

An example of applied AI was witnessed by over half a million Finns during a live special broadcast of the Arto Nyberg talk show: we had the opportunity to implement a real-time talking and moving AI avatar for the program.

On February 16th, Softlandia and Bytewax ran an engaging online workshop designed to introduce the basics of incorporating AI into Slackbots.

Whether you're a marketing professional, a researcher or anyone else seeking efficiency in handling extensive amounts of text, YOKOT.AI's new features enable you to work more effectively.

Small language models are one of the biggest trends in GenAI in 2024. They can be already run for free on serverless platforms!

In this blog post we are discussing the importance of finding and defining just the right use case for your AI solution, why it is more efficient to use a complete RAG architecture instead of figuring out your own solution and how to ensure your corporate data remains private.

What is common with Microsoft Copilot, Grok, ChatGPT and YOKOT.AI? They are all RAGs!

How do you go from an effective internal knowledge management to actually utilizing that knowledge to support your documentation processes?

Learn how to use YOKOT.AI, a private generative AI platform, to create a smart maintenance assistant for your equipment and boost your productivity and efficiency.

The blog post explores the challenges and brittleness of using Large Language Models (LLMs) across various tasks. We introduce three LLM anti-patterns, with focus on the solution infrastructure and RAG.

As AI keeps changing, businesses need to adapt quickly to stay ahead of the competition.

Almost every organization has found ways to make their operations more efficient with the help of LLMs. But privacy questions need to be solved before deploying LLMs at scale. We’ll explain the key aspects of privacy and LLMs in this blog post.