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“Don’t believe everything you get from ChatGPT“ – Abraham Lincoln Let’s talk about hallucinations – those, in the context of LLMs, mean generating plausible-looking but false or misleading information. I sometimes wonder how much of their bad reputation got stuck with us because first impressions are the most lasting. Initially, I thought that once people…
As the language models are improving, their adoption is growing in more complex tasks such as free-form question answering or summarization. On the other hand, the more demanding the task – the higher the risk of LLM hallucinations. In this article, you’ll find: what the problem with hallucination is, which techniques we use to reduce…
Web Agents are no longer just a concept from science fiction—they’re the cutting-edge tools that are automating and streamlining our online interactions at an unprecedented scale. From effortlessly sifting through vast amounts of information to performing complex tasks like form submissions and website navigation, these agents are redefining efficiency in the digital age. Thanks to…
Generative AI and Large Language Models (LLMs) have burst onto the scene, introducing us to “copilots,” “chatbots,” and the increasingly pivotal “AI agents.” These advancements unfold at breakneck speed, making it challenging to keep up. We’ve been at the forefront of this revolution, witnessing how AI agents—or “agentic workflows,” as Andrew Ng refers to them—are…
Every computation requires computing resources. Sure, sometimes a regular calculator, a piece of paper, and a pencil are sufficient. However, in machine learning, powerful computing resources are necessary: The model needs to be fed with a massive amount of data. Appropriate calculations must be performed for each data point to process it into a pattern.…
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In today’s rapidly evolving generative AI world, keeping pace requires more than embracing cutting-edge technology. At deepsense.ai, we don’t merely follow trends; we aspire to establish new solutions. Our latest achievement combines Advanced Retrieval-Augmented Generation (RAG) with Small Language Models (SLMs), aiming to enhance the capabilities of embedded devices beyond traditional cloud solutions. Yet, it’s…
Chances are you’ve already heard about RAG – Retrieval-Augmented Generation. This technology has taken the industry by storm, and for good reason. The emergence of RAG systems is a natural consequence of the popularity of Large Language Models. They make it easier than ever before to create a chatbot – one deeply entrenched in the…
More than a year has passed since the release of ChatGPT, which led hundreds of millions of people to not only talk about AI, but actively use it on a daily basis. The wide adoption of ChatGPT and other large language models (LLMs) among individuals made companies of all sizes and across all sectors of…
Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Collecting a large, diverse, and accurately annotated dataset consisting of pairs of images and corresponding segmentation masks can be time-consuming, expensive, and challenging due to privacy concerns. Fortunately, in…