The Kern AI blog
We delve into the transformative power of large language models (LLMs), offering practical insights, tailored industry use cases, and in-depth technical analysis.
A 360 Degree of DeepSeek-R1
While DeepSeek-R1 advances AI technology, its risks underscore the need for transparency, ethics, and safeguards in enterprise adoption.
View postNavigating EU Regulations: How Financial Institutions Can Use AI for DORA Compliance
In an era of digital acceleration, the financial sector faces growing pressure to ensure resilience and data security amid rising cyber risks. Over two decades, cyber incidents have cost the sector $12 billion, with $2.5 billion reported since 2020.
View postEssential Concepts & Terminology of Large Language Models (LLMs)
Discover the essential concepts and terminology behind Large Language Models (LLMs) in this blog, breaking down how neural networks, transformers, and attention mechanisms power the AI revolution in language understanding and generation.
View postMacros: Turning Co-Pilots into Auto-Pilots
Cognition's new Macros feature automates tasks using natural language, making it easier for domain experts to extract document information and boost productivity.
View postEntity RAG + LLMs: Powering Enterprise Grade AI
Join us to explore the latest cutting-edge AI technology behind the most accurate and reliable GenAI applications transforming customer service.
View postChoosing the right LLM for your RAG project
Barely a week goes by without a new, amazing model release. Claude 3, Llama 3, Phi-3, Command R+, Mixtral 8x22B, or GPT-4o are just a few of the absolute most recent model releases that have caught the attention of many.
View post4 Key components of a success RAG pipeline for your GenAI application
Learn about the key elements of a successful RAG pipeline for Generative AI, focusing on effective data organization, advanced AI techniques, and continuous quality monitoring to enhance AI response accuracy and relevance.
View postWhy Retrieval-Augmented Generation (RAG) can sometimes fail and cause hallucinations.
Let's delve into the primary reasons behind hallucinations in genAI and discuss potential solutions, enabling you to develop the most dependable AI applications to date.
View postIntroducing Data-Centric RAG: Powering the Most Reliable and Accurate GenAI Applications for Enterprise Use
This blog introduces a “data-centric RAG” approach to enhance the reliability and accuracy of Generative AI applications in enterprises, focusing on improving data quality and integrating domain-specific knowledge to combat AI hallucinations and ensure relevant responses.
View postPioneering Innovation: How GenAI is disrupting Finance & Banking - with free ebook download
An actionable guide to the diverse elements of Generative AI in Finance and Banking that are changing the landscape of productivity, customer experience, and the way the industry operates.
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