Posts related to GenAI

The Evolving Landscape of Large Language Model (LLM) Architectures

The Evolving Landscape of Large Language Model (LLM) Architectures

The field of natural language processing (NLP) has witnessed tremendous progress in recent years, driven by the emergence of large language models (LLMs). These models have revolutionized the way we approach NLP tasks, from language translation and text summarization to question answering and text generation. In this blog post, we’ll explore the evolving landscape of LLM architectures, their history and current trends.

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What are Large Language Models and Key Terminologies

Understanding Large Language Models (LLMs): Key Concepts and Terminologies

Large Language Models (LLMs) have changed the field of natural language processing (NLP ), powering applications from chatbots and virtual assistants to machine translation and content generation. Models like OpenAI’s GPT-4, Anthropic’s Claude 3.5 Sonnet or Google’ Gemini 1.5 have demonstrated remarkable results in generating human-like text, performing complex reasoning, and even passing professional exams. But what exactly are LLMs, and what are the key concepts that underpin their functionality?

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AI Engineering, Platform Engineering for AI

AI Engineering, Platform Engineering for AI

In recent years, Platform Engineering has emerged as a cornerstone for building and maintaining the infrastructure that powers software development. It focuses on developer experience and ensuring that the paltform is efficient, scalable, and resilient. As artificial intelligence (AI) continues to revolutionise the tech landscape, a new frontier has emerged: AI Engineering. This discipline not only brings AI to the organisation but also adapts the principles of Platform Engineering to meet the unique demands of AI systems. Essentially, AI Engineering is leveraging the proven strategies of Platform Engineering and tailoring them to the complexities of AI technologies.

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Platform Engineering: Enhancing Cloud-Native and AI Capabilities

Why Your Organization Needs a Platform Team for Successful GenAI Integration

The technological landscape is ever-evolving, presenting organisations with both unprecedented opportunities and complex challenges. From the rise of the internet to the shifts toward cloud computing, mobile technologies, and DevOps practices, each leap has demanded swift and strategic adaptation. Now, Generative AI (GenAI) emerges as the next transformative force, poised to revolutionise data handling, automation, and user experiences. However, integrating GenAI isn’t merely about adopting a new tool—it’s about reshaping workflows, infrastructure, and organisational culture. This is where the establishment of a dedicated platform team becomes not just valuable but essential.

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