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Revolutionising Generative AI: Key Insights from AWS re:Invent Las Vegas, 2024

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AWS re:Invent 2024 was a showcase of how Generative AI is evolving, with a focus on low-code graphical solutions that make building applications simpler than ever. From innovations in Agents and Retrieval-Augmented Generation (RAG) to breakthroughs in fine-tuning Large Language Models (LLMs), the event highlighted tools and methods that are empowering “Builders” to create impactful […]

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Building Effective and Responsible AI Agents: The Importance of Recognising Causal Reasoning Limits in Generative AI

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In this article, we examine why understanding causal reasoning—and recognising the limitations of large language models (LLMs) in this area—is crucial for implementing AI Agents effectively. As organisations increasingly turn to AI Agents to perform complex tasks, awareness of these limitations becomes essential to assess their true capabilities and to ensure responsible, reliable deployments that

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Creating a Serverless AI Bot Fine

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Introduction As technology continues to advance, organisations and developers are constantly seeking efficient, scalable, and cost-effective solutions for their applications. In this article, we’ll explore how to create a powerful, serverless AI bot by leveraging key Amazon Web Services (AWS) technologies like Lambda, Bedrock, and DynamoDB.  Implementing this solution using serverless architecture is often more

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Understanding LLMs’ Reasoning Limits Today: Insights to Shape Your Strategy

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One critical question underpins the excitement around LLM’s potential: just how intelligent are Large Language Models (LLMs) when it comes to reasoning? Asking this question is crucial, as understanding the true capabilities of LLM’s enables us to apply it more effectively and to make strategic decisions on where to invest in skills that foster long-term

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My Aha Moments from MWC24 Las Vegas: The Conference

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After attending MWC24 in Las Vegas, I’d like to share some highlights that captured my attention. Compared to MWC24 Barcelona, the Las Vegas edition was a more intimate experience, with smaller crowds and shorter walks between sessions. The convenience allowed me to attend more AI-focused events, which was perfect for my company Parser, our AI-driven

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Fine-Tuning BERT to Develop a CV Job Description Matcher

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Introduction: In today’s competitive job market, efficiently matching candidates to job openings is crucial for both job seekers and employers. At Parser, we are continually exploring alternatives to improve our existing processes to address challenges like this one. With this idea in mind, we’ve developed a model using BERT (Bidirectional Encoder Representations from Transformers) and

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My Key Takeaways From TED AI San Francisco 2024

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While visiting clients in San Francisco, I had the opportunity to attend TED AI, which presented a range of thought-provoking insights. The event showcased a fascinating array of talks, many of which highlighted contrasting perspectives across key areas. Below, I’ve summarised these contrasts, including the primary arguments presented, and my initial reflections. AI as a

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Rethinking LLMs: A Modular, Distributed Approach to AI

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Large Language Models (LLMs) have emerged as powerful tools for understanding and generating human text across various applications. However, as these models grow, they become more complex and consume a lot of resources, similar to a monolithic application. This raises a key question: Is this the most efficient path forward, or is it time to

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Apache Cassandra: Is it a good database for AI? – Part 2

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Introduction In the first part of the article, we explored the general requirements of AI-specific databases. Now, let’s evaluate how well Apache Cassandra 5.0, the popular open source NoSQL database used by tech leading companies like Apple, Netflix, and Spotify, meets these demands. Specifically, we’ll delve into Cassandra’s capabilities, strengths, and limitations to determine if

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