Why AI in QA isn’t quite ready yet
AI isn’t just the next big thing; it’s here now, and whoever isn’t using it is missing out.Our clients often ask about AI tools in… Read More »Why AI in QA isn’t quite ready yet
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Cloud infrastructure and the hype, reality and hope of generative AI
In Gartner’s Hype Cycle for Artificial Intelligence 2024, we learned AI has made it over the “Peak of Inflated Expectations” and is poised to slip… Read More »Cloud infrastructure and the hype, reality and hope of generative AI
Sports Lessons: Leveraging Organizational Improv to “Do More with Less”
In my blog “The Economics of “Do More With Less”: Blending AI with Organizational Discipline,” I discussed the challenges organizations face when trying to accomplish… Read More »Sports Lessons: Leveraging Organizational Improv to “Do More with Less”
5 tips for fine-tuning LLMs
Master LLM fine-tuning with expert tips on data quality, model architecture, and bias mitigation. Boost performance and efficiency in AI development.
4 strategies for AI-driven vulnerability management
Harnessing artificial intelligence to manage vulnerabilities opens the door to efficient threat detection and proactive risk management. Organizations of all sizes stand to benefit when… Read More »4 strategies for AI-driven vulnerability management
Best practices for structuring large datasets in Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation, or RAG, is a game-changer for AI applications, allowing large language models to pull real-time, factual information from massive datasets to enhance their… Read More »Best practices for structuring large datasets in Retrieval-Augmented Generation (RAG)
A feedback loop alternative to RAG that aligns LLMs with knowledge graph models
Image by Gerd Altmann from Pixabay Discover AI–a YouTube channel run by an unidentified Austrian man who distills and highlights the findings of AI papers… Read More »A feedback loop alternative to RAG that aligns LLMs with knowledge graph models
Techniques for automated feature selection: Filter methods and implementation using Python libraries
Feature Selection is a crucial process in feature engineering as part of the Machine Learning life cycle. It focuses on identifying the most impactful features in… Read More »Techniques for automated feature selection: Filter methods and implementation using Python libraries
The Four Pillars of AI-driven Innovation
Innovation is more than just ideation. Ultimately, innovation is about value creation. AI has sparked a growing urgency in the concepts that drive innovation as… Read More »The Four Pillars of AI-driven Innovation