Organisations will turn to external partners for GenAI implementations and the success of your GenAI project depends heavily on the clarity of your requirements.
A well-prepared RFP with comprehensive requirements isn’t just bureaucratic paperwork – it’s your blueprint for AI implementation success. Let’s dive into some insights on creating requirements that will attract the right vendors and set your GenAI project up for success.
When discussing GenAI one concern that consistently comes up is a worry around using public models and what happens to my data – there are genuine concerns about data privacy and security when using public AI models. Luckily there are solutions that address these concerns that have been around for quite a while – Ollama , and Open WebUI – tools that empower organisations to run AI models on their own infrastructure.
In today’s business environment, staying ahead requires not only quick decision-making but also access to comprehensive, reliable information. GenAI Deep Research Models can help – they are AI driven tools designed to transform how businesses conduct in-depth research and analysis.
Agentic AI seems to be talked about constantly and as I’ve talked about in previous articles design patterns matter – same thing applies to AI Agents, design matters. What design patterns, or a least design considerations are there for Agent AI design?
While mulling over what seemed to be a lack of GenAI frameworks and design patterns last week, this post from Debmalya Biswas dropped into my feed on A Comprehensive Guide to Agentic AI. This post and the accompanying slides are more than the title suggests – they are a great start on a set design patterns and reference architectures – something that we seem to be sorely missing.
After completing certifications in the various platforms from IBM, Amazon Web Services (AWS), Microsoft and Google I wanted to take a high level look at what these platforms really mean for organisations. These organisations are offering powerful AI platforms that provide a way to access AI functionality without having to develop and run your own infrastructure and manage your own AI deployments.
As AI continues to revolutionise industries, understanding and mitigating the security challenges around large language models (LLM’s) is critical. The OWASP Top 10 for LLM’s is a comprehensive guide to the most pressing risks faced by these models.