The Centre For GenAIOps

We recently launched our generative AI manifesto. https://genaiops.ai/ This manifesto has been carefully crafted by the community, for the community. We believe the principles within our manifesto are relevant now, and in the future and so will ground us throughout this journey. This is what we stand for. We would love your feedback.

We recently launched our generative AI manifesto. https://genaiops.ai/ This manifesto has been carefully crafted by the community, for the community. We believe the principles within our manifesto are relevant now, and in the future and so will ground us throughout this journey. This is what we stand for. We would love your feedback.

Adoption of hyperscale LLMs is NOT equal to cloud adoption. If you're saying things like, "people used to be nervous about putting their data in the cloud but they got over it - it'll be the same with LLMs" then you're making a classic category error. This article from The Centre For GenAIOps explains it well. https://lnkd.in/eDUw5gkn Key points: 🍰 Cloud encryption happens at the infrastructure layer, LLMs at the application layer. These are very different propositions. 🔦 Hyperscale LLM providers will receive both prompts and retrieved chunks in plain text 🔎 The mechanisms inside those LLMs are currently "black boxes" making demonstrating security hard - even if it is genuinely robust 🥇 Start your GenAI journey from the end point - how will I demonstrate security, trust and control?

Adoption of hyperscale LLMs is NOT equal to cloud adoption. If you're saying things like, "people used to be nervous about putting their data in the cloud but they got over it - it'll be the same with LLMs" then you're making a classic category error. We explain it further in the article below. https://lnkd.in/eDUw5gkn Key points: 🍰 Cloud encryption happens at the infrastructure layer, LLMs at the application layer. These are very different propositions. 🔦 Hyperscale LLM providers will receive both prompts and retrieved chunks in plain text 🔎 The mechanisms inside those LLMs are currently "black boxes" making demonstrating security hard - even if it is genuinely robust 🥇 Start your GenAI journey from the end point - how will I demonstrate security, trust and control?

From AI to GenAI: A Journey of 30+ Years In 1989, as part of my Maths degree, I wrote my dissertation on Artificial Intelligence (yes, AI was a thing even 30+ years ago!). My project involved creating a simple tool using rule-based logic to diagnose basic faults in electrical appliances. Back then, AI adoption was quite niche—used in manufacturing (think car assembly lines) and retail (like warehouse robots). In the services sector, however, its presence was minimal. Fast forward to today, and everyone is talking about Generative AI (GenAI) as groundbreaking. So, what’s the difference between AI and GenAI? Here's how I explain it: • AI is rules-based—think structured logic and templates. • GenAI goes further, producing creative and often unique content using machine learning. Take writing a poem, for example: • If the poem follows a pre-programmed structure (e.g., rhyming rules), it’s AI. • If it’s generated by a model trained on vast datasets to create something entirely new, it’s GenAI. For instance, many of you have seen my birthday poems for colleagues. I provide the raw content, but it’s ChatGPT (a GenAI tool) that transforms it into a creative masterpiece. Talking of creative masterpieces, the picture with this post was generated by ChatGPT. It's fascinating to witness how AI has evolved from rule-based systems to creative neural networks. What’s your take—are we just scratching the surface of GenAI’s potential? Let’s discuss! 👇 #AI #GenerativeAI #Innovation #TechnologyEvolution

Big thanks to Prasad Prabhakaran and esynergy for hosting us this evening! We revealed our Generative AI Manifesto to the AI community and received some fantastic feedback. Soon we will releasing tgus Manifesto to the online community. Stay tuned.

Our Ambassador community have been working hard defining a tangible and pragmatic Manifesto for Generative AI. We are nearly there and will be releasing this to the world within a few weeks! Please follow The Centre For GenAIOps for the latest updates! PS: We are continuing to recruit and extend our Ambassador community - Please pop us a DM or see our website to get involved !

In an industry that evolves daily, it’s becoming increasingly hard to distinguish true innovation from noise. What remains unchanged, however, are the limitations of Deep Learning and GenAI models—especially at the enterprise level. At the Centre for GenAIOps, as a community we continue to emphasise the importance of a well-rounded approach to deploying these technologies, focusing on: Strategy Model selection Prompting Grounding Guarding Monitoring Keep going! #AI #DeepLearning #GenAI #EnterpriseAI #GenAIOps #Innovation #Strategy

Welcome to Ian Makgill who joins us as an Ambassador! Ian is currently working on advanced RAG (Retrieval Augmented Generation) to search and interact with large document corpus's. RAG is, and will be a key part of "Generative AI Systems" allow for accurate, fast, cost effective and fully transparent retrieval over your own data. A key part of GenAIOps!