Tagged with: #aws

Last night, I had the pleasure of returning to the Chief Wine Officer event series on behalf of AWS, this time addressing leaders from private equity portfolio companies on a topic close to my heart: turning organisational data into strategic value. The evening, hosted at Spring at Somerset House, brought together executives eager to explore how to accelerate value creation through data monetisation within PE timeframes.

Over the past year, I’ve been asked regularly what the best way of selecting a Large Language Model (LLM) is. With over 146 LLMs listed in Ollama’s model library alone, selecting the right model has become increasingly complex. While ChatGPT dominates headlines, businesses must look beyond hype to match the right model to their specific needs. Choosing the right LLM isn’t just a technical decision—it directly impacts your organisation’s ability to drive innovation and achieve its strategic goals, making collaboration between technical and non-technical teams essential to ensure that both business needs and operational constraints are fully understood.

Last week, I had the privilege of delivering a keynote presentation at Monday.com’s Elevate conference in London. The topic, “Leveraging data and artificial intelligence (AI) for organisational transformation,” allowed me to challenge some common misconceptions about AI adoption and share practical insights on harnessing the power of existing data. In this post, I outline the key themes discussed and provide some additional context.

Earlier this week, I got the opportunity to speak at our Amazon Web Services (AWS) office in London, to an audience of Private Equity firms and their portfolio company executives about driving value creation through AI and data. The presentation focused on how Private Equity firms and their portfolio companies can drive value creation through AI and data. I also took the opportunity to introduce a new concept called the AI Stages of Adoption (AISA), which is designed to help organisations assess their maturity and readiness for AI adoption.

Custom Model Import is game changing! If you own your own corpus of data and are using it to train your own models, you can now bring those models to Amazon Bedrock’s secure, managed environment.

Just as we were catching our breath on Claude 3 Opus arriving on Amazon Bedrock, here we go again, this time it’s Meta’s Llama 3 model - designed for you to build, experiment, and responsibly scale your generative artificial intelligence (AI) applications; now with improvements in reasoning, code generation, and instruction.

This just in! Anthropic’s Claude 3 Opus foundation model is now available on Amazon Bedrock, joining Claude Sonnet and Claude Haiku. Bedrock is now the first and only place to offer all three Claude 3 models in general availability.

I recently spoke with Duncan Jefferies about how businesses can effectively harness generative AI to drive organisational transformation. The resulting AWS executive’s guide to generative AI offers a comprehensive roadmap for business leaders navigating this transformative technology. Here are the key insights and practical steps for organisations looking to unlock the potential of generative AI.

Given Adam’s announcement yesterday about Amazon PartyRock powered by Amazon Bedrock, I decided I couldn’t wait to get my hands on it and see what kind of app I could build.

Last night I had the pleasure of speaking at the Chief Wine Officer event hosted by AWS at London’s National Portrait Gallery. The focus was on demystifying generative AI and helping business leaders understand how to harness its potential for real organisational transformation.