A range of AI resources

So many different websites and newsletters jumping on “generative AI’shype cycle at the moment. A course I completed recently made a range of resources available and I wanted to put them in one place.

The intriguing sounding “Hugging Face” shows a range of different approaches to high-speed use of AI tech, along with the kind of tech that is often called AI but doesn’t strictly qualify. Elsewhere, Fairlearn seeks to ensure that upcoming AI systems have greater transparency, to limit the harm that may come from training new systems on biased data sets.

There were reflections on how to use analytics to enhance business, more specifically what to do to improve your experiments, and then how to build a culture of experimentation in your organisation. To make the most of the benefits of experimentation, it will involve making changes to the structure of the organisation, not just to try out the occasional experiment.

What does this look like in practice? A long 2015 article on the Disney theme park MagicBand project shows the breadth of changes involved in rolling out a significant consumer-facing technology project.

There were other resources too: some that could help someone think through a business model – Lean Canvas, Value Proposition Canvas, the various design thinking models and whether they have a measurable impact – event a way to assess the innovation value chain to examine the benefits of innovation more closely.

And some broader resources – the Stanford AI Index Report 2023, a website dedicated to the work of AI pioneer Professor John McCarthy, an outline of how to map out a digital transformation journey or digital partnering, and even a white paper on the metaverse and the NSW government.

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