CHANJONES LTD
innovative, technical, creative, human
Chris Jones
Chris Jones has been programming since he was 10 years old and has built various computer systems, some AI projects and some non-AI systems. He has also been a university lecturer since 2017. Since moving into academia, he has been working out the best ways to demystify AI for his students so they can understand it, leverage it, and learn from it. When not teaching at university, he is available to provide classes for your team, teaching them how to get the most out of this new technology and how to avoid pitfalls.
Chris is also available for consulting in general. He can help to implement some of the more complex automation solutions that you may discover during his training classes. He could support your institution to implement some of his innovative teaching methods. (Chris was a 2020 finalist for the “Innovative Teacher of the Year” award)
You can hear more from Chris on his podcast “How to Get Loads of Marks”. Or via his linked in page.
AI Workshop Implementation
Preparation
Chris will work closely with your company's management to understand their specific needs and challenges. He will customise the workshop to focus on AI applications relevant to your industry.
Workshop Delivery
The 3-hour session will include:
Theoretical Foundation: An introduction to AI principles and their relevance to your industry.
Practical Skills: Hands-on exercises with AI tools tailored to your company's specific processes and goals.
Interactive Discussions: Engaging activities that will encourage participants to explore AI applications in their daily tasks and workflows.
Follow-Up
Chris will provide additional resources and offer follow-up support to ensure the team can effectively implement what they learn.
Workshop Example
In a class for marketing specialists at Kingston University, Chris focused on how an understanding of the underlying theory of AI can help professionals intuit its strengths and weaknesses.
Exercises in the class took these ideas and tried them out in real situations, showing both the strengths and weaknesses of the technology.
By the end of the class, participants had developed a basic marketing campaign, using various AI tools to analyze target markets, develop basic campaign ideas, and finally produce a first draft example of their campaign.
Tools Covered
(Data tools, Chatbots, Image Generation)
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Kaggle datasets
We use Kaggle as an example of freely available data. Participants learn how to turn raw data into contextual insight. This allows them to understand the value of internal proprietary data.
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Spreadsheets
For many spreadsheets are a familiar tool. However most don’t realise their potential. By improving your understanding of spreadsheets you can not only save time on mundane office tasks, but you can start to think of approaching problems in a systematic way. It’s a gateway to more complex automation software.
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ChatGPT
Probably the most well known large language model (LLM). ChatGPT ushered in the current wave of AI hype and it’s probably the AI system most people have tried out for themselves. We look at creative ways to go beyond trite examples and make the most of this strange new addition to our species toolbox.
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Claude
Not unlike his namesake Claude Shannon, Claude AI has a way of seeing things differently from others. By using multiple LLMs participants learn how to generalise their skills. Preparing them for the next LLMs that don’t yet exist.
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Google Gemini
Given their access to huge datasets, most thought that when Google stepped into the ring the fight for AI dominance would be over. But that isn’t what happened. Analysing Gemini’s weaknesses gives a great insight into the less obvious weaknesses of AI in general.
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Dall-e
One of the first image generators. Dall-e is now built into ChatGPT. (it’s also made by OpenAI) The latest version is very powerful, but it sometimes struggles when asked for something specific. Looking at it’s strengths and weaknesses we are able to see inside the mind of a generative AI model.
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Leonardo
Leonardo is a front end interface for “Stable Diffusion”. It has many more complex controls than other free image generation tools. Giving participants access to these controls lets them learn to produce images that are useful for ACTUAL tasks, not just novelty examples.
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Canva
While not an AI tool per-se, Canva is an automation tool. GenAI is not a great fit for everything, but by combining newer generative tools with more traditional systems we can learn to avoid weaknesses and exploit strengths.