An Overview of the State of AI - Discussion The session will last 1 hour and 30 minutes in total, with approximately 45 minutes dedicated to the presentation and the remaining time for an open discussion and Q&A. We’d really encourage questions and discussion, so please come along with anything you’ve been wondering about AI, Machine Learning, or how they might fit into your research.Part 1: The lay of the landWe’ll start with a brief history of AI, followed by a simplified taxonomy of the different subfields. This will include applications in biology, as well as some of the more popular areas such as Generative AI (GenAI) and Large Language Models (LLMs).Part 2: A critical look at AIWe’ll then take a more critical look at the field, being careful to distinguish between criticism of “popular” AI (particularly GenAI and LLMs) and research-focused Machine Learning. We’ll discuss ethical alternatives to commercial LLMs, including open-source and locally hosted models, as well as some common pitfalls to be aware of when using Machine Learning in your research.We’ll finish with some helpful resources (with a little bit of self-promotion) if you’d like to explore how AI and Machine Learning could be applied to your own research.Slides from the presentation will be made available at Bioinformatics Core - GitHub DRP-HCB - AI and ML In the future, the Bioinformatics Core will also be hosting a series of practical workshops, so whether you’re completely new to AI, have only played around with it, or have already started using Machine Learning in your research, we hope there’ll be something useful for you. Oct 08 2026 13.00 - 14.30 An Overview of the State of AI - Discussion Annita Chalka from the DRP-HCB Bioinfomatics Core hosts this beginner-friendly (and slightly humorous) overview of AI as a field. Room 7.15, Michael Swan Building, KB Campus Join on Teams This article was published on Tuesday 6 October 2026
An Overview of the State of AI - Discussion The session will last 1 hour and 30 minutes in total, with approximately 45 minutes dedicated to the presentation and the remaining time for an open discussion and Q&A. We’d really encourage questions and discussion, so please come along with anything you’ve been wondering about AI, Machine Learning, or how they might fit into your research.Part 1: The lay of the landWe’ll start with a brief history of AI, followed by a simplified taxonomy of the different subfields. This will include applications in biology, as well as some of the more popular areas such as Generative AI (GenAI) and Large Language Models (LLMs).Part 2: A critical look at AIWe’ll then take a more critical look at the field, being careful to distinguish between criticism of “popular” AI (particularly GenAI and LLMs) and research-focused Machine Learning. We’ll discuss ethical alternatives to commercial LLMs, including open-source and locally hosted models, as well as some common pitfalls to be aware of when using Machine Learning in your research.We’ll finish with some helpful resources (with a little bit of self-promotion) if you’d like to explore how AI and Machine Learning could be applied to your own research.Slides from the presentation will be made available at Bioinformatics Core - GitHub DRP-HCB - AI and ML In the future, the Bioinformatics Core will also be hosting a series of practical workshops, so whether you’re completely new to AI, have only played around with it, or have already started using Machine Learning in your research, we hope there’ll be something useful for you. Oct 08 2026 13.00 - 14.30 An Overview of the State of AI - Discussion Annita Chalka from the DRP-HCB Bioinfomatics Core hosts this beginner-friendly (and slightly humorous) overview of AI as a field. Room 7.15, Michael Swan Building, KB Campus Join on Teams This article was published on Tuesday 6 October 2026
Oct 08 2026 13.00 - 14.30 An Overview of the State of AI - Discussion Annita Chalka from the DRP-HCB Bioinfomatics Core hosts this beginner-friendly (and slightly humorous) overview of AI as a field.
