ChatGPT’s Sharp Edges: Glitch Tokens
Language Models’ Achilles heel: Rob Miles from Computerphile talks about “glitch” tokens, those mysterious words which, which result in gibberish when entered into some large language models.
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Ch(e)at GPT?
Mike from Computerphile explains a paper from the University of Maryland, proposing a neat trick to ‘watermark’ the output of large language models such as ChatGPT. Dr Mike Pound is an image analyst at the University of Nottingham. The University of Maryland paper: https://arxiv.org/pdf/2301.10226.pdf
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ChatGPT Explained by Rob Miles on Computerphile
I’ve been waiting for a video explaining ChatGPT from Computerphile and here it is.
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Computerphile on Emulation
Computerphile explains emulation. Emulation sounds difficult, begins to look simple and then ends up being difficult after all! Dr Steve Bagley explains.
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Just In Time (JIT) Compilers – Computerphile
Dr Laurence Tratt of KCL explains why (under certain circumstances) JIT Compilers can be so much faster.
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How to Verify AI ‘Black Boxes
Dr Hana Chockler is Reader in the Department of Informatics, King’s College London and Principal Scientist at causaLens and she explains how to check to see if a black box system is giving us the right result for the right reason?
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What is Network Time Protocol (NTP)?
Just how do computers synchronise clocks across the Internet? Dr Julian Onions implemented this at Nottingham after meeting the godfather of Internet time, Dave Mills!
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Robot Decision Making – Computerphile
Deterministic route finding isn’t enough for the real world – Nick Hawes of the Oxford Robotics Institute takes us through some problems featuring probabilities.
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Stable Diffusion in Code (AI Image Generation)
Mike Continues his look at AI Image Generation with Stable Diffusion
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How AI Image Generators Work (Stable Diffusion / Dall-E)
AI image generators are massive, but how are they creating such interesting images? Dr Mike Pound explains what’s going on.
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