Get more out of your presentations with AI-powered annotated slides


With a recording, a presentation already has a longer lifespan than without one. But with a little AI support, it can add even more value.

Programmer Simon Willison presented a method he developed to make presentations and workshops more effective and accessible to the public. He calls the result “annotated presentations” – presentation slides enriched with explanatory text and additional links.

Dedicated browser tool for annotated presentations

To create annotated presentations as efficiently as possible, Willison has developed a browser-based tool. It allows you to upload slides as images, add alt text and comments, and finally export a fully formatted HTML document that can be easily inserted into a WordPress blog, for example.

Image alt text is an essential component for screen readers and search engine optimization, but can be tedious to create. Willison has integrated Optical Character Recognition (OCR) into its tool to provide an initial suggestion for these texts.



Image: Screenshot/THE DECODER

Although the tool runs in the browser, no data is exchanged with the server, according to the developer. The slides have to be numbered correctly so that the order of the slides doesn’t get mixed up. Of course, ChatGPT helped him to write the JavaScript source code.

Edit auto-transcriptions with Claude or ChatGPT

The text on the slides comes from the transcript of the lecture, which Willison processes with a simple AI prompt. This assumes that a transcript is available. If the lecture is available on YouTube, the automatically generated captions can be exported from there (e.g. with

Any errors transferred from speech recognition to the transcript will also be transferred to the edited text. Despite (or perhaps because of) AI editing, it is therefore essential to proofread the text before publication.

Reformat this transcript into paragraphs and sentences, fix the capitalization and make very light edits such as removing ums

Prompt for editing a transcript into readable text by Simon Willison

Willison fed the prompt and transcript into Claude 2 because the context window of the Anthropic language model, at 100,000 tokens, was significantly larger than the OpenAI alternatives at the time he was developing the application.

OpenAI now offers a slightly more accurate (but still imprecise) alternative with GPT-4-Turbo 128K. You will probably get better results if you process the slides step by step.


example of the method described above here and in the following video.

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