Firefox 130 will feature an on-device AI model that automatically generates alt-text for images, integrated into its built-in PDF editor.
New accessibility feature coming to Firefox, an "AI powered" alt-text generator.
"Starting in Firefox 130, we will automatically generate an alt text and let the user validate it. So every time an image is added, we get an array of pixels we pass to the ML engine and a few seconds after, we get a string corresponding to a description of this image (see the code).
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Our alt text generator is far from perfect, but we want to take an iterative approach and improve it in the open.
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We are currently working on improving the image-to-text datasets and model with what we’ve described in this blog post..."
Overall see nothing wrong with this. Encourages users to support alt-text more, which we should be doing for our disabled friends anyway. I really like the confirmation before applying.
On the one hand, having an AI generated alt-text on the client side would be much better than not having any alt-text at all. On the other hand, the pessemist in me thinks that if it becomes widely available, website makers will feel less of a need to add proper alt-text to their content.
A more optimistic way of looking at it is that this tool makes people more interested in alt-text in general, meaning more tools are developed to make use of it, meaning more web devs bother with it in the first place (either using this tool or manually)
If they feel less need to add proper alt-text because peoples' browsers are doing a better job anyway, I don't see why that's a problem. The end result is better alt text.
The biggest problem with AI alt text is that it lacks the ability to determine and add in context, which is particularly important in social media image descriptions. But people adding useless alt text isn’t exactly a new thing either. If people treat this as a starting place for adding an alt text description and not a “click it and I don’t have to think about it” solution I’m massively in support of it.
I would expect it'd be not too hard to expand the context fed into the AI from just the pixels to including adjacent text as well. Multimodal AIs can accept both kinds of input. Might as well start with the basics though.
I like this approach of having a model locally and running it locally. I've been using the firefox website translator and its great. Handy and it doesn't send my data to google. That I know of, ha.
The only issue for Firefox's translator currently is the time it takes to load at first, or the fact you have to download each model first. Its not some monumental task, but it does have more friction than Google's "automatically send the site you are browsing to our server"
Power management is going to be a huge emerging issue with the deployment of transformer model inference to the edge.
I foresee some backpedaling from this idea that "one model can do everything". LLMs have their place, but sometimes a good old LSTM or CNN is a better choice.
Well I do agree it'll be useful for people who need it, but for most people it's pretty pointless and I hope at least they don't enable it by default just like Windoze sticky key because ai use a lot of system resources for a little benefits especially with self hosted ai
Now i want this standalone in a commandline binary, take an image and give me a single phrase description (gut feeling says this already exists but depending on Teh Cloudz and OpenAI, not fully local on-device for non-GPU-powered computers)
So, it's possible to build but no one has made it yet? Because i have negative interest in messing with that kinda tech, and would rather just "apt-get install whatever-image-describing-gizmo" so i wouldn't be the one who does it
When I used a similar feature in Ice Cubes (Mastodon app) it generated very detailed but ultimately useless text because it does not understand the point of the image and focuses on things that don’t matter. Could be better here but I doubt it. I prefer writing my own alt text but it’s better than nothing.
EDIT: the AI creates an initial description, which then receives crowdsourced additional context per-image to improve generated output. look for the “Example Output” heading in the article.
That's wrong. There is nothing crowd sourced. What you read in the article is that when you add an image in the PDF editor it can generate an alt text for the image, and you as a user validate and confirm it. That's still local PDF editing though.
The caching part is about the model dataset, which is static.
One thing I'd love to see in Firefox is a way to offload the translation engine to my local ollama server. This way I can get much better translations but still have everything private.
Once quantized, these models can be under 200MB on disk, and run in a couple of seconds on a laptop – a big reduction compared to the gigabytes and resources an LLM requires.
While a reasonable size for Laptop and desktop, the couple of seconds time could still be a bit of a hindrance. Nevertheless, a significant unblock for blind/text users.
I wonder what it would mean for mobile. If it's an optional accessibility feature, and with today's smartphones storage space I think it can work well though.
Running inference locally with small models offers many advantages:
They list 5 positives about using local models. On a blog targeting developers, I would wish if not expect them to list the downsides and weighing of the two sides too. As it is, it's promotional material, not honest, open, fully informing descriptions.
While they go into technical details about the architecture and technical implementation, I think the negatives are noteworthy, and the weighing could be insightful for readers.
So every time an image is added, we get an array of pixels we pass to the ML engine
An array of pixels doesn't make sense to me. Images can have different widths, so linear data with varying sectioning content would be awful for training.
I have to assume this was a technical simplification or unintended wording mistake for the article.
It is for websites. This is most useful for readers that don't display images. The feature for websites should be added for version 130. I'm on Developer Edition and I am currently on 127. It will be implemented for PDFs in the future after that.
Where did you read this? The article says the opposite.
will be available as part of Firefox’s built-in PDF editor
Firefox is able to add an image in a PDF using our popular open source pdf.js library[…] Starting in Firefox 130, we will automatically generate an alt text and let the user validate it.
They're starting this as an experiment in their PDF editor, yes. They then want to extend to PDF reading, and then hope to extend to the general web browsing.
will be available as part of Firefox’s built-in PDF editor
Firefox is able to add an image in a PDF using our popular open source pdf.js library[…] Starting in Firefox 130, we will automatically generate an alt text and let the user validate it. So every time an image is added, […]
In the future, we want to be able to provide an alt text for any existing image in PDFs, except images which just contain text (it’s usually the case for PDFs containing scanned books).
Once the alt text feature in PDF.js has matured and proven to work well, we hope to make the feature available in general browsing for users with screen readers.
But even for a simple static page there are certain types of information, like alternative text for images, that must be provided by the author to provide an understandable experience for people using assistive technology (as required by the spec)
I wonder if this includes websites that use <figcaption> with alt emptied.
figure does not invalidate or change how img is to be used. The caption may often not but can differ from the image description. If alt describes the image, figcaption captions it.
What the fuck is Lemmy doing, breaking with HTML in code formatting?? Man it's completely broken. I committed sth so it doesn't remove the img lol.
<figure>
img src="party.jpg" alt="people partying" />
<figcaption>Me and my mates</figcaption>
</figure>