Experimenting with local alt text generation in Firefox Nightly – Mozilla Hacks - the Web developer blog
hacks.mozilla.org
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).

…

Our alt text generator is far from perfect, but we want to take an iterative approach and improve it in the open.

…

We are currently working on improving the image-to-text datasets and model with what we’ve described in this blog post…"

  •  Kissaki   ( @Kissaki@beehaw.org ) English
    4•20 days ago

    So, planned experimentation and availabiltiy

    1. PDF editor when adding an image in Firefox 130
    2. PDF reading
    3. [hopefully] general web browsing

    Sounds like a good plan.

    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.