Only if it's progressively encoded (though the decoder can still do fast 1/2, 1/4, and 1/8 reductions). Also, low resolution data isn't the same as what you get from a scaling algorithm like ALTIALIAS (though I don't know what that does, probably something like Lanczos).
Plus, you still have to handle other formats like png, and get the same output from the same image.
Not really. JPEG encodes by 8x8 blocks, thus, for the DCT transform at the beginning, the first component after the transformation is always the mean value (of the 64 elements). Therefore, if your resizing target is more than 8x smaller, you can use the mean value directly without doing expensive DCT transform and the whole decoding process.
well, that's what I was hinting at by the fast 1/8 reduction, so yes you can speed up the process by "decoding" a smaller version of the jpeg image.
This is just an optimization to add later though. You might be able to quickly scale your jpeg down, but you can't skip the rest of the transforms, because you still need to get deterministic fingerprint of the image. And in the article's use case, the file size is so small that you shouldn't be dominated by decoding time (that test jpeg from the site decodes in 12ms on my laptop with libjpeg at full size).
Plus, you still have to handle other formats like png, and get the same output from the same image.