🤖 I’m a bot that provides automatic summaries for articles:
Click here to see the summary
The summaries have been in testing for at least a couple of months, and they’re now more widely available to a “subset” of users in the US on Amazon’s mobile app.
Amazon says they’re available “across a broad selection of products.” So far, we’ve seen them on TVs, headphones, tablets, and fitness trackers.
They also seem to focus primarily on the positives of the product, spending less time on the negatives and leaving them for the end.
That said, that could be because Amazon’s search already elevates highly rated products, so it’s hard to find summaries of anything that people have been particularly frustrated by.
The feature can be found at the top of the review section on mobile under the heading “Customers say.” At the end, the paragraph includes a note that it was AI-generated.
Summarizing customer reviews has turned out to be one of the more obvious and easy to implement uses of generative AI.
Is Generative AI really what is used here? I would’ve assumed a LLM to vastly outperform stuff like a GAN for a summary task? Or do we colloquially group those two under “generative AI?” But if we do then aren’t basically all AI generative since making something is what we typically use code for? What would be an example of a non-generative AI then?
I think the reason people refer to LLMs as generative comes from the term GPT, which is short for generative pre-trained transformer I believe. At its core, it generates new outputs based on previous ones, and its purpose is to create new content. There are plenty of models that are not generative, like dedicated classifiers (think sentiment analyzers, models that try to identify what an object is, etc).
🤖 I’m a bot that provides automatic summaries for articles:
Click here to see the summary
The summaries have been in testing for at least a couple of months, and they’re now more widely available to a “subset” of users in the US on Amazon’s mobile app.
Amazon says they’re available “across a broad selection of products.” So far, we’ve seen them on TVs, headphones, tablets, and fitness trackers.
They also seem to focus primarily on the positives of the product, spending less time on the negatives and leaving them for the end.
That said, that could be because Amazon’s search already elevates highly rated products, so it’s hard to find summaries of anything that people have been particularly frustrated by.
The feature can be found at the top of the review section on mobile under the heading “Customers say.” At the end, the paragraph includes a note that it was AI-generated.
Summarizing customer reviews has turned out to be one of the more obvious and easy to implement uses of generative AI.
Saved 53% of original text.
It’s quite ironic for an AI summarisation tool to talk about an AI summarisation tool.
A real glimpse of things to come.
Depending on what you mean by “AI”, this bot doesn’t fit the criteria. It works by extracting and ranking sentences and does not apply a LLM.
That’s really curious. LLM were usually on the other side of this note and not considered the traditional AI people referred to.
Is Generative AI really what is used here? I would’ve assumed a LLM to vastly outperform stuff like a GAN for a summary task? Or do we colloquially group those two under “generative AI?” But if we do then aren’t basically all AI generative since making something is what we typically use code for? What would be an example of a non-generative AI then?
I think the reason people refer to LLMs as generative comes from the term GPT, which is short for generative pre-trained transformer I believe. At its core, it generates new outputs based on previous ones, and its purpose is to create new content. There are plenty of models that are not generative, like dedicated classifiers (think sentiment analyzers, models that try to identify what an object is, etc).