So Far, A.I. Is a Feature, Not a Product ⇥ daringfireball.net

John Gruber:

An oft-told story is that back in 2009 — two years after Dropbox debuted, two years before Apple unveiled iCloud — Steve Jobs invited Dropbox cofounders Drew Houston and Arash Ferdowsi to Cupertino to pitch them on selling the company to Apple. Dropbox, Jobs told them, was “a feature, not a product”.

[…]

Leading up to WWDC last week, I’d been thinking that this same description applies, in spades, to LLM generative AI. Fantastically useful, downright amazing at times, but features. Not products. Or at least not broadly universal products. Chatbots are products, of course. People pay for access to the best of them, or for extended use of them. But people pay for Dropbox too.

Marques Brownlee published a video about the same topic last week, and referenced a Wired podcast episode from the week before.

This seems to be the way things are shaping up and, anecdotally, describes the kinds of A.I. things I find most useful. Previous site sponsor ListenLater’s pitch is it lets you “listen to articles as podcasts”; that it uses an A.I.-trained voice makes it sound better, but is only one component of a more comprehensive story. Generative features in Adobe’s products enable faster and easier object removal from photos, and extending images beyond the known edges.

These are just features, though. Text-to-speech has been around for ages, and training it on real speech patterns makes it sound more realistic than most digital voices have so far been. Likewise, removal tools have been a core feature in image editing software for decades, and Adobe’s has changed a lot in the time I have used it: from basic clone stamping, which allows you to paint an area with sampled pixels, to the healing brush — sort of similar, but it tries to match the tone of the destination — to Content-Aware Fill. And, now, Generative Fill. These tools have made image editing easier and more realistic. It could take hours to remove an errant street sign from a photo with older tools; now, it really does take mere seconds, and the results are usually at least as good as a manual effort. The same is true for extending a photo — something routinely done to make it fit better in an ad or some other fixed composition.

The irony of the feature-not-product framing is that iCloud Drive and OneDrive, for example, have struggled to become as efficient and reliable as Dropbox was when it launched. But, then again, so has Dropbox today. As synced folders became just a feature within a broader platform, Dropbox expanded its offering to become a collaborative work environment, a cloud backup utility, and more. As a result, its formerly quiet and dutiful desktop app has become less efficient.¹

A similar story could be told about 1Password, too, though perhaps not to the same extent. For many users, the password manager built into their system or browser might be fine. 1Password makes a more robust product marketed heavily toward business and enterprise users. Unfortunately, it has supported that effort with a suite of apps which are less efficient for users to create a better workflow for its developers.

If you are looking for the path the standalone A.I. companies are likely to take — aside from a merger or acquisition — these examples may be lurking along the way. I wonder what has been happening with that OpenAI hardware project.