Rather than what many BigTech companies are currently doing: "Wall Street says we need to 'Use AI Somehow'. Let's invest in AI and Find Things To Do with AI. Later, we'll worry about somehow matching these things with user needs."
This is a testable claim: where were Adobe in previous hype cycles? Googles "Adobe Blockchain"...looks like they were all about blockchains in 2018 [0], then NFTs and "more sustainable blockchains" in 2022 [1].
[0] https://blog.adobe.com/en/publish/2018/09/27/blockchain-and-...
[1] https://www.ledgerinsights.com/adobe-moves-to-sustainable-bl...
Which I'm reading as "Demo-ready, but far from production-ready."
Somewhat relevant: my experience with Photoshop's Generative Fill has been underwhelming. Sometimes it's wrong, often it's comically wrong. I haven't had many easy wins with it.
IMO this is a company that doodles with code for its own entertainment, not a company that innovates robust and highly useful production-ready features for the benefit of users.
So we'll see if Mr Spinny Dragon makes it to production, and is as useful as billed in the demo.
I'll admit I have no idea what % of Adobe licensees/subscribers are individuals and small visual/graphic design firms (who choose Adobe for personal reasons) compared to larger companies (news agencies, web-design body-shops, etc) where employees use the tools given to them despite any personal preferences for rivals like Procreate, etc - and the rest: students, hobbyist photographers, etc.
...but none of the aforementioned market-segments seem like they'd make "AI" (whatever that means) any part of their purchasing-decision. Buzzwords only help sales when the audience is ignorant and/or impressionable; and when your audience are well-informed, seasoned (and cynical) professionals then buzzwords have the opposite effect and damage a company's credibility.
...so I'm not sure who, exactly, Adobe is trying to message with their press-copy for Adobe Firefly (their "generative AI for business" product); perhaps it's just a charade meant only for their shareholders? I'm glad they aren't copying Microsoft and shoving AI branding where it really doesn't belong and compromising the user-experience (...at least not so the same extent).
The gist is that once a company has a captive audience with no alternatives, investors come first. Flashy (no pun intended :-p), cool features to impress investors become more important than the everyday user experience—and this feature does look super cool!
--
Still, when I first heard of Adobe Firefly, my initial reaction was “smart business move, by exclusively using images they have the rights to”. Now seeing Turntable my reaction is “interesting tool which could be truly useful to many illustrators”.
Adobe can be a bad and opportunistic company in general but still do genuinely interesting things. As much as they deserve the criticism, the way in which they’re using AI does seem to be thought out and meant to address real user needs while minimising harm to artists.¹ I see Apple’s approach with Apple Intelligence a bit in the same vein, starting with the user experience and working backwards to the technology, as it should be.²
Worth noting that I fortunately have distanced myself from Adobe for many years now, so my view may be outdated.
¹ Which I don’t believe for a second is out of the goodness of their hearts, it just makes business sense.
² However, in that case the results seem to be subpar and I don’t think I’d use it even if I could.
> I also think “AI art” can be harmful to artists and more often than not produces uninteresting flawed garbage at an unacceptable energy cost.
The big genAI flamewar actually has very little do with copyright or would-be-lost jobs. It's mostly about quality and emotions encoded in the images(deep rage). Lots of tech inclined miss this point.
All of this is orthogonal to Adobe's business practices. You should expect them to operate the way they do given their market share and the limited number of alternatives. I personally have almost moved completely to Affinity products, but I expect that Adobe should be better placed to execute products and for Affinity to be playing catchup to some extent.
The HN guidelines rightfully urge us to make substantive comments that advance the discussion and avoid shallow dismissals.
Yes, that’s the impression I got out of it too. I disapprove either way. I’d sooner defend a good argument against my point than a bad argument in favour of it.
I come to HN for reasoned, thoughtful, curious discussion.
Unfortunately, this gets you some comments that want to disagree with that less specific, initial aside. I’m not sure if people just read the first paragraph and respond entirely based on that, without realizing that it is not the main point of the rest of the post. Or if they just don’t want to give up the ground that you did in the beginning, at all, so they knowingly ignore the rest of the post.
I don’t really know what to do about this sort of thing. It seems like… generally nice to be able to start a post with something that says basically: look I’ve thought about this and it isn’t an uninformed reflexive take. But I’m trying to give up on that sort of thing. It isn’t really logically part of the argument, and it ends with people arguing in a direction that I’m not really interested in defending against in this context.
But it does seem a shame, because, while it isn’t logically part of the argument, it is nice to know beforehand how firm somebody’s stance is.
This is clearly incorrect to some, not to others. This point being unclear to some, leads to those people assuming that the commonly observed strong negativity is generalized response to all shape and form of new technologies, rather than that specific emotional reaction to current generation of still somewhat Lovecraftian generative AI outputs.
A bit like what if a non-vision super LLM was to characterize anti-genAI sentiment and create "techno-luddite artist" persona. But there's across-modal component to it that they don't capture, so that falls flat.
I think another, perhaps more relevant reference could be the replacement of hand-painted cells with computer-generated frames for animation. It replaced one kind of artist with another. Nobody got all that worked up about it, in the long run.
I like this reasoning. If something is new then it must be the future of humanity. People scoffed at Concorde for being “wasteful” and “flawed” but look at the company today
Discussion should assume good faith and responses should become more substantive, not less, as the conversation goes on.
Cool features that excite users (and that they ultimately end of using), and that get investors excited.
(i.e. Adobe mentioned in the day 1 keynote that Generative Fill, released last year and powered by Adobe Firefly is not one of the top 5 used features in Photoshop).
The features we make, and how we use gen ai is based on a lot of discussions and back and forth with the community (both public and private)
I guess Adobe could make features that look cool, but no one wants to use, but that doesn't seem to really make any sense.
(I work for Adobe)
I mean, is there any Photoshop feature that’s come to dominate people’s workflows so quickly?
People (e.g. photographers) who use Photoshop “in anger” for professional use-cases, and who already know how to fix a flaw in an image region without generative fill, aren’t necessarily going to adopt it right out of the gate. They’re going to tinker with it a bit, but time-box that tinkering, otherwise sticking with what they can guarantee from experience will get a “satisfactory” result, even if it takes longer and might not have as high a ceiling for how perfectly the image is altered.
And that’d just people who repair flaws in images. Which I’m guessing aren’t even the majority of Photoshop users. Is the clone brush even in the top 5 Photoshop features by usage?
There was a brief moment in time where freehand was just a better and faster drawing tool than illustrator (which is whats is shown here) but from there on psp, ill & indesign have pretty much killed all competition out there.
The formats they use are sigularly stupid and arcane for legacy reasons, they are all mem hogs and inefficient to the extreme - but nothing beats that unholy trifecta and it is used it or die.
Now to get the point: generative fill is one of the absolute killer features of psp - in an instant it does what could take multiple hours to do previously with 5-10 sec of watching a loader.
There are many mor gamechangers and this really looks like another
So instead of the old workflow:
"visit HR page" → "click link that for whatever reason doesn't give you a permanent link you can bookmark for later"
it's now:
"visit HR page" → "do AI search for the same link which is suggested as the first option" → "wait 10-60 seconds for it to finally return something" → "click link that for whatever reason doesn't give you a permanent link you can bookmark for later"
Sounds like engagement hacking?
As a side note, a similar phenomenon occurred with the Adam optimizer, where the ratio of public/scientific attribution to novelty is disproportionately large (the Adam optimizer is very minor modification of the RMSProp + momentum optimization algorithm presented in the same Graves, 2013 paper mentioned above)
The reusable/stackable block is of course a key part of the design since the key insight was that language is as much hierarchical as sequential, and can therefore be processed in parallel (not in sequence) with a hierarchical stack of layers that each use the key-based lookup mechanism to access other tokens whether based on position or not.
In any case, if you look at the seq2seq architectures than preceded it, it's hard to claim that the Transformer is really based-on/evolved-from any of them (especially prevailing recurrent approaches), notwithstanding that it obviously leveraged the concept of attention.
I find the developmental history of the Transformer interesting, and wish more had been documented about it. It seems from interview with Uszkoreit that the idea of parallel language processing based on an hierarchical design using self-attention was his, but that he was personally unable to realize this idea in a way that beat other contemporary approaches. Noam Shazeer was the one who then took the idea and realized it in the the form that would eventually become the Transformer, but it seems there was some degree of throw the kitchen sink at it and then a later ablation process to minimize the design. What would be interesting to know would be an honest assessment of how much of the final design was inspiration and how much experimentation. It's hard to imagine that Shazeer anticipated the emergence of induction heads when this model was trained at sufficient scale, so the architecture does seem to at least partly be an a accidental discovery, and more than the next generation seq2seq model that it seems to have been conceived as.
I think you're overestimating the degree to which this type of research is motivated by big-picture, top-down thinking. In reality, it's a bunch of empirically-driven, in-the-weeds experiments that guide a very local search in a intractably large search space. I can just about guarantee the process went something like this:
- The authors begin with an architecture similar to the current SOTA, which was a mix of recurrent layers and attention
- The authors realize that they can replace some of the recurrent layers with attention layers, and performance is equal or better. It's also way faster, so they try to replace as many recurrent layers as possible.
- They realize that if they remove all the recurrent layers, the model sucks. They're smart people and they quickly realize this is because the attention-only model is invariant to sequence order. They add positional encodings to compensate for this.
- They keep iterating on the architecture design, incorporating best-practices from the computer vision community such as normalization and residual connections, resulting in the now-famous Transformer block.
At no point is any stroke of genius required to get from the prior SOTA to the Transformer. It's the type of discovery that follows so naturally from an empirically-driven approach to research that it feels all but inevitable.
At least, the Transformer didn't. The abstract idea of a language model goes way back though within the field of linguistics, and people were building simplistic "N-gram" models before ever using neural nets, then using other types of neural net such as LSTMs and CNNs(!) before Google invented the Transformer (primarily with the goal of fully utilizing the parallelism available from GPUs - which couldn't be done with a recurrent model like LSTM).
What's wrong with trying out 100 different AI features across your product suite, and then seeing which ones "stick"? You figure out the 10 that users find really valuable, another 10 that will be super-valuable with improvement, and eventually drop the other 80.
Especially when if Microsoft tries something and Google doesn't, that suddenly gives Microsoft a huge lead in a particular product, and Google is left behind because they didn't experiment enough. Because you're right -- Google investors wouldn't like that, and would be totally justified.
The fact is, it's often hard to tell which features users will find valuable in advance. And when being 6 or 12 months late to the party can be the difference between your product maintaining its competitive lead vs. going the way of WordPerfect or Lotus 123 -- then the smart, rational, strategic thing to do is to build as many features as possible around the technology, and then see what works.
I would suggest that if Adobe is being slower with rolling out AI features, it might be more because of their extreme monopoly position in a lot of their products, thanks to the stickiness of their file formats. That they simply don't need to compete as much, which is bad.
For users? Almost everything is wrong with that.
There are no users looking for wild churn in their user interface, no users crossing their fingers that the feature that stuck for them gets pruned because it didn't hit adoption targets overall, no users hoping for popups and nags interrupting their workflow to promote some new garbage that was rushed out and barely considered.
Users want to know what their tool does, learn how to use it, and get back to their own business. They can welcome compelling new features, of course, but they generally want them to be introduced in a coherent way, they want to be able to rely on the feature being there for as long as their own use of those features persists, and they want to be able to step into and explore these new features on their own pace and without disturbance to their practiced workflow.
The users of https://notebooklm.google/ aren't the same as the users of Google Docs.
And I haven't seen any "wild churn" at all -- like I said in another comment, a few informative popups and a magic wand icon in a toolbar? It's not exactly high on the list of disruptions. I can still continue to use my software the exact same way I have been -- it's not replacing workflows.
But it's way worse if the product you rely on gets discontinued.
Generative ML technologies may dramatically change a lot of our products over time, but there's no great hole they're filling and there's basically no moat besides capital requirements that keeps competitors from catching up with each other as features prove themselves out. They just open a few new doors that people will gradually explore.
Anxiously spamming features simply betrays a lack of confidence in one's own product as it stands, directly frustrates professional users, and soaks up tons capital that almost certainly has other places it could be going.
Sounds like famous last words to me.
The corporate landscape is filled with the corpses of companies that thought they didn't need to rush to adapt to new technologies. That they'd have time to react if something really did take off in the end.
Just think of how Kodak bided its time to see if newfangled digital photography would actually take off and when... and then it was too late.
The discussion you started is about spamming features to see what sticks, as set against making deliberate, selective product decisions as you confidently observe your market.
It's possible that a company that ideologically sets itself against delivering any generative AI features ever might miss where the industry is going over the next 10 or 20 years. But we were never talking about that, were we?
Do you remember two years ago when ChatGPT came out, and people here on HN were confidently declaring it was the end of Google Search, unless Google proved they could respond immediately? And Google released Gemini less than six months later to demonstrate that Search wasn't going to go the way of Kodak, and it still took people a while to calm down after that?
And the AI revolution is moving a lot faster than the digital photography revolution. We're not talking about "the next 10 or 20 years". You seem to be severely underestimating the power of competition and technological progress, and the ability for it to put you out of business.
You're suggesting the correct approach is "deliberate, selective product decisions as you confidently observe your market." What happens when your deliberation is too slow, your selectivity turns out to be wrong, and your confidence is ill-founded? Well, the company that was willing to experiment with a lot more features is more likely to build the winning features and take over the market while you were busy deliberating.
I'm surprised to be having this conversation on HN, where the start-up ethos reigns supreme. The whole idea of the tech world is to try new things and fail fast, because it's better for everyone in the long run. That's what the big corporations are doing with AI features. Isn't that the kind of thing that tech entrepreneurs are supposed to celebrate?
This modern idea of “you’ll own nothing and you’ll like it” ruins that of course, but if someone bought CS6 they can still be using it today. If adobe went bankrupt 5 years ago they could still be legally using it today (they’d have to bypass the license checks if the servers go down, which might be illegal in the US, though). If adobe goes bankrupt tomorrow and I have a CC subscription, I can’t legally keep using photoshop after the subscription runs out.
Even the biggest tech companies have limited engineering bandwidth to allocate to projects. What's wrong with those 100 experiments is the opportunity cost: they suck all the oxygen out of the room and could be shifting the company's focus away from fixing real user problems. There are many other problems that don't require AI to solve, and companies are starving these problems in favor of AI experiments.
It would be better to sort each potential project by ROI, or customer need, or profit, or some other meaningful metric, and do the highest ranked ones. Instead, we're sorting first by "does it use AI" and focusing on those.
If you look at all the recent Google Docs features rolled out, only a small minority are AI-related:
https://workspaceupdates.googleblog.com/search/label/Google%...
There are a few relating to Gemini in additional languages and supporting additional document types, but the vast majority is non-AI.
Seems like the companies are presumably sorting on ROI just fine. But, of course, AI is expected to have a large return, so it's in there too.
Each of our decisions to buy or not buy a product, to use or not use a feature, influences the future design of our products.
And thank goodness, because that's the process by which products improve. It's capitalism at work.
Mature technologies don't need as much experimentation because they're mature. But whenever you get new technologies, yes all these new applications battle each other out in the market in a kind of survival-of-the-fittest. If you want to call consumers "lab rats", I guess that's your choice.
But the point is -- yes, it's not only OK -- it's something to be celebrated!
People buy products for the novelty all the time. Sometimes they are disappointed with what they got, sometimes they discover new things. Take this very feature being discussed. How many people need it if Adobe released it today? How many would like what they see and decide to buy or renew?
> Given the option (in the absence of monopoly) they will search for another company that treats them correctly.
Are we still talking about product features?
It's not "force-feeding". You usually get a little popup highlighting the new feature that you close and never see again.
It's not that hard to ignore a new "magic wand" button in the toolbar or something.
I personally hardly use any of the features, but neither do I feel "force-fed" in the slightest. Aside from the introductory popups (which are interesting), they don't get in my way at all.
"But Google does it. If we do it, we will be like Google".
Were you in my meeting about 40 minutes ago? Because that's almost exactly what was said.
If the big tech companies wanted to be really evil, they could invent a nonsense tech that doesn't work, then watch as all the small upstart competitors bankrupt themselves to replicate it.
The latter one is what overwhelmingly more companies (not only BigTech, not at all!) adopted nowadays.
And Boeing. ;)
"If I asked people what they wanted they would've said faster horses," or whatever Henry Ford is falsely accused of saying.
Also I am sure Adobe is doing both. They released an OpenAI competitor recently
At the same time, apparently their generative autofill is top notch. It's just a shame the industry decided to mix together ML tools with generative art, so that it's hard to tell which from which on a casual glance
Also, Lightroom is one of the worst camera tools out there. It's only known because ADOBE...