Recently, during an interview [1], when questioned about OpenAI's Sora, Shantanu Narayan (Adobe CEO) gave an interesting perspective on where value is created. His view (paraphrased generously)..
GenAI entails 3 'layers': Data, Foundational Models and the Interface Layer.
Why Sora may not be a big threat is because Adobe operates not only at first two layers (Data and Foundational model) but also at the interface layer. Not only Adobe perhaps knows better than anyone else what is need and workflow of a moviemaker, but I guess most importantly they already have moviemakers as their customers.
So product companies like Adobe (& Microsoft, Google etc.) are in better position to monetize GenAI. Pure-play AI companies like OpenAI are perhaps in B2B business. Actually, they maybe really in api business, they would have great data, would be building great foundational models and giving results of those as APIs; which other companies who are closer to their unique set of customers with their unique needs would be able to monetize and some part of those $$ flows back to pure-play AI companies
[1] At 5 mins mark.. https://www.cnbc.com/video/2024/02/20/adobe-ceo-shantanu-nar...
I only ever heard creatives complain about Adobe and their UI/UX and how they don’t understand their customers.
Never really used any of their products myself though. Maybe they still are best-in-class. I can’t tell.
Every major change in the last 6 years has either been weird window dressing changes to welcome panels or new document panels, in all cases building sluggish jank heavy interfaces, try navigating to a folder in the premier one and weep as clicks take actual seconds to recognize.
Or just silly floating tooltips like the ones in Photoshop that also take a second to visible draw in.
All tangible tool changes exist outside the interface or you jump to a web interface in a window and back with the results being passed between in a way that makes it very obvious the developers are trying to avoid touching the core tools code.
Very clear Narayens outsourcing and not being a product guy has lead to this
Every user hates using microsoft products, and don't get me started on SAP. But these are gigantic companies with wildly successful products aimed at enterprise customers.
Only because they've never had a chance to experience the competition.
Having worked in IBM and had to use the Lotus Office Suite I can tell you Microsoft won fair and square. And I'm not even talking about the detestable abomination that is Lotus Notes.
This one was so obscure to find because it seems to exist in a weird space of being Microsoft Office but not.
Figma could build an illustrator killer in 6 months if they wanted to and it would be obliterated.
If they actually tackled this task people would be kicking themselves for putting up with the shambles that is illustrator for this long.
Statements like this are almost always wrong, if for no other reason that a technically superior alternative is rarely compelling enough by itself. It that weren’t the case you would see it happen far more often…
The scenario I was calling out is more: Company A is great at X, so clearly that technology could be used to easily be great at Y, and doom company B in 6 months. The problem with that thinking is that often the technology is the easy part (and sometimes superficial similarity, also).
There are tools no one uses, and there are tools people constantly complain about.
They’re terrible products for the most part. But they buy the competition (Substance) or they develop some half baked substitute (Adobe XD) that people might use since it comes with the subscription.
Where start-ups like Stability need to be rising to compete will have to be AI-native e.g. products re-thought of from the ground up like an AI image editor or as foundation-level AI research companies, agents or AI infrastructure companies.
There's no reason Stability can't play in both B2B and API if planned and strategized well and OpenAI can definitely pull it off with their tech and talent. But Stability has a few important differentiators from OpenAI where I believe if they launch an AI-native product in the multimodal space, they stand to differentiate significantly: - People join because they believed in Emad's vision of open source so it is their job to figure out a commercial model for open source. They can retain AI talent by ensuring a commitment to open source here. If they need to ensure their moat is retained and can commercialize, they should delay releasing model weights until a product surrounding the weights has been released first. Still open source and open weights but give them time to figure out a commercial strategy to capitalize their research. However because of this promise, they will not be able to license their technology to other companies. - Stability's strong research DNA (unsure about their engineering) is so badly fumbled by a lack of a cohesive product strategy that it leads to sub-par product releases. In agreement to the 3 'layers' argument, that's exactly Stability's greatest strength and weakness. Their focus on foundational models is incredibly strong and has come at the cost of the interface layer (and ultimately the data layer as it has a flywheel effect).
The company currently screams a need for effective leadership that can add on interface and data layers to their product strategy so they can build a strong moat outside of a strong research team which has shown it can disappear at any moment...