Interface > Data > Models
While media still focuses on the “next best model” rat race, increasingly believe that the “interface” and “data” layers will further distinguish market leaders while the “models” layer becomes increasingly commoditized and pushed to the edge (becoming increasingly obvious as mobile chips get better and OSes get their act together)
As a growing number of our everyday use-cases of powerful GenerativeAI models fall below the frontier of “the best models,” they will be enabled by cheaper commoditized models.
And we’ll be running many models locally on device within a few years. The distinguishing factors for companies to succeed using AI will be the radical refactoring of workflows via interface innovations and the data itself - enabling companies and people to uniquely leverage their own data in powerful ways.
Data stewards and Designers FTW! :-)
Interface > Data > Models While media still focuses on the “next best model” rat race, increasingly believe that the “interface” and “data” layers will further distinguish market leaders while the “models” layer becomes increasingly commoditized and pushed to the edge (becoming increasingly obvious as mobile chips get better and OSes get their act together) As a growing number of our everyday use-cases of powerful GenerativeAI models fall below the frontier of “the best models,” they will be enabled by cheaper commoditized models. And we’ll be running many models locally on device within a few years. The distinguishing factors for companies to succeed using AI will be the radical refactoring of workflows via interface innovations and the data itself - enabling companies and people to uniquely leverage their own data in powerful ways. Data stewards and Designers FTW! :-)
Interface > Data > Model: The “interface” and “data” layers will further distinguish market leaders while the “models” layer becomes increasingly commoditized and pushed to the edge. As a growing number of our everyday use-cases of powerful GenerativeAI models fall below the frontier of “the best models,” they will be enabled by cheaper commoditize... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Nicolay Gerold added
Better models won't decide the next wave of AI winners. Better experiences'll decide them.
Nickey Skarstad • Your AI is powerful. But will your mom use it?
As we see base models continue to proliferate, and fine-tuned models begin to sit on top of them, our hypothesis is that these “thin layer” products should focus on having a clear opinion of how they form the output or how they shape the human to AI interaction layer. Put simply, the maximally viable product in AI is likely not where the vast major... See more
Michael Dempsey • Thin Layers of AI, Thick Layers of Personality
Joey DeBruin added
Model managers of tomorrow will need to learn the same things. They’ll need to know which AI models to use for which tasks. They’ll need to be able to quickly evaluate new models that they’ve never used before to determine if they’re good enough. They’ll need to know how to break up complex tasks between different models suited to each piece of wor... See more
Dan Shipper • The Knowledge Economy Is Over. Welcome to the Allocation Economy
Britt Gage added
But just like the internet, someone will show up later and think about something like Uber and cab driving. Someone else showed up and thought, “hey, I wanna check out my friends on Facebook.” Those end up being huge businesses, and it’s not just going to be one model that OpenAI or Databricks or Anthropic or someone builds, and that model will dom... See more
Sarah Wang • What Builders Talk About When They Talk About AI | Andreessen Horowitz
Nicolay Gerold added
Not sure about this one. Just an interesting snippet. I figure there are some reinforcing loops in the data, where the models get better with more data, attracting more users, generating more data. At the same time, I believe there are huge advantages in the knowledge on how to train and how to manage inference at scale, which makes a huge difference. I do not see anyone catching up to OpenAI at the moment, especially with their new finetuning offer.
An interesting factor might be figuring out the right data mix for pre-training and using a better screeing to weed out unwanted behavior. Whoever can figure that out at scale might have a huge advantage, if they can keep it a secret.
Scott Belsky Talk at South Park Commons
Often designs from frustration
Right now, greater skill is being brought by compute and developing a democratization of many things (code, design, etc.). Because of this, taste will probably be the most important skill
Taste is derived from culture and overlap of industries
Because of that
Before we know it, saying a product “uses AI” will seem as silly and obvious as saying a product “uses a database.” Today, the average developer might not know how a query planner works, but they definitely use a database. Similarly, we don’t expect the average developer in five years to know how a transformer works. But we guarantee they will know... See more
Bryan Offutt • The Adoption of Machine Learning Will Resemble the Adoption of Databases | by Bryan Offutt | Index Ventures
Nicolay Gerold added
sari added