The Adoption of Machine Learning Will Resemble the Adoption of Databases | by Bryan Offutt | Index Ventures
Bryan Offuttindexventures.com
The Adoption of Machine Learning Will Resemble the Adoption of Databases | by Bryan Offutt | Index Ventures
sari and added
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
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Nicolay Gerold added
Andrea Badia and added
sari and added
In little more than a decade, machine learning has moved from a highly specialized technique to something that almost anyone with data and computational power can do. That is to be welcomed — yet it remains essential that the industry can navigate both the proliferation of tools and frameworks in the space and the ethical issues that are becoming
... See moreThoughtworks • Technology Radar | An opinionated guide to technology frontiers | Thoughtworks
Tom So 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.
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 g... See more
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 g... See more
scott belsky • Tweet
alex added
moats in an AI world
Sobriety source #2: AI as the next platform shift. Every wave of new companies that transforms their respective industries is fueled by a major platform or technology shift. The advent of the web did this. The smartphone and mobile applications did this. And there is no doubt that AI is our next wave. But does every new wave always necessarily favo... See more
The Great Sobriety for Venture Investing, Where To Start with AI, & Undeniable Data
Abie Cohen added
AI notes