skip to Main Content

Open-sourcing the Scale chatbot

Applications that enable a natural language interface between people and data will be at the forefront of LLM enterprise adoption. At Scale, we launched a chatbot to increase access to information about our firm, but we also built it ourselves to gain an understanding of the solutions space. We've just published a blog post where we explore the architecture and share conclusions from this experience. We're also making the full source code available and free to use.
Read more

Peeking under the hood with ChatGPT plugins

The way these plugins are designed is as open as I can possibly imagine, which means we can peek under the hood at how they are made. That is, if you know where to look. It also offers us a glimpse into potential business ramifications, which we’ll take a look at at the end of this post.
Read more

Foundation Models Are The New Public Cloud

Over the last few years, building an AI startup used to require “do-it-yourself AI,” which consisted of gathering training data, labeling it, architecting complex data transformations, tuning hyperparameters, and selecting the right model. It was a herculean task, similar in complexity to the workload of the Salesforce engineer above.  But in the last year or two, foundation models have emerged as a time-saving shortcut that enable entrepreneurs to do more faster. These foundation models aren’t specific to particular AI use cases, but are largely general and have something to offer almost anyone. Entrepreneurs can now decouple parts of the training data and model (which comes pre-packaged in a foundation model) from the application layer, which we at Scale call a cognitive application.  
Read more
Back To Top