AI agents perform real work on our behalf: editing files, running code, and carrying out multi-step tasks over hours or days. This often requires access to private information, which makes where an agent runs matter more than how smart the model is.
Sandboxes keep agents secure, letting them access the tools and files they need to complete these tasks, while keeping sensitive information protected.
When building our agent platform Computer, we explored off-the-shelf sandbox options. Every option required us to consider tradeoffs between functionality, efficiency, and security. Perplexity Computer needed all three, so we built an entirely new type of sandbox.
Today, we’re introducing SPACE, a sandbox platform designed to unlock Computer’s full power while providing the highest level of security for advanced agentic systems. — Read More
Daily Archives: July 16, 2026
Inkling: Our open-weights model
Our mission is to build AI that extends human will and judgment. We have developed a platform that lets anyone customize models, previewed an AI system built for interactive collaboration, and published novel research. Today we are advancing our mission by releasing a model we trained from scratch with the full weights available, so that people can make it their own.
Our model, called Inkling, is a Mixture-of-Experts transformer with 975B total parameters, 41B active. It supports a context window of up to 1M tokens. It was pretrained on 45 trillion tokens of text, images, audio and video. It is the first in a family of models of different sizes: alongside it we are sharing a preview of Inkling-Small, a lighter-weight model with 12B active parameters, trained with a similar recipe, that achieves strong performance with even lower cost and latency. — Read More
The Ultimate Guide for AI, Part II
Last week I wrote my longest newsletter ever, 8,500 words long, which covered the essentials of AI software and hardware, from the very basic key intuitions about AI models (what they are, how they learn), to the key intuitions in AI hardware that helped readers understand why GPUs and other accelerators are used, why memory is so important, and other key ideas the industry holds dear.
And finally, we discussed the “interesting” world of AI finance, particularly some numbers to understand how this entire industry aims to make money.
Today, I bring you the second part of the guide. In this one, I’ve focused more on the product, detailed AI inference maths, and future trends. — Read More
