There are a few types of k8s resources we use without hesitation. I’m only listing resources here that we create explicitly; most of these resources implicitly create other resources (like Pods) that I will not mention but which we of course (indirectly) use.
Deployments : Most of our pods are created through deployments.
Scalability is crucial - systems need to be designed with the assumption that query volume, document corpus size, indexing complexity etc. could increase by 10x. What works at one scale may completely break at a higher scale.
Sharding the index, either by document or by word, is important to distribute the indexing and querying load across machines.
Puter is an advanced open-source desktop environment in the browser, designed to be feature-rich, exceptionally fast, and highly extensible. It can be used to build remote desktop environments or serve as an interface for cloud storage services, remote servers, web hosting platforms, and more.
What’s the best way for an end user to organize and explore millions of latent space features?
I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more
Neuro modulators bias which neurons are likely to be active and which are not active (kind of like a playlist that plays only particular „moods“ or genres). It makes certain circuits more or less active. Chemical systems like neuro-modulators have a lot of receptors, which behave like parking spots. Once the chemical attaches to the receptor it... See more
SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system.
The core features of SGLang include:
A Flexible Front-End Language : This allows for easy programming of LLM applications with multiple
They have a fast jsond ecoding feature with a finite state machine.
GPT-4 Turbo can accept images as inputs in the Chat Completions API, enabling use cases such as generating captions, analyzing real world images in detail, and reading documents with figures. For example, BeMyEyes uses this technology to help people who are blind or have low vision with daily tasks like identifying a product or navigating a store.... See more