OCEAN is a next-generation decentralized AI assistant powered by the industry-leading Cerebras CS-3 wafer-scale chips. OCEAN offers blazing response times to a broad feature set that includes voice interaction and a commitment to decentralization.

Most people are running on default questions they never chose to install. Questions like "Why is this happening to me?" or "What if I fail?" create a self-fulfilling prophecy of mediocrity. The right question can instantly shift your perspective.

A smarter way to allocate computing resources in AI transformers is making them faster and more efficient.

A smarter way to allocate computing resources in AI transformers is making them faster and more efficient.

A smarter way to allocate computing resources in AI transformers is making them faster and more efficient.

A smarter way to allocate computing resources in AI transformers is making them faster and more efficient.

A smarter way to allocate computing resources in AI transformers is making them faster and more efficient.

This section provides a brief review of the Lie group and the geometries of SPD manifolds.

Our framework offers the theoretical guarantee of controlling both the Riemannian mean and variance. Empirically, we focus on Symmetric Positive Definite (SPD) manifolds, which possess three distinct types of Lie group structures.

Our universe at a large scale can be described well if we assume isotropy and homogeneity of space.

This thesis examines several models of Weakly Interacting Massive Particle (WIMP) dark matter and their implications from a phenomenological standpoint.

A good candidate for DM must be stable or have a lifetime greater than the age of the universe.

As an AI practitioner, you're expected to understand machine learning, AI algorithms, and data analysis. You should also be able to design and implement AI solutions in real-world situations. However, attempting to do all this fast may spur a series of mistakes that reduce your expertise. Read on as I break down the 10 most common mistakes I've seen new AI practitioners make and how you can avoid them.

Running a sprint retrospective effectively is hard. In this post, we will look at ways to make the most of your retros to enable your team to be more effective.

Discover different archetypes of data engineers and how their collaboration drives data-driven success.

Fast-Coresets offer a nearly-linear time solution for clustering compression, balancing efficiency and accuracy. While sensitivity sampling remains the gold standard, heuristic methods can achieve competitive results for well-behaved datasets. Experimental results show that Fast-Coresets provide reliable compression with logarithmic runtime scaling, outperforming traditional approaches in speed.

Fast-Coresets offer the best compression guarantees, but uniform sampling suffices for well-behaved datasets. Future research must address fairness and optimality.