Micron: The Dangerous Disconnect Between Physical Wafer Volume And HBM Hype

Micron Technology is currently valued at over $1.1 trillion, driven by AI memory demand and peak commodity pricing. Click for ...

New method separates brain signals to show how complex actions are organized

A new Northwestern Medicine study has introduced a novel machine learning method for analyzing how the brain organizes ...

Adaptive Computation LLC Assessed ‘Awardable’ for DARPA ERIS Marketplace

Bio-inspired AI, hybrid in-memory processing, and sparse-input system-on-chip technologies recognized as readily ...
GitHub

Scalable in-Memory Middleware

SiMM is a high-performance, scalable Key-Value (KV) cache engine designed for LLM inference workloads. It addresses the critical bottlenecks in long-context prompts and multi-turn agent interactions ...
InfoWorld

Do vector-native databases beat add-ons for AI applications?

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.
IEEE

Toward On-Device Distributed Photovoltaic Power Forecasting: A Tiny Online Learning Framework

Abstract: Increasing numbers of distributed photovoltaic (PV) systems are integrated into power grids. Accurate distributed PV power forecasting is pivotal in guiding individual users to manage their ...
IEEE

EdgeHEM: Sparse Federated Reinforcement Learning for Home Energy Management at the Edge

Abstract: With the growth of energy demand and the popularization of distributed energy resources, home energy management (HEM) has emerged as a crucial technology to improve energy efficiency and ...
GitHub

Decoding speech from non-invasive recordings of brain activity

This is the code for the Decoding speech from non-invasive brain recordings. paper, published in Nature Machine Intelligence in 2023 (also available on arxiv). In this work, we present a novel method ...