Categories: AI/ML News

Ultra-low power neuromorphic hardware show promise for energy-efficient AI computation

A team including researchers from Seoul National University College of Engineering has developed neuromorphic hardware capable of performing artificial intelligence (AI) computations with ultra-low power consumption. The research, published in the journal Nature Nanotechnology, addresses fundamental issues in existing intelligent semiconductor materials and devices while demonstrating potential for array-level technology.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

10 Ways to Use Embeddings for Tabular ML Tasks

Embeddings — vector-based numerical representations of typically unstructured data like text — have been primarily…

3 hours ago

Over-Searching in Search-Augmented Large Language Models

Search-augmented large language models (LLMs) excel at knowledge-intensive tasks by integrating external retrieval. However, they…

3 hours ago

How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AI

This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health,…

3 hours ago

Anthropic launches Cowork, a Claude Desktop agent that works in your files — no coding required

Anthropic released Cowork on Monday, a new AI agent capability that extends the power of…

4 hours ago

New Proposed Legislation Would Let Self-Driving Cars Operate in New York State

New York governor Kathy Hochul says she will propose a new law allowing limited autonomous…

4 hours ago

From brain scans to alloys: Teaching AI to make sense of complex research data

Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements,…

4 hours ago