Lifeboat Foundation

In a new Nature study, Columbia Engineering researchers have built a photonic chip that is able to produce high-quality, ultra-low-noise microwave signals using only a single laser. The compact device—a chip so small, it could fit on a sharp pencil point—results in the lowest microwave noise ever observed in an integrated photonics platform.

The achievement provides a promising pathway towards small-footprint ultra-low-noise microwave generation for applications such as high-speed communication, atomic clocks, and autonomous vehicles.

The challenge Electronic devices for global navigation, wireless communications, radar, and precision timing need stable microwave sources to serve as clocks and information carriers. A key aspect to increasing the performance of these devices is reducing the noise, or random fluctuations in phase, that is present on the microwave.

Learn More https://tinyurl.com/ThermonatorThermonator is the first-ever flamethrower-wielding robot dog. This quadruped is coupled with the ARC Flamethrower…

Globally, computation is booming at an unprecedented rate, fueled by the boons of artificial intelligence. With this, the staggering energy demand of the world’s computing infrastructure has become a major concern, and the development of computing devices that are far more energy-efficient is a leading challenge for the scientific community.

LVLM-Intrepret.

An interpretability tool for large vision-language models.

In the rapidly evolving landscape of artificial intelligence, multi-modal large language models are emerging as a significant area of interest.

Continue reading “Paper page — CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching” »

Companies are trying to make the “AI PC” happen with new silicon and software.

With 5,000 tiny robots in a mountaintop telescope, researchers can look 11 billion years into the past. The light from far-flung objects in space is just now reaching the Dark Energy Spectroscopic Instrument (DESI), enabling us to map our cosmos as it was in its youth and trace its growth to what we see today.

DESI Survey announces the most precise measurements of our expanding #universe using the BAO signal in 6.1 Million #galaxies and #Quasars from Year 1, tracing dark energy through cosmic time.

With 5,000 tiny robots in a mountaintop telescope, researchers can look 11 billion years into the past. The light from far-flung objects in space is just now reaching the Dark Energy Spectroscopic Instrument (DESI), enabling us to map our cosmos as it was in its youth and trace its growth to what we see today. Understanding how our universe has evolved is tied to how it ends, and to one of the biggest mysteries in physics: dark energy, the unknown ingredient causing our universe to expand faster and faster.

Continue reading “First Results from DESI Make the Most Precise Measurement of Our Expanding Universe” »

Study links dopamine to learning via optogenetics:

A new study reveals dopamine’s role in animal behavior having potential applications in education and artificial intelligence.

As computer vision (CV) systems become increasingly power and memory intensive, they become unsuitable for high-speed and resource deficit edge applications — such as hypersonic missile tracking and autonomous navigation — because of size, weight, and power constraints.

At the University of Pittsburgh, engineers are ushering in the next generation of computer vision systems by using neuromorphic engineering to reinvent visual processing systems with a biological inspiration — human vision.

Rajkumar Kubendran, assistant professor in Pitt’s Swanson School of Engineering and senior member at the Institute of Electrical and Electronics Engineers (IEEE), received a Faculty Early Career Development (CAREER) award from the National Science Foundation (NSF) for his research on energy-efficient and data-efficient neuromorphic systems. Neuromorphic engineering is a promising frontier that will introduce the next generation of CV systems by reducing the number of operations through event-based computation in a biology-inspired framework.