Blog Posts

Overcoming the Skies: Navigating the Challenges of Drone Autonomy

This blog post was originally published at Inuitive’s website. It is reprinted here with the permission of Inuitive. From early military prototypes to today’s complex commercial operations, drones have evolved from experimental aircraft into essential tools across industries. Since the FAA issued its first commercial permit in 2006, applications have rapidly expanded—from disaster relief and […]

Overcoming the Skies: Navigating the Challenges of Drone Autonomy Read More +

NVIDIA Advances Open Model Development for Digital and Physical AI

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. NVIDIA releases new AI tools for speech, safety and autonomous driving — including NVIDIA DRIVE Alpamayo-R1, the world’s first open industry-scale reasoning vision language action model for mobility — and a new independent benchmark recognizes the openness and

NVIDIA Advances Open Model Development for Digital and Physical AI Read More +

Breaking the Human Accuracy Barrier in Computer Vision Labeling

This article was originally published at 3LC’s website. It is reprinted here with the permission of 3LC. Introduction There’s been a lot of excitement lately around how foundation models (such as CLIP, SAM, Grounding DINO, etc.) can come close to human-level performance when labeling common objects, saving a ton of labeling effort and cost. It’s impressive progress. However,

Breaking the Human Accuracy Barrier in Computer Vision Labeling Read More +

Why Edge AI Struggles Towards Production: The Deployment Problem

There is no shortage of articles about how to develop and train Edge AI models. The community has also written extensively about why it makes sense to run those models at the edge: to reduce latency, preserve privacy, and lower data-transfer costs. On top of that, the MLOps ecosystem has matured quickly, providing the pipelines

Why Edge AI Struggles Towards Production: The Deployment Problem Read More +

Small Models, Big Heat — Conquering Korean ASR with Low-bit Whisper

This blog post was originally published at ENERZAi’ website. It is reprinted here with the permission of ENERZAi. Today, we’ll share results where we re-trained the original Whisper for optimal Korean ASR(Automatic Speech Recognition), applied Post-Training Quantization (PTQ), and provided a richer Pareto analysis so customers with different constraints and requirements can pick exactly what

Small Models, Big Heat — Conquering Korean ASR with Low-bit Whisper Read More +

Introducing Gimlet Labs: AI Infrastructure for the Agentic Era

This blog post was originally published at Gimlet Labs’ website. It is reprinted here with the permission of Gimlet Labs. We’re excited to finally share what we’ve been building at Gimlet Labs. Our mission is to make AI workloads 10X more efficient by expanding the pool of usable compute and improving how it’s orchestrated. Over the

Introducing Gimlet Labs: AI Infrastructure for the Agentic Era Read More +

How semiconductor equipment makers will drive the next $1 trillion wave

This blog post was originally published at HCLTech’s website. It is reprinted here with the permission of HCLTech. Key takeaways AI, mobility and cloud are the growth engines: They’re pushing chips toward a $1 trillion market by 2030 and forcing fabs to invest in sub-3nm nodes and advanced packaging Chips are bigger and more complex: Larger dies and

How semiconductor equipment makers will drive the next $1 trillion wave Read More +

The Image Sensor Size and Pixel Size of a Camera is Critical to Image Quality

This blog post was originally published at Commonlands’ website. It is reprinted here with the permission of Commonlands. The sensor format size and pixel size of digital camera impacts nearly every performance attribute of a camera. The format size is a key element that contributes to system constraints across the low-light performance, dynamic range, size,

The Image Sensor Size and Pixel Size of a Camera is Critical to Image Quality Read More +

Trends in Embedded AI: Designing Hardware for Machine Learning on the Edge

This blog post was originally published at Tessolve’s website. It is reprinted here with the permission of Tessolve. The world is increasingly becoming connected, intelligent, and autonomous. At the core of this transformation is Artificial Intelligence (AI), which is swiftly transitioning from the cloud to the edge, nearer to where data is generated and actions are

Trends in Embedded AI: Designing Hardware for Machine Learning on the Edge Read More +

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

Contact

Address

Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596

Phone
Phone: +1 (925) 954-1411
Scroll to Top