Featuredpodcast
In this episode, we talk about how AI is being leveraged for designing better batteries and training microswimmers.
Be the first to know.
Get our A.I. weekly email digest.
A.I.
podcast
In this episode, we talk about how AI is being leveraged for designing better batteries and training microswimmers.
Featured
5 Questions to Ask Before Getting Started with Data Annotation: What is data annotation? Why is it essential? What are common label types for models? How do AI-powered data annotation tools help with the computer vision labeling process? What’s the best way to get started?
Featured
The in-sensor adaptation strategy widens the range for image perception under different illumination conditions to simplify the complexity of hardware and algorithms.
Engineers Wiki. Most Asked Questions.
Comprehensive Guide
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
What Is Unsupervised Learning? Types, Algorithms, and Examples (2026)
By Muhammad Sufyan.
15 minutes read.
Understanding Nvidia CUDA Cores: A Comprehensive Guide
By Ravi Rao.
20 minutes read.
NPU vs GPU: Understanding the Key Differences and Use Cases
By Ramsha Jawaid.
13 minutes read.
TPU vs GPU: Comprehensive Technical Comparison
By Ramsha Jawaid.
17 minutes read.
Understanding Nvidia CUDA Cores: A Comprehensive Guide for 2026
By Ramsha Jawaid.
25 minutes read.
Top Vision Systems for Manufacturing in 2026
By Muhammad Sufyan.
11 minutes read.
ORGANIZATIONS. SHAPING THE INDUSTRY.
The Next Byte
Entertainment
The Next Byte Podcast is hosted by two young engineers - Daniel and Farbod - who select the most interesting tech/engineering cont...
165 Posts
High Tech Campus Eindhoven
High Tech
High Tech Campus Eindhoven is Europe's smartest square km and has the ultim...
49 Posts
ETH Zurich
University for science and technology
Freedom and individual responsibility, entrepreneurial spirit and open-min...
43 Posts
TAGGED WITH machine learning
From leading experts at the CDFAM Computational Design Symposium
eCozy 2.0 system addresses the limitations of traditional thermostats for water heating radiators, delivering efficiency, convenience and sustainability benefits to households
Protect the cloud by securing the edge with hardware-based security, TPMs, HSMs, and resilient edge computing architectures.
Explore the rise of intelligent EV hardware and how real-time processing, ML acceleration, and hardware virtualization are enabling safer, smarter, software-defined electric vehicles.
TAGGED WITH computer vision
EPFL researchers are developing AI models that could one day enable vision prosthetics able to restore meaningful, object-level sight for the blind.
A deep-dive listicle guiding controls, automation, and quality engineers toward the best vision systems for manufacturing applications in 2026.
Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Latest Posts
In this episode, we talk about how AI is being leveraged for designing better batteries and training microswimmers.
5 Questions to Ask Before Getting Started with Data Annotation: What is data annotation? Why is it essential? What are common label types for models? How do AI-powered data annotation tools help with the computer vision labeling process? What’s the best way to get started?
4 minutes read
The in-sensor adaptation strategy widens the range for image perception under different illumination conditions to simplify the complexity of hardware and algorithms.
Sounds provide important information about how well a machine is running. ETH researchers have now developed a new machine learning method that automatically detects whether a machine is "healthy" or requires maintenance.
4 minutes read
Designed to address the OOD data false prediction by adaptively synthesizing virtual outliers that can maintain the model’s decision boundary during training.
Designed to address the exploding computational demands of deep neural networks, physical neural networks (PNNs) branch out from electronics into optics and even mechanics to boost performance and efficiency.
Designed for use in the human body for everything from drug delivery to less-invasive biopsies, these tiny microrobots operate under the control of a deep-learning system trained with no modelling or prior environmental knowledge.
Intelligent Automation (IA) is a set of technologies and methods for automating the work of white-collar professionals and knowledge workers. Here, we present a framework for explaining its power in terms of four main capabilities—Vision, Execution, Language, and Thinking & Learning—and how they can enable business transformations, with people and business goals at the center.
Taking its cues from the haunting electronic instrument, the MoCapaci project sews a theremin into a blazer to feed a deep-learning system with data for accurate gesture sensing and activity recognition.
Over the last decade, deep neural networks have emerged as the solution to several AI complex applications from speech recognition and object detection to autonomous vehicular systems.
A system with an opto-chemical sensor combined with a battery-free NFC tag of resolution 103 ppm for measuring the CO2 gas concentration in the dead space volume of the facemask
Precise and fast dimensioning of objects moving on a conveyor belt enabled by Photoneo's novel technology of Parallel Structured Light.
2 minutes read
Designed to address the risk to front-line staff from COVID-19, this autonomous swab-sampling robot is designed to take the human element out of sample gathering.
Using a now public-access dataset, a research team has created a robotics control system which can generalize to unseen related tasks — allowing robots to interpret natural-language commands and video demonstrations.
Attention: Don’t presume human or model-generated labels to be the growth truth for machine learning deployment in autonomous vehicular systems.
