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New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.
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New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.
Featured
Transforming Robotics Through Collaboration: Lessons from Shadow Robot and DeepMind's DEX-EE Project
Shadow Robot’s partnership with Google DeepMind exemplifies how collaboration drives innovation in robotics and AI. This article explores how their expertise in dexterous robotic hands, particularly the DEX-EE, is advancing machine learning research.
Featured
New research could improve the safety of drone shows, warehouse robots, and self-driving cars.
Engineers Wiki. Most Asked Questions.
This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!
TPU vs GPU: Comprehensive Technical Comparison
By Umar Waseem.
14 minutes read.
NPU vs GPU: Understanding the Key Differences and Use Cases
By Ravi Rao.
13 minutes read.
RAG vs Fine-Tuning: Differences, Benefits, and Use Cases Explained
By Ravi Rao.
18 minutes read.
LLM Training: Mastering the Art of Language Model Development
By Ravi Rao.
30 minutes read.
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ORGANIZATIONS. SHAPING THE INDUSTRY.
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
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TAGGED WITH machine learning
Nakahira received a Young Investigator Award from the Japan Science and Technology Agency for developing a machine that builds autonomous systems.
Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic frameworks, or MOFs.
EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.
MIT researchers' DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
TAGGED WITH motion capture systems
Latest Posts
New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.
2 minutes read
Transforming Robotics Through Collaboration: Lessons from Shadow Robot and DeepMind's DEX-EE Project
Shadow Robot’s partnership with Google DeepMind exemplifies how collaboration drives innovation in robotics and AI. This article explores how their expertise in dexterous robotic hands, particularly the DEX-EE, is advancing machine learning research.
New research could improve the safety of drone shows, warehouse robots, and self-driving cars.
By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.
Building on the success of conventional wearables, smart rings have been enthusiastically embraced by early adopters with a finger on the pulse of cutting-edge yet fashionable health and fitness wireless products.
3 minutes read
Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
NPUs are integrated units that excel in real-time AI tasks on edge devices like smartphones and IoT systems with low power consumption. TPUs are standalone processors designed for large-scale AI workloads in data centers, delivering exceptional performance in deep learning tasks.
Texas A&M University is creating advanced mapping technologies to further the evolution of autonomous vehicles.
3 minutes read
Learn how agnostic systems like Awentia's No-Data Vision Foundation Model addresses key barriers to AI adoption such as data dependency, cost, and complexity across industries like agriculture, robotics and manufacturing.
For this article we interviewed Niwa and Omura, who are responsible for the design, development, and operation of the system, as well as Toda, who requested its development and is also a user.
9 minutes read
Generative AI has evolved to become an advanced, general-purpose technology that has reached the level of practical use, and the usage scenarios have become more familiar applications. Nowadays, the application of AI including generative AI has even expanded into the field of sports.
6 minutes read
EPFL researchers have developed 4M, a next-generation, open-sourced framework for training versatile and scalable multimodal foundation models that go beyond language.
4 minutes read
Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.
GPUs excel in parallel processing for graphics and AI training with scalability, while NPUs focus on low-latency AI inference on edge devices, enhancing privacy by processing data locally. Together, they complement each other in addressing different stages of AI workloads efficiently.
A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.
