Spatial computing promises to transform the way we interact with our devices as computing goes truly 3D, with early signs of change already underway. While Apple‘s upcoming Vision Pro is bringing new excitement to this space, gaming-focused VR (Virtual Reality) headsets from companies including Meta, Sony, and Pico have sold millions of units, and AR […]
A Tale of Two Realities: Mapping Spatial Computing’s Next Decade Read More +
This blog post was originally published by Onit. It is reprinted here with the permission of Onit. 80 Forklifts for Indoor and Outdoor Logistics Florim is a multinational company recognized in the production of ceramic surfaces. With an innate passion for beauty and design, Florim has been producing ceramic surfaces for every building, architecture and
Case History: Florim Read More +
This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. Learn about the Foundation Models — for object classification, object detection, and segmentation — that are redefining Computer Vision. Foundation models have come to computer vision! Initially limited to language tasks, foundation models can now serve as the backbone of computer
The Foundation Models Reshaping Computer Vision Read More +
This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. The attention mechanism made big changes in deep learning. Thanks to this, models can achieve better results. This mechanism was also the inspiration for perceivers and also transformer neural networks . And transformers led to the development
Deep Learning Models Which Pay Attention (Part I) Read More +
This blog post was originally published at Silo AI’s website. It is reprinted here with the permission of Silo AI. Machine learning in embedded systems is becoming increasingly important. We are seeing it being utilized in a multitude of different application areas including automotive, manufacturing, robotics as well as as well as in advanced consumer
AI On the Edge: Machine Learning in Restricted Environments Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. While robots have proliferated in recent years in smart cities, factories and homes, we are mostly interacting with robots controlled by classical handcrafted algorithms. These are robots that have a narrow goal and don’t learn from their
Embodied AI: How Do AI-powered Robots Perceive the World? Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Autonomous vehicles (AV) come in all shapes and sizes, ranging from small passenger cars to multi-axle semi-trucks. However, a perception algorithm deployed on these vehicles must be trained to handle similar situations, like avoiding an obstacle or
Using Synthetic Data to Address Novel Viewpoints for Autonomous Vehicle Perception Read More +
November 12, 2023 – SiloGen is today announcing a release of the first model checkpoints of a family of multilingual open source large language models (LLMs), covering all official European languages and code. Together with the University of Turku and HPLT, SiloGen launched at the end of August an initiative to build open multilingual LLMs,
Poro – A Family of Open Models that Bring European Languages to the Frontier Read More +
August 20, 2023 – Europe’s largest private AI lab Silo AI, with its large language model (LLM) arm SiloGen, is today announcing a large-scale initiative on open and trustworthy LLMs. SiloGen launches a consortium together with TurkuNLP, a research group at the University of Turku, to develop a family of open LLMs, including the world’s
SiloGen Launches a Consortium to Build the World’s Largest Open LLM Read More +
This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. In Part 2 of our NVIDIA TAO Toolkit series, we describe & address the common challenges of model deployment, in particular edge deployment. We explore practical solutions to these challenges, especially on the issues surrounding model comparison. Here
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.
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