Software

Deep Learning Models Which Pay Attention (Part I)

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 […]

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AI On the Edge: Machine Learning in Restricted Environments

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

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Embodied AI: How Do AI-powered Robots Perceive the World?

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

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Using Synthetic Data to Address Novel Viewpoints for Autonomous Vehicle Perception

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

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Poro – A Family of Open Models that Bring European Languages to the Frontier

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,

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SiloGen Launches a Consortium to Build the World’s Largest Open LLM

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

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NVIDIA TAO Toolkit “Zero to Hero”: A Simple Guide for Model Comparison in Object Detection

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

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Preserving Privacy and Security In a Generative AI World

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. AI and privacy: How on-device AI enhances privacy and security The rapid adoption of generative artificial intelligence (AI) has opened a new world promising explosive creativity, convenience and productivity. With large language models (LLMs), as well as

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Why is Explaining Machine Learning Models Important?

This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. Why is explaining machine learning models important? The main focus in machine learning projects is to optimize metrics  like accuracy, precision, recall, etc. We put effort into hyper-parameter tuning or designing good data pre-processing. What if these

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The Role of the Inertial Measurement Unit in 3D Time-of-flight Cameras

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. An Inertial Measurement Unit (IMU) detects movements and rotations across six degrees of freedom, representing the types of motion a system can experience. When paired with Time-of-flight (ToF) cameras, it ensures accurate spatial understanding and

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