Tesla stands apart from other automakers thanks to its global fleet of constantly connected vehicles, each one continuously collecting real-world driving data. Every second of footage and every sensor reading has the potential to improve Tesla’s AI models. However,…

What is Data Centric Machine Learning? And how can it be utilised in practice? The Data Centric approach to ML introduces an additional data improvement loop into the standard model development lifecycle. Instead of treating data as a static resource…

Navigating the data maze: Decoding the optimal data size for Machine Learning and AI   Introduction In today’s digital era, data is the lifeblood of innovation and decision-making. From customer profiles to shifting market dynamics, data enables organizations to anticipate…

Learn the fundamentals of 2D and 3D data annotation with this in-depth guide. We cover techniques, tools, and applications that power real-world AI systems across industries.     An Introduction to 2D and 3D Data Annotation What is data annotation?…

Outsourcing data annotation is a strategic decision that many organizations face today. While some prefer to keep the process in-house to maintain control, others turn to specialized service providers to handle the growing demands of AI and ML training data.…

Let’s take a closer look at the fundamentals of data labeling: what it means, the different categories it falls into, and how it is used in real-world AI applications. Data labeling: A quick overview Data labeling is the process of…

Spiking Neural Networks (SNNs) represent a new generation of neural networks designed to better imitate how biological neurons communicate and process information. Let’s take a closer look at what makes them unique.     Neural Connections Neural connections inside the…

With data security becoming one of the biggest concerns in AI projects today, a new decentralized way of training ML models is emerging as a promising solution: Federated Learning (FL).     Federated Learning Federated Learning was first introduced by…

What does data annotation mean in Machine Learning? What types of annotation exist, and what methods are used? Let’s dive deeper.     Data labeling examples Three common applications of Data Annotation – Bounding Boxes, Semantic Segmentation, and 3D Point…

Exploring the roadblocks and technical hurdles in labeling LiDAR point clouds for real-world AI applications Light Detection and Ranging (LiDAR) has fundamentally reshaped how machines sense and understand their surroundings. By sending out laser pulses and measuring their return time,…