Insights, tips, and product updates

Understanding and training Computer vision model satellite imagery.

A practical guide to automating labeling geospatial data.

Dive into the disparities between aerial and satellite imagery, revealing their profound impact on ML pipelines. Discover distinctive features and applications to make informed choices for optimal results.

Looking for a labeling tool to annotate geospatial imagery? Here is a list of features to consider when choosing the right tool for your machine learning project.

Explore how Covea transformed their customer satisfaction analysis using advanced data labeling and AI with Kili Technology, setting a new standard in customer insights and service.

Not all data labeling services are made equal, and choosing a service that ensures accurate data labeling is critical to ensure both the quality and cost of your machine learning models.

A low proportion of AI projects make it from pilot to production. Often, poor data and inefficient model operations are at the heart of these challenges. Here's how Kili Technology and CraftAI can help data science teams succeed.

Poor data quality can have significant and far-reaching consequences across various industries and applications. But how do we measure data quality? What metrics can we use to ensure the quality of our labeled data remains of the highest standard?

Image Recognition is an Artificial Intelligence task meant to analyze an image and classify the items in their various categories. This article focuses on the training phase of Image Recognition.

Image recognition is a mechanism used to identify objects within an image and to classify them in specific categories, based on the way human people recognize objects within different sets of images

In this article, we shall conduct a more comprehensive exploration of DinoV2's characteristics and functionalities.

In our latest endeavor, we have created a comprehensive tutorial that showcases how to seamlessly integrate Google Vertex AI AutoML with our platform to automate object detection.

Want to learn more about object detection and YOLO? Discover the versions, key features and limitations of YOLO and its real-world applications.

Deep learning combined with natural language processing empowers AI to comprehend and create human language. Read on to learn how and where this is used.

Dive into video object detection, learn its applications and algorithms, and gain tips and tricks to deliver the best model through high-quality video labeling.

Data Augmentation, Advanced Labeling techniques: Direct, Semi-supervised, Active Learning, Weak Supervision.

Every CV application relies on high-quality data, which necessitates a strong image annotation process. This enables data scientists and computer vision experts to train models more effectively. However, maintaining data quality is challenging due to growing data volumes and complexity. Check out our guide for best practices in creating top-notch datasets for your models.

Unleash the Power of Falcon-40B: Enhancing Data Labeling Efficiency and Accuracy in Machine Learning Development. Explore how this remarkable 40-billion-parameter LLM revolutionizes downstream tasks.

Explore 6 open source large language models and discover how to evaluate and fine-tune them for your data labeling needs.

While the digital world is moving from a code-centric to a data-centric paradigm, building datasets remains a complex task. Many companies around the world are currently trying to make dataset building as easy and efficient as possible. Among them, two contestants stand out: Kili Technology and Quality Match. Let's dive into how to use them to your advantage!