by Victor Sonck, Developer Advocate, ClearML Sarcasm can be difficult to detect in text, especially for machines. However, with the power of large language models, it’s possible to create a tool that can identify sarcastic comments with high accuracy. That’s exactly what the ClearML team did with their latest project: a sarcasm detector that combines various ClearML tools to showcase the capabilities of MLOps.

The world of artificial intelligence and machine learning is constantly evolving, with new challenges and innovations emerging every day. Tzag Elita is a leading provider of HPC and AI solutions in Israel, and understands the importance of staying ahead of the curve and delivering cutting-edge solutions to their customers. That’s why ClearML is excited to announce our partnership with Tzag Elita.

Machine learning (ML) enables organizations to extract more value from their data than ever before. Companies who successfully deploy ML models into production are able to leverage that data value at a faster pace than ever before. But deploying ML models requires a number of key steps, each fraught with challenges.

We are announcing BigQuery ML inference engine, which allows you to run predictions on a broad range of models hosted across multiple locations.

We recently rolled out our very own GPU autoscaler in Collaboration with Genesis Cloud and it has been quite a success. Also recently, YOLOv8 by Ultralytics was unveiled, the new king of object detection, segmentation and classification. In this blogpost we’ll see that you can train a computer vision model using the ClearML/Genesis Cloud autoscaler at a fraction of the cost of competing cloud services like AWS or GCP. And it even runs 100% off of green energy! 😎

The open source ML tooling ecosystem has become vast in the last few years, with many tools both overlapping in their capabilities as well as complimenting each other nicely. In part because AI/ML is a still-immature practice, the messaging around what all these tools can accomplish can be quite vague. In this article, we’ll dive into three tools to better understand their capabilities, and how they fit into the ML lifecycle.

2023 is looking likely to be a breakout year for artificial intelligence (AI) and machine learning (ML). Some industry-watchers predict that recent breakthroughs in AI might lead to a new revolution in society akin to the industrial revolution, the invention of the internet, or the advent of the smartphone. Yet, 2023 doesn’t mark the invention of AI—just the year it went viral thanks to OpenAI’s ChatGPT technology.

10 years ago, it would be ridiculous for people to believe that someday they would be able to use their faces to unlock their phones. That’s because it had been extremely difficult to create cartoon characters without profound drawing skills – but now we can easily turn photos into cartoon characters. Struggling with parallel parking? No worries, because self-parking systems are becoming standard equipment in vehicles.

Seagate is the world’s leading data storage solution. Together with Iguazio, Seagate is able to manage data engineering at scale while harnessing petabytes of data, efficiently utilize resources, bridge the gap between data engineering and data science and create one production-ready environment with enterprise capabilities. In this new webinar, Vamsi Paladugu, Sr.

Deep learning has become a buzzword in the field of artificial intelligence (AI) in recent years. It has achieved impressive results in a variety of tasks, including image and speech recognition, natural language processing, and even playing games.