Bridging the chasm between ‘Just AI’ and ‘Useful AI’ can be challenging, however it’s apparent that leveraging valuable data is crucial to this. As access to data increases, computer vision teams need to produce informative and reliable training data as a priority, one approach is through developing active learning pipelines. From data curation to annotation and beyond, this webinar will provide you with the tools to implement active learning pipelines and level up your computer vision models Here are the key resources from the webinar: [Guide] How to curate your data [Case Study] How one customer improved per-class performance by 67%

The European Parliament recently voted to adopt the EU AI Act, marking the world’s first piece of legislation on artificial intelligence. The legislation intends to ban systems with an “unacceptable level of risk” and establish guardrails for developing and deploying AI systems into production. We've put together this learning pack to equip you with all the resources you need to understand how the AI Act will impact you, whether or not you're based in the EU. From webinar recordings to the most informative blogs, sign up now to get access to these crucial resources.

OpenAI’s ChatGPT and CLIP releases have revolutionised the ways in which organisations and individual contributors can ship features to their users. At Encord, we’ve focused on how the neural network (CLIP) and LLM (ChatGPT) can be combined to build an effective and powerful Semantic Visual Search. Frederik Hvilshøj, Lead ML Engineer with a PhD in Generative AI, joins Eric Landau, CEO and Co-Founder of Encord, to provide actionable insights into how to build this function from scratch. Here are the key resources from the webinar: Collaboration notebook used by Frederik CLIP [paper/repo] ChatGPT [product updates, documentation] Encord blog: Lessons Learned: Employing ChatGPT as an ML Engineer for a Day Encord blog: What is vector similarity search?