Latest posts
- AI in cybersecurity an introduction and case studies
- An introduction to AI in cybersecurity with real-world case studies in a Fortune 500 organization and a government agency Despite all the recent advances in artificial intelligence and machine learning (AI/ML) applied to a vast array of application areas and use cases, success in AI in cybersecurity remains elusive. The… ... - Active learning: an overview
- A primer on active learning presented by Josh McGrath. Machine learning whiteboard (MLW) open-source series This video defines active learning, explores variants and design decisions made within active learning pipelines, and compares it to related methods. It contains references to some seminal papers in machine learning that we find instructive.… ... - Using few-shot learning language models as weak supervision
- Utilizing large language models as zero-shot and few-shot learners with Snorkel for better quality and more flexibility Large language models (LLMs) such as BERT, T5, GPT-3, and others are exceptional resources for applying general knowledge to your specific problem. Being able to frame a new task as a question for… ... - Accelerating AI in healthcare
- How can data-centric AI speeds your end-to-end healthcare AI development and deployment Healthcare is a field that is awash in data, and managing it all is complicated and expensive. As an industry, it benefits tremendously from the ongoing development of machine learning and data-centric AI. The potential benefits of AI… ... - Bill of materials for responsible AI: collaborative labeling
- In our previous posts, we discussed how explainable AI is crucial to ensure the transparency and auditability of your AI deployments and how trustworthy AI adoption and its successful integration into our country’s critical infrastructure and systems are paramount. In this post, we dive into making trustworthy and responsible AI possible with Snorkel Flow,… ... - ICLR 2022 recap from Snorkel AI
- We are honored to be part of the International Conference on Learning Representations (ICLR) 2022, where Snorkel AI founders and researchers will be presenting five papers on data-centric AI topics The field of artificial intelligence moves fast! Hardly a month goes by without exciting new state-of-the-art techniques, results, datasets, and… ... - Explainability through provenance and lineage - In our previous post, we discussed how trustworthy AI adoption and its successful integration into our country’s critical infrastructure and systems are paramount. In this post, we discuss how explainability in AI is crucial to ensure the transparency and auditability of your AI deployments. Outputs from trustworthy AI applications must be explainable… ...
- Spring 2022 Snorkel Flow release roundup
- Latest features and platform improvements for Snorkel Flow 2022 is off to a strong start as we continue to make the benefits of data-centric AI more accessible to the enterprise. With this release, we’re further empowering AI/ML teams to drive rapid, analysis-driven training data iteration and development. Improvements include streamlined data… ...
Results: 137 - 144 of : 198
