Announcing the winners of the first Databricks Asia-Pacific LLM Cup!
Announcement of the winners of the inaugural Databricks Asia-Pacific LLM Cup showcasing innovative projects in telecommunications and cybersecurity
New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
New benchmark results highlight Snorkel AI's advanced approach to LLM alignment
How GitHub’s Developer Experience team improved innerloop development
Improving innerloop development with GitHub's 'Hubber Codespace' solution
New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
New benchmark results demonstrate value of programmatic Snorkel AI approach to aligning LLMs
How GitHub’s Developer Experience team improved innerloop development
GitHub's Developer Experience team created 'Hubber Codespace' to improve innerloop development in a distributed service ecosystem by bringing the GitHub ecosystem to developers.
Generating the policy of tomorrow
Exploring the role of generative AI in shaping future policies through the MIT Policy Hackathon.
Q&A: A blueprint for sustainable innovation
A blueprint for sustainable innovation: Atacama Biomaterials combines architecture, machine learning, and chemical engineering to create eco-friendly materials with multiple applications.
New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
Exploring the Animation Landscape of 2023 Wrapped
Exploring the Animation Landscape of 2023 Wrapped
How Vodafone puts customers first with an environment built on data intelligence
Vodafone leverages data intelligence to prioritize customers through a partnership with Google Cloud and Quantexa.
Achieving Military Interoperability: APIs as Catalysts for Modernizations
Achieving Military Interoperability: APIs as Catalysts for Modernizations
RLHF Tuning with Vertex AI
RLHF Tuning with Vertex AI: Learn how to improve the performance of foundation models and align them with human preferences using Reinforcement Learning from Human Feedback (RLHF).