
OpenAI Voice Engine
Exploring OpenAI's Voice Engine and its comparison with ElevenLabs in the realm of voice technology

Announcing the General Availability of Databricks Notebooks on SQL Warehouses
Introducing Databricks Notebooks on SQL Warehouses for enhanced data analysis and workflow integration

Generative AI to quantify uncertainty in weather forecasting
Utilizing generative AI to efficiently quantify uncertainty in weather forecasting for improved accuracy and scalability

International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024
Apple's participation and events at the International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024 in Seoul, South Korea.

Researchers create “The Consensus Game” to elevate AI’s text comprehension and generation skills
Researchers develop 'The Consensus Game' to enhance AI's text comprehension and generation abilities through a game-theoretic approach.

Dev Connect at Next ‘24: Master AI on Google Cloud with Firebase, Kaggle, Android, and more
Accelerate your development journey with Google Cloud at Dev Connect, featuring sessions on Firebase, Kaggle, Android, and AI innovations

Minimizing on-call burnout through alerts observability
Enhancing on-call personnel's efficiency by optimizing alert observability through the use of open-source tools and best practices within Cloudflare's architecture

Provide live agent assistance for your chatbot users with Amazon Lex and Talkdesk cloud contact center
Enable live agent assistance for chatbot users using Amazon Lex and Talkdesk cloud contact center

Managed Sportlogiq to Databricks Data Ingestion Pipelines for NHL Teams: A Game-Changing Alliance
Advanced data ingestion pipeline collaboration between Sportlogiq, Databricks, and Koantek revolutionizes analytics for NHL teams

Making education data accessible
Unlocking insights through data accessibility in education

MIT launches Working Group on Generative AI and the Work of the Future
Exploring the impact of generative AI on future jobs through a collaborative working group at MIT.

AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks
Automating interpretable time series forecasting with probabilistic neural networks based on compositional Bayesian approaches