Releases

The Telum announcement established a new generation of IBM infrastructure with integrated AI acceleration.

IBM unveiled Telum with on-chip AI acceleration for high-volume transactional inference.

Baidu said its second-generation Kunlun AI chip had entered mass production.

DeepMind and EMBL-EBI launch a freely accessible database of AlphaFold protein structure predictions.

GitHub launches Copilot in technical preview as an AI pair programmer that suggests code inside the editor.

NVIDIA made Fleet Command generally available for centrally deploying and managing edge AI applications.

NVIDIA launched a hosted enterprise program offering immediate access to its end-to-end AI infrastructure and software stack.

Hugging Face launched AutoTrain to automate model training and fine-tuning from user-provided datasets.

Databricks introduced a managed Feature Store integrated with Delta Lake, MLflow and model serving.

Databricks introduced Unity Catalog as a unified governance layer for data and AI assets across clouds.

Databricks introduced AutoML to automatically train models while generating editable notebooks.

Google announces fourth-generation TPU pods for large-scale machine-learning training.

Google Cloud launches Vertex AI as a unified platform for building, deploying and operating ML models.

Hugging Face introduced a paid individual plan with expanded private, storage, and compute capabilities on the Hub.

NVIDIA introduced Morpheus for real-time AI-assisted threat detection using GPUs and BlueField DPUs.

NVIDIA introduced Base Command to provision, schedule and operate shared DGX SuperPOD AI infrastructure.

NVIDIA announced an enterprise software suite for virtualized AI workloads on VMware vSphere.

NVIDIA opened the Omniverse collaboration and simulation platform to beta users.

AWS introduced a HIPAA-eligible health data lake using FHIR and machine learning.

AWS introduced tools for bias detection and model explainability.

AWS introduced machine-learning-based anomaly detection for business and operational metrics.

AWS introduced an end-to-end condition-monitoring system using sensors and machine learning.

AWS introduced predictive maintenance from industrial sensor data.

AWS introduced a computer-vision service for visual defect and anomaly detection.

AWS introduced an ML-powered service for detecting abnormal operational behavior and recommending remediation.