Companies aim to improve drug discovery by training AI on one another’s data and generating large, open datasets ...

Algorithms can analyze significant amounts of biological data at once to uncover hidden relationships, identify potential drug targets and screen for novel molecular compounds at unprecedented speeds.

AI-powered vision is closing the gaps in digital process tracing by automatically documenting manual operations, reducing ...

Though both utilize data centers, the efficiency levels and resource requirements of AI and cloud storage data centers are ...

James McDonagh discusses how AI and machine learning are transforming drug discovery and safety assessment, enhancing ...

AI's ability to accelerate research cycles, in and of itself, will be crucial for freeing researchers for higher-level tasks.

Dynamic AI systems applied in biopharmaceutical manufacturing must be governed within established regulatory frameworks.

In a previous article, we explored how BBVA is scaling its Machine Learning capabilities with a new architecture based on AWS ...

As generative AI captures public attention, a different kind of AI is reshaping drug discovery. Machine learning models are ...

Legacy systems and fragmented processes continue to create challenges for insurance lines across underwriting, claims and ...

Is artificial intelligence flight ready?

Overview: GPUs provide the flexibility and computing power needed to train large AI models, while TPUs optimize tensor-heavy ...