Machine Learning

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Survey: AI Must Be a ‘Strategic Lever’

Hyper-scalers are racing to deploy AI technologies. Meanwhile, other sectors such as finance, healthcare and transportation ramping up AI initiatives are confronting challenges while considering precisely where automation technologies ...Full Article

Insilico, Pfizer Join AI Forces on Drug Discovery

Previous attempts to apply AI to drug discovery have yielded mixed results. For example, IBM ended sales last year of its Watson AI software used by pharmaceutical firms for ...Full Article

AI Is Changing Web Development

According to Accenture, 77 percent of smart devices include at least one AI feature. It is anticipated that by 2025 the global AI market will reach $60 billion. The ...Full Article

ARPA-E Brings ML to Power System Design

The U.S. Energy Department’s research arm is leveraging machine learning technologies to simplify the design process for energy systems ranging from photovoltaics and wind turbines to aircraft engine compressors. ...Full Article

MLOps Initiatives Seek to Boost Stalled Deployments

The deployment of machine learning models in production is failing to keep pace with the everyday operations of hyper-scalers. Those scaling and deployment gaps are being addressed through collaborations ...Full Article

Enterprise ML Moves Slowly Up the Value Chain

While developers are moving up the machine-learning learning curve, a vendor survey finds they still have a way to go in scaling ML deployments. Algorithmia’s annual survey of the ...Full Article

Kubernetes Gets a GPU Boost

An infrastructure vendor zeroing in on AI and machine learning workloads has added GPU support to a Kubernetes-based appliance designed to handle those emerging applications in containers while adding ...Full Article

AWS’s Web-based IDE for ML Development: SageMaker Studio

AWS, Azure, Google Cloud, IBM Cloud, Oracle – they’ll all vying to become the dominant force of gravity in the public cloud services market, and among the most fiercely ...Full Article

What to Ask When Implementing Machine Learning

Successfully operationalizing machine learning models in production environments can be incredibly difficult, as the industry has already seen. In fact, Gartner has predicted 85 percent of AI projects in ...Full Article

At SC19: Who’s Accountable ‘When Technology Kills’?

“One of the things we are witnessing is the compute requirement for (AI) training jobs is doubling every three-and-a-half months. So we were very impressed with Moore’s Law doubling ...Full Article