April 9, 2024, 9 a.m. | Kevin Cochrane

InfoWorld Machine Learning www.infoworld.com



Chip manufacturers are producing a steady stream of new GPUs. While they bring new benefits to many different use cases, the number of GPU models available from each manufacturer can overwhelm developers working with machine learning workloads. To decide which GPU is right for your organization, a business and its developers must consider the costs of buying or renting the GPU to support the type of workload to be processed. Further, if considering an on-premises deployment, they must account for …

artificial intelligence benefits business cases chip cloud computing data center developers generative-ai gpu gpus hardware machine machine learning manufacturer organization use cases workloads

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Research Scientist (Computer Science)

@ Nanyang Technological University | NTU Main Campus, Singapore

Intern - Sales Data Management

@ Deliveroo | Dubai, UAE (Main Office)