This month, Tensorflow, the open source machine learning and deep learning framework from Google, has turned five. TensorFlow has become the most popular tool and…
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With RHEL as the edge-optimized OS, OpenShift as the container platform for edge and ACM as the multi-cluster control plane, Red Hat has a compelling portfolio for edge computing.
TinyML is the latest from the world of deep learning and artificial intelligence. It brings the capability to run machine learning models in a ubiquitous…
Lobe aims to turn any user with essential programming skills into an AI developer. The intuitive user interface combined with features like model optimization and a choice of export formats makes it one of the best AI tools available today.
Amazon’s investment in the Nitro project starts to pay off. After launching bare metal instances and EC2 instances based on the Graviton2 processor, AWS Nitro Enclaves is the latest enhancement powered by the Nitro project.
The evolution of application software led by containers and Kubernetes and the infrastructure evolution driven by specialized hardware accelerators mark the beginning of a new era. With Project Pacific and Project Monterey, VMware is well-positioned to exploit both these trends.
With DPU, NVIDIA aims to bring efficiency and optimization to the enterprise data center that was once available only to cloud service providers.
The Jetson Nano 2GB Developer Kit puts the power of AI in the hands of the masses. With an affordable price tag of $59, it is expected to democratize AI.
With Azure Sphere, customers can connect legacy, brownfield devices to the cloud securely through AT&T’s cellular network.
With tight integration with GKE and Kubeflow, the service has evolved into an end-to-end platform that supports data preparation, transformation, training, model management, deployment, and inference.
