Categoría: machine learning

Telecom AI: a guide for data teams

Data is the new oil, and Artificial Intelligence is the way to monetize it. According to an IDC report, Artificial Intelligence (AI), alongside 5G, IoT, and cloud computing, is one of the technologies reshaping the telecom industry. From data-driven decisions to fully automated and self-healing networks, AI developments are accelerating innovation and driving costs of […]

Security at the Edge: hardware accelerated AI-based cybersecurity with Canonical Ubuntu and the BlueField-2 DPU

During GTC last fall, NVIDIA announced an increased focus on the enterprise datacenter, including their vision of the datacenter-on-a-chip. The three pillars of this new software-defined datacenter include the data processing unit (DPU) along with the CPU and GPU. The NVIDIA BlueField DPU advances SmartNIC technology, which NVIDIA acquired through their Mellanox acquisition in 2020. […]

Data science workflows on Kubernetes with Kubeflow pipelines: Part 2

This blog series is part of the joint collaboration between Canonical and Manceps. Visit our AI consulting and delivery services page to know more. Introduction Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is a part of the Kubeflow project that aims to reduce the complexity and time involved […]

Building Kubeflow pipelines: Data science workflows on Kubernetes – Part 2

This blog series is part of the joint collaboration between Canonical and Manceps. Visit our AI consulting and delivery services page to know more. Introduction Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is a part of the Kubeflow project that aims to reduce the complexity and time involved […]

Open source holds the key to autonomous vehicles

A growing number of car companies have made their autonomous vehicle (AV) datasets public in recent years.  Daimler fueled the trend by making its Cityscapes dataset freely available in 2016. Baidu and Aptiv respectively shared the ApolloScapes and nuScenes datasets in 2018. Lyft, Waymo and Argo followed suit in 2019. And more recently, automotive juggernauts […]

Demystifying Kubeflow pipelines: Data science workflows on Kubernetes – Part 1

Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is one part of a larger Kubeflow ecosystem that aims to reduce the complexity and time involved with training and deploying machine learning models at scale. In this blog series, we demystify Kubeflow pipelines and showcase this method to produce reusable […]