CEO of Align, Effortlessly turn your site into an advisor marketplace that generates revenue for experts and you. Every year, technology advancements continue to change business as we know it. The rate at which new devices, software and digital business methods are introduced continues to speed up into new frontiers. In addition, societal changes due to health, politics, geography and more have contributed to rethinking how business leadership has to perform today as opposed to just ten years ago. You don't have to be an IT expert to realize the organizational possibilities of these opportunities, either.
Intel on Tuesday officially launched "Ice Lake," its new 3rd Gen Xeon Scalable processor. The 10 nanometer-based CPU, delivering up to 40 cores per processor, is the foundation for Intel's data center platform. The chip is designed for workloads spanning a range of markets, from the cloud to the network and the edge. Intel says every "top tier" cloud service provider will be offering services based on Ice Lake. It's launching the chip with more than 50 OEMs building more than 250 servers based on the platform.
Intel on Tuesday officially launched "Ice Lake," its new third-generation Xeon Scalable processor. The 10 nanometer-based CPU, delivering up to 40 cores per processor, is the foundation for Intel's data center platform. The chip is designed for workloads spanning a range of markets, from the cloud to the network and the edge. Intel says every "top tier" cloud service provider will be offering services based on Ice Lake. It's launching the chip with more than 50 OEMs building more than 250 servers based on the platform.
Trifacta, which has become the last pure play data prep tools provider still standing, sees its future as a broader based cloud software-as-a-service (SaaS) service. This week, it is unveiling a new Data Engineering Cloud that will deliver a fully managed service on each of the major clouds. That will be in addition to, not instead of Wrangler, its long-established on-premises prep suite. Here's a look at how the cloud leaders stack up, the hybrid market, and the SaaS players that run your company as well as their latest strategic moves. Trifacta's niche will continue to be serving as the front end design studio where the data engineer, data scientist, or business developer creates the "recipes" for data preparation and transformation.
Verizon Business and Amazon Web Services said they will start delivering private mobile edge computing to enterprises in the US via integration with Verizon's private 5G network and AWS Outposts. The two partners will start providing private edge computing platforms to be used in factories, warehouses, school campuses, as well as autonomous robots. Corning plans to use Verizon 5G Edge with AWS Outposts for self-guided vehicles and robotics in its smart factory. Verizon and AWS outlined a partnership at re:Invent 2019 and has expanded it since. The mobile edge computing (MEC) offering offers unified connectivity, compute, and storage and is fully managed.
In our last post, we demonstrated how to develop a machine learning pipeline and deploy it as a web app using PyCaret and Flask framework in Python. If you haven't heard about PyCaret before, please read this announcement to learn more. In this tutorial, we will use the same machine learning pipeline and Flask app that we built and deployed previously. This time we will demonstrate how to deploy a machine learning pipeline as a web app using the Microsoft Azure Web App Service. In order to deploy a machine learning pipeline on Microsoft Azure, we will have to containerize our pipeline in a software called "Docker".
Digital transformations are being fuel-injected by leading enterprise tech like hybrid clouds, containers, and AI. Adding to the acceleration is 5G, which is adding decentralized data and application processing from millions of endpoints outside the traditional datacenter and public cloud. But while transformation and modernization are bringing improved enterprise performance, efficiency, and agility, these increasingly complicated infrastructures are also complicating data management and availability, especially for AI workloads. For example, capturing data from the edge of the network, not to mention exogenous data from external sources, usually means moving and copying data -- a process that is not only time consuming and expensive, but also introduces new levels of risk, governance, and security challenges. Today, one of the few ways around this challenge is to flip the equation and push the AI to the data, rather than the other way around.
One of the initial hesitations in many enterprise organizations moving into the cloud in the last decade was the question of security. Significant amounts of money had been put into corporate firewalls, and now technology companies were suggesting corporate data reside outside that security barrier. Early questions were addressed, and information began to move into the cloud. However, nothing stands still, and the extra volume of data and networking intersects with the increased complexity of attacks, and artificial intelligence (AI) is being used to keep things safe. The initial hesitation for enterprise organizations to move to the cloud was met by data centers improving hardware and networking security, while the cloud software providers, both cloud hosts and application providers, increased software security past what was initially offered in the cloud.
Deloitte announced a collaboration today with Automation Anywhere to drive further adoption of cloud deployments on Automation 360, the first cloud-native, AI-powered robotic process automation (RPA) platform. Deloitte will combine its leading capabilities in cloud infrastructure and automation to provide a first-of-its-kind solution that enables a successful migration of client automations to the cloud, helping organizations accelerate the rate and delivery of business performance while effectively limiting costs. Mutual customers, both first-time RPA and existing Automation Anywhere users, will experience a smooth transition to the cloud platform with Deloitte's migration as a service capabilities. "The need for digital transformation is more prevalent than ever as organizations continue to navigate the effects of the pandemic and pivot to cloud-based solutions that can seamlessly integrate with their existing systems," said Douglas Williams, managing director, Deloitte Consulting LLP. "Our solutions are designed for Automation 360 to help customers through the migration process to get the most value out of their RPA investment with minimal disruption, all while finding efficiencies and reducing investment costs."
Baking is as much science as it is art. Perhaps to find out whether the former's more important, Google Cloud AI is taking on a Great British Bake Off winner in a dessert face-off. Sara Robinson, an amateur baker and Google Cloud developer advocate, built a machine learning model that examined hundreds of baking recipes (including ones for traybakes, cookies and scones) to help her come up with a new one. The model generated lists of ingredients and amounts that were used as the basis for step-by-step recipes. The model was able to come up with hybrid recipes and Robinson opted for one that had a machine learning-generated cake batter on top of a machine learning-generated cookie.