War Of The Visions Cloud
Vinnie Breidenthal
Currently designing a new machine and I would like to use the cloud/iot services provided by unitronics. I notice all of the controllers with built in cloud are the unistream range, ideally I would like to stick with visilogic software and say a V1210 controller. Now, I see this is possible by using the Unitronics router but my internet searches are not bringing up any concrete information on how this works so hoping to get some assistance with the following questions;
- Current setup has an existing router that controls the networks DHCP, it also has port forwarding for multiple unitronics controllers to enable remote access & remote operator, this router cannot be changed as it is ISP specific. So my question is, can the vision with unitronics router work in this situation? can the unitronics router sit as a device on an existing network?
I have a Unitronics router I've been playing with. It interfaces with Vision series PLCs with a built-in PCOM to UniCloud gateway. You set up the configuration in the router with register tables on its local network and then you configure UniCloud to come down and scoop up the data.
Ausman, yes it's a great feature and would be really nice for something like a remote installation but in this instance I don't believe it's very practical with the large data requirements of this business plus 4G static IP addresses are becoming increasingly difficult these days with Telstra no longer issuing them and the specialist ISP that do provide them are very expensive on the data front.
Azure AI Vision is a unified service that offers innovative computer vision capabilities. Give your apps the ability to analyze images, read text, and detect faces with prebuilt image tagging, text extraction with optical character recognition (OCR), and responsible facial recognition. Incorporate vision features into your projects with no machine learning experience required.
Read this 2022 commissioned study conducted by Forrester Consulting to learn how to help developers of any skill level at your organization deploy AI solutions quickly using prebuilt, production-ready cloud AI services.
No. Microsoft automatically deletes your images and videos after processing and does not train on your data to enhance the underlying models. Video data does not leave your premises, and video data is not stored on the edge where the container runs. Learn more about privacy and terms of usage.
The model customization feature of the service is optimized to quickly recognize major differences between images, so you can start prototyping your model with a small amount of data. You may start with as little as one image per label. If you have more labeled images, you may add more. Depending on the complexity of the problem and degree of accuracy required, you can continue adding additional images per label to improve your model.
You can label the images in Azure Machine Learning Studio, which is integrated with Vision Studio for easy export of labeled data. You can also label the data in the COCO file format and import the COCO file directly in Vision Studio. See documentation for details.
The model customization feature for Azure AI Vision is the next generation of Custom Vision, with improved accuracy and few-shot learning capabilities. You may continue to use Custom Vision, or you can migrate your training data to retrain your model with model customization from Azure AI Vision. See documentation for details.
After using Azure AI Vision to extract insights and text from images and video, you can use text analytics to analyze sentiment, Translator to translate text into your desired language, or Immersive Reader to read the text aloud, making it more accessible. Related services and capabilities include Azure Form Recognizer to extract key-value pairs and tables from documents, Azure AI Video Indexer for extracting advanced metadata from audio and video files, and Content Moderator to detect unwanted text or images.
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I spent most of this morning trying to wrap my head around the complexities of managing a modern multi-cloud platform environment. Keeping tabs on every single component - NICs, BMC, storage, compute nodes, CPUs and GPUs - to make sure they're healthy and talking to each other within expected limits even when no workloads are running is no small task.
Obviously, lifecycle management (LCM) is crucial as well. (I grok that from my days as an instructor for Oracle Exadata DBM infrastructure courses - an extremely complex bundle of hardware, firmware, and software aimed that composes a high-performance and resilient database platform.) For each set of components that need to be upgraded, it's especially important to apply patches to firmware, drivers, and other software across a cluster's components in an appropriate order to minimize downtime and insure that nothing conflicts while the patches are applied; otherwise, cluster health could unexpectedly degrade or its survivability could be threatened.
Our colleagues at Dell Corporation this morning showed us ACP as their solution for providing a consistent way of managing cloud infrastructure, regardless of whether it's deployed in an OpenShift Red Hat environment (which is primarily aimed at Kubernetes containerization) or within a Microsoft Azure environment.
Dell also made some pretty big claims on how fast their ACS storage performed against other block storage already available on public clouds. I'll withhold my judgment on how accurate those claims are until I read over their white papers and check out their testing methodology for extremely intense and realistic Oracle Database workload performance against ACS - more to come in a future blog post.
As part of its journey to simplification, Cisco has been working to create a simpler network management platform experience to help customers easily access and navigate its platforms to manage all Cisco networking products from one place. Featuring cloud-driven automation, rich network insights, and innovation through its partner ecosystem, Cisco Networking Cloud will accelerate the delivery of unified experiences and drive measurable business outcomes.
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Odin is an award-winning Cloud AI endoscopy company founded by a team of eminent clinicians and artificial intelligence experts with the mission of creating the next generation of cloud AI-enabled applications for endoscopy.
We believe that cloud and AI will create a new era of healthcare by supporting doctors to deliver higher-quality care leading to improved patient outcomes, better patient experiences and increased value for healthcare providers.
"Caddie is Simple and and user friendly.The device sits on our endoscopy stack and is quick and easy to set up in the procedure room. The foot pedal allows CADDIE to integrate into our clinical workflow. Artificial intelligence with CADDIE certainly helps with polyp characterisation".
Distributing, collecting, and assessing student writing is typically a time-consuming process for teachers. Cloud-based tools promise to simplify and automate these processes, allowing teachers to focus more time on classroom instruction. Although these tools have been widely adopted in suburban schools across the country, urban schools often lag behind because they lack the infrastructure and support to leverage them.
New Visions is looking to change this inequity with a new pilot program that aims to improve student literacy in high-needs high schools in New York City by providing teachers and administrators with curricular resources and Google Apps for Education (GAFE) tools to organize, manage, and facilitate student writing projects.
The i3 grant will directly impact 5,000 students in New York City by supporting high school English Language Arts (ELA) and social studies teachers, who are using New Visions-developed curriculum, in delivering writing instruction aligned with Common Core standards. The pilot project will help teachers use the free GAFE platform to improve their ability to distribute, collect, and offer feedback on student assignments.
The grant will enable New Visions to test the theory that cloud-based technology can improve the amount and quality of student writing, even in high poverty urban schools. New Visions will work with 10 New York City high schools, selected from its network of 77 district and charter schools. MDRC, an independent evaluation partner, will study the impact by analyzing the program at 10 project and 10 comparison schools.
Program teachers will learn how to use the Google Apps for Education suite of productivity apps and Add-ons, including Google Classroom and the New Visions Cloud Lab-developed Add-ons, Goobric and Doctopus.
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