Irish agtech company Cainthus uses vision technology to improve dairy herd management. Ireland's multi-generations of dairy farmers know a thing or two about raising dairy cows. Its more than 18,000 dairy farmers tend 1.4 million animals and are recognized globally for productivity and quality. So, it's no surprise that an Irish agtech company called Cainthus would invent a way to use artificial intelligence--the same technology developed for terrorist detection of humans--to manage dairy cows. At its simplest, Cainthus' technology has been described as facial recognition for cows, but Cainthus CEO Aidan Connolly explains that it is actually much more.
During our last trip Los Angeles, conference participants experienced a thrilling machine-learning, real-time demonstration as part of the SIGGRAPH 2017 Real-Time Live! showcase: Physics Forests. This data-driven fluid simulation, with surface generation, foam, coupling with rigid bodies, and rendering, is capable of simulating several million particles in real time. It uses the regression forest to estimate the behavior of particles and rendered surfaces. The method can handle a wide range of fluid parameters. Since then, Physics Forests has only grown and built on the capabilities it boasted in 2017.
Over the past four years, Microsoft has tinkered with its Windows 10 update mechanism, offering minor tweaks that were ultimately unsatisfying. The biggest complaints centered around unexpected restarts, especially those associated with the twice-annual feature updates that are at the core of the "Windows as a service" model. The problems came to a head last October, when a series of embarrassing bugs forced Microsoft to pull its October 2018 Update just days after its release. It took another six weeks before the company announced that the issues had been fully investigated and resolved and the update was ready to resume its rollout. At the time, Windows managers promised sweeping changes in the way it approaches quality issues.
The world's biggest carmaker Volkswagen has said it will use cloud computing and Internet of Things (IoT) technologies from Amazon Web Services (AWS) to connect and manage its manufacturing plants and supply chain. Infrastructure around the world is being linked together via sensors, machine learning and analytics. We examine the rise of the digital twin, the new leaders in industrial IoT (IIoT) and case studies that highlight the lessons learned from production IIoT deployments. The two companies said they have signed a multi-year deal to build what they are calling the'Volkswagen Industrial Cloud', which will manage the automotive giant's manufacturing and logistics. The aims of the project are to increase plant efficiency and uptime, improve production flexibility, and increase vehicle quality.
AI application include expert systems, machine vision, and speech recognition. ATI Solo Travel Packages 3. AI enables humans to make predictions based on patterns and data AI helps you with mundane tasks that you need to accomplish on a daily basis Since AI helps in intensive data you get more time to focus on complex tasks AI is a good fit for those industries that require an error- free approach like in accounting industry BENEFITS OF AI 4. Accounting profession has existed since the pre-historic times.During it's long journey, it has seen many transformations as a result of the changing world and the resources available. Accounting software exhibits superior performance in comparison to traditional method of pen-paper based accounting. This evolution of technology led to the digitization of the entire accounting process. These software uses AI capabilities to automate tasks such as data entry, account payable, reconciliation, and more.
This Tricky aphorism of a song came to mind once more a couple of years back, when Streamlio came out of stealth. Streamlio is an offering for real-time data processing based on a number of Apache open source projects, and it directly competes with Confluent and Apache Kafka, which is at the core of Confluent's offering. Also: Processing time series data: What are the options? In 2017, Apache Kafka was generally considered an early adopter thing: Present in many whiteboard architecture diagrams, but not necessarily widely adopted in production in enterprises. Since then, Kafka has laid a claim to enterprise adoption, and Confluent has acquired open-core unicorn status after its latest funding.
There is no question that artificial intelligence, machine learning and automation is changing the marketing function in many businesses. For many consumer brands these technologies are now they most effective way of communication with a customer. As AI continues to develop, the ability to personalise every piece of marketing material is becoming a reality. How can artificial intelligence and machine learning allow for better personalisation, and ultimately improve the customer experience? For many brands, apps are now the way consumers shop and spend, and for many push notifications are a great way of communicating and connecting with the customer directly.
Artificial intelligence (AI) is more present in our lives than we think, it provides limitless potential and advantages that diffuse through many industries. It has been argued that the construction sector has been one of the fastest to adopt applications, processes and technological implementations in relation to artificial intelligence. In this article we look at analysis of the topic, with findings published by The BBN Times magazine. Using drones to undertake AI enabled processes such as Infrastructure planning, design and risk management are just a few of the many applications possible in the construction sector. The BBN Times magazine highlights how good it is to see how the new-age technology has penetrated several industries, including construction.
Let's say you've developed a predictive model in R, and you want to embed predictions (scores) from that model into another application (like a mobile or Web app, or some automated service). If you expect a heavy load of requests, R running on a single server isn't going to cut it: you'll need some kind of distributed architecture with enough servers to handle the volume of requests in real time. This reference architecture for real-time scoring with R, published in Microsoft Docs, describes a Kubernetes-based system to distribute the load to R sessions running in containers. You can find detailed instructions for deploying this architecture in Github. For more details on this architecture, take a look at the Microsoft Docs article linked below.
Most of the business trends surrounding the CPG industry have a common goal: bottom-line growth. To achieve growth, a large number of data comprised around consumer preferences, marketing campaign, sales promotions, purchasing choices, reviews, feedback, and expressed interest must be taken into account. Data is the oil of the 21st century. However, it is impossible for decision-makers to browse and make sense of data. Consumer Goods businesses produce a humongous amount of data and this overwhelms decision-makers as they have to spend scouring through data.