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5 Leading AI Application Areas and Why You Must Care About Them

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5 Leading AI Application Areas and Why You Must Care About Them

Due to its deep learning and independent decision-making capabilities, applications of AI in different business areas are seeing a steady rise in ubiquity in some industries.

The concept of artificial intelligence or machines that aim to emulate human thinking is undergoing vigorous research and is a topic that is increasingly being associated with the Internet of things. An AI enabled IoT system extends the functionality and value of an organization’s offering, without the need for committing additional resources to achieve the increased value. This is exemplified by under Armour(UA) and IBM’s collaboration on the UA Record app, which is an AI-based personal fitness coaching system, that uses a variety of sensor data to suggest highly personalized, context-relevant fitness activities to users. Such applications of AI are going to be more commonplace in the future as they are already having a significant impact on many industries. Here are a few application areas that you can consider for AI implementation:

Applications of Artificial Intelligence in Different Business Areas

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1. Customer Engagement 

As businesses, especially in the service sector industries, evolve from the basic transactional model of customer interaction to a more continuous engagement sequence, the role of IoT and artificial intelligence is rapidly gaining importance. For example, the use of digital concierge and virtual assistants is being discussed in the hospitality industry to automate, personalize and streamline interactions between guests and the service delivery system. The trial deployment of an AI assistant at the Munich airport that helps visitors with directions is an example that forebodes the use of AI in similar cases and for broader purposes in the future. Improved engagement can also be extended to employees by using virtual employee assistants to ensure continued connectivity and simplified task execution.

2. Predictive Analytics

Growing applications of IoT in enterprises has entailed a corresponding increase in the data being generated by the installed systems. This data, continuously collected through the myriad of sensors used in the system, can be used in machine learning models that can be used to make highly informed decisions. The enormity of data volume can be easily managed using AI based data management tools and then be used to derive insights that impact more than just the operational performance. For example, in a healthcare institution, continuous diagnostic analysis is performed to track operational parameters such as the availability of personnel, machines, drugs and other resources; the utilization of different functional units; and the number and types of cases being admitted; to improve responsiveness to changing conditions. AI can be used to perform predictive analysis to ensure preparedness of the facility to respond to different situations and can also be used to provide prescriptive long-term solutions to repetitive issues.

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3. Security Systems

IoT sensors that scan biometric information to authenticate the identity are already being used by numerous business and government organizations. Combining IoT and AI can make biometric scanning even more effective and secure by including the recognition of facial features and voice. CCTV cameras used today require a pair of human eyes to monitor the live footage and identify potential threats or to find clues after an incident. AI infused security camera networks enable scanning of multiple parameters including movements and high risk objects, and automatically raise alarm when a potentially suspicious event occurs. Use of AI surveillance systems like Ella, which finds and distinguishes video footage elements for easy identification of suspicious or missing items, is one way AI can be used for enhanced security.

4. Process Automation

Manufacturing automation has been one of the earliest areas of application of robotics and artificial intelligence. A manufacturing process operated by an AI control system, that is linked to sources of different kinds of data, from the demand in market to the availability of parts from vendors; can function with maximum efficiency, as the process can be regulated through real-time analysis of data. Even service organizations such as restaurants can automate processes by using automated kitchen robots for cooking that emulates human chefs.

5. Artificial Creativity

Artificial creativity is the concept of using algorithms that allow machines to produce content that is random yet desirable for human perception. Multiple online services that provide AI compositions to inspire or completely create new content are already available, and are indicative of a future where an increasing portion of creative content will be inspired or created by AI technology. The focus of AI implementation at present must be to minimize human involvement in the routine and non-creative tasks, so that human effort can be directed towards innovation and planning, where AI can be used for guidance. Following the lead of industry leaders, organizations aiming for sustained relevance should prepare for the use of AI based technology, embedded in an IoT foundation.

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Next-gen chips, Amazon Q, and speedy S3

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AWS re:Invent, which has been taking place from November 27 and runs to December 1, has had its usual plethora of announcements: a total of 21 at time of print.

Perhaps not surprisingly, given the huge potential impact of generative AI – ChatGPT officially turns one year old today – a lot of focus has been on the AI side for AWS’ announcements, including a major partnership inked with NVIDIA across infrastructure, software, and services.

Yet there has been plenty more announced at the Las Vegas jamboree besides. Here, CloudTech rounds up the best of the rest:

Next-generation chips

This was the other major AI-focused announcement at re:Invent: the launch of two new chips, AWS Graviton4 and AWS Trainium2, for training and running AI and machine learning (ML) models, among other customer workloads. Graviton4 shapes up against its predecessor with 30% better compute performance, 50% more cores and 75% more memory bandwidth, while Trainium2 delivers up to four times faster training than before and will be able to be deployed in EC2 UltraClusters of up to 100,000 chips.

The EC2 UltraClusters are designed to ‘deliver the highest performance, most energy efficient AI model training infrastructure in the cloud’, as AWS puts it. With it, customers will be able to train large language models in ‘a fraction of the time’, as well as double energy efficiency.

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As ever, AWS offers customers who are already utilising these tools. Databricks, Epic and SAP are among the companies cited as using the new AWS-designed chips.

Zero-ETL integrations

AWS announced new Amazon Aurora PostgreSQL, Amazon DynamoDB, and Amazon Relational Database Services (Amazon RDS) for MySQL integrations with Amazon Redshift, AWS’ cloud data warehouse. The zero-ETL integrations – eliminating the need to build ETL (extract, transform, load) data pipelines – make it easier to connect and analyse transactional data across various relational and non-relational databases in Amazon Redshift.

A simple example of how zero-ETL functions can be seen is in a hypothetical company which stores transactional data – time of transaction, items bought, where the transaction occurred – in a relational database, but use another analytics tool to analyse data in a non-relational database. To connect it all up, companies would previously have to construct ETL data pipelines which are a time and money sink.

The latest integrations “build on AWS’s zero-ETL foundation… so customers can quickly and easily connect all of their data, no matter where it lives,” the company said.

Amazon S3 Express One Zone

AWS announced the general availability of Amazon S3 Express One Zone, a new storage class purpose-built for customers’ most frequently-accessed data. Data access speed is up to 10 times faster and request costs up to 50% lower than standard S3. Companies can also opt to collocate their Amazon S3 Express One Zone data in the same availability zone as their compute resources.  

Companies and partners who are using Amazon S3 Express One Zone include ChaosSearch, Cloudera, and Pinterest.

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Amazon Q

A new product, and an interesting pivot, again with generative AI at its core. Amazon Q was announced as a ‘new type of generative AI-powered assistant’ which can be tailored to a customer’s business. “Customers can get fast, relevant answers to pressing questions, generate content, and take actions – all informed by a customer’s information repositories, code, and enterprise systems,” AWS added. The service also can assist companies building on AWS, as well as companies using AWS applications for business intelligence, contact centres, and supply chain management.

Customers cited as early adopters include Accenture, BMW and Wunderkind.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London. Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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HCLTech and Cisco create collaborative hybrid workplaces

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Digital comms specialist Cisco and global tech firm HCLTech have teamed up to launch Meeting-Rooms-as-a-Service (MRaaS).

Available on a subscription model, this solution modernises legacy meeting rooms and enables users to join meetings from any meeting solution provider using Webex devices.

The MRaaS solution helps enterprises simplify the design, implementation and maintenance of integrated meeting rooms, enabling seamless collaboration for their globally distributed hybrid workforces.

Rakshit Ghura, senior VP and Global head of digital workplace services, HCLTech, said: “MRaaS combines our consulting and managed services expertise with Cisco’s proficiency in Webex devices to change the way employees conceptualise, organise and interact in a collaborative environment for a modern hybrid work model.

“The common vision of our partnership is to elevate the collaboration experience at work and drive productivity through modern meeting rooms.”

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Alexandra Zagury, VP of partner managed and as-a-Service Sales at Cisco, said: “Our partnership with HCLTech helps our clients transform their offices through cost-effective managed services that support the ongoing evolution of workspaces.

“As we reimagine the modern office, we are making it easier to support collaboration and productivity among workers, whether they are in the office or elsewhere.”

Cisco’s Webex collaboration devices harness the power of artificial intelligence to offer intuitive, seamless collaboration experiences, enabling meeting rooms with smart features such as meeting zones, intelligent people framing, optimised attendee audio and background noise removal, among others.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London. Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: Cisco, collaboration, HCLTech, Hybrid, meetings

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Canonical releases low-touch private cloud MicroCloud

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Canonical has announced the general availability of MicroCloud, a low-touch, open source cloud solution. MicroCloud is part of Canonical’s growing cloud infrastructure portfolio.

It is purpose-built for scalable clusters and edge deployments for all types of enterprises. It is designed with simplicity, security and automation in mind, minimising the time and effort to both deploy and maintain it. Conveniently, enterprise support for MicroCloud is offered as part of Canonical’s Ubuntu Pro subscription, with several support tiers available, and priced per node.

MicroClouds are optimised for repeatable and reliable remote deployments. A single command initiates the orchestration and clustering of various components with minimal involvement by the user, resulting in a fully functional cloud within minutes. This simplified deployment process significantly reduces the barrier to entry, putting a production-grade cloud at everyone’s fingertips.

Juan Manuel Ventura, head of architectures & technologies at Spindox, said: “Cloud computing is not only about technology, it’s the beating heart of any modern industrial transformation, driving agility and innovation. Our mission is to provide our customers with the most effective ways to innovate and bring value; having a complexity-free cloud infrastructure is one important piece of that puzzle. With MicroCloud, the focus shifts away from struggling with cloud operations to solving real business challenges” says

In addition to seamless deployment, MicroCloud prioritises security and ease of maintenance. All MicroCloud components are built with strict confinement for increased security, with over-the-air transactional updates that preserve data and roll back on errors automatically. Upgrades to newer versions are handled automatically and without downtime, with the mechanisms to hold or schedule them as needed.

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With this approach, MicroCloud caters to both on-premise clouds but also edge deployments at remote locations, allowing organisations to use the same infrastructure primitives and services wherever they are needed. It is suitable for business-in-branch office locations or industrial use inside a factory, as well as distributed locations where the focus is on replicability and unattended operations.

Cedric Gegout, VP of product at Canonical, said: “As data becomes more distributed, the infrastructure has to follow. Cloud computing is now distributed, spanning across data centres, far and near edge computing appliances. MicroCloud is our answer to that.

“By packaging known infrastructure primitives in a portable and unattended way, we are delivering a simpler, more prescriptive cloud experience that makes zero-ops a reality for many Industries.“

MicroCloud’s lightweight architecture makes it usable on both commodity and high-end hardware, with several ways to further reduce its footprint depending on your workload needs. In addition to the standard Ubuntu Server or Desktop, MicroClouds can be run on Ubuntu Core – a lightweight OS optimised for the edge. With Ubuntu Core, MicroClouds are a perfect solution for far-edge locations with limited computing capabilities. Users can choose to run their workloads using Kubernetes or via system containers. System containers based on LXD behave similarly to traditional VMs but consume fewer resources while providing bare-metal performance.

Coupled with Canonical’s Ubuntu Pro + Support subscription, MicroCloud users can benefit from an enterprise-grade open source cloud solution that is fully supported and with better economics. An Ubuntu Pro subscription offers security maintenance for the broadest collection of open-source software available from a single vendor today. It covers over 30k packages with a consistent security maintenance commitment, and additional features such as kernel livepatch, systems management at scale, certified compliance and hardening profiles enabling easy adoption for enterprises. With per-node pricing and no hidden fees, customers can rest assured that their environment is secure and supported without the expensive price tag typically associated with cloud solutions.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London. Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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Tags: automation, Canonical, MicroCloud, private cloud

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