TECHNOLOGY
How Artificial Intelligence Revolutionized Computer Vision
Businesses are leveraging advanced technologies such as artificial intelligence (AI), machine learning (ML), and computer vision to derive valuable insights. AI is the ability of machines to perform human-like tasks. It learns to make decisions based on data and can be categorized as weak AI or strong AI. Weak AI is limited to performing specific tasks, while strong AI is capable of performing any task that requires human intelligence. AI is significantly contributing to the evolution of computer vision. Computer vision is a technology that enables computers to understand and interpret visual data using algorithms and models. This includes the ability to analyze digital images and videos, identify objects and patterns and make decisions based on previously collected data. Computer vision finds its applications in various fields, such as facial recognition, image search, autonomous vehicles and medical imaging. In addition, it is being employed by enterprises for quality control, customer behavior analysis and other essential tasks. The incorporation of AI in computer vision is revolutionizing and augmenting the capabilities of computer vision, leading to improved outcomes.
Understanding the Differences Between Artificial Intelligence and Computer Vision
Artificial intelligence and computer vision are related fields, but they are not the same thing. A few differential factors are mentioned below.
Scope
AI is a broader field that encompasses any technology that enables machines to perform tasks that would typically require human intelligence. This includes NLP, decision-making and problem-solving. Computer vision, on the other hand, is a specific subset of AI that focuses on enabling machines to interpret and understand visual data.
Applications
AI is used in a wide range of applications, from voice recognition and speech synthesis to autonomous vehicles and medical diagnosis. Computer vision, on the other hand, is used primarily in applications such as object recognition and image and video analysis.
Interdisciplinary Fields
Both AI and computer vision are interdisciplinary fields that draw on knowledge from computer science, mathematics, statistics, and engineering. However, computer vision also draws heavily on fields such as optics, physics, and psychology, among others.
Use Cases of Artificial Intelligence In Computer Vision
Despite their differences, AI’s capabilities are assisting computer vision in:
Object Detection and Recognition
AI algorithms can be trained to recognize and classify objects in images and videos with high accuracy. This technology is already being used in applications such as self-driving cars, security systems and medical imaging.
Image and Video Analysis
Artificial intelligence can also be used to automatically analyze large amounts of visual data, identifying patterns and trends that might be missed by human analysts. This can be particularly useful in fields such as marketing, where companies can use computer vision to track customer behavior and identify trends in consumer preferences.
Natural Language Processing
Natural language processing is a branch of artificial intelligence that can be used to understand and interpret text within images and videos, enabling machines to recognize and respond to spoken commands and written instructions.
Artificial Intelligence is Improving Computer Vision
AI in computer vision is revolutionizing its scope for various industries. From banking to healthcare, computer vision can assist several industries in enhancing customer services and making accurate analyses.
TECHNOLOGY
Next-gen chips, Amazon Q, and speedy S3
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.
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.
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.
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TECHNOLOGY
HCLTech and Cisco create collaborative hybrid workplaces
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.”
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.
TECHNOLOGY
Canonical releases low-touch private cloud MicroCloud
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.
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.
