TECHNOLOGY

Who Will Really Benefit from AI?

Published

11 months ago

October 17, 2023

Artificial Intelligence (AI) has become an undeniable force in our lives, transforming industries, influencing decision-making, and altering the way we live and work.

While the promises of AI are abundant, there is an ongoing debate about who stands to gain the most from this technological revolution. Will AI benefit everyone equally, or will it exacerbate existing disparities? In this in-depth exploration, we will delve into the various aspects of AI’s impact on society to answer the question: Who will really benefit from AI?

The Pioneers and Early Adopters

· Tech Giants’ Dominance: Tech giants like Google, Amazon, Facebook, and Microsoft have been at the forefront of AI innovation. Their substantial investments in AI research and development have given them a competitive edge across a wide range of sectors. These companies have leveraged AI to improve their products and services, from search engines and recommendation systems to virtual assistants and autonomous vehicles.

· Industry Disruption: AI has disrupted traditional industries, with early adopters using AI to streamline operations, enhance customer experiences, and gain valuable insights from data. This has led to increased market dominance for companies that embraced AI early on.

Small and Medium-sized Enterprises (SMEs)

· Accessibility of AI: Cloud-based AI solutions and open-source tools have made AI more accessible to small and medium-sized enterprises (SMEs). These businesses can now harness the power of AI for various tasks, such as data analysis, customer support, and marketing, without the need for large investments in infrastructure or expertise.

· Enhanced Competitiveness: AI empowers SMEs to compete with larger corporations by improving efficiency and providing data-driven decision-making capabilities. This levels the playing field and allows SMEs to deliver better products and services to their customers.

Healthcare: Saving Lives and Transforming Medicine

· Improved Patient Care: AI applications in healthcare, such as diagnostic tools, predictive analytics, and personalized treatment plans, have the potential to revolutionize patient care. Patients benefit from earlier disease detection, more accurate diagnoses, and tailored treatment options, ultimately saving lives and improving health outcomes.

· Ethical Concerns: The integration of AI in healthcare also raises ethical concerns, particularly regarding patient privacy and bias in AI algorithms. Ensuring that patient data is handled securely and that AI systems do not reinforce existing healthcare disparities is a critical challenge.

Education: Empowering Learners

· Personalized Learning: AI’s ability to provide personalized learning experiences through adaptive learning platforms can revolutionize education. These platforms use AI to tailor educational content to individual student needs, making education more engaging and effective.

· Addressing Equity: To fully harness the potential of AI in education, concerns about data privacy and the digital divide must be addressed. Ensuring equitable access to AI-powered education for all students is essential to avoid exacerbating educational inequalities.

Automation and Job Displacement

· Job Transformation: While AI has the potential to automate certain jobs, it also creates new opportunities in fields related to AI development, data science, and ethical AI auditing. The workforce needs to adapt to these changes through reskilling and upskilling programs.

· Impact on Industries: Industries that rely on routine and repetitive tasks, such as manufacturing and customer service, are more susceptible to job displacement due to automation. Governments and businesses must consider strategies to support affected workers and facilitate their transition to new roles.

Income Inequality: The Growing Gap

· Economic Growth vs. Inequality: The impact of AI on income inequality is a complex issue. AI-driven productivity improvements can lead to economic growth, potentially benefiting everyone. However, if the benefits of AI primarily accrue to the wealthy and corporations, it may exacerbate income inequality.

· Policy Considerations: Policymakers must carefully consider measures to ensure a fair distribution of AI’s benefits. This may include policies related to taxation, income redistribution, and social safety nets to mitigate the negative effects of income inequality.

Bias and Fairness in AI

· Addressing Bias: AI algorithms can inherit biases present in the data they are trained on, leading to discrimination and unfair outcomes. Addressing bias in AI applications, particularly in critical areas like criminal justice, lending, and hiring, is imperative.

· Transparent and Accountable AI: Ensuring that AI systems are transparent, accountable, and subject to scrutiny is essential for building trust in AI technology. Ethical guidelines, auditing processes, and regulatory frameworks are being developed to mitigate bias and ensure fairness.

Ethics and Accountability

· Responsible AI Development: As AI systems become more autonomous and powerful, the need for responsible AI development and deployment grows. Developers and organizations must prioritize ethical considerations and be accountable for the actions of AI systems.

· Regulatory Frameworks: Governments and international organizations are working on establishing regulatory frameworks to address ethical concerns in AI. These frameworks aim to define standards for ethical AI behavior and establish mechanisms for holding AI developers and users accountable for their actions.

The Role of Governments and Regulation

Governments play a pivotal role in shaping the trajectory of AI technology and its impact on society. Their actions and policies can influence AI research, development, deployment, and regulation. Here are several key aspects to consider regarding the role of governments and regulation in the AI landscape:

· Promoting AI Research and Development: Governments invest in AI research and development, offering incentives and collaborating with academia and industry to drive innovation, boost competitiveness, and stimulate economic growth.

· Regulation for Ethical and Fair AI: Governments establish regulatory frameworks to ensure AI systems are developed and used transparently, fairly, and safely, addressing concerns related to ethics, data privacy, bias, and accountability. Additionally, they engage in international collaboration to set common AI standards and principles, while balancing innovation with regulation to foster technological advancement responsibly.

Global Impact and Geopolitical Dynamics

AI is a transformative technology that has significant global implications, influencing geopolitics, economic power, and national security:

· Geopolitical Competition and Economic Power: Superpowers like the U.S. and China engage in fierce AI competition, recognizing its potential for economic growth and military capabilities. AI’s advancement may lead to shifts in global economic power dynamics.

· National Security and Ethics: AI technologies have implications for defense and national security, prompting investments in AI-powered military systems and cybersecurity measures. Ethical concerns related to privacy, surveillance, and human rights arise globally, necessitating international cooperation to establish norms and agreements, fostering collaborative diplomacy to prevent potential AI arms races.

Environmental Concerns

· Energy Consumption and Data Centers: AI technology’s substantial energy demands, particularly in training large models, are a major environmental concern. Data centers, crucial to AI, consume vast amounts of electricity, often from non-renewable sources, exacerbating carbon emissions and climate change.

· Mitigation Efforts: To address these concerns, efforts focus on developing energy-efficient AI solutions, including more power-efficient hardware and optimized algorithms. Additionally, initiatives promote responsible AI development with an emphasis on sustainability and ethical considerations, essential for mitigating AI’s environmental impact and ensuring long-term sustainability.

The Future of Work and Education

The advent of AI technology has ushered in a transformative era for work and education, presenting both opportunities and challenges. Here are some key aspects to consider:

· Impact on Jobs and Careers: AI and automation have the potential to replace certain tasks, raising concerns about job displacement. However, they also create new career opportunities in AI-related fields, emphasizing the importance of acquiring relevant skills.

· Education Transformation and Ethical Considerations: AI transforms education with personalized learning and administrative automation, while ethical and social considerations gain importance. Ensuring responsible AI development and usage, without bias or harm, is a critical challenge requiring ongoing attention and regulation.

The impact of AI on the environment, work, and education is multifaceted. While environmental concerns highlight the need for energy-efficient AI solutions, the future of work and education underscores the importance of adaptation, reskilling, and responsible AI development. Managing these challenges effectively will determine how AI technology shapes our future in a sustainable and equitable manner.

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TECHNOLOGY

Next-gen chips, Amazon Q, and speedy S3

Published

9 months ago

December 1, 2023

Max

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.

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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TECHNOLOGY

HCLTech and Cisco create collaborative hybrid workplaces

Published

9 months ago

November 29, 2023

Max

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.

Tags: Cisco, collaboration, HCLTech, Hybrid, meetings

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TECHNOLOGY

Canonical releases low-touch private cloud MicroCloud

Published

9 months ago

November 28, 2023

Max

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.

Tags: automation, Canonical, MicroCloud, private cloud

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