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How Artificial Intelligence is Disrupting Physics

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How Artificial Intelligence is Disrupting Physics

Artificial Intelligence (AI) is transforming many industries, including the field of physics.

AI is being used in physics to solve complex problems and make new discoveries that were previously thought to be impossible. From finding new particles to understanding the mysteries of the universe, AI is disrupting the field of physics in exciting ways. This article will explore how AI is being used in physics including the potential benefits and limitations of this technology.

Understanding Artificial Intelligence in Physics

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Source: Towards Data Science

Artificial Intelligence refers to the ability of machines to perform tasks that normally require human intelligence, such as problem solving and decision making. AI systems can be trained to perform specific tasks by learning from large amounts of data. This allows AI systems to make predictions, identify patterns, and make decisions based on this data.

In physics, AI is being used to analyze data from experiments and simulations, as well as to develop new models and theories. AI can also be used to find new patterns and correlations in data that were previously hidden, allowing physicists to make new discoveries.

Use Cases of Artificial Intelligence in Physics

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Source: Nature Magazine

There are numerous use cases of artificial intelligence in physics including:

Particle Physics

AI is analyzing data from particle accelerators, such as the Large Hadron Collider (LHC), to identify new particles and understand the fundamental forces of the universe. AI algorithms can analyze vast amounts of data from experiments and simulations, helping physicists make new discoveries and advance our understanding of the universe.

Astrophysics

Artificial intelligence is utilized in astrophysics to analyze data from telescopes and simulations to understand the mysteries of the universe. For example, AI can be used to analyze data from the Kepler space telescope to identify exoplanets, or planets outside our solar system.

Materials Science

AI is deployed in materials science to develop new materials and understand the properties of existing materials. For example, AI algorithms can be used to analyze data from experiments and simulations to identify new materials with specific properties, such as high strength or conductivity.

Climate Modeling

Artificial intelligence is leveraged in climate science to develop more accurate models of the Earth’s climate and predict future climate change. For example, AI algorithms can be used to analyze data from climate simulations and make predictions about future temperatures and sea levels.

Benefits of Using Artificial Intelligence in Physics

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Source: Semantic Scholar

There are several benefits to using AI in physics, including:

Improved Accuracy

AI algorithms can analyze vast amounts of data and identify patterns and correlations that were previously hidden. This can lead to more accurate predictions and a deeper understanding of complex phenomena, such as the behavior of subatomic particles or the climate.

Increased Efficiency

By automating the data analysis process, AI can reduce the time and resources required for data analysis. This can help physicists make new discoveries and advance their understanding of the universe more quickly.

Better Simulations

AI can be used to develop more accurate simulations, which can help physicists better understand complex phenomena, such as the behavior of materials or the climate.

New Discoveries

AI has the potential to make new discoveries that were previously thought to be impossible. By analyzing vast amounts of data and identifying patterns and correlations that were previously hidden, AI can help physicists make new breakthroughs and advance our understanding of the universe.

Limitations of Artificial Intelligence in Physics

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Source: IBM

While AI has the potential to transform the field of physics, there are also some limitations to this technology. These include:

Bias in Training Data

AI algorithms are only as accurate as the data they are trained on. If the training data is biased or inaccurate, the algorithms will not be able to provide accurate results. In physics, this can be a concern as the data used to train AI algorithms may not accurately represent the real world.

Limited Understanding

AI algorithms can only make predictions and analyze data based on the patterns they have been trained on. They may not be able to understand the underlying physical principles behind complex phenomena, such as the behavior of subatomic particles.

Lack of Transparency

AI algorithms can be difficult to understand and interpret, making it difficult for physicists to know exactly how the algorithms are making predictions. This can make it challenging to assess the accuracy of AI predictions and understand how they could be improved.

Privacy Concerns

The use of AI in physics can also raise privacy concerns, as the data being analyzed may contain sensitive information. For example, data from experiments and simulations may contain information about the behavior of sensitive materials or the properties of new particles.

What’s Next for AI in Physics?

AI is disrupting the field of physics by improving the accuracy of predictions, increasing efficiency, and making new discoveries. However, it is important to consider the limitations of AI in physics and use this technology in conjunction with traditional methods and techniques. As AI continues to advance, it has the potential to provide physicists with a more comprehensive understanding of the universe and help make new breakthroughs in our understanding of the world around us.

As AI continues to evolve and advance, it is likely that its role in physics will become even more important. Here are some potential developments for AI in physics:

  • Improved accuracy and efficiency: AI algorithms will continue to become more accurate and efficient as they are trained on larger and more diverse datasets. This will help physicists make more precise predictions and discover new patterns in the data.

  • Integration with traditional methods: AI and traditional physics techniques are likely to become increasingly integrated, providing physicists with a more comprehensive understanding of complex phenomena.

  • Interdisciplinary applications: AI has the potential to play a role in interdisciplinary fields, such as biophysics and materials science, where it can be used to analyze data from experiments and simulations to gain new insights into the behavior of materials and living systems.

  • New discoveries: AI has the potential to make new breakthroughs in our understanding of the universe, including the discovery of new particles and a deeper understanding of the fundamental forces of the universe.

  • Enhanced simulations: AI will play an increasingly important role in developing more accurate simulations, which can help physicists better understand complex phenomena, such as the behavior of materials or the Earth’s climate.

The future of AI in physics looks promising, and the technology has the potential to make significant contributions to our understanding of the world around us. As AI continues to advance, it is likely that it will play an even greater role in physics and help us make new discoveries and breakthroughs.

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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.”

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.

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.

Tags: automation, Canonical, MicroCloud, private cloud

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AWS and SoftwareOne collaborate on RISE with SAP

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Amazon Web Services (AWS) and SoftwareOne Holding AG, a global provider of end-to-end software and cloud technology solutions, have partnered to help customers transition to RISE with SAP on an AWS cloud environment.

Called the Ready for RISE on AWS bundle, it combines SoftwareOne’s deep SAP advisory and implementation knowledge with AWS technologies to expedite a client’s SAP transformation journey.

The collaboration comes at a time when there is growing pressure on organisations to decide how to modernise their SAP environments driven in part by the end of mainstream support for SAP ERP Central Component (SAP ECC) in 2027. Despite the imminent deadline, many organisations are still confused as to which path to take, including when to adopt RISE with SAP, SAP’s bundled offering of cloud solutions, infrastructure, and services that helps migrate SAP ERP to the cloud.

Ireneusz Hołowacz, Director of Application Development Center at GAVDI Polska, said: “A stable, efficient, and cost-effective environment for consultants and programmers is one of the most important priorities of our daily work. Thanks to the migration of our SAP systems to the AWS cloud with the help of SoftwareOne, GAVDI Polska has achieved all the goals set for this process.

In a survey recently conducted by SoftwareOne with Americas’ SAP Users’ Group (ASUG) – the full details of which will be revealed in January 2024 – showed that while 42% of respondents were familiar with RISE with SAP, 40% had heard of it but weren’t familiar with the details and 18% had never heard of it. Over half (52%) said they were still unsure how RISE with SAP would impact their existing relationship with cloud service providers.

“SAP customers have implemented some of the most comprehensive and complex enterprise systems in the industry and moving them to cloud services like AWS requires many important decisions to be made to optimise these investments,” says Joshua Greenbaum, Principal at EAC. “SoftwareOne’s extensive experience in the SAP ecosystem, combined with its unique capabilities around system rationalisation, cost containment, contracts and licenses, and cloud service management, among others, will provide customers deploying on AWS with the ability to make the most of RISE on SAP and other SAP offerings. Ready for RISE on AWS is an important offering for SAP customers at this critical moment in their business transformations.”

The Ready for RISE on AWS bundle will help clients understand their SAP transformation options and offer a comprehensive solution to organisations who consider RISE with SAP. It includes advisory data preparation, conversion services, data and AI, cloud innovation platform, supporting the entire journey to RISE on AWS. Clients will benefit from accelerated Return on Investment (ROI), optimal data management, and cost-saving strategies while laying the foundation for ongoing innovation and long-term business success.

Matt Schwartz, worldwide director, SAP Alliance & Partner Network at AWS, said: “As a valued AWS Premier Consulting Partner, AWS is working closely with SoftwareOne to offer SAP customers comprehensive assistance through each step of their journey to RISE with SAP on AWS.  SoftwareOne’s ability to bundle Advisory, Data & AI, Cloud Platform, and Operations considerations can be of high interest to customers who are seeking to understand RISE with SAP as well as the cloud native and operation considerations that surround and support the RISE with SAP construct.”

PF Grillet, SAP Business Lead at SoftwareOne, said: “There are many choices available to SAP clients who know they need to modernise but aren’t sure of the best option, particularly given the business-critical nature of the applications.

“All of our services are centered around our customers and what is right for them. This includes supporting and optimising RISE with SAP in scenarios when it’s the right decision based on their requirements. Our extensive knowledge of and relationship with AWS means we can help them better prepare and achieve a seamless transition to S/4HANA using RISE with SAP on AWS with reduced costs and risks. This collaboration goes beyond preparing businesses for change; it’s making transformation and becoming innovation-ready a reality using AWS technologies.”

The offering includes SNP tooling to reduce a customer’s data footprint and accelerate migration. SoftwareOne will migrate selected data to an AWS data lake, accelerate innovation readiness and ensure SAP data is suitable for broader data analytics and AI use cases. Clients gain access to innovative tools like AWS’ Sagemaker for Machine Learning, continuous data management and optimisation within the AWS environment. The AWS innovation platform also includes Amazon Bedrock that helps organisations accelerate adapting Large Language Models and deploying GenAI use cases that leverage the extended data set.

“While the future innovation opportunities are exciting, clients need to balance these with a pragmatic approach to costs,” explained Marilyn Moodley, Country Leader for South Africa and WECA at SoftwareOne, “We integrate ‘Cost-Out’ recommendations into the core of our services, providing a more cost-effective solution for customers, like reducing the data footprint size and optimising storage and archiving.

“Our expertise in the complexities of SAP licensing further drives cost savings while our FinOps capabilities enable customers to optimise their AWS cloud spend and effectively manage their AWS cloud environment, ensuring full transparency in their budgets. The overall result is a significantly reduced time for RISE migration, which translates into a quicker time to value.”

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: AWS, partnership, SAP, SoftwareOne, transition

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