At the forefront of technological advancements, Microsoft has recently emphasized its significant investment in artificial intelligence (AI) and cloud solutions within its partner ecosystem. The company announced an array of updates, aimed at empowering partners to innovate and grow. These initiatives promise to reshape how Microsoft collaborates with its global network of solutions providers and expand the companys influence in small to midsize businesses (SMBs).

Microsofts key focus on AI has resulted in Solution Partners utilizing Azures AI capabilities across more than 53,000 customer implementations. The enthusiasm for AI has translated into a substantial increase in partner involvement, downloads of Microsofts AI resources, and personalized AI-driven security solutions. The newly announced Copilot for Security, for instance, which will be available in all commerce channels, stands as testament to the rapid integration of AI into security measures.

The Solutions Partner program has seen enhancements through certified software designations, allowing partners to specialize and differentiate themselves effectively. These designations span a variety of sectors, including healthcare, retail, financial services, manufacturing, and sustainability, showcasing the extensive reach of Microsofts AI and cloud services.

In supporting the SMB market, Microsoft aims to roll out tailored partner pathways for Azure and security solutions later this year. This strategic initiative is expected to furnish SMB-focused solution providers with critical resources and benefits.

Additionally, new partner designations for training and support services are set to be launched, offering exclusive resources and customer-facing recognition. These designations highlight an ongoing commitment to fostering a skilled partner base, ready to tackle emerging tech challenges.

In an ever-evolving digital landscape, Microsofts partner program updates signal a transformative phase where AI is turning from a concept into large-scale implementation, enabling partners to deliver cutting-edge solutions and foster growth in their specific domains.

Microsofts Commitment to AI and Cloud Innovation in the Partner Ecosystem

Microsofts latest endeavors underscore a deep commitment to harnessing the potential of artificial intelligence (AI) and cloud technology, particularly within its partner ecosystem. The technology giant is set on empowering its partners to pioneer innovations and expand their reach, especially within the small to midsize business market.

AI and Cloud Solutions Driving Industry Transformation

The push into AI by Microsoft has been especially notable, with Solution Partners harnessing Azures AI capabilities in over 53,000 customer implementations. This enthusiasm is not unfounded; artificial intelligence is radically transforming industries by enabling new capabilities and workflows. These advances have not only led to an uptick in partner engagement and utilization of Microsofts AI tools but also in the development of more refined AI-driven security solutionshighlighted by the introduction of Copilot for Security, which reflects the deep integration of AI into modern cybersecurity measures.

Program Enhancements and New Specializations

Enhancements to the Solutions Partner program, including new certified software designations, are facilitating greater specialization, allowing partners to differentiate themselves in key sectors such as healthcare, retail, finance, manufacturing, and sustainability. These sectors are increasingly dependent on cloud and AI technologies to drive efficiency, customer engagement, and innovation. By focusing on these areas, Microsoft is not only expanding its reach but also empowering its partners to gain a competitive edge.

Market Forecasts and Industry Adoption

The market forecasts for AI and cloud computing are bullish, projecting significant growth driven by the twin engines of technological advancement and industry adoption. Organizations are leveraging cloud infrastructure and AI to improve decision-making, automate processes, and deliver personalized services. Consequently, this generates additional opportunities for partners who can provide tailored solutions.

Issues in AI and Cloud Industries

While the future looks bright, the integration of AI and cloud solutions is not without its challenges. Issues such as data privacy, security, ethical use of AI, and the demand for skilled professionals remain at the forefront of industry discussions. Organizations and their partners must navigate these complex issues while ensuring compliance with regulatory standards and fostering public trust in AI applications.

Supporting the SMB Market and Partner Growth

Microsofts commitment to the SMB sector is evident through its strategy to unveil bespoke pathways for Azure and security solutions. By providing SMB-focused solution providers with essential resources, Microsoft is tackling the unique challenges faced by smaller enterprises, often in need of scalable and cost-effective solutions that do not compromise on functionality.

Furthermore, the tech giant is on track to introduce new partner designations aimed at enhancing training and support services. This move is poised to provide partners with exclusive resources and recognition, helping them to stand out in a crowded marketplace.

Conclusion

In an ever-changing digital space, Microsofts program updates are leading a transformative shiftwhere once AI was a burgeoning concept; it now takes center stage in large-scale implementation efforts. The partners of Microsoft are equipped to supply high-tech solutions and drive growth across various domains, an indication that the future of cloud and AI within the partner ecosystem is not just promisingits already unfolding.

For additional insights and information, feel free to visit Microsofts official website at Microsoft for a more comprehensive understanding of their investments and advancements in AI and cloud technologies.

Iwona Majkowska is a prominent figure in the tech industry, renowned for her expertise in new technologies, artificial intelligence, and solid-state batteries. Her work, often at the forefront of innovation, provides critical insights into the development and application of cutting-edge AI solutions and the evolution of energy storage technologies. Majkowskas contributions are pivotal in shaping the future of sustainable energy and intelligent systems, making her a respected voice in both academic and industrial circles. Her articles and research papers are a valuable resource for professionals and enthusiasts alike, seeking to understand the impact and potential of these transformative technologies.

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Microsoft Expands Its Partner Ecosystem with AI and Cloud Advancements - yTech

New AI infrastructure offerings and integrations enable more open and accessible AI

GTCGoogle Cloud and NVIDIA today announced a deepened partnership to enable the machine learning (ML) community with technology that accelerates their efforts to easily build, scale and manage generative AI applications.

To continue bringing AI breakthroughs to its products and developers, Google announced its adoption of the new NVIDIA Grace Blackwell AI computing platform, as well as the NVIDIA DGX Cloud service on Google Cloud. Additionally, the NVIDIA H100-powered DGX Cloud platform is now generally available on Google Cloud.

Building on their recent collaboration to optimize the Gemma family of open models, Google also will adopt NVIDIA NIM inference microservices to provide developers with an open, flexible platform to train and deploy using their preferred tools and frameworks. The companies also announced support for JAX on NVIDIA GPUs and Vertex AI instances powered by NVIDIA H100 and L4 Tensor Core GPUs.

The strength of our long-lasting partnership with NVIDIA begins at the hardware level and extends across our portfolio from state-of-the-art GPU accelerators, to the software ecosystem, to our managed Vertex AI platform, said Google Cloud CEO Thomas Kurian. Together with NVIDIA, our team is committed to providing a highly accessible, open and comprehensive AI platform for ML developers.

Enterprises are looking for solutions that empower them to take full advantage of generative AI in weeks and months instead of years, said Jensen Huang, founder and CEO of NVIDIA. With expanded infrastructure offerings and new integrations with NVIDIAs full-stack AI, Google Cloud continues to provide customers with an open, flexible platform to easily scale generative AI applications.

The new integrations between NVIDIA and Google Cloud build on the companies longstanding commitment to providing the AI community with leading capabilities at every layer of the AI stack. Key components of the partnership expansion include:

Adoption of NVIDIA Grace Blackwell: The new Grace Blackwell platform enables organizations to build and run real-time inference on trillion-parameter large language models. Google is adopting the platform for various internal deployments and will be one of the first cloud providers to offer Blackwell-powered instances.

Grace Blackwell-powered DGX Cloud coming to Google Cloud: Google will bring NVIDIA GB200 NVL72 systems, which combine 72 Blackwell GPUs and 36 Grace CPUs interconnected by fifth-generation NVLink, to its highly scalable and performant cloud infrastructure. Designed for energy-efficient training and inference in an era of trillion-parameter LLMs, NVIDIA GB200 NVL72 systems will be available via DGX Cloud, an AI platform offering a serverless experience for enterprise developers building and serving LLMs. DGX Cloud is now generally available on Google Cloud A3 VM instances powered by NVIDIA H100 Tensor Core GPUs.

Support for JAX on GPUs: Google Cloud and NVIDIA collaborated to bring the advantages of JAX to NVIDIA GPUs, widening access to large-scale LLM training among the broader ML community. JAX is a framework for high-performance machine learning that is compiler-oriented and Python-native, making it one of the easiest to use and most performant frameworks for LLM training. AI practitioners can now use JAX with NVIDIA H100 GPUs on Google Cloud through MaxText and Accelerated Processing Kit (XPK).

NVIDIA NIM on Google Kubernetes Engine (GKE): NVIDIA NIM inference microservices, a part of the NVIDIA AI Enterprise software platform, will be integrated into GKE. Built on inference engines including TensorRT-LLM, NIM helps speed up generative AI deployment in enterprises, supports a wide range of leading AI models and ensures seamless, scalable AI inferencing.

Support for NVIDIA NeMo: Google Cloud has made it easier to deploy the NVIDIA NeMo framework across its platform via Google Kubernetes Engine (GKE) and Google Cloud HPC Toolkit. This enables developers to automate and scale the training and serving of generative AI models, and it allows them to rapidly deploy turnkey environments through customizable blueprints that jump-start the development process. NVIDIA NeMo, part of NVIDIA AI Enterprise, is also available in the Google Marketplace, providing customers with another way to easily access NeMo and other frameworks to accelerate AI development.

Vertex AI and Dataflow expand support for NVIDIA GPUs: To advance data science and analytics, Vertex AI now supports Google Cloud A3 VMs powered by NVIDIA H100 GPUs and G2 VMs powered by NVIDIA L4 Tensor Core GPUs. This provides MLOps teams with scalable infrastructure and tooling to confidently manage and deploy AI applications. Dataflow has also expanded support for accelerated data processing on NVIDIA GPUs.

Google Cloud has long offered GPU VM instances powered by NVIDIAs cutting-edge hardware coupled with leading Google innovations. NVIDIA GPUs are a core component of the Google Cloud AI Hypercomputer a supercomputing architecture that unifies performance-optimized hardware, open softwareand flexible consumption models. The holistic partnership enables AI researchers, scientistsand developers to train, fine-tuneand serve the largest and most sophisticated AI models now with even more of their favorite tools and frameworks jointly optimized and available on Google Cloud.

Runways text-to-video platform is powered by AI Hypercomputer. At the base, A3 VMs, powered by NVIDIA H100 GPUs gave our training a significant performance boost over A2 VMs, enabling large-scale training and inference for our Gen-2 model. Using GKE to orchestrate our training jobs enables us to scale to thousands of H100 GPUs in a single fabric to meet our customers growing demand.

By moving to Google Cloud and leveraging AI Hypercomputer architecture with NVIDIA T4 GPUs, G2 VMs powered by NVIDIA L4 GPUs and Triton Inference Server, we saw a significant boost in our model inference performance while lowering our hosting costs 15% using novel techniques enabled by the flexibility that Google Cloud offers.

Writers platform all comes together through this extremely productive partnership with Google and NVIDIA. Were able to use NVIDIA GPUs optimally for training and inference. We leverage NVIDIA NeMo to build our industrial-strength models, which generate 990,000 words a second with over a trillion API calls per month. Were delivering the highest quality models that exceed those from companies with larger teams and bigger budgets and all of that is possible with the Google and NVIDIA partnership. The benefits of their AI expertise are passed down to our enterprise customers, who can build meaningful AI workflows in days not months or years.

Learn more about Google Clouds collaboration with NVIDIA at GTC, the global AI conference, March 18-21 (booth #808).

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Google Cloud and NVIDIA Expand Partnership to Scale AI Development - NVIDIA Blog

MAXHUB, a leading provider of collaborative communication and interactive display solutions, proudly announces it will integrate Microsoft Azure technology. MAXHUB will harness the power of Azure to significantly amplify its international business growth and further AI technology advancements.

Amidst expanding global business horizons, MAXHUB integrates with Microsoft Azure to empower itself by meeting the surging needs for scalable cloud computing and storage. MAXHUB seamlessly shares data across multiple global data centers using the robust capabilities of Azure Cosmos DB and Blob Storage. By segregating foundational business data from personal privacy data and integrating with Azure Kubernetes Services, MAXHUB have established a globally distributed architecture for deploying key services like OTA (Over-The-Air) andCMS (Content management system). This setup is tailored for MAXHUB operational management within a worldwide scope. Not only does this enhance the research and operational efficiency, but it also effectively aligns with the data compliance regulations of various regions.

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MAXHUBs integration of Azure services will support its global business and drive it forward, helping users move into a new era of more efficient and high-quality service experiences. In addition, this move will promote MAXHUBs innovative development in the field of artificial intelligence, which in turn will enhance users interactive experience with smarter and more comprehensive technology solutions.

We are preparing to harness Azure OpenAI features to explore AI applications in education. Our aim is to assist teachers in lesson planning and curriculum evaluation by integrating AI capabilities. Said DavidMeng, President of Global Business Group atMAXHUB. Our objective is to nurture a high efficient and intelligent ecosystem where creativity flourishes into meaningful human interactions. Microsoft Azures offerings align strategically with our vision and will establish a solid foundation for our success in global markets.

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At present, the global demand for cloud computing and AI services is growing. MAXHUBs application and exploration of Microsoft Azure will provide users with a solid technical foundation and empower businesses with cutting-edge technology. Microsoft is committed to empowering our customers and partners with supreme solutions that drive productivity and enrich collaborative experiences. Said Min ZHENG, Vice President of Microsoft China.

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[To share your insights with us as part of editorial or sponsored content, please write to sghosh@martechseries.com]

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MAXHUB to Build Advanced AI Solutions with Microsoft Azure Cloud to Drive Global Business Growth - AiThority

Over the next few years, the number of organizations navigating to the cloud is expected to grow exponentially. According toGartner, more than 70% of enterprises will use cloud platforms to accelerate their business initiatives by 2027. (Thats up from fewer than 15% in 2023.)Part of this growth will result from public cloud providers increasingaccess to and adoption of innovative technologies like AI.

It may be time for your organization to initiate its own cloud migration process. Before you start, you need to learn about your options and figure out where to start your journey.

Why you want to migrate to the cloud

Migrating to the cloud means hosting your infrastructure in a secure multi-tenant environment managed by a cloud provider. This allows you to focus on application delivery that provides value to your business.

You can achieve several benefits by migrating to the cloud, among them improved resiliency and higher availability through leveraging the redundancy built into cloud providers Infrastructure-as-a-Service(IaaS) offerings. It also helps to remove equipment procurement cycles, enabling IT to experiment with solutions and act on changing business requirements faster than you otherwise could.

Navigating to the cloud also comes with security advantages. For instance, all cloud providers offer security settings that have been tested over time. Another advantage is the ability to use tested solutions from the cloud vendors marketplaces to eliminate the need to build and maintain these images and applications yourself.

Understanding where you want to go in the cloud

When it comes to planning your cloud migration, there are three common types of cloud storage from which your organization can choose.

1. Blob or object storage

Accessible by HTTPS, blob or object storage is suitable for mass file transfers/migrations. It is also independent of systems or virtual machines (VMs), and, in many cases, you can use it to deliver content to users. The risk of using this type of storage is that it can be made publicly available.

2. Block storage

Block storage is attached directly to individual VMs. You can typically use direct attached or Storage Area Network (SAN) storage for block storage in an on-premises data center. You can also provision it for performance, but youre ultimately responsible for configuring redundancy, fault tolerance and high availability along with enabling encryption and data protection.

3. Network attached storage

Network attached storage (NAS) is similar to a fileserver, which can be accessed by multiple users/systems simultaneously. NAS effectively shares data amongst systems internally, reducing the need to keep multiple copies on individual systems and maintaining updates on each system. Here, you are also usually responsible for enabling encryption and data protection methods.

Cloud service models: Your responsibility in the cloud

Beyond cloud storage types, every cloud provider offers varying levels of service models from which you can pick based on your organization, staff capabilities and skill sets. You can choose from bare metal platforms, where youre responsible for everything above the base hardware and networking level (IaaS), all the way up to fully managed services and applications in which the responsibility for configuring and maintaining the servers, applications and environments is taken on by the cloud provider (Software-as-a-Service [SaaS] or Function-as-a-Service [FaaS]).

Source:Cloud Security and the Shared Responsibility Model

Each level of managed services has pros and cons. The pros of managed services are that you dont have to focus on the details of systems management and maintenance. Even so, you may lose customization options, access to lower-level resources, and cost savings.

How to migrate to the cloud

If you're looking to move to the cloud, there are three common ways to do so.

1. Lift and shift

Lift and shift takes the servers and applications running in the on-premises datacenter and simply re-hosts them in the cloud. This can be the easiest way to migrate to the cloud, and it is the first step many companies take. However, this method doesnt help with reducing technical debt and it is often not a means of cost-effective migration, as you are not right-sizing your infrastructure or taking advantage of the elastic nature of the cloud.

2. Refactoring

Refactoring includes modifying on-premises infrastructure, code and deployments to take advantage of the clouds elastic nature. This method includes the advantage of having web services behind a load balancer and scaling computing resources up and down based on demand rather than building a web farm to support peak load, thus saving you money. You may also take advantage of managed services or Platform-as-a-Service (PaaS) offerings such as CDN, database and data replication services. The risk with this approach is that you are changing multiple variables during the migration process, which makes troubleshooting more complex.

3. Redesigning to be cloud native

This is a more complex migration strategy in which the applications architecture is redesigned during migration to take full advantage of the benefits of the cloud. The benefit of this approachis that it can be a highly resilient, cost-effective solution that scales to meet demand without over-provisioning. However, it adds complexity and risk, as many architecture components are changing at the same time. Additionally, it can be more challenging to ensure resiliency and security.

Your responsibility in moving to the cloud

Migrating to the cloud is a multi-stage program. You will learn a great deal and ultimately save on costs by starting small, building on the experience and working toward designing your applications and infrastructure to scale up and down.

Moving to the cloud does not make you automatically secure, however. You are always responsible for securing your own applications, OS images, networks, access rules and data in the cloud. Cloud vendors provide security of the computing assets, not the data placed on their assets. You will need to establish a relationship with your cloud provider to understand where your security responsibilities lie.

To learn more, explore CIS cloud security guidance.

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Migrating to the cloud: An overview of process and strategy - Healthcare IT News