Persistent Systems a global Digital Engineering and Enterprise Modernization leader, announced a multi-year Strategic Collaboration Agreement with Amazon Web Services (AWS) to accelerate the pace of innovation and development of generative AI solutions for clients. Persistent is a long-standing AWS Partner and has a proven track record of early scale generative AI adoption across multiple industry verticals leveraging services like Amazon CodeWhisperer and Amazon Bedrock. Amazon CodeWhisperer provides generative AI-powered code recommendations directly in multiple integrated development environments (IDEs) to help developers build applications quickly in more than 15 coding languages; Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI companies accessible via an API to build and scale generative AI applications.

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This strategic collaboration with AWS will help Persistent to further increase the impact it delivers to its clients that are embracing generative AI. Through this teaming, Persistent will have access to additional resources from AWS to build proofs of concept to help clients identify tangible business outcomes from generative AI. This will also support use case discovery and rapid build out of solutions with additional go-to-market funds from AWS. One of the key benefits to combined clients will be continued early access to AWS’s generative AI services and investments that will help clients with their aspirations around growth, time-to-market, and better customer experience.

The Strategic Collaboration Agreement builds on Persistent’s 30+ years of software engineering heritage, its best practices from more than 120 AWS engagements for cloud migration and modernization, and its 2,500 AWS practitioners to enable flexible and scalable generative AI-powered solutions tailored to clients’ unique needs. Persistent’s AWS Migration Competency status provides proven cloud expertise to help clients move successfully to AWS through all phases of complex migration projects. This collaboration reflects Persistent’s proficiency in building robust cloud infrastructure, crucial in today’s cloud-first, AI-first world, enabling clients to implement cloud-powered generative AI solutions.

These combined assets from AWS and Persistent can bolster the value provided to joint clients, helping them unlock the full potential of their technology investments.

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“Enterprises across industries are looking to tap into the transformative potential of generative AI to reimagine, redefine, and rethink their business models for improved customer experiences and business growth. Combined with our newly acquired AWS Migration Competency status and our SCA, AWS will help us scale generative AI adoption among our clients so they can identify and implement use cases where this technology can have a real impact. We remain committed to helping clients reach their technology goals by leveraging the agility, breadth of services, and rapid innovation that AWS provides.”

“Generative AI unlocks new opportunities to transform the life sciences industry. We are modernizing our legacy research applications to help accelerate the drug development process and simplify workflows. With Persistent’s Digital Engineering expertise, powered by the AWS platform, Regeneron’s research and pre-clinical development teams help bring our new life-savings drugs to market faster.”

“We are delighted to be working with Persistent to help our customers accelerate growth, enable business transformation, and enhance their digital experience. Together, we aim to redefine what’s possible with generative AI, setting new standards for efficiency, innovation, and technological advancements.”

Read Top 20 Uses of Artificial Intelligence In Cloud Computing For 2024

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According to a recently published report from Dell’Oro Group, the trusted source for market information about the telecommunications, security, networks, and data center industries, 3Q 2023 marks the fifth sequential quarter of double-digit year-over-year (Y/Y) growth for the Data Center Physical Infrastructure (DCPI) market, that has historically grown at mid-single digit rates for the past decade. Growth from pandemic induced orders is waning, but early AI deployments are materializing as a new driver of revenue growth. Some vendors have secured orders for equipment optimized for large scale AI workloads, which are more than offsetting the decline in pandemic-related orders, and backlogs are rising.

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“The generative AI infrastructure story began with the NVDIA H100 in 1Q 2023, which has remained the industry barometer for AI adoption. End-users have utilized significant resources to obtain initial shipments of the costly and supply constrained GPU,” said Lucas Beran, Research Director at Dell’Oro Group. Due to the effort required here, many end-users are only able to address the power and thermal management infrastructure requirements after or close to receiving those initial GPU shipments.

“Without a doubt, these AI related power and cooling investments started contributing to market growth in 3Q 2023. This was particularly prominent for rack power distribution units, where customized products with higher power ratings were notable. The next few quarters will increasingly emphasize the transition in DCPI market drivers, from broad based pandemic induced digitalization and supply chain constraints, to large scale, purpose-built AI facilities,” Beran added.

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Additional highlights from the 3Q 2023 Data Center Physical Infrastructure Quarterly Report:

• Vertiv continued to outpace market growth and gained over 2 percentage points of market share in 3Q 2023.
• North America, Asia Pacific (excluding China), Europe, and the Middle East and Africa (EMEA) were the fastest-growing regions in 3Q 2023, maintaining double-digit growth rates. Caribbean and Latin American (CALA) revenues grew at a high single-digit rate, while the China market was the only region to decline.
• Product growth was broad-based, but Thermal Management and Power Distribution grew at the fastest rates.
• Looking ahead, we forecast worldwide DCPI market growth to moderate in 2024 as pandemic induced orders are filled. However, we predict the market growth rates will remain at higher than historic levels, as AI deployments increasingly materialize throughout the year.

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Processes vast amounts of complex data for safety-critical applications such as autonomous driving

 Kognic, industry leader in machine learning tools for safety-critical AI, launches The Alignment Platform, a new offering that will allow AI businesses to accelerate their product development and ensure AI systems are trusted and safe.

As AI adoption and development continues to advance, McKinsey’s latest research reveals that models and tools are the biggest challenge for high-performing AI businesses. In the near future, everything that moves will need autonomous solutions, including automotive, heavy manufacturing and robotics industries. Kognic’s AI Alignment Platform fills this critical gap in the market, defining, refining and validating large datasets to train machine learning models.

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For the pioneering builders of AI, who often find the lack of dataset engineering tools to be the most challenging aspect of their work, Kognic provides an efficient and flexible toolset that enables developers to explore, define and refine their datasets.

Daniel Langkilde, CEO and Co-Founder at Kognic commented: “The future of positive, helpful and impactful AI will depend on aligning human and machine intent. As AI continues to develop at a rapid rate, the volume of data AI developers and businesses manage will explode. In order to manage these increasingly complex data models more effectively, our customers need enterprise-grade tools to get the job done.”

At the core of The Alignment Platform™ is Kognic’s industry-leading annotation engine which enables multi-sensor fusion – merging data from sensors such as radar, LiDAR and camera. With intuitive interfaces for visualizing complex sequences, Kognic’s solution speeds AI product teams’ efforts to explore, shape and explain their datasets. The fine-tuning capabilities of the solution provide significant efficiencies that are essential to gaining leverage on improving model performance for perception.

“At Kognic, we are relentless in our pursuit of safety,” said Oscar Petersson, CFO and Co-Founder. “The most common reason AI products and projects fail is because of misaligned expectations. Without human feedback, AI will try to solve the ‘how’ on its own and may make mistakes in the process. That’s why it’s so crucial that we make it as easy as possible to give feedback to AI systems to ensure high-performance and trust. This is vital for safety-critical applications such as robotics and autonomous driving.”

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Daniel Jeffries, Managing Director of the AI Infrastructure Alliance added: “The AI infrastructure landscape is evolving incredibly rapidly. Enterprises are facing increasing pressure to make sure their models and AI systems are safe and reliable. Innovative AI alignment platforms like Kognic will be essential in making sure that the next gen of models closely reflect our values and do what we want them to do much more often.”

Kognic’s composable architecture allows tailored workflows for a wide range of businesses, providing transparency for all stakeholders and enables enterprise orchestration and integration with pre-existing MLOps infrastructure, 3rd-party tools, internal and external annotation workforces, synthetic data generation, et al.

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Study highlights data and ethical implementation among top priorities as administrators look to embrace the promise of AI

A new report released by Ellucian, the leading higher education technology solutions provider, reveals that despite the recognized benefits of Artificial Intelligence (AI), its use in higher education is not as widespread as perceived. The comprehensive survey conducted with 1,140 U.S. higher education administrators from 768 institutions uncovers a significant opportunity, highlighting gaps between the perceived prevalence of AI and the actual reported usage by individuals.

“The findings of our survey highlight the untapped potential of AI in higher education,” said Jeff Dinski, Chief Strategy and Corporate Development Officer, Ellucian. “While there is a clear gap between the perceived and actual use of AI, our data shows that over 70% of respondents view AI favorably. This indicates a promising future for AI in enhancing efficiency, staying abreast with technological advances, and better supporting students and outcomes. At Ellucian, we believe we have a role to play in facilitating this transition, helping institutions navigate the process of adopting and leveraging AI technologies for increased effectiveness.”

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Key Findings:

• 60% of administrators claim their institution uses AI functionality, but less than one third of higher education professionals have experience using AI at work.
• About half of respondents expect that the positive effects of AI will span the student experience, from better supporting the student journey to improving student outcomes at their institution.
• Almost 48% of respondents say they have yet to utilize AI in their personal or professional capacities.
• 30% of staff report “advanced” or “extensive” use of data analytics and data-driven decision-making.
• Main barriers to AI adoption include data security concerns, the need for AI training programs, and ethical implications.
• Institutional Research and Analytics, Admissions and Advising were identified as the three business functions across higher education that could benefit the most from AI integration.
• Less than a third of institutions have initiated conversations about the ethical implications of AI in higher education.

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Blackstraw AI, an enterprise-grade AI solutions provider announced its partnership with Databricks, the Data and AI company and pioneer of the data lakehouse paradigm. Together, Blackstraw and Databricks will focus on helping enterprise customers to optimize their business workflows with AI which will be enabled by a strong foundation of the Databricks Lakehouse Platform.

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Businesses are embracing multi-cloud and hybrid cloud environments. As a result, it has become imperative to modernize their data foundation for seamless operations across different environments and deploy advanced cloud-based technologies – including analytics tools with advanced machine learning (ML) and MLOps capabilities.

As Databricks Consulting Partners, Blackstraw will accelerate AI-driven innovation for clients across industries. Blackstraw’s in-depth knowledge and deep expertise in helping enterprise customers modernize and democratize their Data and AI footprint at scale are valuable for the partnership with Databricks. Databricks’ Lakehouse Platform is cloud-agnostic and enables users to unify their data warehousing and AI use cases on a consistent platform across multiple infrastructures simultaneously.

“We are delighted to enter into a strategic partnership with Databricks,” said Atul Arya, CEO of Blackstraw. “By combining the power of Databricks’ Lakehouse Platform and Blackstraw’s advanced AI/ML capabilities, our teams will empower customers to leverage data-driven MLOps and enable enterprise AI success.”

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The collaboration is set to actively support customers with various data and AI services such as digital transformation strategy, AI innovation roadmap, MLOps, data modernization and migration, data management, security, and governance implementations. Blackstraw’s team of dedicated applied AI Databricks experts will further help customers implement and scale data engineering, collaborative data science, full-lifecycle machine learning, and business analytics initiatives.

“Today, there is a rising need for every business to have a strong foundation of data and AI. By combining the strength of Databricks’ Lakehouse Platform in data engineering, data science, and analytics and Blackstraw’s AI-first digital engineering capabilities, we can help companies transform their businesses through the power of data”, said Kiran Ramesh, Chief Customer Officer of Blackstraw.

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77% of UK small business owners are concerned AI development and adoption is outpacing regulation 

New research from Xero, the global small business platform, has revealed that UK small business owners are concerned that AI development is outpacing regulation and a third (32%) want more training and resources to support AI adoption, as generative AI tools permeate various industries and the workforce. 

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 Xero’s Future Focus AI research surveyed over 500 UK small business owners – and 3000 globally – on what they are thinking, feeling and doing about AI and emerging technologies. It revealed that nearly two-thirds (64%) believe emerging technologies such as AI will have an impact on their business in the next five years. 

 Small businesses are recognising the benefit of AI, with a quarter (24%) planning to experiment with available AI tools in the next 12 months to stay ahead of the curve. But there is some caution and 39% of UK small businesses say data privacy is the biggest ethical challenge to adoption for them.  

 Alex von Schirmeister, EMEA Managing Director at Xero, said, “Our research shows that UK small businesses are recognising the benefits of AI but more knowledge, training, and regulation is needed to ensure the nation’s smallest firms are not left behind and can continue to thrive. Xero’s always looking at how we can bring new technology safely into the hands of customers, in a way that will make a positive difference in their lives. It’s about putting the customer first; not shipping lots of AI features for the sake of it.” 

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 Taking steps to mitigate the risks 

Many small businesses are proactively exploring ways to use AI in their organisations. A quarter (24%) are experimenting with or investing (16%) in new AI tools, 16% are dedicating more resources to AI use, and 14% are working with third party AI experts. But, 46% of UK small businesses aren’t taking any proactive steps – higher than any other region surveyed and the average of 32% globally.   

 While exploring the benefits of AI, mitigating any associated risks is a big concern and focus for businesses. The top actions taken by small businesses to help manage the risks of generative AI tools include providing training to employees on identifying biases or inaccuracies (20%), creating policies and guidelines for employees (18%), and establishing procedures for any AI-related incidents (17%). 

 Despite these concerns, many are trusting AI tools with sensitive data, highlighting a need to support them in assessing security and privacy risks. For example, almost half (49%) of UK small businesses said they trust AI with identifiable customer information, while 40% trust AI with their sensitive commercial information. By being too comfortable with sharing personal identifiable information with AI tools, many small businesses are putting their data at risk. Xero is guided by its responsible data use commitments and strives to support customers navigating data use. 

 New guide for advisors to help small businesses navigate the world of AI 

There is a clear desire for greater education and support, with a third (32%) feeling that training and resources on using AI to increase productivity is necessary for their business. Using AI to increase productivity (35%) and responsible AI practices and the ethical considerations (26%) were also the top knowledge areas that small businesses owners felt were necessary. 

 As accountants and bookkeepers become trusted advisors to small businesses on new technology and how it can be used, Xero has published the Future Focus: AI Guide for Accountants and Bookkeepers to help them navigate the impact of AI on their practices and clients. 

 “We wanted to cut through the hype and answer a really simple question: what does AI mean for your typical practice? The Xero guide is intended to help accountants and bookkeepers make well informed choices when it comes to using AI tools, to help manage the risks and realise the benefits for them and their small business customers,” said von Schirmeister. 

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The enterprise AI adoption wave is driving forward momentum for Arcion, the only real-time, in-memory change data capture (CDC) solution. Arcion replicates enterprise databases using log-based change data capture in real time into cloud lakehouses and data warehouses to power the next generation of AI applications.

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“Arcion’s solution integrated directly with Databricks’ Unity Catalog, had single-digit minutes of latency during peak database load, and was able to process more than 30,000 operations per second with room to grow”

News highlights include:

• New connectors to extract data in real time from cloud warehouses.
• Rapidly growing enterprise adoption of Arcion to serve real-time AI applications.
• New partnerships with Confluent and Redis to further democratize data mobility.
• New funding from Hewlett Packard Enterprise to fuel further development.

“The resulting forward momentum is incredible,” said Arcion CEO Gary Hagmueller. “These latest strides further position Arcion as the unrivaled leader in real-time, large-scale CDC data pipeline technology for the enterprise AI era and beyond, setting up the company for unprecedented growth and development well into the foreseeable future.”

New Product Capabilities

Arcion continues to innovate in its journey to power the next generation of AI and analytics applications with real-time enterprise data from online transaction processing (OLTP) databases like Oracle, SQL Server, DB2, Sybase, MySQL, and Postgres. Arcion’s new connectors for Oracle and MySQL offer 10x more throughput, effectively utilizing the underneath scalable architecture.

Enterprises have started embracing Snowflake to store and manage operational data, and Arcion is proud to announce a first-of-its-kind native connector for Snowflake. Using Arcion’s new Snowflake connector, enterprises can seamlessly replicate data stored in Snowflake to any platform. This is especially exciting to firms that are beginning to use such data to feed the vector databases and large language models (LLMs) that power their customized AI initiatives. Arcion also added online schema change support for all its OLTP connectors, ensuring no pipeline downtime if database schemas are changed.

To deliver real-time pipeline experience for big data, Arcion has made monumental improvements to its Snowflake and Databricks target connectors. The enhancements are taking data pipeline performance to the next level and allowing customers to achieve extreme per-table throughput. Arcion users reported that it now processes more than 30,000 operations per second with room to grow, with single digit minutes of latency during peak database load.

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Expanded Customer Base

As a result of its impressive performance and industry-changing innovation, Arcion is expanding its customer base beyond its projections. For new customer Chegg, the efficiency and reliability Arcion offers for ingesting data from transactional sources into the company’s lakehouse is proving vital for their analytics, data science requirements, and AI initiatives.

“Arcion’s in-memory log-based CDC combines low-latency transactional data with click-stream data, greatly benefiting our business and data customers,” concurred Chegg Director of Engineering Gopinath Rangappa and Senior Manager of Data Engineering Madhuri Prathikantam. “Arcion now plays an important part in our next-gen data platform to ingest near real-time relational data into the Databricks lakehouse and build streaming data analytics pipelines.”

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— Nearly 7 in 10 IT leaders believe AI-enabled technologies will make teams more efficient, but 52% say their organizations don’t yet have needed IT infrastructure —

AMD released the findings from a new survey of global IT leaders¹ which found that 3 in 4 IT leaders are optimistic about the potential benefits of AI — from increased employee efficiency to automated cybersecurity solutions — and more than 2 in 3 are increasing investments in AI technologies. However, while AI presents clear opportunities for organizations to become more productive, efficient, and secure, IT leaders expressed uncertainty on their AI adoption timeliness due to their lack of implementation roadmaps and the overall readiness of their existing hardware and technology stack.

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AMD commissioned the survey of 2,500 IT leaders across the United States, United Kingdom, Germany, France, and Japan to understand how AI technologies are re-shaping the workplace, how IT leaders are planning their AI technology and related Client hardware roadmaps, and what their biggest challenges are for adoption. Despite some hesitations around security and a perception that training the workforce would be burdensome, it became clear that organizations that have already implemented AI solutions are seeing a positive impact and organizations that delay risk being left behind. Of the organizations prioritizing AI deployments, 90% report already seeing increased workplace efficiency.

“There is a benefit to being an early AI adopter,” said Matthew Unangst, senior director, commercial client and workstation, AMD. “IT leaders are seeing the benefits of AI-enabled solutions, but their enterprises need to outline a more focused plan for implementation or risk falling behind. Open software ecosystems, with high-performance hardware, are essential, and AMD believes in a multi-faceted approach of leveraging AI IP across our full portfolio of products to the benefit of our partners and customers.”

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Future of AI-Powered Computing for the Enterprise

To ensure IT leaders have the best computing platform as they implement AI solutions, AMD is focused on developing cutting-edge solutions with AI capabilities across our product portfolio – from the cloud to the edge to endpoints – while working in close collaboration with open industry-standard software.

This year, AMD launched the first AMD Ryzen™ 7040 Series processors with select models featuring a Ryzen™ AI Engine with support for Windows Studio Effects, along with Ryzen AI developer tools – delivering unique experiences not currently available on other x86 processors² and paving the way for greater AI capabilities directly on laptops.

A dedicated AI engine for mobile PCs is complementary to cloud-based AI and essential to the adoption of AI applications in the workplace. It has the potential to:

• Enable more personalized, secure experiences for employees by running AI models locally.
• Enhance the laptop’s power efficiency, which means better employee productivity and connectivity.
• Increase the overall bandwidth for a business to run AI workloads by enabling the laptop to run next generation software.

For businesses that also want to run AI workloads in their on-premise data centers, having up-to-date infrastructure is critical. By upgrading a data center to modern AMD EPYC™ processors, customers could reduce the number of racks needed in their existing infrastructure by up to 70%.³

AMD also recently shared details about its AMD Instinct™ MI300X accelerator (192 GB) based on AMD CDNA™ 3 accelerator architecture, which will be the world’s most advanced accelerator for generative AI,⁴   and will provide the compute and memory efficiency needed for large language model training and inference for generative AI workloads.

To complement the hardware, AMD is bringing an open, ready, and established AI software platform to market through the AMD ROCm™ software ecosystem for data center accelerators.

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