Creative Optimization empowers marketing teams to drive significant results with optimized creative decisions and precise ad campaigns

AppsFlyer, the global leader in marketing measurement, attribution, and data analytics, launched Creative Optimization, its new product that provides marketers with unparalleled insights into their creative assets and data-driven guidance on maximizing their impact. Coupled with Artificial Intelligence (AI), Creative Optimization identifies patterns, trends, and features that drive optimal audience engagement, enabling marketers to capture the most value from their ad spend while enhancing the effectiveness of their creative content and campaigns.

Creative Optimization empowers stakeholders across performance marketing, creative, and Business Intelligence (BI) teams to collaborate to craft diverse asset variations, test, and validate winning variables within advertisements – saving time and resources while elevating performance. Marketing teams now possess the tools to make creative decisions that marry human intuition with the precision, speed, and scalability of the AI capabilities embedded within the product.

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“The new Creative Optimization product presents a real breakthrough for marketers, bridging the gap between creative and growth marketing teams while addressing key pain points to drive success for both,” said Yevgeny Peres, EVP of Product Strategy at AppsFlyer. “By delivering sophisticated, in-depth creative insights, it enables growth marketing teams to optimize spend, increase scale, and drive profitability by automatically identifying which creatives perform best in campaigns. Simultaneously, it equips the creative team with valuable insights on the attributes of winning creatives, empowering them to focus on the most effective elements and allocate their time and resources more efficiently. This seamless collaboration closes the feedback loop, boosts confidence in creative production, reduces risk by minimizing investment in underperforming creatives while scaling the production of winning ones to drive profitability at scale.”

AppsFlyer worked with more than 100 companies, including fintech company Dave and mobile gaming leader Papaya Gaming, through the development and testing of Creative Optimization over the last year. Companies across gaming, fintech, e-commerce, and entertainment industries employed the product to enhance their marketing efforts to great effect. Brands utilizing the product were able to grow their ad spend by as much as 300% while seeing vast improvements in key performance indicators. Campaigns resulted in increases in ad click-through rates of up to 50%, decreases in cost-per-install by as much as 30%, and saw up to 100% uplift in customer retention and revenue metrics.

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“AppsFlyer’s Creative Optimization has been a game-changer for our cross-team creative collaboration efforts,” said Christian Espinoza, Senior Marketing Technology Manager at Dave. “We’ve seen a significant increase in efficiency, and it’s transformed our creative optimization process by providing a deep understanding of what works best on specific channels and allowing us to extract maximum value from our top-performing assets. We’ve seen a major increase in efficiency – what used to take us 8-10 hours a week, we can now effortlessly pull and share reports with the creative team, making data-driven decisions without the need for manual data extraction or platform hopping.”

“Creative Optimization is transformative for our campaigns, allowing our marketing team to reach larger audiences, improve our efficiency and collaboration,” said Dan Hayoun, Performance Group Manager at Papaya Gaming. “This has led to great results and helped turn the creative marketing process into a growth engine across our award-winning portfolio of games. As a leader in the next generation of gaming, we are constantly looking for cutting edge tools that can help us operate on a larger scale, while providing the best options for attracting and retaining players to continue growing our business.”

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Creative Optimization enables users to marry best-in-class AI creative capabilities and AppsFlyer’s analytics-driven dashboards to deliver the most efficient and effective campaigns:

• AI-powered insights for maximizing ad spend and creatives’ effectiveness. Creative Optimization automatically analyzes creative assets, breaking them down into scenes, and provides performance data and guidance for effectively replacing underperforming elements.
• Access granular performance data to uncover the winning formula for your creative strategy. Creative Optimization aggregates all creative performance data in one place, providing an unbiased, comprehensive overview of creative performance, including cost, installs, clicks, and down-funnel metrics like retention, lifetime value and more.
• Turn creative performance into meaningful data for your BI system. Creative Optimization consolidates all creative data, offering a reliable and up-to-date system that incorporates recent changes in the marketing ecosystem. This streamlines the data integration process and ensures a credible and trustworthy source for creative data within the BI system.

[To share your insights with us, please write to sghosh@martechseries.com]

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Partnership Helps Government Agencies Eliminate the Cost and Complexity of Legacy Data Environments

Dremio, the easy and open data lakehouse, and Carahsoft Technology Corp.,The Trusted Government IT Solutions Provider announced a partnership. Under the agreement, Carahsoft will serve as Dremio’s Master Government Aggregator, making the company’s complete cloud and software portfolio for Government, Defense, Intelligence and Education available through Carahsoft’s reseller partners and NASA Solutions for Enterprise-Wide Procurement (SEWP) V, Information Technology Enterprise Solutions – Software 2 (ITES-SW2), National Association of State Procurement Officials (NASPO) ValuePoint, National Cooperative Purchasing Alliance (NCPA) and OMNIA Partners contracts.

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This collaboration paves the way for Public Sector organizations to harness cutting-edge data analytics capabilities which empower them to make smarter decisions and significantly enhance operational efficiency through lightning-fast data access. Dremio propels agencies into the future by embracing a state-of-the-art data lakehouse architecture in Public Sector organizations. By transitioning to Dremio’s solutions, organizations can enjoy sub-second query performance and a remarkable 10-fold improvement in price performance. The new environment eliminates costly and complex legacy data lake solutions and implements a flexible, highly modern architecture.

Dremio provides cost-effective self-service analytics and data management, simplifying data pipelines and ETL complexity while accelerating insights across diverse storage locations. With a proven track record of modernizing legacy Hadoop environments and implementing the modern data lakehouse solution, Dremio and Carahsoft aim to transform Public Sector data management by breaking down data silos. Embracing a data mesh concept enables efficient handling of various data sources, fostering cross- collaboration and decentralized data control. Dremio’s expertise supports Public Sector agencies in implementing these principles, eradicating data silos for a more collaborative and efficient approach to data analytics.

“Public sector organizations face a range of data infrastructure challenges, many of which are common to both Government and non-government entities. These issues often hinder effective data management, analysis, and decision-making,” said Roger Frey, Vice President of Alliances at Dremio. “Dremio’s mission is to make data easily accessible and analyzable for all users, regardless of where it resides. We are excited to partner with Carahsoft to bring our state-of-the-art data analytics solutions to the Public Sector.”

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“Within the Public Sector’s intricate data landscape, complexities often impede efficient data management and decision making,” said Laura Howton, Sales Director who leads the Analytics and Data Management Team at Carahsoft. “By adding Dremio to our AI and Machine Learning portfolio, our reseller partners can now provide modern, cost-effective and easily accessible data analytics tools to Government customers, bolstering their modernization efforts.”

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 [To share your insights with us, please write to sghosh@martechseries.com] 

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Hi, welcome to the AiThority Interview Series. Please tell us a bit about yourself and your company, RelationalAI.

I am the founder and CEO of RelationalAI. I have three decades of AI experience and I often share insights on the rise of the data cloud, knowledge graphs, generative AI and other new-gen technologies. My company brings together decades of experience in industry, technology, and product development to advance the first and only real cloud-native knowledge graph data management system to power the next generation of intelligent data applications.

How do you see the Data Cloud industry shaping in 2024?

In 2024, we will witness the rise of the Data Cloud to advance AI and analytics.

While data clouds are not new, I believe there will be a continued emergence and a clear distinction made between data clouds and compute clouds in 2024. With compute clouds like AWS or Azure, we have had to assemble and stitch together all the components needed to work with AI. So with data clouds, like Snowflake or Microsoft Fabric, users have it all prepackaged together in a single platform, making it much easier to run analytics on data needed to build AI systems. The rise of the data clouds will offer a better starting point for data analytics, Artificial Intelligence (AI), and Machine Learning (ML).

2023 was all about Generative AI and its impact on the Cloud computing platforms. Where is GenAI headed in 2024?

The extreme hype around Generative AI will diminish in 2024. True Generative AI deployments will emerge as its augmented replacement.

In the new year, we will also begin to see the extreme over-hype around generative AI start to diminish. I’ve been working in, and around, AI since the early nineties, AI has always been prone to be over-hyped. Having said that, I think we are going to see enterprises deploying generative AI in more measured and meaningful ways. As with most new technology adoption in the enterprise, it’s going to take longer for these kinds of AI systems to become part of enterprise software in the ERP or HCM sense, but real value will start to be created next year.  We will be able to calibrate our expectations appropriately once we begin to see its true impact.

Please tell us about your predictions about AI startups and the VC landscape.

The venture capital climate has been tough as of late and will be even more so in 2024. I believe we will begin to see a shift in the industry when it comes to the survival of AI startups, as AI startups start to get “acqui-hired” by the big tech companies for their talent. This has already started to happen and in the last few months we’ve seen higher than normal venture-funded companies big and small either shut down or quietly get acquired by bigger players.

I think there will be an evolutionary cycle for the companies that can survive the next 18 months or so. It has been said before that some of the best and most valuable companies are usually created in difficult times, like during the 2008 recession and in 2000 when the dot-com bubble burst, as they usually tend to have better products and more disciplined companies. Companies that can run efficiently, be agile, and adapt quickly to tough situations will be better positioned. At the end of the day, companies that have a strong product, and a demonstrated value proposition, will be in a better position to outrun the competition.

How should IT leaders approach Knowledge Graph solutions? 

Knowledge Graphs will help users eliminate “Data Silos.”

As enterprises continue to move more data into a data cloud, they are collecting hundreds, thousands, and sometimes even tens of thousands, of data silos in their clouds. Knowledge graphs can easily drive language models to navigate all of the data silos present by leveraging the relationships between various data sources. In the new year, we will see a variety of established and novel AI techniques that support the development of intelligent applications emerge.

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Thank you, Molham! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

• About Molham
• About RelationalAI

About Molham

Molham is the Chief Executive Officer of RelationalAI. He has more than 30 years of experience in leading organizations that develop and implement high-value machine learning and artificial intelligence solutions across various industries. Prior to RelationalAI he was CEO of LogicBlox and Predictix (now Infor), CEO of Optimi (now Ericsson), and co-founder of Brickstream (now FLIR). Molham also held senior leadership positions at HNC Software (now FICO) and Retek (now Oracle).

About RelationalAI

The executive team at RelationalAI brings together decades of experience in industry, technology, and product development to advance the first and only real cloud-native knowledge graph data management system to power the next generation of intelligent data applications.

The post AiThority Interview with Molham Aref, Founder and CEO of RelationalAI appeared first on AiThority.

SnapLogic Chief Scientist Greg Benson reveals his predictions on Generative AI, and the challenges and opportunities it presents in 2024.

Prediction 1 – GenAI won’t take your job, but it might change it.

In 2024, Generative AI won’t lead to mass job displacements and redundancies, as many early sensationalist reports might have suggested. GenAI won’t completely replace experts in any field, as although models have access to an insurmountable amount of information, users still have to articulate concepts well enough to get the right answers – thus, expertise and human input and, more importantly, human review always will be necessary.

Collaboration with GenAI is a trend we can expect to continue in 2024, as businesses look to capitalize even further on its benefits, reaping the rewards of increased productivity and quality of content creation. This means adopting even more GenAI tools and encouraging even more use of them; the goal being not to replace workers, but instead assist what they do.

Prediction 2 – Now that we’ve invented GenAI, the next step is understanding it.

Next year, we can expect to see businesses attempt to improve the consistency of output from Generative AI. Currently, there is no set rule book for achieving great results with GenAI; there are tips and tricks you can deploy for better or faster results, of course, but overall the process is largely trial and error.

Interacting with GenAI in its current iteration is like a science experiment – you come up with a hypothesis and continue to test different manners of prompts until it produces the result you’re looking for. In the future, the focus of experimentation will be on figuring out how we evaluate the responses it gives us and using that data to inform prompts further.

Companies that want to apply GenAI to their products will need to think about how they carry forward and evolve prompts that can improve results directly. Qualitative and quantitative improvements can only be brought about by reevaluating their approach to AI application and development.

Prediction 3 –Expect an onslaught of GenAI tools and GenAI startups.

In 2024, we’re going to see another year of the AI market expanding, with more variety as GenAI startups try to find their niche among the masses.

Rather than consolidation, more GenAI solutions will continue to pop up in different industries. Of course, there will be a lot of attempts that don’t get traction, or just don’t work, but this won’t deter the wave of opportunistic entrepreneurs and businesses who look to capitalize on the GenAI wave.

There’s already the start of a huge race on the hardware side too: companies such as Google and AWS are building their own AI hardware in addition to NVIDIA, which is worth watching. If successful, these advances in hardware could lead to another explosion in how large language models are trained, as currently, it takes a lot of human input, money, and effort to build from the ground up.

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Prediction 4 – GenAI regulation is essential to adoption.

Regulating GenAI will be a huge focus for governing bodies and business leaders in 2024. Earlier this year, calls were heard for a pause in AI development from numerous visionaries, but this isn’t realistic as the fundamental technology is increasingly available through open-source models available on Hugging Face. Rather than focusing on halting development, creating clear regulations, guidelines and best-use practices will be necessary to ensure partnership with AI will move forward safely and securely.

Like any other technology, defining the boundaries that keep safety in mind will allow for leveraging the benefits without sacrificing progress. We can liken this to all manners of tools and equipment that need to be regulated; for example, we don’t stop ourselves from building cars that go fast, but we do put speed limits in place to ensure safety. Internationally, governments will draw their attention first to the areas of regulation that present the greatest impact on citizens, including frontier AI.

From an industry perspective, the GenAI applications and most helpful cases will emerge as front runners for wider business use cases. Understanding the risks, challenges, and security issues potentially imposed by these tools will be vital for businesses to understand exactly when and how these tools need to be regulated internally.

Likewise, companies hoping to leverage GenAI will have to communicate to customers exactly how it’s used and how it complies with current and future regulation requirements.

Prediction 5 – GenAI and Legacy technology: Why the key to modernization may reside in GenAI tools.

After a year of GenAI practice, legacy businesses are starting to understand that GenAI interest is not just driven by ‘hype’, and instead could be truly transformative for their sector. Therefore, in 2024, we can expect even more traditional businesses to deploy the technology to help evolve legacy systems and modernize their technology stack.

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Typically, traditional companies are not amenable to change or agile enough to adopt the latest in new technology. Many companies are tied to legacy software due to a combination of outdated procurement processes, familiarity, or concerns about data loss or disruption, making modernization inaccessible. The key here is that GenAI can assist with migrating off old code bases and technology stacks to modern programming languages and platforms.

However, GenAI could bridge this gap by allowing companies previously locked into legacy systems to access a more modern workforce’s knowledge and work practices. GenAI also makes some modern tools far more user-friendly, and therefore more likely to be deployed across businesses.

Prediction 6 – AI and the question of originality

Next year we’ll see the average person become more adept at using AI, both in business and in their personal lives. Students will also interact with GenAI at a greater scale.

On the one hand, ChatGPT and others can be great personal tutors to help students understand concepts. On the other hand, ChatGPT can be used to generate solutions to problems. I tell my students that they can use GenAI to help them as they are learning, but they must turn in their own original work. The problem is that it is extremely tempting to have GenAI provide the answers, perhaps just partially. In addition, since the answers are coming from a computer program and not another student, it distances students from the notion they are cheating. So far, for my classes in computer systems, it has been fairly easy to determine if a student has turned in GenAI solutions because they don’t follow the conventions in code that I’ve taught in class and require in student solutions.

How GenAI is used in classrooms is very much a work in progress. At the moment there’s still no best practice model – even at my University, we have workshops about AI, but no succinct policy. Beyond the classroom, there is the larger question of intellectual property and how GenAI is trained on internet-accessible creations and works available in digital form. We will see this play out in all industries and the courts in 2024.

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Prediction 7 – Universities will begin to teach prompt engineering

In 2024, universities will teach prompt engineering as a minor field of study and through certificate programs. Prompt engineering for GenAI is a skill already augmenting domain experts, similar to how computing has augmented other domains. The successful use of large language models (LLMs) relies heavily on giving the models the right prompts. When looking to fill the role of a prompt engineer, the task becomes finding a domain expert who can formulate a question with examples in a specific domain, a skill critical for today’s IT

professionals to refine to successfully implement LLMs. Given this, universities will introduce new academic focus areas to address the growing demand for professionals with specific skills required to build the next generation of GenAI applications.

Currently, SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrate faster and easier.

Whether you are automating business processes, democratizing data, or delivering digital products and services, SnapLogic enables you to simplify your technology stack and take your enterprise further. Thousands of enterprises around the globe rely on SnapLogic to integrate, automate, and orchestrate the flow of data across their business.

[To share your insights with us, please write to sghosh@martechseries.com]

The post SnapLogic Chief Scientist Reveals GenAI Predictions for 2024 appeared first on AiThority.

RoboSense, a leading innovator in LiDAR technology, is set to unveil the newest in its M Platform line of sensors at CES 2024. Join the company’s executives and experts at the Las Vegas Convention Center, West Hall, Booth #5172 for an exclusive look at how RoboSense’s cutting-edge perception solutions are enabling advanced autonomy in vehicles and robots.

Here is a peek into what visitors will experience at the RoboSense booth:

Cutting-edge solid-state LiDAR

• Witness the newest product innovation in the M Platform line of sensors, designed to meet the level 3 autonomous driving demands of OEM and Tier 1 customers globally.
• The M1 is the world’s first automotive-grade solid-state LiDAR sensor in mass production. Both the M1 and the M1 Plus are deployed by OEMs globally for advanced driver assistance (ADAS) and autonomy. These sensors are tailored for customers to enable enhanced safety features and deliver more intelligent vehicles.
• The E1, developed with RoboSense’s proprietary chip technology, provides superior blind spot detection to enhance navigation capabilities and advance safety in vehicles and robots.

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Mechanical LiDAR innovations

• The Ruby Plus is an upgraded 128-beam sensor designed for level 4 autonomous vehicle commercial operations.
• The BPearl, with a unique ultra-wide field, delivers precise short-range blind spot detection.
• The versatile Helios series, including 16- and 32-beam lidar sensors, is customized to meet a broad range of customer applications, including robotics, intelligent vehicles and V2X.

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Advanced software solutions

• HyperVison is a full-stack system that combines RoboSense sensors and software to deliver comprehensive data analytics for critical decision-making, enabling customers’ development of better, safer solutions.

Partner demos and exhibitions:

• RoboSense will display various vehicle replicas from its 21 OEM and Tier 1 customers, showcasing several of its 62 design wins and 22 vehicle integrations that have achieved SOP by November 2023.
• Unitree and BOWE will host live demonstrations of their latest robotic technologies, including the Unitree B2 Quadruped Robot Dog and the BOWE Tugbot.
• Partners including AMD and TIER IV will feature RoboSense in their booths to show how RoboSense’s solutions are an integral part of their systems.

We cordially invite attendees to a welcome happy hour. At this event, RoboSense showcase the latest innovations in their M Platform line of sensors and discuss how its advanced LiDAR solutions are shaping the future of safety and autonomy in the robotics and automotive industries.

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“As the world’s first LiDAR company to achieve mass production of automotive-grade solid state LiDAR, in parallel with remarkable milestones in production and delivery, CES 2024 is the perfect stage to launch the latest cutting-edge solutions in our M Platform,” said Dr. Steven Qui, Robosense’s founder and chief executive officer. “Alongside our key partners, RoboSense is providing attendees an inside look into how we are making LiDAR commercialization a reality.”

[To share your insights with us, please write to sghosh@martechseries.com]

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Supercomputers “Hunter” and “Herder” will power cutting-edge academic and industrial research in computational engineering and the applied sciences

The University of Stuttgart and Hewlett Packard Enterprise have announced an agreement to build two new supercomputers at the High-Performance Computing Center of the University of Stuttgart (HLRS).

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“Supporting cutting-edge science while maximizing energy efficiency is a central concern for everyone at the University of Stuttgart. Hunter and Herder constitute a decisive reaction to the challenges of limiting CO₂ emissions, and Herder will deliver not only dramatically higher computing performance but also excellent energy performance.”

In the first stage, a transitional supercomputer, called Hunter, will begin operation in 2025. This will be followed in 2027 with the installation of Herder, an exascale system that will provide a significant expansion of Germany’s high-performance computing (HPC) capabilities. Hunter and Herder will offer researchers world-class infrastructure for simulation, artificial intelligence (AI), and high-performance data analytics (HPDA) to power cutting-edge academic and industrial research in computational engineering and the applied sciences.

The total combined cost for Hunter and Herder is €115 million. Funding will be provided through the Gauss Centre for Supercomputing (GCS), the alliance of Germany’s three national supercomputing centers. Half of this funding will be provided by the German Federal Ministry of Education and Research (BMBF), and the second half by the State of Baden-Württemberg’s Ministry of Science, Research, and Arts.

Hunter to Herder: a two-step climb to exascale

Hunter will replace HLRS’s current flagship supercomputer, Hawk. It is conceived as a stepping stone to enable HLRS’s user community to transition to the massively parallel, GPU-accelerated structure of Herder.

Hunter will be based on the HPE Cray EX4000 supercomputer, which is designed to deliver exascale performance to support large-scale workloads across modeling, simulation, AI, and HPDA. Each of the 136 HPE Cray EX4000 nodes will be equipped with four HPE Slingshot high-performance interconnects. Hunter will also leverage the next generation of Cray ClusterStor, a storage system purpose-engineered to meet the demanding input/output requirements of supercomputers, and the HPE Cray Programming Environment, which offers programmers a comprehensive set of tools for developing, porting, debugging, and tuning applications.

Hunter will raise HLRS’s peak performance to 39 petaFLOPS (39*10¹⁵ floating point operations per second), an increase from the 26 petaFLOPS possible with its current supercomputer, Hawk. More importantly, it will transition away from Hawk’s emphasis on CPU processors to make greater use of more energy-efficient GPUs.

Hunter will be based on the AMD Instinct™ MI300A accelerated processing unit (APU), which combines CPU and GPU processors and high-bandwidth memory into a single package. By reducing the physical distance between different types of processors and creating unified memory, the APU enables fast data transfer speeds, impressive HPC performance, easy programmability and great energy efficiency. This will slash the energy required to operate Hunter in comparison to Hawk by approximately 80% at peak performance.

Herder will be designed as an exascale system capable of speeds on the order of one quintillion (10¹⁸) FLOPS, a major leap in power that will open exciting new opportunities for key applications run at HLRS. The final configuration, based on accelerator chips, will be determined by the end of 2025.

The combination of CPUs and accelerators in Hunter and Herder will require that current users of HLRS’s supercomputer adapt existing code to run efficiently. For this reason, HPE will collaborate with HLRS to support its user community in adapting software to harness the full performance of the new systems.

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Supporting scientific excellence in Stuttgart, Germany, and beyond

HLRS’s leap to exascale is part of the Gauss Centre for Supercomputing’s national strategy for the continuing development of the three GCS centers: The upcoming JUPITER supercomputer at the Jülich Supercomputing Centre will be designed for maximum performance and will be the first exascale system in Europe in 2025, while the Leibniz Supercomputing Centre is planning a system for widescale usage in 2026. The focus of HLRS’s Hunter and Herder supercomputers will be on computational engineering and industrial applications. Together, these systems will be designed to ensure that GCS provides optimized resources of the highest performance class for the entire spectrum of cutting-edge computational research in Germany.

For researchers in Stuttgart, Hunter and Herder will open many new opportunities for research across a wide range of applications in engineering and the applied sciences. For example, they will enable the design of more fuel-efficient vehicles, more productive wind turbines, and new materials for electronics and other applications. New AI capabilities will open new opportunities for manufacturing and offer innovative approaches for making large-scale simulations faster and more energy efficient. The systems will also support research to address global challenges like climate change, and could offer data analytics resources that help public administration to prepare for and manage crisis situations. In addition, Hunter and Herder will be state-of-the-art computing resources for Baden-Württemberg’s high-tech engineering community, including the small and medium-sized enterprises that form the backbone of the regional economy.

Statements

Mario Brandenburg (Parliamentary State Secretary, Federal Ministry for Education and Research, BMBF)

“Funded by the BMBF and the State of Baden-Württemberg, the expansion of the computing infrastructure of the Gauss Centre for Supercomputing at its Stuttgart location is an important step on the road to more computing power for Germany’s research and innovation landscape. The unique concept behind the computing architecture at HLRS will ensure that not just science but also industry, SMEs, and start-ups will have first-class conditions for developing new innovations. This expansion also means increased computing capacity for the development of AI and a strengthening of Germany’s AI infrastructure, in accordance with the federal research ministry’s AI action plan.“

Petra Olschowski (Baden-Württemberg Minister of Science, Research, and Arts)

“High-performance computing means rapid development. As the peak performance of supercomputers grows, they are as crucial for cutting-edge science as for innovative products and processes in key industrial sectors. Baden-Württemberg is both a European leader and internationally competitive in the fields of supercomputing and artificial intelligence. As part of the University of Stuttgart, HLRS thus has a key role to play — it is not just the impressive performance of the supercomputer but also the methodological knowledge that the center has assembled that helps our cutting-edge computational research to achieve breathtaking results, for example in climate protection or for more environmentally sustainable mobility.“

Prof. Dr. Wolfram Ressel (Rector, University of Stuttgart)

“With Hunter and Herder, the University of Stuttgart continues its commitment to high-performance computing as the foundation of its successful excellence strategy. This expansion will especially strengthen Stuttgart’s leading position in research using computer simulation and artificial intelligence.”

Anna Steiger (Chancellor, University of Stuttgart)

“Supporting cutting-edge science while maximizing energy efficiency is a central concern for everyone at the University of Stuttgart. Hunter and Herder constitute a decisive reaction to the challenges of limiting CO₂ emissions, and Herder will deliver not only dramatically higher computing performance but also excellent energy performance.”

Prof. Dr. Michael Resch (Director, High-Performance Computing Center Stuttgart)

“HPE has been a reliable partner since 2019, and we are excited to be making the jump with them to the next order of magnitude in computing performance, the exaFLOP. Using GPU technology from AMD, we are also confident that we will be well prepared for the challenges of the future.”

Justin Hotard (Executive Vice President and General Manager, HPC, AI & Labs, Hewlett Packard Enterprise)

“HLRS has demonstrated the power of supercomputing in research and applied science, and we are honored to have been with them on this journey. We look forward to building on our collaboration to pave the way to exascale for HLRS using the HPE Cray EX supercomputer. The new system will enable scientific and technological innovation to accelerate economic growth.”

Mario Silveira (Corporate Vice President OEM Sales, AMD)

”AMD is pleased to expand our collaboration with HLRS in Stuttgart and HPE. We are providing our cutting-edge AMD Instinct™ MI300A datacenter accelerator to the Hunter project, aiming to enhance performance, efficiency, and data transfer speeds. This initiative will establish a state-of-the-art infrastructure tailored for research, AI workloads, and simulations. Anticipated for arrival by 2025, Hunter aligns with HLRS’s ambitious exascale plans for Germany, showcasing our commitment to advancing technological capabilities and fostering innovation together with our partners in the years to come.”

Dr. Bastian Koller (General Manager, HLRS)

“Increasingly it’s not just faster hardware but optimal usage of the system that is the greatest performance factor in simulation and artificial intelligence. We are particularly excited that we have found a globally leading partner for these topics in Hewlett Packard Enterprise, who together with AMD will open up new horizons of performance for our clients.”

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RaceTrac deploys HPE ProLiant servers in every store to transform technology environment and optimize workloads across self-service gas pumps, in-store checkout, inventory management, and employee resources

Hewlett Packard Enterprise announced a collaboration with RaceTrac, a company that operates a chain of gasoline service stations and convenience stores across the southern United States.

HPE supports RaceTrac’s digital transformation to modernize and deliver a consistent experience for its customers across its 800+ stores. The two organizations work together closely to achieve RaceTrac’s business goals with HPE compute at the foundation. HPE ProLiant servers were implemented in every store to deliver reliability, industry-leading security, and optimized performance for a range of applications.

RaceTrac also relies on HPE Alletra Storage, a cloud-native data infrastructure, to improve ease of use and increase operational efficiency. The upgrade boosts RaceTrac’s storage capacity and simplifies its data management.

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“HPE compute and storage solutions provide retailers a unique foundation to fuel seamless customer experiences and optimized operations,” said Neil MacDonald, executive vice president and general manager, Compute, at HPE. “RaceTrac is a powerful example of a retail organization embracing data-first modernization to power new applications and drive better business outcomes. We had the pleasure of teaming up with RaceTrac to support them on this journey to unlock greater value for their customers and boost competitiveness.”

RaceTrac improves daily operations and future-proofs business with new compute environment

RaceTrac’s new compute environment supports workloads that are critical to enhancing the customer experience, including self-pumping gas stations, credit card and payment processing, and a customer loyalty platform.

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RaceTrac will also apply HPE compute and storage technology to improve overall store management programs such as camera surveillance, employee digital timecards to clock-in and clock-out, daily accounting summaries, staff scheduling, and inventory order placements.

“The average time spent by a RaceTrac customer is approximately two and a half minutes, and our goal is to offer a frictionless experience during every visit,” said Tyler Grubbs, executive director, Store Systems and Technologies, at RaceTrac. “We chose HPE because they entered the trenches with our IT team to understand our needs and how to support our organization’s mission. In addition to making our customers’ experience simpler and more enjoyable, the new compute environment will enable us with capabilities to harness the power of data to make better business decisions.”

HPE and RaceTrac are also exploring future use cases to improve other areas such as increasing fraud prevention and detection with video surveillance and analytics, and real-time inventory tracking using computer vision.

HPE delivers next-generation compute for the hybrid world with HPE ProLiant Gen11 servers

HPE ProLiant servers support a range of workloads from bare metal and virtualized applications, including VDI, data analytics, AI, and machine learning, to cloud-native, telco vRAN (5G), virtual private cloud, and remote offices or SMBs.

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HPE has built on 30 years of continuous innovation with the new HPE ProLiant Gen11 servers to deliver an intuitive cloud operating experience, trusted security by design, and optimized performance for workloads.

The new HPE ProLiant Gen11 servers are available today to deliver high performance on an organization’s most data-intensive workloads.

[To share your insights with us, please write to sghosh@martechseries.com]

The post RaceTrac Boosts Customer Experience With HPE ProLiant Servers at 800+ Stations appeared first on AiThority.

Embracing Edge AI can be a game-changer for businesses, propelling them toward a future where real-time data processing and decision-making are at the forefront of innovation. Edge AI is a term that refers to the deployment of artificial intelligence (AI) models closer to users and devices, either on-premises — such as in a retail store or bank branch — or on edge computing platforms. With this approach, AI processing occurs near where data is created, on the “edge” of the network, in a decentralized manner, instead of using cloud-based solutions or centralized computing. This results in reduced latency, improved performance, and enhanced privacy and security.

Many industries, including retail, finance, manufacturing, healthcare, automotive, and telecommunications, are investing in Edge AI to increase efficiency in their operations — essentially by providing a large set of automation possibilities — and to improve their customer experiences. Demand for this technology is growing, and the overall state of Edge AI adoption is gaining traction.

According to Gartner, “More than 55% of all data analysis by deep neural networks will occur at the point of capture in an edge system by 2025, up from less than 10% in 2021.” And according to IDC, by “2023 more than 70% of organizations will run varying levels of data processing at the IoT edge.”

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The Benefits of an Edge AI Approach

One of the main benefits of Edge AI over running AI in centralized computing is improved efficiency. By processing data locally rather than sending it to a central server, Edge AI can drastically reduce latency and remove bandwidth constraints, leading to faster decision-making and improved operational efficiency.

This allows for real-time or near-real-time processing of data, a critical feature in many applications, such as autonomous vehicles, manufacturing processes, and healthcare monitoring. This type of processing is also a key advantage when the goal is to improve the customer experience.

Businesses also save on bandwidth and data storage costs by minimizing the need to transmit vast amounts of raw data back to the cloud or a data center; instead, only the relevant preprocessed information is sent.

This is much more scalable and sometimes can enable solutions that otherwise wouldn’t be technically or economically feasible, and it also brings increased resiliency: Edge AI systems can continue to process data even when they lose connectivity, enhancing the reliability of weak communication links and optimizing costs.

Last, but not least, the Edge AI approach can offer enhanced privacy and security: since data is processed locally, Edge AI reduces the risk of data breaches or loss during transmission. This makes it suitable for industries with stringent privacy regulations because sensitive data does not need to leave the premises.

Edge AI in Action

It has been said that “data is the new oil,” which means that any connected source of information is also a juicy target for criminals. AI is increasingly important in these scenarios as the attacks become more advanced.

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Edge AI security measures, like access control, can be delegated to edge nodes, which can run sophisticated AI-based algorithms for inference and behavioral analysis that can detect and stop suspicious activity from cyberattacks — including the feared “zero-day” attacks — before they even enter business networks and cause any harm.

In retail, Edge AI can enable smarter customer experiences, such as personalized recommendations based on real-time in-store behavior, including monitoring self-checkouts to reduce losses or running real-time inventory management. In manufacturing, it can assist in predictive maintenance by processing data from numerous sensors to predict equipment failures and suggest timely maintenance, minimizing downtime.

In healthcare, patient monitoring devices can use Edge AI to process health data in real-time, alert healthcare providers of any immediate risks, and ensure patient privacy by keeping sensitive health data localized. Security systems equipped with Edge AI can process video footage in real-time for facial recognition, anomaly detection, or immediate threat analysis and alerting.

Telecom operators can use Edge AI to optimize network operations by analyzing network traffic in real-time and dynamically managing network resources. Similarly, Edge AI can be used for managing smart power grids, detecting anomalies, and predicting energy demand to optimize power generation and distribution.

Steps for Preparing to Adopt Edge AI

Organizations looking to adopt Edge AI will first need to identify the specific use cases or areas in their business where Edge AI could provide a considerable benefit. This should be followed by an evaluation of the technical requirements since Edge AI involves different technology than traditional cloud-based AI.

The next step is to ensure your team has the necessary skill set or that your organization has a mechanism in place for training. Teams will need to be educated on edge computing, AI model development, and edge node orchestration.

At this stage, a partnership with edge computing providers and companies that provide ready-to-use AI models is all it takes to start collecting results, as your company will be able to leverage an integrated solution and vendor expertise.

Edge AI aligns with strategic growth initiatives, seamlessly integrates with change management practices, and may even catalyze the emergence of groundbreaking business models. The adoption of Edge AI signifies a commitment to staying ahead of the curve, ensuring that your enterprise remains competitive in a rapidly evolving digital landscape.

[To share your insights with us, please write to sghosh@martechseries.com]

The post How Can Businesses Benefit from the Edge AI Boom? appeared first on AiThority.

Airports Council International (ACI) World and Cirium, a global leader in aviation data analytics, begin a landmark collaboration to strengthen the Airport Service Quality (ASQ) program—the world’s leading airport customer experience measurement and benchmarking program.

The ASQ program’s methodology is renowned for its robustness, ensuring the most accurate representation of airport traffic. In recognizing the critical role that flight databases play in the assessment of respondent sampling, Cirium will serve as the reference database for flights supporting the ASQ methodology—solidifying the ASQ program’s commitment to accuracy and reliability. Cirium’s core platform provides details on more than 35 million flights per year and covers 97% of scheduled flights worldwide.

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Compared to other programs in the aviation industry, the ASQ program is based on live research via surveys gathered at the airport—direct from the traveller—rating their satisfaction on the day of travel. It serves as the basis for the annual ASQ Awards which recognize the best airports for customer experience worldwide, as selected by passengers.

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ACI World Director General Luis Felipe de Oliveirasaid: “With close to 400 participating airports in 95 countries, more than half of the world’s travellers pass through an Airport Service Quality (ASQ) airport—highlighting both the relevancy and popularity of the program and airports’ commitment to the passenger experience. Partnering with Cirium, a global leader in aviation data analytics, makes business sense: we are two organizations known for the accuracy of our data and the rigorousness of our methodology and analyses. Leveraging Cirium’s database for flights not only strengthens the operational aspects of the ASQ program, but also establishes a foundation for collaborative growth and innovation within the aviation industry.”

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Cirium CEO Jeremy Bowen said: “Our partnership with ACI World signifies our commitment to providing best-in-class data and analytics to the global aviation industry. The industry already relies on our extensive and trusted schedules data, but the partnership with ACI World will provide even more extensive coverage through the ASQ program and greatly benefit the participating airports and travellers alike.”

[To share your insights with us, please write to sghosh@martechseries.com]

The post ACI World & Cirium: Elevating Airport Service Quality Through Data Collaboration appeared first on AiThority.

IPWAY, a dynamic startup with European roots, announced the launch of its state-of-the-art platform, designed to revolutionize the leasing of IPv4 addresses for proxy services.

The IPWAY platform stands out for its commitment to transparency and ethical sourcing. It provides a vital link between IPv4 suppliers and a wide range of businesses, including those in big data analytics, market research, cybersecurity, and brand copyright protection”, said Flavius Porumb, IPWAY’s CEO.

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This pioneering solution is set to transform how companies access and manage IPv4 resources, thereby enhancing their data collection capabilities for artificial intelligence (AI). The pre-launch phase, initiated on October 20, 2023, marks a significant step towards making AI more accessible. Through its user-friendly platform, IPWAY simplifies the complexities of IP management, enabling organizations to fully leverage AI technologies.

Bengen.com, an early investor in IPWAY with a capital commitment of up to $5 million, “is thrilled to see IPWAY successfully launch their new platform, bridging the gap in IP supply and demand”, said George Berar, CEO of Bengen.com.

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Highlights of the IPWAY Platform:

• Ethical IP Sourcing: IPWAY guarantees the ethical procurement of IPv4 addresses, adhering to the highest standards of responsible IP usage.
• Transparent Operations: The platform facilitates a transparent and reliable process for connecting IP suppliers with businesses.
• Optimized for Large-Scale Scraping: Tailored for efficiency, IPWAY enhances data scraping operations, saving time and resources.
• Support for Multiple Protocols: Accommodating various needs, IPWAY supports HTTP, HTTPS, and SOCKS5 protocols.
• Detailed Usage Analytics: Users receive comprehensive analytics on proxy usage, providing insights for optimal performance and resource management.

IPWAY, or IP Way LLC, is a dynamic startup revolutionizing the leasing of IPv4 addresses for proxy services through its state-of-the-art platform. The platform provides a vital link between IPv4 suppliers and a wide range of businesses.

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[To share your insights with us, please write to sghosh@martechseries.com]

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