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Taiwanese tech giant Foxconn (officially known as Hon Hai Precision Industry), the world's biggest contract electronics manufacturer, has forecasted that its artificial intelligence (AI) server business will at least double in the second half of this year.

Best known for manufacturing and assembling Apple's iPhone products, Foxconn has recently moved to diversify beyond contract electronics manufacturing assembly by foraying into areas ranging from electric vehicles to semiconductors and servers.

"In 2022 alone, Hon Hai's revenue for servers reached $36 billion to obtain a 40 percent global market share," Chairman Young Liu told an annual shareholders' meeting in Taipei.

"For the second half of this year, we may have a three-digit growth, not two digits... We will continue to boost our market share for servers," Liu said.

In the first quarter, Foxconn's cloud and network products segment, which includes servers, accounted for 22% of revenue, second only to smart consumer electronics - which includes smartphones - at 56%.

AI servers made up about 20 per cent of Foxconn's total server sales last year, Liu said, adding that the company had taken advantage of solutions provided by Intel Corp, Advanced Micro Devices Inc and ARM Ltd to roll out AI servers.

Liu attributed the jump in demand to the rapid rise of generative artificial intelligence systems such as ChatGPT.

The huge surge in demand for AI servers catapulted chip designer Nvidia, albeit briefly, into the $1 trillion valuation club.

Foxconn's latest AI servers also use Nvidia chips.

In 2016, Foxconn and Nvidia formed a partnership to develop servers that offer artificial intelligence capabilities.

Foxconn has been aggressively foraying into semiconductor and EV business amid concern about its reliance on its low-margin business as an Apple supplier.

Foxconn is partnering with Infineon Technologies to develop silicon carbide (SiC) semiconductors, leveraging Infineon's automotive SiC innovations and Foxconn's expertise in automotive systems. Infineon is a world leader in power semiconductors.

It recently started trial production of a third-generation SiC semiconductor for use in electric vehicles for five clients. A 6-inch SiC wafer plant in Hsinchu acquired by it from Macronix International Co in 2021 has begun commercial production.

Foxconn also established a joint venture with Taiwanese electronics component maker Yageo in 2021 to design automotive chips, securing a foothold in front-end chipmaking.

Foxconn has set an ambitious goal of capturing at least a 5 per cent share of the global electric vehicle market by 2025, aiming to generate US$30 billion in EV sales. It will face tough competition from established players like Tesla, Volkswagen and General Motors.

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Foxconn Forecasts Big Surge For AI Server Business As It Gains From Rise Of Generative AI - Swarajya

At its annual Dell Technologies World conference in Las Vegas last week, Dell joined a spate of companies this year in releasing new products that address emerging needs in edge management, secure generative AI development, zero trust security and multicloud workload management. Its no surprise that these are the hottest sectors of enterprise IT products and services sales here in 2023.

New items Dell introduced include the NativeEdge platform; a partnership between itself and Nvidia to build Project Helix, a secure on-premises-based generative AI management package; Project Fort Zero, another new crack at providing an end-to-end zero trust security solution; and updates for its multicloud app-service management platform, Apex.

Dell had only a loosely coordinated edge strategy for a few years until last October when the company previewed a new development called Project Frontier, which was to result in a standalone edge operations software and hardware platform sometime in 2023.

Sometime in 2023 is now here. Project Frontier is now closed, and Dell said its replacement, dubbed NativeEdge, is the industrys only edge operations software platform delivering secure device onboarding at scale, remote management and multicloud application orchestration. Companies such as IBM, AWS, Google, HP, Microsoft, Hitachi, Oracle and several others may dispute the only claim, however. Here is Gartners most recent edge computing market report.

This is the industrys only edge operation platform that mixes up and delivers three things in parallel: secure device onboarding at scale; remote management of devices in those locations; and multicloud application orchestration to edge devices from data centers to make sure that the edge outcome end-to-end is deployed in the lifecycle, Dell SVP of Edge Solutions Gil Schneorson told reporters.

Edge operations, which make use of automated processes, are generally found in locations ranging from manufacturing floors and retail stores to remote wind turbines and long-distance hospital operating rooms.

Use cases for edge computing are growing because more organizations want to manage and secure data at the source but often have limited IT support to do it.

For example, a large manufacturer may need to automate packaging and shipping across its numerous factory sites in various geographies. This means connecting multiple technologies, such as IoT, streaming data and machine vision, which requires dedicated devices to run multiple software applications across locations. Testing and deploying infrastructure to run the applications can take months. With NativeEdge, the manufacturer can consolidate its technology stacks using existing investments and reduce the time to deploy edge assets and applications from months to weeks, Schneorson said. The platform uses automation to streamline edge operations and helps the manufacturer securely roll out new applications to all sites from a central location.

NativeEdge is designed to run any enterprise edge use case with automated deployment, Schneorson said, integrating with various Dell data center hardware nodes. NativeEdge includes built-in zero trust internal use-confidential capabilities, Schneorson said.

The NativeEdge software platform will be available in 50 countries beginning in August, the company said.

Everybody needs easier when it comes to incorporating generative AI into an enterprise system, no matter where its use is being considered. Pre-built AI data models are one major step in that direction.

Dell and Nvidia revealed that Project Helix will result in a series of full-stack solutions with technical expertise and prebuilt tools based on their own infrastructure and software. This includes a complete blueprint to help enterprises use their proprietary data and more easily deploy generative AI responsibly and accurately, Dell said.

Project Helix gives enterprises purpose-built AI models to more quickly and securely gain value from the immense amounts of data underused today, Jeff Clarke, Dell Technologies vice chairman and co-chief operating officer, said in a media advisory. With highly scalable and efficient infrastructure, enterprises can create a new wave of generative AI solutions that can reinvent their industries.

Blueprints for on-premises generative AI Project Helix will support the complete generative AI lifecycle, from infrastructure provisioning, modeling, training, fine-tuning, application development and deployment, to deploying inference and streamlining results, Dell said. The validated designs will use Dell PowerEdge servers, such as the PowerEdge XE9680 and PowerEdge R760xa, which are optimized to deliver performance for generative AI training and AI inferencing, the company said. They will combine with Nvidia H100 Tensor Core GPUs and networking to form the infrastructure backbone for these workloads.

Dell did not indicate whether the Helix models could be run optimally on other brands of servers. Dell Validated Designs based on the Project Helix initiative will be available through traditional channels and Apex flexible consumption options beginning in July.

Dell Apex software, introduced in May 2021, is designed to work across all cloud platforms, public cloud storage software, client devices and computing environments. New additions to the companys multicloud portfolio span data centers to public cloud and client devices include:

Dell, Microsoft, VMware and Red Hat platforms for specific cloud-based use cases:

Dell Apex Cloud Platform for Microsoft Azure features full-stack software integration and automated lifecycle management through Microsoft native management tools. The platform is designed for application modernization and is said to offer faster time to value of Azure based on Azure Arc-enabled infrastructure with consistent operations and governance across on-premises data centers, edge locations, and the Azure public cloud using Azure Arc.

Apex Cloud Platform for Red Hat OpenShift aims to simplify container-based application development and management, wherever applications are developed and deployed, through full stack software integration and automation with Kubernetes. Users can run containers and virtual machines side by side, natively within Kubernetes, for a wide variety of workloads including AI/ML and analytics, with broad GPU support across any hybrid cloud footprint, Dell said.

Apex Cloud Platform for VMware gives users the flexibility to deploy vSphere on a fully integrated system with Dell software-defined storage. It joins Dell Apex Private Cloud and Dell Apex Hybrid Cloud within the broader Dell Apex portfolio to offer more choices for VMware users.

This is still on the drawing and testing boards for the next year until further notice. Project Fort Zero is designed to make zero trust more available for mid-range and smaller enterprises and is engineered to provide a hardened end-to-end zero trust security solution for global organizations to protect against cyberattacks.

Fort Zero is part of an ecosystem of more than 30 technology companies and will result in a validated, advanced maturity zero trust solution within the next 12 months, Dell said. Zero trust is designed for decentralized environments, but integrating it across hundreds of point products from dozens of vendors is complex making it out of reach for most organizations, Herb Kelsey, industry CTO of government projects at Dell, told reporters. Were helping global organizations solve todays security challenges by easing integration and accelerating adoption of Zero Trust.

The fully configured Fort Zero solution will serve a variety of use cases, including on-premises data centers; remote or regional locations such as retail stores where secure, real-time analysis of customer data can deliver a competitive advantage; in the field, where a temporary implementation is needed in places with intermittent connectivity, such as airplanes or vehicles, for operational continuity.

Read more here:
Dell Intros New Edge, Generative AI, Cloud, Zero Trust Prods - The New Stack

When it comes to moving large volumes of data between storage locations, there are two main approaches: data migration and ETL. This article explains the differences and similarities of both methods, how they work, and the best tools on the market for each.

Data migration involves moving data from one system to another, often to upgrade or replace a legacy system. ETLwhich stands for Extract, Transform, and Loadis the process of pulling data from one or more sources, transforming it into a suitable format, and loading it into the target location. The key difference is scale. Data migration is typically used to transfer whole databases while ETL is often used for smaller datasets or parts of a database. Organizations are more likely to use data migration when replacing an outdated system, moving to the cloud, or merging with another company because it allows for better business continuity by moving all of the companys data wholesale.

At a high level, data migration is simply the process of moving a database from one storage system to another. There are several approaches, including transfering the data directly or exporting it externally and then importing it to the new system. The goal of the process is to ensure all data is retained during the move and that it remains consistent with the new systems data format.

One of the biggest challenges of data migration comes when moving it from an outdated system to a new system, which can increase the likelihood of data loss or corruption. Its important to have a migration strategy in place that takes both systems and transfer paths into consideration.

ETL is a migration process that involves extracting data from its sources, transforming it to fit the specific format of the target system, and loading it into the new system. Done in three separate steps, ETL is often used by smaller organizations or when smaller data sets are required for a hyper-specific purpose, such as annual reports or business intelligence.

The first step is data extraction, which can be done using a variety of methods from querying a database to directly reading a file. Once the data has been extracted, it may or may not need to go through a format transformation process using a series of rules and algorithms. Finally, the transformed data is imported, or loaded, into the target system.

ETLs advantage is that it allows the transfer of only specific data rather than an entire database, which can save time and resources and reduce the risk of error and inconsistencies. But the process tends to require more manual intervention than data migration and it can interrupt business continuity at times.

There are a number of tools available for data migration and ETL, each with its own strengths and weaknesseshere are a few of the most popular.

Microsoft SQL Server Migration Assistant simplifies the process of migrating data from to SQL servers. It supports a variety of database sources, such as Oracle, MySQL, and Access, as well as many data formats, including JSON, hierarchical data, spatial data, and XML data.

Kettle is Pentahos free, open-source data migration tool capable of performing ETL processes, data cleaning, and data synchronization tasks. It supports various data formats, including XML data, CSV, and JASON, and can extract data from sources ranging from SQL and NoSQL databases to APIs, applications, and web services.

Informatica PowerCenter is a comprehensive data integration solution that combines a wide range of proprietary and open-source data integration strategies and solutions. It enables companies to export, transform, and load data from a variety of sources, but its best used for real-time integration.

AWS Database Migration Service (DMS) is a cloud-based solution that facilitates the movement of data from old systems to the AWS cloud. It supports a variety of database sources, including Oracle, SQL Servers, MySQL, and PostgreSQL. Also, as a fully-managed service, it ensures minimal downtime and continuous replication as well as automation of scalable features.

Talend Open Studio is a free and open-source data integration tool that combines various data and application integration services, such as ETL, data quality, data profiling, and MDM (Master Data Management). It supports a wide range of data formats and can be used for batch and real-time data migration and integration.

Quest Migration Manager is a data migration and consolidation solution that facilitates and automates the process of moving data for active directories. Its best used for the migration and restructuring of user accounts, data, and systems with a minimal impact on business continuity.

While data migration and ETL may seem identical at first glance, there are a number of differences between the two approaches that better suit them for different tasks. Data migration is a good fit for moving entire databases, while ETL works best for limited or specific data sets. Choosing the right method depends on the volume of the data, the type of migration, and whether the data needs to be reformatted for the new database.

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Data Migration vs. ETL: What's the Difference? - Datamation