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Ampere accelerates expansion into telecom networking processors - Related to memory, ampere, cargill, plans, keep

Ampere accelerates expansion into telecom networking processors

Ampere accelerates expansion into telecom networking processors

Ampere is accelerating its expansion from Arm-based server processors for AI processing into networking chips for the telecom market.

The business unveiled the ampere Altra Family of processors uniquely suited to address growing market.

Ampere showcased today that it is accelerating its effort to address the telecom market, bringing.

its high-performance, energy-efficient processors to next-generation RAN networks.

With the rapid expansion of 5G, edge computing and AI-driven workloads, the firm mentioned it is seizing a major market opportunity by enabling telecom providers to meet growing performance demands while lowering costs and energy use.

, the global telecom services market size is estimated to reach $[website] billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of [website] from 2025 to 2030.

“Rising spending on the deployment of 5G infrastructures due to the shift in customer inclination toward next-generation technologies and smartphone devices is one of the key factors driving this industry,” Grandview stated.

Ampere noted its processors provide numerous advantages for the telecom market due to their high core density, energy efficiency and scalability, which support the industry’s growing need for high-performance and low power. Low power consumption and efficient thermal design make Ampere-.

based platforms ideal for a variety of edge form factors found in telecom network infrastructure.

They help lower operational costs, a key benefit for telcos managing large-scale deployments across many regions with unpredictable and rising energy costs.

Because of this strong product fit, Ampere is strengthening its presence in the telecom sector to capitalize on this significant market opportunity. The firm views this market as a natural extension of the Cloud Native workloads it already supports today, delivering Ampere’s benefits to the edge and across distributed networks.

Today, Ampere is announcing new trials with global telecom clients as it expands its reach in.

Ampere and Parallel Wireless are collaborating on the deployment of the Parallel Wireless.

GreenRANTM Hardware-Agnostic cloud-native Distributed Unit (DU) stack for 5G SA, 5G NSA,.

4G and 2G, which will be the first stack to commercialize a comprehensive portfolio of.

cellular network technologies on Ampere.

By collaborating with Parallel Wireless—which offers a hardware-agnostic All G (2G/4G/5G NSA/5G SA) solution—Ampere further expands its Open RAN supply chain reach. This partnership combines Ampere’s energy-efficient processors with Parallel Wireless’s GreenRANTM hardware-agnostic DU, enabling operators to support multiple network generations on a single, flexible infrastructure. The result is a high-performing system that significantly reduces power usage and lowers total cost of ownership (TCO).

Netanel Gabizon, Parallel Wireless chief product officer, noted in a statement, “This collaboration will enable the first fully software-based cloud native, carrier-grade, All G solution targeting Ampere platforms. It demonstrates Parallel Wireless’ ongoing commitment to secure, innovative and more energy efficient networks.”.

Advancing existing ecosystem partnerships.

To enable its telecom consumers, Ampere has also broadened the ecosystem of providers and suppliers using or supporting Ampere products. Today, the corporation is announcing multiple advancements through collaboration with a variety of foundational partners in all aspects of the ORAN solution stacks. The collective set of partners are now ready for production deployments throughout the ORAN market within the calendar year 2025.

Supermicro Ampere-based ARS-210ME-FNR short-depth telecom platforms are now in qualification for carrier trials.

“Supermicro’s Ampere Arm-based MegaDC platforms are a state-of-the-art advancement for its cutting-edge power-efficient design for sustainable next generation cloud-native 5G networks,” noted Michael Clegg, VP of 5G/Edge at Supermicro, in a statement. “The ARS-210ME-FNR short-depth telecom platforms are now in qualification for carrier trials and support expansion to the densest massive MIMO metro environments. Supermicro’s expanding portfolio of telecom products are ideally suited for 5G, Telco, and edge solutions for cloud-based open RAN applications including AI.”.

SynaXG, a leading provider of baseband O-RAN software, offers full support for Ampere.

Arm-based vDU solutions in commercial telecom deployments. Its comprehensive suite of.

RAN software and hardware accelerator card adheres to the 3GPP standards, ensuring a.

robust feature set that meets the evolving demands of today’s 4G and 5G networks.

SynaXG vDU products have been fully qualified for production on Ampere Supermicro.

platforms, further solidifying their readiness for large-scale commercial implementation.

“As a leading provider of O-RAN solutions, SynaXG is committed to delivering Ampere best-.

in-class, carrier-grade software, tools, and support to accelerate the implementation of Ampere’s platform,” noted Mantosh Malhotra, chief business officer at SynaXG, in a statement. “Our RAN software, fully compliant with the latest 3GPP standards and O-RAN specifications, ensures optimized network performance and energy efficiency – an ideal match for the Ampere platform and the evolving needs of today’s 5G networks.”.

Fujitsu has now delivered its innovative 5G virtualized network services stack with O-RAN Alliance compliant interfaces for trials beginning in early 2025 based on the low power Ampere platform, cementing their commitment to deliver sustainable virtualized RAN solutions in 2025. Ampere is working with Fujitsu for the first time to enable this stack.

“We are very pleased to announce the availability of our 5G virtualized RAN solution for 5G commercial services based on sustainable, low power Ampere Arm-based infrastructure. Fujitsu’s embrace of open network architecture is central to our ongoing efforts to develop high-quality and secure mobile solutions, contributing to cost effective and sustainable services for our valued global telecommunications end-customers,” noted Masaki Taniguchi, head of the mobile system business unit at Fujitsu, in a statement.

Building on the existing partnership between Ampere Computing and SUSE for the enterprise Linux market, SUSE’s horizontal telco cloud platform has been fully validated for RAN use cases on Ampere-based aarch64 servers from Supermicro.

This joint work also enables Parallel Wireless’ energy-efficient GreenRAN solutions to flexibly manage,.

optimize and process data securely, while significantly reducing total cost of ownership for service operators.

“When we started our partnership with Parallel Wireless, we could build on a fair amount of already existing hardware enablement for Ampere-based hardware platforms due to our established collaboration with Ampere Computing for other industry segments,” stated Tim Irnich, distinguished product manager edge for telco at SUSE, in a statement. “After integrating a couple of additional kernel patches, we saw really good performance and power efficiency for RAN workloads on Ampere CPUs without requiring a lot of performance tuning. The support of Arm-based hardware is a core pillar of SUSE’s telco strategy due to the undeniable advantages in terms of core density and power efficiency, and we are very happy to see our related investments bear fruit.”.

Canonical’s cloud-native software stack runs on Ampere silicon as a fully upstream open-source solution with 12 year LTS, providing secure, low-touch and energy efficient edge clouds for telco networks. Canonical, the publisher of Ubuntu, provides end-to-end solutions for Open RAN and 5G deployments on Arm-based platforms. Canonical’s solutions include bare metal provisioning, systems management, automation tooling, Ubuntu server with real-time kernel, Canonical Kubernetes and AI/ML tooling for AI-RAN operations.

“Canonical is committed to enabling telco innovation with scalable, secure, and optimized solutions on Arm-based platforms,” expressed Ivan Ramos, global head of telco at Canonical, in a statement. “Through our partnership with Ampere, we leverage Ubuntu certified platforms to deliver exceptional performance, reduced TCO, and accelerated time-to-market, enabling seamless deployment of ORAN and 5G infrastructure for next-generation telecom networks.”.

With an expanding ecosystem of partners now delivering Ampere-based products and services, Ampere is capitalizing on the immense opportunities in the telecom market. As telcos evolve to support 5G, Cloud Native networks and AI-driven applications, Ampere’s high-performance, power-efficient solutions offer a strategic advantage. By enabling telecom operators to optimize performance and lower energy and operating costs, Ampere is well-positioned to lead the industry’s transition to more efficient and scalable telecom infrastructure.

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Micron launches new memory chips to keep up with AI processing

Micron launches new memory chips to keep up with AI processing

Micron revealed its first 1y (1-gamma) DDR5 memory chip samples this week, and it says this is part of its contribution to systems that keep up with AI processing.

The organization mentioned being the first to market with 1y samples proves Micron’s continued technology and manufacturing leadership — and the Boise, Idaho-based organization is extending the capabilities of this advanced node to its broader portfolio of dynamic random access memory (DRAM) chips. Those are coming In the second quarter.

Smartphones at Mobile World Congress in Barcelona have AI-powered attributes such as visual search, translation, and intelligent tools to unblur or erase objects in photos.

These innovations show how AI can transform smartphones into intuitive and context-aware tools.

that enhance our daily lives when supercharged with the right memory and storage.

Micron will sample 1y LPDDR5X 16Gb products to select partners for use in 2026 flagship smartphones, enabling industry-leading performance and up to 15% power savings — critical as energy-intensive use cases such as video- and AI-based apps make smartphone battery life more crucial than ever.

At MWC, Micron also revealed mobile storage devices including the world’s first G9-based UFS [website] and UFS [website] mobile storage solutions. The G9 process node enables significant improvements in speed and power efficiency while allowing us to deliver scalable mNAND capacities from 256GB to 1TB at the industry’s highest performance.

These mobile storage solutions are now available in the small and ultra-thin form factors required for slim and foldable smartphone designs.

Micron expressed it partners with smartphone OEMs to engineer differentiated firmware elements that solve their latest pain points and enable smoother, more intuitive experiences for end consumers. Micron’s latest UFS [website] solution delivers proprietary firmware elements for flagship smartphones such as Zoned UFS for read/write efficiency, data defragmentation for 60% faster read speed, pinned WriteBooster for 30% faster random read speed and intelligent latency tracker for advanced debugging.

Most in recent times, Micron collaborated with Samsung on its Galaxy S25 suite of smartphones. These.

smartphones deliver breakthroughs in natural language processing and are designed with Micron’s.

most power-efficient LPDDR5X and advanced UFS [website] solutions. The LPDDR5X improves power.

Samsung’s Galaxy AI suite enhances user interactions with AI-powered aspects like call transcript summaries, message composition, creative tools and Nightography mode for optimized low-light photography.

None of these capabilities would be possible without ample internal storage to house the large amounts of data required for such on-device AI experiences, which is where our high-capacity UFS [website] comes in. This storage solution allows data to be processed quickly by doing so locally rather than in the cloud, in addition to ensuring greater privacy and control of your data.

Micron noted that AI in our smartphones and PCs are already beginning to anticipate our needs, manage our schedules and curate personalized content, enhancing our productivity, creativity and connectivity.

beyond what we could have ever imagined.

New AI innovations such as multimodal agents can now simultaneously interpret and produce insights from various types of data from text, images — opening a whole new world of applications as compared to previous AI agents which were limited to handling one type of data. Another innovation, federated learning, allows AI models to learn from decentralized data insights while maintaining privacy. As these technologies mature, they will enable smartphones to predict our habits and patterns to anticipate our next move and offer suggestions to make life more streamlined.

As we move toward agentic and multimodal AI that autonomously reason, plan and execute complex tasks, a strong hardware foundation is critical. To keep pace with these rising memory and storage needs, Micron is constantly optimizing our roadmap and collaborating with the ecosystem to drive and shape what is possible, from ramping our mobile portfolio on our leading process nodes to exploring new architectures to optimizing memory performance and power for game-changing AI smartphones.

The memory and storage embedded in today’s smartphones play a pivotal role in enabling AI tasks.

and storing people’ critical data, safely and securely on their device. Key factors — such as high.

bandwidth, low latency and power efficiency — are essential for handling demanding AI workloads.

and delivering ultra-smooth user experiences.

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Cargill Plans Major Expansion with 500 New Jobs at Indian GCCs

Cargill Plans Major Expansion with 500 New Jobs at Indian GCCs

Cargill, a family-owned multinational organization, that provides food, ingredients, agricultural solutions and industrial products, has showcased plans to increase its digital and technology workforce in India.

As per reports, the corporation plans to add 500 positions over the next two to three years, increasing its total headcount to 3,500.

The recruitment will focus on tech-based roles in data engineering, analytics, and artificial intelligence, primarily in Bengaluru.

This expansion is separate from Cargill’s global restructuring introduced in December, which included job cuts in sectors like supply chain and inventory controls, Reuters reported. The enterprise aims to reduce its technology outsourcing from 80% to 40% within the same timeframe.

Cargill operates two global capability centres (GCCs) in India. While the one in Bengaluru focuses on technology operations, another in Gurugram handles finance and human resource functions. The corporation collaborates with partners like Tata Consultancy Services (TCS) and Accenture.

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Market Impact Analysis

Market Growth Trend

2018201920202021202220232024
23.1%27.8%29.2%32.4%34.2%35.2%35.6%
23.1%27.8%29.2%32.4%34.2%35.2%35.6% 2018201920202021202220232024

Quarterly Growth Rate

Q1 2024 Q2 2024 Q3 2024 Q4 2024
32.5% 34.8% 36.2% 35.6%
32.5% Q1 34.8% Q2 36.2% Q3 35.6% Q4

Market Segments and Growth Drivers

Segment Market Share Growth Rate
Machine Learning29%38.4%
Computer Vision18%35.7%
Natural Language Processing24%41.5%
Robotics15%22.3%
Other AI Technologies14%31.8%
Machine Learning29.0%Computer Vision18.0%Natural Language Processing24.0%Robotics15.0%Other AI Technologies14.0%

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity:

Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity AI/ML Blockchain VR/AR Cloud Mobile

Competitive Landscape Analysis

Company Market Share
Google AI18.3%
Microsoft AI15.7%
IBM Watson11.2%
Amazon AI9.8%
OpenAI8.4%

Future Outlook and Predictions

The Expansion Ampere Accelerates landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:

Year-by-Year Technology Evolution

Based on current trajectory and expert analyses, we can project the following development timeline:

2024Early adopters begin implementing specialized solutions with measurable results
2025Industry standards emerging to facilitate broader adoption and integration
2026Mainstream adoption begins as technical barriers are addressed
2027Integration with adjacent technologies creates new capabilities
2028Business models transform as capabilities mature
2029Technology becomes embedded in core infrastructure and processes
2030New paradigms emerge as the technology reaches full maturity

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:

Time / Development Stage Adoption / Maturity Innovation Early Adoption Growth Maturity Decline/Legacy Emerging Tech Current Focus Established Tech Mature Solutions (Interactive diagram available in full report)

Innovation Trigger

  • Generative AI for specialized domains
  • Blockchain for supply chain verification

Peak of Inflated Expectations

  • Digital twins for business processes
  • Quantum-resistant cryptography

Trough of Disillusionment

  • Consumer AR/VR applications
  • General-purpose blockchain

Slope of Enlightenment

  • AI-driven analytics
  • Edge computing

Plateau of Productivity

  • Cloud infrastructure
  • Mobile applications

Technology Evolution Timeline

1-2 Years
  • Improved generative models
  • specialized AI applications
3-5 Years
  • AI-human collaboration systems
  • multimodal AI platforms
5+ Years
  • General AI capabilities
  • AI-driven scientific breakthroughs

Expert Perspectives

Leading experts in the ai tech sector provide diverse perspectives on how the landscape will evolve over the coming years:

"The next frontier is AI systems that can reason across modalities and domains with minimal human guidance."

— AI Researcher

"Organizations that develop effective AI governance frameworks will gain competitive advantage."

— Industry Analyst

"The AI talent gap remains a critical barrier to implementation for most enterprises."

— Chief AI Officer

Areas of Expert Consensus

  • Acceleration of Innovation: The pace of technological evolution will continue to increase
  • Practical Integration: Focus will shift from proof-of-concept to operational deployment
  • Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
  • Regulatory Influence: Regulatory frameworks will increasingly shape technology development

Short-Term Outlook (1-2 Years)

In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing ai tech challenges:

  • Improved generative models
  • specialized AI applications
  • enhanced AI ethics frameworks

These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.

Mid-Term Outlook (3-5 Years)

As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:

  • AI-human collaboration systems
  • multimodal AI platforms
  • democratized AI development

This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.

Long-Term Outlook (5+ Years)

Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:

  • General AI capabilities
  • AI-driven scientific breakthroughs
  • new computing paradigms

These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.

Key Risk Factors and Uncertainties

Several critical factors could significantly impact the trajectory of ai tech evolution:

Ethical concerns about AI decision-making
Data privacy regulations
Algorithm bias

Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.

Alternative Future Scenarios

The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:

Optimistic Scenario

Responsible AI driving innovation while minimizing societal disruption

Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.

Probability: 25-30%

Base Case Scenario

Incremental adoption with mixed societal impacts and ongoing ethical challenges

Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.

Probability: 50-60%

Conservative Scenario

Technical and ethical barriers creating significant implementation challenges

Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.

Probability: 15-20%

Scenario Comparison Matrix

FactorOptimisticBase CaseConservative
Implementation TimelineAcceleratedSteadyDelayed
Market AdoptionWidespreadSelectiveLimited
Technology EvolutionRapidProgressiveIncremental
Regulatory EnvironmentSupportiveBalancedRestrictive
Business ImpactTransformativeSignificantModest

Transformational Impact

Redefinition of knowledge work, automation of creative processes. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.

The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.

Implementation Challenges

Ethical concerns, computing resource limitations, talent shortages. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.

Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.

Key Innovations to Watch

Multimodal learning, resource-efficient AI, transparent decision systems. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.

Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.

Technical Glossary

Key technical terms and definitions to help understand the technologies discussed in this article.

Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.

Filter by difficulty:

large language model intermediate

algorithm

platform intermediate

interface Platforms provide standardized environments that reduce development complexity and enable ecosystem growth through shared functionality and integration capabilities.

federated learning intermediate

platform

scalability intermediate

encryption

API beginner

API APIs serve as the connective tissue in modern software architectures, enabling different applications and services to communicate and share data according to defined protocols and data formats.
API concept visualizationHow APIs enable communication between different software systems
Example: Cloud service providers like AWS, Google Cloud, and Azure offer extensive APIs that allow organizations to programmatically provision and manage infrastructure and services.

interface intermediate

cloud computing Well-designed interfaces abstract underlying complexity while providing clearly defined methods for interaction between different system components.