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Processing in-Memory AI Chips Market Set to Skyrocket from $231M in 2025 to $44B by 2032 at 112.4% CAGR | Valuates Reports

Published

4 months ago

on

What is the Market Size of Processing in-Memory AI Chips?

BANGALORE, India, April 29, 2026 /PRNewswire/ — The global Processing in-memory AI Chips market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.

 

 

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What are the key factors driving the growth of the Processing in-Memory AI Chips Market?

The processing in-memory AI chips market is expanding due to growing pressures on compute architectures from data movement inefficiency, latency constraints, rising power sensitivity, and deployment cost control across AI workloads.Demand is shifting toward chip designs that minimize the distance between memory and computation, enabling faster inference execution and better throughput under constrained thermal and energy conditions.This trend is especially relevant for workloads where bandwidth pressure, response time, and local processing efficiency directly determine system value.The market benefits from broader interest in architectures supporting both edge and data center AI tasks, without full reliance on conventional processor-memory separation.These factors create a strong commercial foundation for processing in-memory adoption.

Source from Valuates Reports: https://reports.valuates.com/market-reports/QYRE-Auto-15O17238/global-processing-in-memory-ai-chips

TRENDS INFLUENCING THE GROWTH OF THE PROCESSING IN-MEMORY AI CHIPS MARKET:

DRAM-PIM is driving growth in the processing in-memory AI chips market by addressing one of the most persistent bottlenecks in AI computing, which is the heavy cost of transferring data between memory and logic. By embedding compute capability closer to high-capacity memory structures, DRAM-PIM improves efficiency in bandwidth-intensive inference and parallel data handling environments. This makes it highly relevant for larger models and workloads that require sustained access to large datasets with lower latency overhead. Its role in improving throughput while reducing external data shuttling is strengthening its position in advanced AI infrastructure, particularly where performance scaling must happen without proportionate increases in power draw or board-level complexity.

SRAM-PIM is supporting market growth by serving AI use cases that prioritize low latency, fast local access, and power-efficient computation in compact environments. Its architectural suitability for tightly coupled memory and processing enables faster execution of inference tasks where response speed is critical and repeated memory access patterns are concentrated. This makes SRAM-PIM especially attractive in edge AI systems, embedded intelligence platforms, and applications where energy budgets and footprint limitations are decisive purchase factors. As device-side intelligence becomes more valuable across industrial, consumer, and autonomous systems, SRAM-PIM is gaining traction as a practical route to delivering on-chip efficiency without the penalties associated with conventional memory-transfer-heavy architectures.

In-memory processing chips are driving the growth of the processing in-memory AI chips market by creating a more application-aligned hardware approach for modern AI inference. Their appeal lies in improving usable performance per watt, reducing system bottlenecks, and enabling more scalable deployment economics across both small and large computing power environments. These chips are increasingly viewed as a structural response to the limitations of traditional architectures in handling AI workloads efficiently. As buyers seek solutions that can balance throughput, heat, latency, and integration flexibility, in-memory processing chips are moving from niche experimentation toward broader commercial adoption, supporting a market that is increasingly defined by workload efficiency rather than raw compute expansion alone.

A major factor supporting the market is the growing need to reduce the cost of data movement inside AI systems. In conventional architectures, moving data back and forth between memory and processors consumes time, power, and system resources. Processing in-memory chips directly address this problem by bringing computation closer to stored data. This improves execution efficiency and makes the architecture attractive for inference-heavy environments where repetitive data access creates performance drag. As buyers increasingly evaluate compute systems based on usable efficiency rather than nominal processing strength, demand for architectures that minimize data transport overhead continues to strengthen the market.

Power efficiency is emerging as a decisive growth factor for the processing in-memory AI chips market. AI deployment is no longer limited to environments where power availability is secondary. Enterprises, edge operators, and embedded system developers now require hardware that can support meaningful intelligence under tight energy and thermal budgets. Processing in-memory designs improve energy utilization by reducing unnecessary memory access traffic and enabling more efficient task execution. This gives them strong relevance in a market where lower operating cost, thermal manageability, and sustained performance matter as much as raw computational output, especially across continuously running inference systems and distributed AI infrastructure.

The expansion of edge AI is supporting market growth by increasing demand for chips that can perform inference closer to the source of data. Edge systems need fast decision-making, low energy consumption, and compact integration, all of which align well with processing in-memory designs. As intelligence moves into cameras, sensors, industrial devices, and smart endpoints, conventional architectures often face efficiency tradeoffs that reduce suitability in such environments. Processing in-memory chips help overcome these limitations by supporting local computation with lower latency and reduced data transfer dependency. This makes the technology increasingly relevant as edge intelligence shifts from optional capability to essential product differentiation.

The growing complexity of AI inference workloads is creating favorable conditions for processing in-memory adoption. As models become more memory-intensive and inference demand spreads across commercial applications, the limitations of traditional compute-memory separation become harder to ignore. Buyers are looking for architectures that can handle repeated memory access more efficiently and sustain performance under real deployment conditions. Processing in-memory chips respond to this need by improving memory interaction efficiency, which is particularly valuable in workloads where bandwidth and latency determine real-world usefulness. This shift is helping the market as hardware decisions become increasingly shaped by inference practicality rather than theoretical compute scale.

The market is also benefiting from a growing emphasis on cost-per-inference rather than simple peak performance comparisons. Buyers increasingly want AI hardware that can deliver consistent workload execution with better efficiency, lower supporting infrastructure requirements, and more practical deployment economics. Processing in-memory chips are well positioned in this context because they help reduce some of the overhead traditionally associated with memory bottlenecks, energy consumption, and system complexity. Their value proposition becomes stronger when purchasing decisions are based on long-term operating efficiency and scalable deployment. This cost discipline is pushing interest toward architectures that offer more balanced performance across real commercial use cases.

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What are the major product types in the Processing in-memory AI Chips Market?

DRAM-PIMSRAM-PIM

What are the main applications of the Processing in-memory AI Chips Market?

Near-Memory Computing (PNM) ChipIn-Memory Processing (PIM) ChipIn-Memory Computing (CIM) Chip

Key Players in the Processing in-memory AI Chips Market:

MyhticSyntiantD-MatrixHangzhou Zhicun (Witmem) TechnologyBeijing Pingxin TechnologyAistarTekSAMSUNGSK HynixShenzhen Reexen TechnologyGraphcoreAxelera AISuzhou Yizhu Intelligent TechnologyBeijing Houmo TechnologyEnCharge AI

Which region dominates the Processing in-memory AI chips market?

Asia-Pacific remains the most dynamic region due to its deep semiconductor ecosystem, expanding edge device manufacturing base, strong memory technology orientation, and increasing integration of AI into consumer and industrial electronics. China is supporting market formation through locally aligned compute architecture development, while South Korea, Japan, and Taiwan provide supply-side depth through memory and advanced chip ecosystem capabilities. Other regions are adopting more gradually, mainly through selective edge AI and infrastructure modernization use cases.

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What are some related markets to the Processing in-memory ai chips market?

Computing in Memory Technology Market was valued at USD 268 Million in the year 2024 and is projected to reach a revised size of USD 175260 Million by 2031, growing at a CAGR of 154.7% during the forecast period.In-memory Computing Chips for AI market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.HTAP-Enabling In-Memory Computing Technologies MarketIMDG (In-Memory Data Grid) Software Market Research ReportEmbedded Ai Chips Market Research ReportUltra-low Power AI Chips Market Research ReportHigh-Bandwidth Memory Chips Market was valued at USD 3816 Million in the year 2024 and is projected to reach a revised size of USD 139450 Million by 2031, growing at a CAGR of 68.2% during the forecast period.LPDDR Chips Market was valued at USD 6891 Million in the year 2024 and is projected to reach a revised size of USD 10870 Million by 2031, growing at a CAGR of 6.8% during the forecast period.Semiconductor Memory Market was valued at USD 125890 Million in the year 2024 and is projected to reach a revised size of USD 232900 Million by 2031, growing at a CAGR of 9.3% during the forecast period.AI Calculus Chips Market was valued at USD 46520 Million in the year 2024 and is projected to reach a revised size of USD 269300 Million by 2031, growing at a CAGR of 25.1% during the forecast period.Military Chips Market was valued at USD 1168 Million in the year 2024 and is projected to reach a revised size of USD 1583 Million by 2031, growing at a CAGR of 4.5% during the forecast period.

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Technology

East Side Games Group Announces Cost Reduction Initiatives to Strengthen Financial Position

Published

41 minutes ago

on

September 4, 2026

By

VANCOUVER, BC, Sept. 3, 2026 /CNW/ — East Side Games Group Inc. (TSX: EAGR) (“East Side Games” or the “Company”), a leading developer and publisher of free-to-play mobile games, today announced a series of cost reduction and operational restructuring initiatives designed to strengthen its balance sheet, improve free cash flow, and position the Company for sustainable, profitable operations.

Key Highlights

Workforce Reduction: The Company has reduced its workforce by approximately 30 employees, representing approximately 32% of its total headcount, effective September 1st through a combination of layoffs and furloughs. With its streamlined workforce, the Company is positioned to operate more efficiently, in-line with its renewed focus on profitability.Annualized Cost Savings: The workforce reduction, together with related operational efficiencies, is expected to generate approximately $3.5 million in annualized cost savings, with the majority of savings expected to be realized beginning in Q4 2026. This is in addition to the $4M in annualized cost savings implemented year-to-date.Portfolio Rationalization: The Company is reprioritizing its development portfolio, including the pausing or scaling back of certain titles and projects, allowing the Company to concentrate resources on its highest-performing and highest-potential live games.Partner Payment Restructuring: The Company is restructuring payment terms with certain development and publishing partners to better align cash outlays with project performance and cash flow generation.

‘These are necessary decisions. Our objective is to build a leaner, more focused organization that can deliver consistent profitability for our shareholders while continuing to invest in the titles and franchises with the greatest long-term potential,’ said Jason Bailey, CEO of East Side Games Group.

About East Side Games Group Inc.

East Side Games Group Inc. (TSX: EAGR) is a leading developer and publisher of mobile games based in Vancouver, Canada, known for creating immersive experiences built around some of the world’s most beloved entertainment franchises. For more information, visit [www.eastsidegames.com].

Forward-Looking Information

This press release contains “forward-looking information” within the meaning of applicable Canadian securities legislation, including statements regarding expected cost savings, the timing and amount of related charges, the Company’s relationship with RBC, anticipated financial impacts, and future operating and financial performance. Forward-looking information is based on the Company’s current expectations, estimates, and assumptions, and is subject to known and unknown risks, uncertainties, and other factors that may cause actual results to differ materially from those expressed or implied, including but not limited to: the Company’s ability to realize anticipated cost savings on the expected timeline or at all; the outcome of discussions with RBC and the Company’s ability to maintain compliance with, or obtain relief from, its credit facility covenants; the impact of workforce reductions and project cancellations on the Company’s operations, employee morale, and relationships with development partners; general economic and industry conditions; and other risk factors described in the Company’s public disclosure documents filed with Canadian securities regulators and available on SEDAR+ at www.sedarplus.ca. Readers are cautioned not to place undue reliance on forward-looking information, which speaks only as of the date of this press release. Except as required by applicable law, the Company undertakes no obligation to update or revise any forward-looking information.

SOURCE East Side Games Group Inc.

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Technology

HSG Laser Contributes to ISO 11553‑2:2026, the world’s first international safety standard for handheld laser processing machinery, developed under China’s leadership.

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41 minutes ago

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September 4, 2026

By

FOSHAN, China, Sept. 3, 2026 /PRNewswire/ — ISO 11553‑2:2026 Safety of machinery—Laser processing machines—Part 2: Safety requirements for hand-held or hand-operated laser processing machines was officially published on August 28, 2026. As a core member of the Chinese expert group, HSG Laser was deeply involved in the initiation, technical discussions, and drafting of this standard.

This is the world’s first ISO/IEC international safety standard for complete laser processing systems, developed under China’s leadership. The seven-year development process included global technical reviews, cross-border voting, and multi-stakeholder consultations. The standard shifts the focus of safety management from “personnel management and end-user protection” to the inherent safety design of the product itself, establishing a unified global safety benchmark for the rapidly growing market of handheld laser welding and cleaning equipment.

HSG Laser has contributed decades of R&D experience, as well as practical application data and on-site safety practice data, to this international standard. In addition to this ISO standard-setting effort, HSG Laser has participated in the development of numerous national and international standards for laser processing systems and remains committed to translating its engineering expertise into global industry standards. Furthermore, HSG Laser contributes to the development of the industry in various ways. HSG Laser holds 445 patents, has installed more than 50,000 units worldwide, and serves nearly 30,000 customers in over 100 countries through its 20 global branches.

Participating in the development of ISO standards demonstrates HSG Laser’s commitment to advancing the global laser industry. HSG Laser will promote the local adoption and implementation of the ISO 11553-2:2026 standard and continue to contribute China’s technical insights to global standard-setting efforts.

About HSG Laser

Founded in 2006, HSG Laser is a global manufacturer of intelligent metal fabrication equipment, specializing in laser cutting, tube processing, bending, welding, and automation solutions. The company serves customers in more than 100 countries and regions worldwide.

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SOURCE HSG Laser

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EPC Power Announces Sale to Flex for $4.4 Billion

Published

2 hours ago

on

September 4, 2026

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EPC Power’s Intelligent Power Conversion Solutions Directly Address the Fundamental Challenges of an Aging U.S. Power Grid Supporting the Energy Demand Supercycle and the AI Era

POWAY, Calif., Sept. 3, 2026 /PRNewswire/ — EPC Power Corp. (“EPC Power”), a leading North American designer and manufacturer of high-performance, software-defined power conversion solutions for data centers, utility-scale energy storage, and microgrids, today announced it has entered into a definitive agreement to be acquired by Flex (NASDAQ: FLEX) for $4.4 billion. The transaction is subject to customary closing conditions, including the receipt of required regulatory approvals, and is expected to close in the fourth quarter of 2026. Building on the two companies’ existing collaboration, EPC Power will become, upon closing, a business within Flex’s Cloud and Power Infrastructure segment.

The transaction brings EPC Power’s differentiated power conversion technology platform to Flex’s broad portfolio of power and thermal management technologies for mission-critical applications. EPC Power’s next-generation 800-volt data center power architectures, including digital rectifiers and solid-state transformers, enable more efficient power delivery for higher-density AI infrastructure and extend leadership with Flex into an integrated grid-to-chip portfolio. The combined company is positioned to help solve one of the most pressing challenges facing the technology and energy industries today: delivering the fast, resilient and secure power that AI data centers need while supporting stable grid operations amid a generational surge in power demand.

“What we accomplished over the last four years demonstrates the power of strong partnerships and a shared commitment to innovation. Together with Goldman Sachs Alternatives and Cleanhill Partners, EPC Power emerged as a U.S. technology leader in power conversion solutions that enable the next generation of data centers, AI computing, and grid modernization. We expanded our domestic manufacturing footprint nearly tenfold, strengthening America’s industrial base and reinforcing the critical role of U.S. innovation in powering the future economy. This is only the beginning of what EPC Power can accomplish,” said Jim Fusaro, Chief Executive Officer of EPC Power.

“This is a landmark moment for EPC Power and every colleague who helped build this company. When we founded EPC Power, we set out to solve the hardest problems in power electronics, and our partnership with Goldman Sachs Alternatives and Cleanhill Partners enabled us to solve those problems for mission-critical infrastructure globally,” added Devin Dilley, Co-Founder, President and Chief Innovation Officer of EPC Power.

Solving the Binding Constraint on AI Infrastructure

Power availability has become the gating factor for data center growth. As AI workloads drive unprecedented increases in power density, resilience and control requirements, operators must address speed-to-power and load volatility, where the rapid, large-swing power draw of AI training and inference clusters can destabilize the local grid.

EPC Power’s technology is purpose-built for these conditions. The company’s solutions, including its Agile Grid Forming™ technology, deliver performance and reliability that enables on-site energy storage, microgrid and grid-support configurations for data centers, which allow operators to energize capacity faster and ride through grid instability. Grid operators and utilities benefit from stronger reliability and power quality across their networks.

“We are immensely proud of our partnership with Jim, Devin and the EPC Power team that saw the company launch new product platforms, increase domestic U.S. manufacturing and partner with customers to solve novel challenges in AI power architecture. EPC Power plays a critical role in supporting grid reliability and speed to power during a period of growing concerns around energy security. We wish Flex and the EPC team continued success during their stage of growth,” said Alexander Mass, Global Co-Head of Energy Transition Investing within Private Equity at Goldman Sachs Alternatives.

“As grid resilience and data center power demand have converged into one of the defining challenges of the next decade, it has been a privilege to support EPC Power’s operational and commercial scale-up into a global platform positioned at the center of those megatrends,” added Eddie Sigman, Investor within Private Equity at Goldman Sachs Alternatives.

“We first invested in EPC Power in 2021 because we believed power conversion would become a critical enabling technology as renewable generation, grid modernization and digital infrastructure converged. That conviction came well before the extraordinary growth in power demand driven by AI. Since then, we have had the privilege of working closely with Jim, Devin and the EPC team as the company grew, expanded its U.S. manufacturing footprint and created high-quality jobs in the U.S. We are proud to have supported EPC from an early stage and, in its next phase, alongside Goldman Sachs Alternatives as the business entered a new period of growth. Seeing what the team has built over the past five years has been incredibly rewarding, and we believe Flex is the right partner for EPC’s next chapter,” said Ash Upadhyaya and Rakesh Wilson, Managing Partners at Cleanhill Partners.

Goldman Sachs & Co. LLC. and J.P. Morgan Securities LLC served as financial advisors, and Vinson & Elkins LLP served as legal counsel, to EPC Power and its controlling shareholders Goldman Sachs Alternatives and Cleanhill Partners.

About EPC Power

EPC Power Corp. (EPC Power) is a power solutions platform that develops high-performance power conversion systems for mission-critical applications, including data centers, utility-scale energy storage, and microgrids. EPC Power’s solutions are designed to deliver reliable, resilient, and secure energy for demanding applications, including AI-driven workloads and grid stability use cases supported by EPC Power’s Agile Grid Forming™ technology. Visit EPCPower.com for more information.

About Flex

Flex (Reg. No. 199002645H) is the manufacturing partner of choice that helps leading brands design, build, and manage products that improve the world. With a global footprint spanning 30 countries, Flex delivers advanced manufacturing and supply chain solutions, innovative products and technology, and lifecycle services that support customers from concept to scale. In the AI era, Flex is helping customers accelerate data center deployment by solving power, heat, and scale challenges through cutting-edge power and cooling technology and scalable IT infrastructure solutions. For information about Flex’s intent to spin off its Cloud and Power Infrastructure portfolio, visit: https://flex.com/transaction-resources 

About Private Equity at Goldman Sachs Alternatives

Goldman Sachs (NYSE: GS) is one of the leading investors in alternatives globally, with over $706 billion in assets and more than 30 years of experience. The business invests in the full spectrum of alternatives including private equity, growth equity, venture capital, private credit, real estate, infrastructure, sustainability, and hedge funds. Clients access these solutions through direct strategies, customized partnerships, and open-architecture programs.

The business is driven by a focus on partnership and shared success with its clients, seeking to deliver long-term investment performance drawing on its global network and deep expertise across industries and markets.

The alternative investments platform is part of Goldman Sachs Asset Management, which delivers investment and advisory services across public and private markets for the world’s leading institutions, financial advisors and individuals. Goldman Sachs has more than $4.0 trillion in assets under supervision globally as of June 30, 2026.

Established in 1986, Private Equity at Goldman Sachs Alternatives has invested over $75 billion since inception. The business combines a global network of relationships, unique insight across markets, industries and regions, and the worldwide resources of Goldman Sachs to build businesses and accelerate value creation across its portfolios.

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About Cleanhill Partners

Cleanhill Partners is a private equity firm focused on energy transition and digital infrastructure. The firm invests in companies across power generation, energy storage, grid modernization, domestic manufacturing and related technologies that support the growing demand for reliable power.

Cleanhill works closely with management teams to help companies scale and build long-term value. The firm is led by investors and operators with more than two decades of experience across. For more information, visit www.cleanhillpartners.com.

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SOURCE EPC Power

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Processing in-Memory AI Chips Market Set to Skyrocket from $231M in 2025 to $44B by 2032 at 112.4% CAGR | Valuates Reports

Published

4 months ago

on

What is the Market Size of Processing in-Memory AI Chips?

BANGALORE, India, April 29, 2026 /PRNewswire/ — The global Processing in-memory AI Chips market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.

 

 

Get Free Sample: https://reports.valuates.com/request/sample/QYRE-Auto-15O17238/Global_Processing_in_memory_AI_Chips_Market_Research_Report_2024

What are the key factors driving the growth of the Processing in-Memory AI Chips Market?

The processing in-memory AI chips market is expanding due to growing pressures on compute architectures from data movement inefficiency, latency constraints, rising power sensitivity, and deployment cost control across AI workloads.Demand is shifting toward chip designs that minimize the distance between memory and computation, enabling faster inference execution and better throughput under constrained thermal and energy conditions.This trend is especially relevant for workloads where bandwidth pressure, response time, and local processing efficiency directly determine system value.The market benefits from broader interest in architectures supporting both edge and data center AI tasks, without full reliance on conventional processor-memory separation.These factors create a strong commercial foundation for processing in-memory adoption.

Source from Valuates Reports: https://reports.valuates.com/market-reports/QYRE-Auto-15O17238/global-processing-in-memory-ai-chips

TRENDS INFLUENCING THE GROWTH OF THE PROCESSING IN-MEMORY AI CHIPS MARKET:

DRAM-PIM is driving growth in the processing in-memory AI chips market by addressing one of the most persistent bottlenecks in AI computing, which is the heavy cost of transferring data between memory and logic. By embedding compute capability closer to high-capacity memory structures, DRAM-PIM improves efficiency in bandwidth-intensive inference and parallel data handling environments. This makes it highly relevant for larger models and workloads that require sustained access to large datasets with lower latency overhead. Its role in improving throughput while reducing external data shuttling is strengthening its position in advanced AI infrastructure, particularly where performance scaling must happen without proportionate increases in power draw or board-level complexity.

SRAM-PIM is supporting market growth by serving AI use cases that prioritize low latency, fast local access, and power-efficient computation in compact environments. Its architectural suitability for tightly coupled memory and processing enables faster execution of inference tasks where response speed is critical and repeated memory access patterns are concentrated. This makes SRAM-PIM especially attractive in edge AI systems, embedded intelligence platforms, and applications where energy budgets and footprint limitations are decisive purchase factors. As device-side intelligence becomes more valuable across industrial, consumer, and autonomous systems, SRAM-PIM is gaining traction as a practical route to delivering on-chip efficiency without the penalties associated with conventional memory-transfer-heavy architectures.

In-memory processing chips are driving the growth of the processing in-memory AI chips market by creating a more application-aligned hardware approach for modern AI inference. Their appeal lies in improving usable performance per watt, reducing system bottlenecks, and enabling more scalable deployment economics across both small and large computing power environments. These chips are increasingly viewed as a structural response to the limitations of traditional architectures in handling AI workloads efficiently. As buyers seek solutions that can balance throughput, heat, latency, and integration flexibility, in-memory processing chips are moving from niche experimentation toward broader commercial adoption, supporting a market that is increasingly defined by workload efficiency rather than raw compute expansion alone.

A major factor supporting the market is the growing need to reduce the cost of data movement inside AI systems. In conventional architectures, moving data back and forth between memory and processors consumes time, power, and system resources. Processing in-memory chips directly address this problem by bringing computation closer to stored data. This improves execution efficiency and makes the architecture attractive for inference-heavy environments where repetitive data access creates performance drag. As buyers increasingly evaluate compute systems based on usable efficiency rather than nominal processing strength, demand for architectures that minimize data transport overhead continues to strengthen the market.

Power efficiency is emerging as a decisive growth factor for the processing in-memory AI chips market. AI deployment is no longer limited to environments where power availability is secondary. Enterprises, edge operators, and embedded system developers now require hardware that can support meaningful intelligence under tight energy and thermal budgets. Processing in-memory designs improve energy utilization by reducing unnecessary memory access traffic and enabling more efficient task execution. This gives them strong relevance in a market where lower operating cost, thermal manageability, and sustained performance matter as much as raw computational output, especially across continuously running inference systems and distributed AI infrastructure.

The expansion of edge AI is supporting market growth by increasing demand for chips that can perform inference closer to the source of data. Edge systems need fast decision-making, low energy consumption, and compact integration, all of which align well with processing in-memory designs. As intelligence moves into cameras, sensors, industrial devices, and smart endpoints, conventional architectures often face efficiency tradeoffs that reduce suitability in such environments. Processing in-memory chips help overcome these limitations by supporting local computation with lower latency and reduced data transfer dependency. This makes the technology increasingly relevant as edge intelligence shifts from optional capability to essential product differentiation.

The growing complexity of AI inference workloads is creating favorable conditions for processing in-memory adoption. As models become more memory-intensive and inference demand spreads across commercial applications, the limitations of traditional compute-memory separation become harder to ignore. Buyers are looking for architectures that can handle repeated memory access more efficiently and sustain performance under real deployment conditions. Processing in-memory chips respond to this need by improving memory interaction efficiency, which is particularly valuable in workloads where bandwidth and latency determine real-world usefulness. This shift is helping the market as hardware decisions become increasingly shaped by inference practicality rather than theoretical compute scale.

The market is also benefiting from a growing emphasis on cost-per-inference rather than simple peak performance comparisons. Buyers increasingly want AI hardware that can deliver consistent workload execution with better efficiency, lower supporting infrastructure requirements, and more practical deployment economics. Processing in-memory chips are well positioned in this context because they help reduce some of the overhead traditionally associated with memory bottlenecks, energy consumption, and system complexity. Their value proposition becomes stronger when purchasing decisions are based on long-term operating efficiency and scalable deployment. This cost discipline is pushing interest toward architectures that offer more balanced performance across real commercial use cases.

Claim Yours Now! https://reports.valuates.com/api/directpaytoken?rcode=QYRE-Auto-15O17238&lic=single-user

What are the major product types in the Processing in-memory AI Chips Market?

DRAM-PIMSRAM-PIM

What are the main applications of the Processing in-memory AI Chips Market?

Near-Memory Computing (PNM) ChipIn-Memory Processing (PIM) ChipIn-Memory Computing (CIM) Chip

Key Players in the Processing in-memory AI Chips Market:

MyhticSyntiantD-MatrixHangzhou Zhicun (Witmem) TechnologyBeijing Pingxin TechnologyAistarTekSAMSUNGSK HynixShenzhen Reexen TechnologyGraphcoreAxelera AISuzhou Yizhu Intelligent TechnologyBeijing Houmo TechnologyEnCharge AI

Which region dominates the Processing in-memory AI chips market?

Asia-Pacific remains the most dynamic region due to its deep semiconductor ecosystem, expanding edge device manufacturing base, strong memory technology orientation, and increasing integration of AI into consumer and industrial electronics. China is supporting market formation through locally aligned compute architecture development, while South Korea, Japan, and Taiwan provide supply-side depth through memory and advanced chip ecosystem capabilities. Other regions are adopting more gradually, mainly through selective edge AI and infrastructure modernization use cases.

Purchase Regional Report: https://reports.valuates.com/request/regional/QYRE-Auto-15O17238/Global_Processing_in_memory_AI_Chips_Market_Research_Report_2024

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What are some related markets to the Processing in-memory ai chips market?

Computing in Memory Technology Market was valued at USD 268 Million in the year 2024 and is projected to reach a revised size of USD 175260 Million by 2031, growing at a CAGR of 154.7% during the forecast period.In-memory Computing Chips for AI market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.HTAP-Enabling In-Memory Computing Technologies MarketIMDG (In-Memory Data Grid) Software Market Research ReportEmbedded Ai Chips Market Research ReportUltra-low Power AI Chips Market Research ReportHigh-Bandwidth Memory Chips Market was valued at USD 3816 Million in the year 2024 and is projected to reach a revised size of USD 139450 Million by 2031, growing at a CAGR of 68.2% during the forecast period.LPDDR Chips Market was valued at USD 6891 Million in the year 2024 and is projected to reach a revised size of USD 10870 Million by 2031, growing at a CAGR of 6.8% during the forecast period.Semiconductor Memory Market was valued at USD 125890 Million in the year 2024 and is projected to reach a revised size of USD 232900 Million by 2031, growing at a CAGR of 9.3% during the forecast period.AI Calculus Chips Market was valued at USD 46520 Million in the year 2024 and is projected to reach a revised size of USD 269300 Million by 2031, growing at a CAGR of 25.1% during the forecast period.Military Chips Market was valued at USD 1168 Million in the year 2024 and is projected to reach a revised size of USD 1583 Million by 2031, growing at a CAGR of 4.5% during the forecast period.

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Technology

East Side Games Group Announces Cost Reduction Initiatives to Strengthen Financial Position

Published

41 minutes ago

on

September 4, 2026

By

VANCOUVER, BC, Sept. 3, 2026 /CNW/ — East Side Games Group Inc. (TSX: EAGR) (“East Side Games” or the “Company”), a leading developer and publisher of free-to-play mobile games, today announced a series of cost reduction and operational restructuring initiatives designed to strengthen its balance sheet, improve free cash flow, and position the Company for sustainable, profitable operations.

Key Highlights

Workforce Reduction: The Company has reduced its workforce by approximately 30 employees, representing approximately 32% of its total headcount, effective September 1st through a combination of layoffs and furloughs. With its streamlined workforce, the Company is positioned to operate more efficiently, in-line with its renewed focus on profitability.Annualized Cost Savings: The workforce reduction, together with related operational efficiencies, is expected to generate approximately $3.5 million in annualized cost savings, with the majority of savings expected to be realized beginning in Q4 2026. This is in addition to the $4M in annualized cost savings implemented year-to-date.Portfolio Rationalization: The Company is reprioritizing its development portfolio, including the pausing or scaling back of certain titles and projects, allowing the Company to concentrate resources on its highest-performing and highest-potential live games.Partner Payment Restructuring: The Company is restructuring payment terms with certain development and publishing partners to better align cash outlays with project performance and cash flow generation.

‘These are necessary decisions. Our objective is to build a leaner, more focused organization that can deliver consistent profitability for our shareholders while continuing to invest in the titles and franchises with the greatest long-term potential,’ said Jason Bailey, CEO of East Side Games Group.

About East Side Games Group Inc.

East Side Games Group Inc. (TSX: EAGR) is a leading developer and publisher of mobile games based in Vancouver, Canada, known for creating immersive experiences built around some of the world’s most beloved entertainment franchises. For more information, visit [www.eastsidegames.com].

Forward-Looking Information

This press release contains “forward-looking information” within the meaning of applicable Canadian securities legislation, including statements regarding expected cost savings, the timing and amount of related charges, the Company’s relationship with RBC, anticipated financial impacts, and future operating and financial performance. Forward-looking information is based on the Company’s current expectations, estimates, and assumptions, and is subject to known and unknown risks, uncertainties, and other factors that may cause actual results to differ materially from those expressed or implied, including but not limited to: the Company’s ability to realize anticipated cost savings on the expected timeline or at all; the outcome of discussions with RBC and the Company’s ability to maintain compliance with, or obtain relief from, its credit facility covenants; the impact of workforce reductions and project cancellations on the Company’s operations, employee morale, and relationships with development partners; general economic and industry conditions; and other risk factors described in the Company’s public disclosure documents filed with Canadian securities regulators and available on SEDAR+ at www.sedarplus.ca. Readers are cautioned not to place undue reliance on forward-looking information, which speaks only as of the date of this press release. Except as required by applicable law, the Company undertakes no obligation to update or revise any forward-looking information.

SOURCE East Side Games Group Inc.

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Technology

HSG Laser Contributes to ISO 11553‑2:2026, the world’s first international safety standard for handheld laser processing machinery, developed under China’s leadership.

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41 minutes ago

on

September 4, 2026

By

FOSHAN, China, Sept. 3, 2026 /PRNewswire/ — ISO 11553‑2:2026 Safety of machinery—Laser processing machines—Part 2: Safety requirements for hand-held or hand-operated laser processing machines was officially published on August 28, 2026. As a core member of the Chinese expert group, HSG Laser was deeply involved in the initiation, technical discussions, and drafting of this standard.

This is the world’s first ISO/IEC international safety standard for complete laser processing systems, developed under China’s leadership. The seven-year development process included global technical reviews, cross-border voting, and multi-stakeholder consultations. The standard shifts the focus of safety management from “personnel management and end-user protection” to the inherent safety design of the product itself, establishing a unified global safety benchmark for the rapidly growing market of handheld laser welding and cleaning equipment.

HSG Laser has contributed decades of R&D experience, as well as practical application data and on-site safety practice data, to this international standard. In addition to this ISO standard-setting effort, HSG Laser has participated in the development of numerous national and international standards for laser processing systems and remains committed to translating its engineering expertise into global industry standards. Furthermore, HSG Laser contributes to the development of the industry in various ways. HSG Laser holds 445 patents, has installed more than 50,000 units worldwide, and serves nearly 30,000 customers in over 100 countries through its 20 global branches.

Participating in the development of ISO standards demonstrates HSG Laser’s commitment to advancing the global laser industry. HSG Laser will promote the local adoption and implementation of the ISO 11553-2:2026 standard and continue to contribute China’s technical insights to global standard-setting efforts.

About HSG Laser

Founded in 2006, HSG Laser is a global manufacturer of intelligent metal fabrication equipment, specializing in laser cutting, tube processing, bending, welding, and automation solutions. The company serves customers in more than 100 countries and regions worldwide.

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SOURCE HSG Laser

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Technology

EPC Power Announces Sale to Flex for $4.4 Billion

Published

2 hours ago

on

September 4, 2026

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EPC Power’s Intelligent Power Conversion Solutions Directly Address the Fundamental Challenges of an Aging U.S. Power Grid Supporting the Energy Demand Supercycle and the AI Era

POWAY, Calif., Sept. 3, 2026 /PRNewswire/ — EPC Power Corp. (“EPC Power”), a leading North American designer and manufacturer of high-performance, software-defined power conversion solutions for data centers, utility-scale energy storage, and microgrids, today announced it has entered into a definitive agreement to be acquired by Flex (NASDAQ: FLEX) for $4.4 billion. The transaction is subject to customary closing conditions, including the receipt of required regulatory approvals, and is expected to close in the fourth quarter of 2026. Building on the two companies’ existing collaboration, EPC Power will become, upon closing, a business within Flex’s Cloud and Power Infrastructure segment.

The transaction brings EPC Power’s differentiated power conversion technology platform to Flex’s broad portfolio of power and thermal management technologies for mission-critical applications. EPC Power’s next-generation 800-volt data center power architectures, including digital rectifiers and solid-state transformers, enable more efficient power delivery for higher-density AI infrastructure and extend leadership with Flex into an integrated grid-to-chip portfolio. The combined company is positioned to help solve one of the most pressing challenges facing the technology and energy industries today: delivering the fast, resilient and secure power that AI data centers need while supporting stable grid operations amid a generational surge in power demand.

“What we accomplished over the last four years demonstrates the power of strong partnerships and a shared commitment to innovation. Together with Goldman Sachs Alternatives and Cleanhill Partners, EPC Power emerged as a U.S. technology leader in power conversion solutions that enable the next generation of data centers, AI computing, and grid modernization. We expanded our domestic manufacturing footprint nearly tenfold, strengthening America’s industrial base and reinforcing the critical role of U.S. innovation in powering the future economy. This is only the beginning of what EPC Power can accomplish,” said Jim Fusaro, Chief Executive Officer of EPC Power.

“This is a landmark moment for EPC Power and every colleague who helped build this company. When we founded EPC Power, we set out to solve the hardest problems in power electronics, and our partnership with Goldman Sachs Alternatives and Cleanhill Partners enabled us to solve those problems for mission-critical infrastructure globally,” added Devin Dilley, Co-Founder, President and Chief Innovation Officer of EPC Power.

Solving the Binding Constraint on AI Infrastructure

Power availability has become the gating factor for data center growth. As AI workloads drive unprecedented increases in power density, resilience and control requirements, operators must address speed-to-power and load volatility, where the rapid, large-swing power draw of AI training and inference clusters can destabilize the local grid.

EPC Power’s technology is purpose-built for these conditions. The company’s solutions, including its Agile Grid Forming™ technology, deliver performance and reliability that enables on-site energy storage, microgrid and grid-support configurations for data centers, which allow operators to energize capacity faster and ride through grid instability. Grid operators and utilities benefit from stronger reliability and power quality across their networks.

“We are immensely proud of our partnership with Jim, Devin and the EPC Power team that saw the company launch new product platforms, increase domestic U.S. manufacturing and partner with customers to solve novel challenges in AI power architecture. EPC Power plays a critical role in supporting grid reliability and speed to power during a period of growing concerns around energy security. We wish Flex and the EPC team continued success during their stage of growth,” said Alexander Mass, Global Co-Head of Energy Transition Investing within Private Equity at Goldman Sachs Alternatives.

“As grid resilience and data center power demand have converged into one of the defining challenges of the next decade, it has been a privilege to support EPC Power’s operational and commercial scale-up into a global platform positioned at the center of those megatrends,” added Eddie Sigman, Investor within Private Equity at Goldman Sachs Alternatives.

“We first invested in EPC Power in 2021 because we believed power conversion would become a critical enabling technology as renewable generation, grid modernization and digital infrastructure converged. That conviction came well before the extraordinary growth in power demand driven by AI. Since then, we have had the privilege of working closely with Jim, Devin and the EPC team as the company grew, expanded its U.S. manufacturing footprint and created high-quality jobs in the U.S. We are proud to have supported EPC from an early stage and, in its next phase, alongside Goldman Sachs Alternatives as the business entered a new period of growth. Seeing what the team has built over the past five years has been incredibly rewarding, and we believe Flex is the right partner for EPC’s next chapter,” said Ash Upadhyaya and Rakesh Wilson, Managing Partners at Cleanhill Partners.

Goldman Sachs & Co. LLC. and J.P. Morgan Securities LLC served as financial advisors, and Vinson & Elkins LLP served as legal counsel, to EPC Power and its controlling shareholders Goldman Sachs Alternatives and Cleanhill Partners.

About EPC Power

EPC Power Corp. (EPC Power) is a power solutions platform that develops high-performance power conversion systems for mission-critical applications, including data centers, utility-scale energy storage, and microgrids. EPC Power’s solutions are designed to deliver reliable, resilient, and secure energy for demanding applications, including AI-driven workloads and grid stability use cases supported by EPC Power’s Agile Grid Forming™ technology. Visit EPCPower.com for more information.

About Flex

Flex (Reg. No. 199002645H) is the manufacturing partner of choice that helps leading brands design, build, and manage products that improve the world. With a global footprint spanning 30 countries, Flex delivers advanced manufacturing and supply chain solutions, innovative products and technology, and lifecycle services that support customers from concept to scale. In the AI era, Flex is helping customers accelerate data center deployment by solving power, heat, and scale challenges through cutting-edge power and cooling technology and scalable IT infrastructure solutions. For information about Flex’s intent to spin off its Cloud and Power Infrastructure portfolio, visit: https://flex.com/transaction-resources 

About Private Equity at Goldman Sachs Alternatives

Goldman Sachs (NYSE: GS) is one of the leading investors in alternatives globally, with over $706 billion in assets and more than 30 years of experience. The business invests in the full spectrum of alternatives including private equity, growth equity, venture capital, private credit, real estate, infrastructure, sustainability, and hedge funds. Clients access these solutions through direct strategies, customized partnerships, and open-architecture programs.

The business is driven by a focus on partnership and shared success with its clients, seeking to deliver long-term investment performance drawing on its global network and deep expertise across industries and markets.

The alternative investments platform is part of Goldman Sachs Asset Management, which delivers investment and advisory services across public and private markets for the world’s leading institutions, financial advisors and individuals. Goldman Sachs has more than $4.0 trillion in assets under supervision globally as of June 30, 2026.

Established in 1986, Private Equity at Goldman Sachs Alternatives has invested over $75 billion since inception. The business combines a global network of relationships, unique insight across markets, industries and regions, and the worldwide resources of Goldman Sachs to build businesses and accelerate value creation across its portfolios.

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About Cleanhill Partners

Cleanhill Partners is a private equity firm focused on energy transition and digital infrastructure. The firm invests in companies across power generation, energy storage, grid modernization, domestic manufacturing and related technologies that support the growing demand for reliable power.

Cleanhill works closely with management teams to help companies scale and build long-term value. The firm is led by investors and operators with more than two decades of experience across. For more information, visit www.cleanhillpartners.com.

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SOURCE EPC Power

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