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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

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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

EPC Power Announces Sale to Flex for $4.4 Billion

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5 minutes ago

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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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VeriPark selected by Queensland Country Bank to support major technology transformation

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1 hour ago

on

September 3, 2026

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LONDON, Sept. 4, 2026 /PRNewswire/ — VeriPark, a global financial services technology provider, announced that Queensland Country Bank has selected its customer experience solutions as part of a major transformation program designed to deliver more connected, and member-focused banking experiences.

Queensland Country Bank will implement VeriPark’s VeriChannel digital banking platform, VeriTouch CRM platform and VeriLoan loan origination system. Together, the solutions will support digital banking, onboarding, lending and customer engagement across digital and assisted channels.

The broader transformation also includes Fiserv’s Finxact core banking platform and Vision Next card management solution. By bringing these technologies together, Queensland Country Bank is creating a future-ready environment spanning core banking, cards, lending, customer relationship management and digital channels.

The program will help the bank progressively modernize its platforms, reduce technology complexity and create more integrated experiences across member touchpoints, while preserving its community and member-owned focus.

“This is an important step in the next chapter of Queensland Country Bank,” said Shawn Anderson, Chief Transformation Officer of Queensland Country Bank. “Our Members expect banking to be simple, reliable and personal. By partnering with Fiserv and VeriPark, we are investing in the foundations that will help us deliver better experiences, support our people and continue serving Queensland communities well into the future.”

“We are proud to partner with Queensland Country Bank as it builds the foundations for its next generation of Member experiences,” said David Dervish, Chief Revenue Officer at VeriPark. “By connecting digital banking, lending and customer engagement, our platform will help the bank deliver more personalised and seamless journeys while giving its teams a more unified view of every Member. We look forward to turning this transformation vision into tangible value for Members and employees.”

QCB (www.queenslandcountry.bank)
Queensland Country Bank is a member-owned bank committed to helping Queenslanders live better lives through better financial wellbeing achieved through personal service, local understanding and community-focused banking. With roots across regional Queensland, the bank provides a range of banking products and services for Members across the state.

VeriPark (veripark.com) 
VeriPark is a global solutions provider enabling financial institutions to become digital leaders by placing Customer Experience at the core of digital transformation. From Omnichannel Delivery and Customer Engagement to Branch Automation and Loan Origination, VeriPark helps financial institutions accelerate digital transformation, increase productivity, and achieve tangible business outcomes.

 

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Intouch Insight to Unveil Annual Drive-Thru Study at QSR Evolution Conference

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2 hours ago

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September 3, 2026

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Intouch Insight (INX: CA) to reveal the results of its annual Drive-Thru Study during the main stage session at the QSR Evolution Conference in AtlantaMain stage reveal to be delivered by VP Sales, Marketing & Product Strategy Sarah Beckett and Chief Revenue Officer Laura Livers on Thursday, September 10, 2026, ahead of the day’s keynoteBeckett and Livers will also moderate a panel of quick service restaurant operators on the technologies shaping the drive-thru of the future

OTTAWA, ON, Sept. 3, 2026 /CNW/ — Intouch Insight Ltd. (OTCQX: INXSF) (“Intouch” or the “Company”), a provider of customer experience measurement solutions, today announced that it will present the findings of its annual Drive-Thru Study on the main stage at the QSR Evolution Conference, taking place September 8-10, 2026, at the Hyatt Regency Atlanta. This marks the fourth consecutive year Intouch has partnered with QSR Magazine and Arrowfly, formerly WTWH Media, to bring the study’s results to the conference stage.

The main stage session, “Intouch Insight Drive-Thru Report Reveal,” is scheduled for Thursday, September 10, 2026, at 8:45 a.m. Eastern Time, immediately ahead of the day’s keynote. Sarah Beckett, VP Sales,Marketing & Product Strategy, and Laura Livers, Chief Revenue Officer, will give attendees an early, exclusive look at the fastest, most accurate, and best customer service drive-thrus in America.

Beckett and Livers will also moderate a panel session, “Unveiling the Drive-Thru of the Future,” which goes deeper into the technologies and innovations separating winning brands, and what it takes to run a modern drive-thru that delivers consistency and experience at scale. Panelists include Taylor Crookston-Grace, Director, Brand Standard, BK US&C Operations; Michael MacLennan, Cofounder and Co-CEO, Tryarc; Chris Cheek, Chief Development Officer, Newk’s Eatery; Trace Miller, Founder & CEO, Konala; and Tim Sharpe, COO, Oliver’s Real Food.

Now in its fourth year, the QSR Evolution Conference brings together senior leaders from across the quick service restaurant industry for practitioner-led sessions on operations, technology, and customer experience. Intouch’s participation on the main stage reflects its continued work in customer experience measurement and operational audits for restaurant operators and other multi-location brands.

Cameron Watt, President and Chief Executive Officer of Intouch Insight, said:

“The drive-thru study has become one of the most anticipated benchmarks in the industry, and the main stage at QSR Evolution is the right place to reveal it. Our research shows where brands are winning on speed, accuracy, and service, and where the gaps still are. We are looking forward to putting that data in front of the operators who can act on it, and to a fourth year of partnering with QSR Magazine and Arrowfly to make it happen.”

About Intouch Insight

Intouch Insight offers a complete portfolio of customer experience management (CEM) products and services that help global brands delight their customers, strengthen brand reputation and improve financial performance. Intouch helps clients collect and centralize data from multiple customer touch points, gives them actionable, real-time insights, and provides them with the tools to continuously improve customer experience. Founded in 1992, Intouch is trusted by over 300 of North America’s most-loved brands for their customer experience management, customer survey, mystery shopping, mobile forms, operational and compliance audits, geolocation data capture and event marketing automation solutions. For more information, visit intouchinsight.com.

Certain statements included in this news release including those related to the Company’s quarterly results, future products, opportunities and cost initiatives, strategies, and other statements that are predictive in nature that depend upon or refer to future events or conditions, or that include words such as “expects”, “anticipates”, “intends”, “plans”, “believes”, “estimates”, or similar expressions, are forward-looking statements within the meaning of applicable Canadian securities laws. Forward-looking statements that are made as of the date hereof, which by their nature are necessarily subject to risks and uncertainties and other factors that may cause actual results, performance or achievements of the Company to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. Such statements reflect the Company’s current views with respect to future events, and are based on information currently available to the Company and on hypotheses which it considers to be reasonable; however, management cautions the reader that hypotheses relative to future events which are beyond the control of management could prove to be false, given that they are subject to certain risks and uncertainties. Please refer to the risks set forth in the Company’s most recent annual MD&A and the Company’s continuous disclosure documents that can be found on SEDAR+ at www.sedarplus.ca. The Company does not intend, and disclaims any obligation, except as required by law, to update or revise any forward-looking statements whether as a result of new information, future events or otherwise.

Neither TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

SOURCE Intouch Insight Ltd.

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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

EPC Power Announces Sale to Flex for $4.4 Billion

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5 minutes ago

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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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Technology

VeriPark selected by Queensland Country Bank to support major technology transformation

Published

1 hour ago

on

September 3, 2026

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LONDON, Sept. 4, 2026 /PRNewswire/ — VeriPark, a global financial services technology provider, announced that Queensland Country Bank has selected its customer experience solutions as part of a major transformation program designed to deliver more connected, and member-focused banking experiences.

Queensland Country Bank will implement VeriPark’s VeriChannel digital banking platform, VeriTouch CRM platform and VeriLoan loan origination system. Together, the solutions will support digital banking, onboarding, lending and customer engagement across digital and assisted channels.

The broader transformation also includes Fiserv’s Finxact core banking platform and Vision Next card management solution. By bringing these technologies together, Queensland Country Bank is creating a future-ready environment spanning core banking, cards, lending, customer relationship management and digital channels.

The program will help the bank progressively modernize its platforms, reduce technology complexity and create more integrated experiences across member touchpoints, while preserving its community and member-owned focus.

“This is an important step in the next chapter of Queensland Country Bank,” said Shawn Anderson, Chief Transformation Officer of Queensland Country Bank. “Our Members expect banking to be simple, reliable and personal. By partnering with Fiserv and VeriPark, we are investing in the foundations that will help us deliver better experiences, support our people and continue serving Queensland communities well into the future.”

“We are proud to partner with Queensland Country Bank as it builds the foundations for its next generation of Member experiences,” said David Dervish, Chief Revenue Officer at VeriPark. “By connecting digital banking, lending and customer engagement, our platform will help the bank deliver more personalised and seamless journeys while giving its teams a more unified view of every Member. We look forward to turning this transformation vision into tangible value for Members and employees.”

QCB (www.queenslandcountry.bank)
Queensland Country Bank is a member-owned bank committed to helping Queenslanders live better lives through better financial wellbeing achieved through personal service, local understanding and community-focused banking. With roots across regional Queensland, the bank provides a range of banking products and services for Members across the state.

VeriPark (veripark.com) 
VeriPark is a global solutions provider enabling financial institutions to become digital leaders by placing Customer Experience at the core of digital transformation. From Omnichannel Delivery and Customer Engagement to Branch Automation and Loan Origination, VeriPark helps financial institutions accelerate digital transformation, increase productivity, and achieve tangible business outcomes.

 

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Technology

Intouch Insight to Unveil Annual Drive-Thru Study at QSR Evolution Conference

Published

2 hours ago

on

September 3, 2026

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Intouch Insight (INX: CA) to reveal the results of its annual Drive-Thru Study during the main stage session at the QSR Evolution Conference in AtlantaMain stage reveal to be delivered by VP Sales, Marketing & Product Strategy Sarah Beckett and Chief Revenue Officer Laura Livers on Thursday, September 10, 2026, ahead of the day’s keynoteBeckett and Livers will also moderate a panel of quick service restaurant operators on the technologies shaping the drive-thru of the future

OTTAWA, ON, Sept. 3, 2026 /CNW/ — Intouch Insight Ltd. (OTCQX: INXSF) (“Intouch” or the “Company”), a provider of customer experience measurement solutions, today announced that it will present the findings of its annual Drive-Thru Study on the main stage at the QSR Evolution Conference, taking place September 8-10, 2026, at the Hyatt Regency Atlanta. This marks the fourth consecutive year Intouch has partnered with QSR Magazine and Arrowfly, formerly WTWH Media, to bring the study’s results to the conference stage.

The main stage session, “Intouch Insight Drive-Thru Report Reveal,” is scheduled for Thursday, September 10, 2026, at 8:45 a.m. Eastern Time, immediately ahead of the day’s keynote. Sarah Beckett, VP Sales,Marketing & Product Strategy, and Laura Livers, Chief Revenue Officer, will give attendees an early, exclusive look at the fastest, most accurate, and best customer service drive-thrus in America.

Beckett and Livers will also moderate a panel session, “Unveiling the Drive-Thru of the Future,” which goes deeper into the technologies and innovations separating winning brands, and what it takes to run a modern drive-thru that delivers consistency and experience at scale. Panelists include Taylor Crookston-Grace, Director, Brand Standard, BK US&C Operations; Michael MacLennan, Cofounder and Co-CEO, Tryarc; Chris Cheek, Chief Development Officer, Newk’s Eatery; Trace Miller, Founder & CEO, Konala; and Tim Sharpe, COO, Oliver’s Real Food.

Now in its fourth year, the QSR Evolution Conference brings together senior leaders from across the quick service restaurant industry for practitioner-led sessions on operations, technology, and customer experience. Intouch’s participation on the main stage reflects its continued work in customer experience measurement and operational audits for restaurant operators and other multi-location brands.

Cameron Watt, President and Chief Executive Officer of Intouch Insight, said:

“The drive-thru study has become one of the most anticipated benchmarks in the industry, and the main stage at QSR Evolution is the right place to reveal it. Our research shows where brands are winning on speed, accuracy, and service, and where the gaps still are. We are looking forward to putting that data in front of the operators who can act on it, and to a fourth year of partnering with QSR Magazine and Arrowfly to make it happen.”

About Intouch Insight

Intouch Insight offers a complete portfolio of customer experience management (CEM) products and services that help global brands delight their customers, strengthen brand reputation and improve financial performance. Intouch helps clients collect and centralize data from multiple customer touch points, gives them actionable, real-time insights, and provides them with the tools to continuously improve customer experience. Founded in 1992, Intouch is trusted by over 300 of North America’s most-loved brands for their customer experience management, customer survey, mystery shopping, mobile forms, operational and compliance audits, geolocation data capture and event marketing automation solutions. For more information, visit intouchinsight.com.

Certain statements included in this news release including those related to the Company’s quarterly results, future products, opportunities and cost initiatives, strategies, and other statements that are predictive in nature that depend upon or refer to future events or conditions, or that include words such as “expects”, “anticipates”, “intends”, “plans”, “believes”, “estimates”, or similar expressions, are forward-looking statements within the meaning of applicable Canadian securities laws. Forward-looking statements that are made as of the date hereof, which by their nature are necessarily subject to risks and uncertainties and other factors that may cause actual results, performance or achievements of the Company to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. Such statements reflect the Company’s current views with respect to future events, and are based on information currently available to the Company and on hypotheses which it considers to be reasonable; however, management cautions the reader that hypotheses relative to future events which are beyond the control of management could prove to be false, given that they are subject to certain risks and uncertainties. Please refer to the risks set forth in the Company’s most recent annual MD&A and the Company’s continuous disclosure documents that can be found on SEDAR+ at www.sedarplus.ca. The Company does not intend, and disclaims any obligation, except as required by law, to update or revise any forward-looking statements whether as a result of new information, future events or otherwise.

Neither TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

SOURCE Intouch Insight Ltd.

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