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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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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.

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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

Hexagon releases new targets at its Capital Markets Day 2026

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April 30, 2026

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Hexagon is the global leader in precision measurement, positioning and autonomous solutions with a serviceable addressable market of ~€38bn by 2030.Hexagon’s €3.7bn in revenue and ~17,000 employees are across three Business Areas – Manufacturing Intelligence, Infrastructure & Especial and Autonomous Solutions plus a Robotics Division currently in an investment phase.Recent portfolio actions, including the upcoming separation of Octave, the sale of the Design & Engineering business and the announced acquisition of Agate Technologies, have focused Hexagon on its strong core business in precision measurement & positioning technologies.Hexagon’s organic growth will be driven by strong end market potential and structural tailwinds, new product introductions and an operating model focused on accountability and closeness to customers.Hexagon launches new financial targets for the 2026 – 2030 period of average organic revenue growth of 4-6%, an EBITDA margin of 24-26%[1] and an EBITDA cash conversion of 90-100%. It also targets reducing Scope 1 & 2 emissions by 70% by 2030, from a 2022 baseline.

[1] EBITAC is defined as adjusted EBIT1 excluding capitalised and amortised R&D. See pages the appendix for further information

STOCKHOLM, April 30, 2026 /PRNewswire/ — Hexagon AB is hosting its Capital Markets Day today in London. At the event, President and CEO Anders Svensson, CFO Enrique Patrickson and the Presidents of Hexagon’s Business Areas will set out Hexagon’s ambitious growth strategy and its new 2026–2030 financial targets.

“Hexagon enters this new phase as a focused global leader in precision measurement and positioning, with a solutions portfolio essential to enabling industrial autonomy,” said Anders Svensson, President and CEO of Hexagon. “Our new targets reflect both the quality of our portfolio and the discipline of The Hexagon Way. With a strong leadership team and the financial flexibility to invest behind our growth priorities both organically and through synergistic acquisitions, we are well placed to deliver value creation for shareholders.”

“Today we are taking transparency to the next level — enhancing our disclosures, introducing EBITAC as our key profitability metric and providing clarity around our capital allocation priorities,” said Enrique Patrickson, CFO of Hexagon. “EBITAC is the right metric for Hexagon, a technology company with a significant R&D spend, funding market-leading product launches that drive our growth. With additional transparency comes additional accountability. We commit to drive capital allocation around R&D, M&A and Dividends with discipline and rigor.”

New sustainability targets

70% reduction in Scope 1 & 2 emissions by 2030 (from 2022 baseline)Net-zero by 2050

New 2026–2030 financial targets

Average annual organic revenue growth of 4-6%EBITAC margin in the range of 24-26%Annual cash conversion (of EBITAC) of 90-100%

A focused group focused on enabling industrial autonomy

Hexagon has undertaken significant portfolio changes, namely the upcoming spin-off of Octave and the sale of the Design & Engineering business. The resulting business is a focused global leader in precision measurement and positioning with proforma 2025 revenue of €3.7bn, EBITAC of €826m (22% EBITAC margin) and ~17,000 employees.

Hexagon is organised into three business areas – Manufacturing Intelligence, Infrastructure & Geospatial (formerly Geosystems) and Autonomous Solutions – alongside the Robotics Division, currently in an investment phase.

The overarching growth opportunity that underpins Hexagon’s long-term strategy is enabling customers to move towards true autonomy in their industrial operations.

President and CEO Anders Svensson will outline how Hexagon’s precision measurement and positioning technologies, digital twins and spatial intelligence capabilities are essential to enabling this true industrial autonomy. Hexagon holds market leadership positions across its serviceable addressable market, which is estimated to grow to ~€38bn by 2030.

Anders will also outline the key changes to Hexagon’s operating model. The Hexagon Way is an accountability-driven, decentralised model built around three strategic enablers: innovation and AI; portfolio management and M&A; and people & culture.

Central to this model is a clear accountability structure: the group’s three Business Areas are divided into 17 Divisions, each with full ownership of its financial performance and a defined strategic mandate covering three value creation priorities – Stability, Profitability and Growth.

The group-wide enablers allow Divisions to identify and execute on strategies targeted specifically to their markets and customers while drawing on the scale and resources of the broader Hexagon organisation. This balance of focused execution at the Division level and shared capability at the group level is designed to unlock each Division’s full potential and drive overall performance and shareholder value.

Hexagon’s new mid-term financial targets for 2026 to 2030 will be outlined by CFO Enrique Patrickson alongside a new financial framework including revised metric definitions designed to improve transparency, capital allocation and shareholder value creation.

The new 2026-30 through the cycle targets are:

Average annual organic revenue growth of 4–6% (CAGR 2026–2030)EBITAC margin in the range of 24–26%Annual cash conversion (of EBITAC) of 90–100%

In 2025, Hexagon achieved organic growth of 2.6%, an EBITAC margin of 22% and cash conversion (of EBITAC) of 109%.

Capital allocation

Hexagon’s capital allocation priorities are, in order: reinvestment in organic growth, value-accretive bolt-on M&A, a progressive dividend, and selective larger strategic moves where they enhance long-term shareholder value. The Group’s strong cash conversion and balance sheet provide the flexibility to pursue these priorities through the cycle.

Business Area presentations

Senior leadership from Hexagon’s Business Areas will provide additional context on strategy, markets and Business Area targets. The presenters will be:

Andreas Renulf, President, Manufacturing Intelligence Business AreaHenning Sandfort, President, Infrastructure & Geospatial Business AreaGordon Dale, President, Autonomous Solutions Business AreaArnaud Robert, President, Robotics Division

EBITAC – EBIT1 excluding capitalisation & amortisation of R&D

Hexagon is introducing EBITAC as its primary profitability measure. By immediately reflecting the full cost of R&D investments on the P&L, it will provide a tool to focus management firmly on the return on investment of R&D, go-to-market and capital investments and support performance management and capital allocation. The top end of the target EBITAC margin range (26%) was last achieved in 2021 and corresponds to the highest EBIT1 margin achieved by Hexagon in the last 5-years.

It is defined as adjusted EBIT1 excluding capitalised and amortised R&D.

Hexagon will continue to report EBIT1 (adjusted operating profit) for full transparency. A bridge between reported EBIT, EBIT1 and EBITAC and the EBITAC performance between 2024 and 2025 can be found in the appendix to this announcement.

Profitability metric bridge, 2025

Item

€M

Reported EBIT

575

Add: in year adjustments (impairments, restructuring, LTIP, PPA)

+372

EBIT1

947

Subtract: R&D capitalisation

-340

Add: R&D amortisation

+195

EBITAC

802

Subtract: in year robotics costs

+24

EBITAC (target definition)

826

Robotics – AEON, a potential global market leader in humanoid Robotics

Investment in Robotics to double from €24m in 2025 to €50m in 2026.Pilots with BMW, Schaeffler, Pilatus & Fill underway.Robotics is an exciting opportunity for significant value creation.

Due to its rapidly evolving structure Hexagon has decided to exclude Robotics from the 2026-30 financial targets and the calculation of EBITAC. This gives better visibility on the core group performance.

The financial performance of Robotics will be disclosed on a quarterly basis.

New sustainability targets

Hexagon is committed to operating responsibly for the good of the environment. It has set challenging new targets for emission reductions. Hexagon targets a 70% reduction in Scope 1 & 2 emissions by 2030 (from a 2022 baseline) and net-zero in Scope 1, 2 & 3 by 2050.

In 2025 Hexagon saw a 33% reduction in Scope 1 & 2 emissions from its 2022 baseline.

Joining instructions

The webcast will be streamed here: https://edge.media-server.com/mmc/p/d2han2qw/

FOR MORE INFORMATION, CONTACT:  
Tom Hull, Head of Investor Relations, Hexagon AB, +44 7442 678 437, ir@hexagon.com
Anton Heikenström, Investor Relations Manager, Hexagon AB, +46 8 601 26 26, ir@hexagon.com

This is information that Hexagon AB is obliged to make public pursuant to the EU Market Abuse Regulation. The information was submitted for publication, through the agency of the contact person set out above, at 08:00 CET on 30 April 2026.

Appendix – Reconciling EBIT1 & EBITAC performance, 2025 quarterly

Metric

Q1 2025

Q2 2025

Q3 2025

Q4 2025

FY 2025

Revenue €m

961.5

1,010.5

976.0

1,053.1

4,001.2

EBIT1 €m

248.7

260.0

264.7

299.1

1,072.4

Subtract: capitalisation of R&D €m

-94.6

-94.7

-91.1

-84.1

-364.5

Add: amortisation of R&D €m

54.6

54.3

59.2

50.4

218.5

EBITAC €m

208.7

219.6

232.8

265.3

926.4

In year robotics cost €mEBIT

-4.7

-5.9

-5.6

-7.6

-23.7

EBITAC (excluding robotics costs)

213.4

225.5

238.3

272.9

950.1

EBIT1 margin %

25.9 %

25.7 %

27.1 %

28.4 %

26.8 %

EBITAC margin %

21.7 %

21.7 %

23.8 %

25.2 %

23.2 %

EBITAC margin % (excluding robotics costs)

22.2 %

22.3 %

24.4 %

25.9 %

23.7 %

Appendix – Reconciling EBIT1 & EBITAC performance, 2025 quarterly, excluding Design & Engineering

Metric

Q1 2025

Q2 2025

Q3 2025

Q4 2025

FY 2025

Revenue €m

888.2

939.4

907.1

980.3

3,715.0

EBIT1 €m

225.0

231.1

235.5

255.4

947.0

Subtract: capitalisation of R&D €m

-88.6

-88.0

-84.8

-78.3

-339.6

Add: amortisation of R&D €m

48.2

48.0

53.3

45.8

195.3

EBITAC €m

184.6

191.1

204.0

223.0

802.7

In year robotics cost €m

-4.7

-5.9

-5.6

-7.6

-23.7

EBITAC (excluding robotics costs)

189.3

196.9

209.6

230.5

826.4

EBIT1 margin %

25.3 %

24.6 %

26.0 %

26.1 %

25.5 %

EBITAC margin %

20.8 %

20.3 %

22.5 %

22.7 %

21.6 %

EBITAC margin % (excluding robotics costs)

21.3 %

21.0 %

23.1 %

23.5 %

22.2 %

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Hexagon releases new targets at its Capital Markets Day 2026

 

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Accountants Streamline Cash Flow with ezACH Direct Deposit Software

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April 30, 2026

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Eliminate payment delays, reduce manual errors, and gain full control with a low-cost and high-quality ACH solution built for modern accounting workflows.

REDMOND, Wash., April 30, 2026 /PRNewswire/ — Halfpricesoft.com developers understand that businesses demand faster payments and greater financial control, and now accountants are rethinking how they manage transactions. ezACH direct deposit software will simplify payment processing, accelerate cash flow, and reduce costly errors.

Clients are encouraged to download and test ezACH today to purchase to confirm compatibility.

ezACH empowers accountants to securely process electronic payments for clients, vendors, payroll, and tax obligations, all from one streamlined platform. By generating ACH files that can be uploaded directly to a bank, the software removes the need for manual payment handling and outdated processes.

“Speed and accuracy are critical in today’s financial environment,” said Dr. Ge, Founder of Halfpricesoft.com. “ezACH gives accountants the ability to process multiple payments quickly and securely, without added complexity or cost.”

Designed with flexibility in mind, ezACH allows users to manage unlimited transactions for unlimited companies at a one-time flat rate of $199.00, making it a cost-effective alternative to subscription-based payment platforms. Try it today!

Why Accountants Are Making the Switch:

Process ACH payments for vendors, clients, payroll, and tax agenciesEliminate manual entry and reduce costly errorsImport data easily from CSV files or other Halfpricesoft applicationsHandle unlimited companies and transactions with no recurring feesMaintain full control over payment timing and processingClients can upload transactions for up to $4.99 to test compatibility

Halfpricesoft.com offers a variety of applications that will seamlessly integrate with ezACH software:

ezPaycheck: A new version of ezACH has just been released to support import CSV with ezPaycheck importing. ezCheckprinting: Business check writer for vendors, miscellaneous and draft checks. https://www.halfpricesoft.com/product_ezCheck.aspezAccounting: DIY in-house bookkeeping and payroll solution for one flat rate. https://www.halfpricesoft.com/accounting/accounting-software.asp

With a one-time cost of $199 per installation, ezACH offers long-term savings compared to subscription-based services. There are no hidden fees, and users can process unlimited ACH transactions. (Note: Banks may apply their own ACH processing fees. We recommend contacting your bank for compatibility prior to purchase).

Simplify the business operations and boost efficiency with the powerful, all-in-one solutions fromHalfpricesoft.com. To save both time and money, get started today at HalfPriceSoft.com for no cost or obligation

About Halfpricesoft.com

Halfpricesoft.com has been delivering affordable, reliable business software solutions for over 20 years. Its suite of products, including payroll, accounting, check printing, tax filing, and ACH deposit software, helps small businesses, accountants, and nonprofits streamline operations and reduce costs. Trusted by thousands nationwide, Halfpricesoft.com remains committed to simplifying financial management with powerful, budget-friendly tools.

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Neusoft Smart Go and Tencent Cloud Forge Strategic Partnership to Build a New AI-Powered Intelligent Cockpit Ecosystem

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BEIJING, April 30, 2026 /PRNewswire/ — At Auto China 2026, Neusoft Smart Go, a subsidiary of Neusoft Corporation (SSE:600718), officially announced its strategic upgrade. The company now aims to become a global leading provider in full-domain upper-body electronics solutions for intelligent vehicles. At the same time, Neusoft Smart Go and Tencent Cloud announced a strategic partnership. Aligning with “AI-defined vehicles” trend, the two parties will focus on key areas such as intelligent cockpits, on-device AI large model applications, ecosystem content integration, in-vehicle cybersecurity, and cloud services. By integrating their technologies and resources, they will engage in in-depth collaboration to develop AI-powered intelligent cockpit products and solutions that offer enhanced interactivity and emotional experiences, accelerating the intelligent transformation of entire vehicles.

The integration of AI large models and ecosystems into vehicles is essentially a full-chain systematic project covering hardware-software architecture adaptation, data processing, compliance assurance, and real-time response. Currently, automakers face challenges such as high in-house R&D expenses, ecosystem integration hurdles, and a lack of differentiated user experiences. They urgently require full-domain solutions that seamlessly integrate hardware and software, offer comprehensive ecosystem coverage, and enable rapid mass production to meet users’ core demands for multi-modal interaction, full-scenario services, and continuous OTA updates.

As a leading cloud service provider in China, Tencent Cloud has core strengths in on-device large models, in-vehicle ecosystems and applications, cloud services, and data compliance assurance. It also offers a full-chain app ecosystem spanning social media, music, maps, and more. In this partnership, the two parties will take Neusoft Smart Go’s next-gen intelligent cockpit system as the core platform, deeply integrating Tencent Cloud’s on-device large models to jointly develop a benchmark AI-powered intelligent cockpit featuring natural conversations, proactive interactions, and highly emotional, smooth experiences. Furthermore, they will fully integrate a wide range of ecosystem apps, enabling seamless transitions between mobile phones and in-vehicle systems across all scenarios.

At present, Neusoft Smart Go has established a product matrix covering a full range of in-vehicle electronics solutions, including central computing platforms, cockpit-driving-parking integration, intelligent cockpits, intelligent communications, intelligent audio systems, and zonal control units. Through a dual-track strategy of high-end cutting-edge solutions and mature standardized products, it can flexibly meet the mass production needs of vehicle models across different regions and price segments worldwide. Leveraging Tencent’s intelligent driving cloud, data compliance, OTA technical support, and AI platform services, the two parties will provide stable, secure, and intelligent hardware-software integrated solutions tailored to the diverse needs of global automakers, comprehensively assisting them in achieving intelligent and AI-driven upgrades for entire vehicles.

Jian Guodong, Senior Vice President of Neusoft and CEO of Neusoft Smart Go, said, “The integration of AI large models and full-scenario ecosystems represents an inevitable trend and a shared vision for both Neusoft Smart Go and Tencent Intelligent Mobility. Leveraging Neusoft Smart Go’s technical expertise in the full domain of upper-body electronics and Tencent’s leading solutions in AI large models and full-chain ecosystems, the two parties will collaborate to provide global automakers with truly mass-producible and evolvable AI-powered intelligent cockpit solutions.”

Zhong Xuedan, Vice President and Head of Tencent Intelligent Mobility, said, “We share complementary strengths and similar philosophies with Neusoft Smart Go, laying a solid foundation for cooperation. Both parties will further deepen cooperation in AI-powered intelligent cockpits, jointly exploring proactive interactions and emotional services powered by large models, transforming the cockpit into a smarter companion that better understands users.”

The deep integration of on-device AI large models and full-scenario ecosystems is reshaping the value boundaries and user experiences of intelligent cockpits. The automotive industry needs to accelerate innovation and mass production, achieving a balance between advanced technologies and cost-effectiveness. Neusoft Smart Go will focus on enhancing its systematic integration, software-hardware synergy, and global delivery capabilities. Through collaboration with more ecosystem partners, it will provide sustained momentum for the intelligent transformation of the automotive industry.

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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

15 hours ago

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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.

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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

Hexagon releases new targets at its Capital Markets Day 2026

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April 30, 2026

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Hexagon is the global leader in precision measurement, positioning and autonomous solutions with a serviceable addressable market of ~€38bn by 2030.Hexagon’s €3.7bn in revenue and ~17,000 employees are across three Business Areas – Manufacturing Intelligence, Infrastructure & Especial and Autonomous Solutions plus a Robotics Division currently in an investment phase.Recent portfolio actions, including the upcoming separation of Octave, the sale of the Design & Engineering business and the announced acquisition of Agate Technologies, have focused Hexagon on its strong core business in precision measurement & positioning technologies.Hexagon’s organic growth will be driven by strong end market potential and structural tailwinds, new product introductions and an operating model focused on accountability and closeness to customers.Hexagon launches new financial targets for the 2026 – 2030 period of average organic revenue growth of 4-6%, an EBITDA margin of 24-26%[1] and an EBITDA cash conversion of 90-100%. It also targets reducing Scope 1 & 2 emissions by 70% by 2030, from a 2022 baseline.

[1] EBITAC is defined as adjusted EBIT1 excluding capitalised and amortised R&D. See pages the appendix for further information

STOCKHOLM, April 30, 2026 /PRNewswire/ — Hexagon AB is hosting its Capital Markets Day today in London. At the event, President and CEO Anders Svensson, CFO Enrique Patrickson and the Presidents of Hexagon’s Business Areas will set out Hexagon’s ambitious growth strategy and its new 2026–2030 financial targets.

“Hexagon enters this new phase as a focused global leader in precision measurement and positioning, with a solutions portfolio essential to enabling industrial autonomy,” said Anders Svensson, President and CEO of Hexagon. “Our new targets reflect both the quality of our portfolio and the discipline of The Hexagon Way. With a strong leadership team and the financial flexibility to invest behind our growth priorities both organically and through synergistic acquisitions, we are well placed to deliver value creation for shareholders.”

“Today we are taking transparency to the next level — enhancing our disclosures, introducing EBITAC as our key profitability metric and providing clarity around our capital allocation priorities,” said Enrique Patrickson, CFO of Hexagon. “EBITAC is the right metric for Hexagon, a technology company with a significant R&D spend, funding market-leading product launches that drive our growth. With additional transparency comes additional accountability. We commit to drive capital allocation around R&D, M&A and Dividends with discipline and rigor.”

New sustainability targets

70% reduction in Scope 1 & 2 emissions by 2030 (from 2022 baseline)Net-zero by 2050

New 2026–2030 financial targets

Average annual organic revenue growth of 4-6%EBITAC margin in the range of 24-26%Annual cash conversion (of EBITAC) of 90-100%

A focused group focused on enabling industrial autonomy

Hexagon has undertaken significant portfolio changes, namely the upcoming spin-off of Octave and the sale of the Design & Engineering business. The resulting business is a focused global leader in precision measurement and positioning with proforma 2025 revenue of €3.7bn, EBITAC of €826m (22% EBITAC margin) and ~17,000 employees.

Hexagon is organised into three business areas – Manufacturing Intelligence, Infrastructure & Geospatial (formerly Geosystems) and Autonomous Solutions – alongside the Robotics Division, currently in an investment phase.

The overarching growth opportunity that underpins Hexagon’s long-term strategy is enabling customers to move towards true autonomy in their industrial operations.

President and CEO Anders Svensson will outline how Hexagon’s precision measurement and positioning technologies, digital twins and spatial intelligence capabilities are essential to enabling this true industrial autonomy. Hexagon holds market leadership positions across its serviceable addressable market, which is estimated to grow to ~€38bn by 2030.

Anders will also outline the key changes to Hexagon’s operating model. The Hexagon Way is an accountability-driven, decentralised model built around three strategic enablers: innovation and AI; portfolio management and M&A; and people & culture.

Central to this model is a clear accountability structure: the group’s three Business Areas are divided into 17 Divisions, each with full ownership of its financial performance and a defined strategic mandate covering three value creation priorities – Stability, Profitability and Growth.

The group-wide enablers allow Divisions to identify and execute on strategies targeted specifically to their markets and customers while drawing on the scale and resources of the broader Hexagon organisation. This balance of focused execution at the Division level and shared capability at the group level is designed to unlock each Division’s full potential and drive overall performance and shareholder value.

Hexagon’s new mid-term financial targets for 2026 to 2030 will be outlined by CFO Enrique Patrickson alongside a new financial framework including revised metric definitions designed to improve transparency, capital allocation and shareholder value creation.

The new 2026-30 through the cycle targets are:

Average annual organic revenue growth of 4–6% (CAGR 2026–2030)EBITAC margin in the range of 24–26%Annual cash conversion (of EBITAC) of 90–100%

In 2025, Hexagon achieved organic growth of 2.6%, an EBITAC margin of 22% and cash conversion (of EBITAC) of 109%.

Capital allocation

Hexagon’s capital allocation priorities are, in order: reinvestment in organic growth, value-accretive bolt-on M&A, a progressive dividend, and selective larger strategic moves where they enhance long-term shareholder value. The Group’s strong cash conversion and balance sheet provide the flexibility to pursue these priorities through the cycle.

Business Area presentations

Senior leadership from Hexagon’s Business Areas will provide additional context on strategy, markets and Business Area targets. The presenters will be:

Andreas Renulf, President, Manufacturing Intelligence Business AreaHenning Sandfort, President, Infrastructure & Geospatial Business AreaGordon Dale, President, Autonomous Solutions Business AreaArnaud Robert, President, Robotics Division

EBITAC – EBIT1 excluding capitalisation & amortisation of R&D

Hexagon is introducing EBITAC as its primary profitability measure. By immediately reflecting the full cost of R&D investments on the P&L, it will provide a tool to focus management firmly on the return on investment of R&D, go-to-market and capital investments and support performance management and capital allocation. The top end of the target EBITAC margin range (26%) was last achieved in 2021 and corresponds to the highest EBIT1 margin achieved by Hexagon in the last 5-years.

It is defined as adjusted EBIT1 excluding capitalised and amortised R&D.

Hexagon will continue to report EBIT1 (adjusted operating profit) for full transparency. A bridge between reported EBIT, EBIT1 and EBITAC and the EBITAC performance between 2024 and 2025 can be found in the appendix to this announcement.

Profitability metric bridge, 2025

Item

€M

Reported EBIT

575

Add: in year adjustments (impairments, restructuring, LTIP, PPA)

+372

EBIT1

947

Subtract: R&D capitalisation

-340

Add: R&D amortisation

+195

EBITAC

802

Subtract: in year robotics costs

+24

EBITAC (target definition)

826

Robotics – AEON, a potential global market leader in humanoid Robotics

Investment in Robotics to double from €24m in 2025 to €50m in 2026.Pilots with BMW, Schaeffler, Pilatus & Fill underway.Robotics is an exciting opportunity for significant value creation.

Due to its rapidly evolving structure Hexagon has decided to exclude Robotics from the 2026-30 financial targets and the calculation of EBITAC. This gives better visibility on the core group performance.

The financial performance of Robotics will be disclosed on a quarterly basis.

New sustainability targets

Hexagon is committed to operating responsibly for the good of the environment. It has set challenging new targets for emission reductions. Hexagon targets a 70% reduction in Scope 1 & 2 emissions by 2030 (from a 2022 baseline) and net-zero in Scope 1, 2 & 3 by 2050.

In 2025 Hexagon saw a 33% reduction in Scope 1 & 2 emissions from its 2022 baseline.

Joining instructions

The webcast will be streamed here: https://edge.media-server.com/mmc/p/d2han2qw/

FOR MORE INFORMATION, CONTACT:  
Tom Hull, Head of Investor Relations, Hexagon AB, +44 7442 678 437, ir@hexagon.com
Anton Heikenström, Investor Relations Manager, Hexagon AB, +46 8 601 26 26, ir@hexagon.com

This is information that Hexagon AB is obliged to make public pursuant to the EU Market Abuse Regulation. The information was submitted for publication, through the agency of the contact person set out above, at 08:00 CET on 30 April 2026.

Appendix – Reconciling EBIT1 & EBITAC performance, 2025 quarterly

Metric

Q1 2025

Q2 2025

Q3 2025

Q4 2025

FY 2025

Revenue €m

961.5

1,010.5

976.0

1,053.1

4,001.2

EBIT1 €m

248.7

260.0

264.7

299.1

1,072.4

Subtract: capitalisation of R&D €m

-94.6

-94.7

-91.1

-84.1

-364.5

Add: amortisation of R&D €m

54.6

54.3

59.2

50.4

218.5

EBITAC €m

208.7

219.6

232.8

265.3

926.4

In year robotics cost €mEBIT

-4.7

-5.9

-5.6

-7.6

-23.7

EBITAC (excluding robotics costs)

213.4

225.5

238.3

272.9

950.1

EBIT1 margin %

25.9 %

25.7 %

27.1 %

28.4 %

26.8 %

EBITAC margin %

21.7 %

21.7 %

23.8 %

25.2 %

23.2 %

EBITAC margin % (excluding robotics costs)

22.2 %

22.3 %

24.4 %

25.9 %

23.7 %

Appendix – Reconciling EBIT1 & EBITAC performance, 2025 quarterly, excluding Design & Engineering

Metric

Q1 2025

Q2 2025

Q3 2025

Q4 2025

FY 2025

Revenue €m

888.2

939.4

907.1

980.3

3,715.0

EBIT1 €m

225.0

231.1

235.5

255.4

947.0

Subtract: capitalisation of R&D €m

-88.6

-88.0

-84.8

-78.3

-339.6

Add: amortisation of R&D €m

48.2

48.0

53.3

45.8

195.3

EBITAC €m

184.6

191.1

204.0

223.0

802.7

In year robotics cost €m

-4.7

-5.9

-5.6

-7.6

-23.7

EBITAC (excluding robotics costs)

189.3

196.9

209.6

230.5

826.4

EBIT1 margin %

25.3 %

24.6 %

26.0 %

26.1 %

25.5 %

EBITAC margin %

20.8 %

20.3 %

22.5 %

22.7 %

21.6 %

EBITAC margin % (excluding robotics costs)

21.3 %

21.0 %

23.1 %

23.5 %

22.2 %

This information was brought to you by Cision http://news.cision.com

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Hexagon releases new targets at its Capital Markets Day 2026

 

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Accountants Streamline Cash Flow with ezACH Direct Deposit Software

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April 30, 2026

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Eliminate payment delays, reduce manual errors, and gain full control with a low-cost and high-quality ACH solution built for modern accounting workflows.

REDMOND, Wash., April 30, 2026 /PRNewswire/ — Halfpricesoft.com developers understand that businesses demand faster payments and greater financial control, and now accountants are rethinking how they manage transactions. ezACH direct deposit software will simplify payment processing, accelerate cash flow, and reduce costly errors.

Clients are encouraged to download and test ezACH today to purchase to confirm compatibility.

ezACH empowers accountants to securely process electronic payments for clients, vendors, payroll, and tax obligations, all from one streamlined platform. By generating ACH files that can be uploaded directly to a bank, the software removes the need for manual payment handling and outdated processes.

“Speed and accuracy are critical in today’s financial environment,” said Dr. Ge, Founder of Halfpricesoft.com. “ezACH gives accountants the ability to process multiple payments quickly and securely, without added complexity or cost.”

Designed with flexibility in mind, ezACH allows users to manage unlimited transactions for unlimited companies at a one-time flat rate of $199.00, making it a cost-effective alternative to subscription-based payment platforms. Try it today!

Why Accountants Are Making the Switch:

Process ACH payments for vendors, clients, payroll, and tax agenciesEliminate manual entry and reduce costly errorsImport data easily from CSV files or other Halfpricesoft applicationsHandle unlimited companies and transactions with no recurring feesMaintain full control over payment timing and processingClients can upload transactions for up to $4.99 to test compatibility

Halfpricesoft.com offers a variety of applications that will seamlessly integrate with ezACH software:

ezPaycheck: A new version of ezACH has just been released to support import CSV with ezPaycheck importing. ezCheckprinting: Business check writer for vendors, miscellaneous and draft checks. https://www.halfpricesoft.com/product_ezCheck.aspezAccounting: DIY in-house bookkeeping and payroll solution for one flat rate. https://www.halfpricesoft.com/accounting/accounting-software.asp

With a one-time cost of $199 per installation, ezACH offers long-term savings compared to subscription-based services. There are no hidden fees, and users can process unlimited ACH transactions. (Note: Banks may apply their own ACH processing fees. We recommend contacting your bank for compatibility prior to purchase).

Simplify the business operations and boost efficiency with the powerful, all-in-one solutions fromHalfpricesoft.com. To save both time and money, get started today at HalfPriceSoft.com for no cost or obligation

About Halfpricesoft.com

Halfpricesoft.com has been delivering affordable, reliable business software solutions for over 20 years. Its suite of products, including payroll, accounting, check printing, tax filing, and ACH deposit software, helps small businesses, accountants, and nonprofits streamline operations and reduce costs. Trusted by thousands nationwide, Halfpricesoft.com remains committed to simplifying financial management with powerful, budget-friendly tools.

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Neusoft Smart Go and Tencent Cloud Forge Strategic Partnership to Build a New AI-Powered Intelligent Cockpit Ecosystem

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April 30, 2026

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BEIJING, April 30, 2026 /PRNewswire/ — At Auto China 2026, Neusoft Smart Go, a subsidiary of Neusoft Corporation (SSE:600718), officially announced its strategic upgrade. The company now aims to become a global leading provider in full-domain upper-body electronics solutions for intelligent vehicles. At the same time, Neusoft Smart Go and Tencent Cloud announced a strategic partnership. Aligning with “AI-defined vehicles” trend, the two parties will focus on key areas such as intelligent cockpits, on-device AI large model applications, ecosystem content integration, in-vehicle cybersecurity, and cloud services. By integrating their technologies and resources, they will engage in in-depth collaboration to develop AI-powered intelligent cockpit products and solutions that offer enhanced interactivity and emotional experiences, accelerating the intelligent transformation of entire vehicles.

The integration of AI large models and ecosystems into vehicles is essentially a full-chain systematic project covering hardware-software architecture adaptation, data processing, compliance assurance, and real-time response. Currently, automakers face challenges such as high in-house R&D expenses, ecosystem integration hurdles, and a lack of differentiated user experiences. They urgently require full-domain solutions that seamlessly integrate hardware and software, offer comprehensive ecosystem coverage, and enable rapid mass production to meet users’ core demands for multi-modal interaction, full-scenario services, and continuous OTA updates.

As a leading cloud service provider in China, Tencent Cloud has core strengths in on-device large models, in-vehicle ecosystems and applications, cloud services, and data compliance assurance. It also offers a full-chain app ecosystem spanning social media, music, maps, and more. In this partnership, the two parties will take Neusoft Smart Go’s next-gen intelligent cockpit system as the core platform, deeply integrating Tencent Cloud’s on-device large models to jointly develop a benchmark AI-powered intelligent cockpit featuring natural conversations, proactive interactions, and highly emotional, smooth experiences. Furthermore, they will fully integrate a wide range of ecosystem apps, enabling seamless transitions between mobile phones and in-vehicle systems across all scenarios.

At present, Neusoft Smart Go has established a product matrix covering a full range of in-vehicle electronics solutions, including central computing platforms, cockpit-driving-parking integration, intelligent cockpits, intelligent communications, intelligent audio systems, and zonal control units. Through a dual-track strategy of high-end cutting-edge solutions and mature standardized products, it can flexibly meet the mass production needs of vehicle models across different regions and price segments worldwide. Leveraging Tencent’s intelligent driving cloud, data compliance, OTA technical support, and AI platform services, the two parties will provide stable, secure, and intelligent hardware-software integrated solutions tailored to the diverse needs of global automakers, comprehensively assisting them in achieving intelligent and AI-driven upgrades for entire vehicles.

Jian Guodong, Senior Vice President of Neusoft and CEO of Neusoft Smart Go, said, “The integration of AI large models and full-scenario ecosystems represents an inevitable trend and a shared vision for both Neusoft Smart Go and Tencent Intelligent Mobility. Leveraging Neusoft Smart Go’s technical expertise in the full domain of upper-body electronics and Tencent’s leading solutions in AI large models and full-chain ecosystems, the two parties will collaborate to provide global automakers with truly mass-producible and evolvable AI-powered intelligent cockpit solutions.”

Zhong Xuedan, Vice President and Head of Tencent Intelligent Mobility, said, “We share complementary strengths and similar philosophies with Neusoft Smart Go, laying a solid foundation for cooperation. Both parties will further deepen cooperation in AI-powered intelligent cockpits, jointly exploring proactive interactions and emotional services powered by large models, transforming the cockpit into a smarter companion that better understands users.”

The deep integration of on-device AI large models and full-scenario ecosystems is reshaping the value boundaries and user experiences of intelligent cockpits. The automotive industry needs to accelerate innovation and mass production, achieving a balance between advanced technologies and cost-effectiveness. Neusoft Smart Go will focus on enhancing its systematic integration, software-hardware synergy, and global delivery capabilities. Through collaboration with more ecosystem partners, it will provide sustained momentum for the intelligent transformation of the automotive industry.

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SOURCE Neusoft Corporation

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