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Artificial Intelligence (AI) Chips Market to Grow by USD 902.65 Billion (2025-2029), Focus on AI Chips for Smartphones Drives Growth, Report with AI Trends – Technavio

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NEW YORK, Jan. 24, 2025 /PRNewswire/ — Report on how AI is redefining market landscape – The global artificial intelligence (AI) chips market size is estimated to grow by USD 902.65 billion from 2025-2029, according to Technavio. The market is estimated to grow at a CAGR of over 81.2% during the forecast period. Increased focus on developing AI chips for smartphones is driving market growth, with a trend towards convergence of AI and IoT. However, dearth of technically skilled workers for ai chips development poses a challenge. Key market players include Advanced Micro Devices Inc., Baidu Inc., Broadcom Inc., Cerebras, Fujitsu Ltd., Google LLC, Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd., and Tesla Inc..

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Artificial Intelligence (AI) Chips Market Scope

Report Coverage

Details

Base year

2024

Historic period

2019 – 2023

Forecast period

2025-2029

Growth momentum & CAGR

Accelerate at a CAGR of 81.2%

Market growth 2025-2029

USD 902.65 billion

Market structure

Fragmented

YoY growth 2022-2023 (%)

61.7

Regional analysis

North America, Europe, APAC, South America, and Middle East and Africa

Performing market contribution

North America at 42%

Key countries

US, Canada, China, UK, Germany, France, Japan, Italy, India, and Brazil

Key companies profiled

Advanced Micro Devices Inc., Baidu Inc., Broadcom Inc., Cerebras, Fujitsu Ltd., Google LLC, Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd., and Tesla Inc.

Market Driver

Artificial Intelligence (AI) is revolutionizing industries from healthcare to retail, finance, automotive, and more. Deep learning and machine learning algorithms require powerful hardware components like AI chips. Advanced Micro Devices (AMD) and Nvidia lead the market with their Trainium2 chip and A100 chip, respectively. These chips use highbandwidth memory for energy efficiency and high computing power. Quantum computing and generative AI are emerging trends in AI technologies. AI chip lines, such as Ascend 910B chipset and H200 chipset, are designed specifically for AI applications. Cloud providers like Microsoft Azure, Amazon Web Services, and Google Cloud offer AI services, while edge computing enables real-time data processing on Edge devices. Ethical concerns surrounding AI use are rising. AI applications in healthcare, elder care, and IoT devices require high security and privacy. ML and DL algorithms power computer vision, image recognition, and pose detection, while cognitive computing and machine intelligence enable personalized health and treatment devices. AI technologies require various hardware components, including CPUs, GPUs, FPGAs, ASICs, DSPs, microcontrollers, frame buffers, and display devices. Energy efficiency, latency, and parallel computing are crucial factors for AI data centers. Theoretical and algorithmic basis, automatic analysis, and extraction are essential for AI applications. Patent filings for AI technologies are increasing, with applications in various industries, including manufacturing machines, wearable devices, smart homes, and connected cars. System failure and malfunctioning are concerns, and ethical considerations are necessary for the successful implementation of AI technologies. 

The Internet of Things (IoT) market is experiencing significant growth due to the numerous advantages it offers in various industries, including aerospace and defense, automotive, consumer electronics, healthcare, and more. IoT devices, which include cameras, drones, smart speakers, smartphones, smart TVs, and others, are making decisions based on data they receive without human intervention. To enhance the capabilities of these devices, manufacturers are integrating Human-Machine Interface (HMI) technologies and deploying AI chips. These chips enable power-efficient data processing and machine learning computation, allowing IoT devices to function more intelligently and autonomously. The integration of AI chips in IoT devices is a key trend driving market growth. 

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Market Challenges

Artificial Intelligence (AI) is revolutionizing industries from healthcare to retail, finance, and automotive. However, the growing demand for AI technologies, including deep learning and machine learning, puts pressure on hardware components like AI chips. Companies like Advanced Micro Devices and Nvidia are investing in AI chip lines, such as the Trainium2 chip and Nvidia’s A100 chip, to meet this demand. These chips enable AI algorithms to run efficiently, powering applications like image recognition and pose detection. However, challenges remain. Energy efficiency is crucial, as AI data centers require vast amounts of power. Quantum computing and generative AI may offer solutions, but they present complexities. Ethical concerns around AI use also arise. Edge computing and Edge devices are becoming essential for real-time applications, reducing latency and processing data locally. Big data requires high-bandwidth memory and parallel computing, which can be achieved through system on chip, multichip module, or ASICs. Major cloud providers like Microsoft Azure, Amazon Web Services, and Google Cloud offer AI services, but they face competition from edge devices and AI data centers. AI applications in industries like healthcare, retail, finance, and automotive require specialized hardware, such as CPUs, GPUs, FPGAs, and DSPs. The future of AI lies in the intersection of AI technologies, hardware components, and ethical considerations.The AI chips market is experiencing significant growth due to the potential revenue increases for businesses adopting artificial intelligence. However, the lack of skilled labor in AI technology poses a significant challenge to market expansion. Companies must carefully consider the high research and development costs and potential talent shortage before implementing AI solutions. Enterprise AI implementation is currently hindered by the scarcity of experienced professionals with the necessary technical expertise in this field.

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Segment Overview

This artificial intelligence (ai) chips market report extensively covers market segmentation by

Product 1.1 ASICs1.2 GPUs1.3 CPUs1.4 FPGAsEnd-user 2.1 Media and advertising2.2 BFSI2.3 IT and telecommunication2.4 OthersGeography 3.1 North America3.2 Europe3.3 APAC3.4 South America3.5 Middle East and AfricaProcessing TypeApplicationTechnology

1.1 ASICs- Artificial Intelligence (AI) chips are experiencing significant growth, with application-specific integrated circuits (ASICs) leading the way. ASICs are customized chips designed for specific functions, offering faster performance than GPUs and FPGAs. Google’s Tensor Processing Unit (TPU) is an ASIC-based AI chip, specifically engineered for deep neural networks. TPU is a hardware-software solution that learns tasks by analyzing large data sets. It’s already being used in Google Search and Google Street View. Data centers are integrating TPUs into servers to manage data efficiently. TPU’s instruction set allows TensorFlow programs to be modified, enabling new algorithms. TensorFlow is an open-source machine learning library, making ASIC-based AI chips a promising choice for data center applications. The use of ASICs is driving the growth of AI chips market, providing superior performance and speed compared to GPUs, FPGAs, and CPUs.

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Research Analysis

Artificial Intelligence (AI) Chips Market: The global AI Chips Market is experiencing significant growth due to the increasing demand for advanced AI technologies in various industries. AI Chips are specialized hardware components designed to accelerate AI algorithms, including deep learning and machine learning. These chips are integral to AI applications in robotics, autonomous vehicles, healthcare, retail, finance, automotive, IoT devices, and more. Quantum computing is also expected to revolutionize AI technologies, leading to the development of more powerful AI chips. Advanced Micro and other key players are investing heavily in AI chip research and development. The market includes various types of chips such as CPU, FPGA, GPU, system on chip, multichip module, and Trainium2 chip. Ethical concerns surrounding AI are also driving the need for more efficient and specific integrated AI chips. The market is segmented into cloud and edge computing, with the edge computing segment expected to grow rapidly due to the increasing demand for real-time AI processing. Highbandwidth memory is another critical component of AI chips, enabling faster data processing and analysis. Overall, the AI Chips Market is poised for significant growth in the coming years.

Market Research Overview

Artificial Intelligence (AI) Chips Market: Overview The Artificial Intelligence (AI) Chips Market is a rapidly growing sector that focuses on designing and manufacturing specialized hardware components for AI applications. These chips are designed to accelerate AI algorithms, including deep learning and machine learning, to enable advanced functionalities such as image recognition, pose detection, behavioral patterns analysis, and natural language processing. AI Chips are essential components of various AI technologies, including robotics, quantum computing, and cognitive computing. They come in different forms, such as System on Chip (SoC), Multichip Module (MCM), CPU, GPU, FPGA, ASIC, DSP, and microcontrollers. The market for AI Chips is driven by the increasing demand for AI applications in various industries, including healthcare, retail, finance, automotive, and manufacturing. The need for real-time data processing and energy efficiency is also a significant factor driving the growth of the market. AI Chips are used in both centralized cloud servers and edge devices for data processing. Centralized cloud servers, such as Microsoft Azure, Amazon Web Services, and Google Cloud, require high computing power and high-bandwidth memory, making GPUs and CPUs popular choices for AI Chips. Edge devices, on the other hand, require low power consumption and small form factors, making FPGAs and ASICs popular choices. The market for AI Chips is also driven by the increasing use of AI in mobile applications, healthcare, and IoT devices. Ethical concerns regarding AI and the elderly population’s growing demand for personalized health solutions are also expected to fuel the market’s growth. Some of the notable AI Chips in the market include Nvidia’s A100 chip, Ascend 910B chipset, and H200 chipset. Companies are also investing heavily in patent filing and system failure prevention to ensure the reliability and efficiency of their AI Chips. The market for AI Chips is expected to continue growing as AI applications become more prevalent in various industries. The increasing use of AI in real-time applications, such as autonomous vehicles and smart homes, is also expected to drive the market’s growth. However, the market’s growth may be hindered by the high cost of developing and manufacturing AI Chips and the ethical concerns surrounding AI. In conclusion, the AI Chips Market is a dynamic and growing sector that plays a crucial role in enabling advanced AI applications across various industries. The market’s growth is driven by the increasing demand for AI applications, the need for energy efficiency, and the development of new AI technologies, such as generative AI and cognitive computing. However, the market’s growth may be hindered by ethical concerns and the high cost of developing and manufacturing AI Chips.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

ProductASICsGPUsCPUsFPGAsEnd-userMedia And AdvertisingBFSIIT And TelecommunicationOthersGeographyNorth AmericaEuropeAPACSouth AmericaMiddle East And AfricaProcessing TypeApplicationTechnology

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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Genedata Expands AI Discovery Workflows with NVIDIA BioNeMo Open Models, Including the New RFD4-Proteina Release

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Bringing next-generation binder design models into production discovery

BASEL, Switzerland, Oct. 22, 2026 /PRNewswire/ — Genedata, a Danaher company, and the leading provider of enterprise software solutions for biopharmaceutical R&D, today announced the addition of the new RFD4-Proteina binder design model into Genedata’s AI-enabled discovery workflows, following the model’s introduction at NVIDIA GTC Berlin. As an early ecosystem partner, Genedata is among the first companies to make RFD4-Proteina available within its production discovery workflows. By connecting AI-generated molecular designs, scientific data, and laboratory results, Genedata helps researchers transform AI predictions into continuous learning cycles that accelerate biologics discovery.

The workflow begins with scientists defining target characteristics and required properties using Genedata’s AI co-scientist. NVIDIA’s open protein design models then generate and evaluate candidate binders within Genedata. As candidates move into laboratory testing, results are captured and linked back to the original designs, helping scientists refine and rank the next round.

“Advances in AI are creating unprecedented opportunities for protein and antibody discovery, but unlocking their full value requires more than access to powerful models alone,” said Othmar Pfannes, Ph.D., President of Genedata. “Researchers need a way to connect molecular design, experimental execution, and scientific data into a continuous learning process. Genedata serves as the digital backbone that brings these elements together, helping scientists evaluate more candidates before testing, preserve the scientific context behind each outcome, and build knowledge from one discovery cycle to the next.”

While advances in generative AI are rapidly expanding what scientists can design, many organizations still struggle to operationalize these models within production scientific research workflows. Genedata provides the orchestration, governance, and scientific data foundation needed to deploy NVIDIA BioNeMo open models, including RFD4-Proteina, directly within the discovery workflows scientists use every day. Researchers can apply AI-generated designs within established processes while maintaining lineage, traceability, and scientific context across the discovery lifecycle.

Within Danaher’s autonomous laboratory initiative, these capabilities connect AI, automation, and scientific data in a closed-loop discovery framework where each experimental outcome informs the next design cycle, creating a continuous learn-and-improve process that advances science while keeping scientists in control.

About Genedata
Genedata, a Danaher company and the leading provider of enterprise software solutions for biopharma R&D, transforms biopharma data into intelligence. Our innovative solutions combine deep science, technology, and AI domain knowledge. Leading biopharma organizations and cutting-edge biotechs partner with Genedata to digitalize and automate complex data workflows. Our advanced analytics and embedded AI enable data-driven decisions. From early discovery through development to the clinic, Genedata solutions drive innovation and maximize ROI being trusted by customers worldwide for more than 25 years.

www.genedata.com
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About Danaher
Danaher is a leading global life sciences and diagnostics innovator, committed to accelerating the power of science and technology to improve human health. Through our connected ecosystem of industry-leading businesses, we work side by side with customers to solve their most complex scientific and clinical challenges—helping move innovations from discovery to delivery faster for patients who depend on them. Powered by the Danaher Business System, our advanced science and technology and proven ability to innovate help enable faster, more accurate diagnoses and reduce the time, cost, and risk required to discover, develop, and deliver life-changing therapies. Through continuous improvement and operational excellence, our approximately 60,000 associates worldwide are focused on delivering lasting impact and improving quality of life around the world, while building a healthier, more sustainable tomorrow. Explore more at www.danaher.com.

Disclaimer

The statements in this press release that relate to future plans, events or performance are forward-looking statements that involve risks and uncertainties, including risks associated with uncertainties related to contract cancellations, developing risks, competitive factors, uncertainties pertaining to customer orders, demand for products and services, development of markets for the Company’s products and services. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date hereof. The Company undertakes no obligation to release publicly the result of any revisions to these forward-looking statements that may be made to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events.

All product and service names mentioned are the trademarks of their respective companies.

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SOURCE Genedata

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Bybit AI Empowers Users with Their Personal Financial Edge, Adding Personalization and Memory

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DUBAI, UAE, Oct. 22, 2026 /PRNewswire/ — Bybit, the New Financial Platform trusted by more than 80 million users worldwide, has announced new personalization and memory features for Bybit AI, its in-app intelligent conversational layer. Bybit AI now builds a profile from each user’s assets, positions, behavior and risk profile, connecting wealth, markets and trading across the Bybit ecosystem.

Launched in September, Bybit AI organically unifies Bybit’s core services within a single chat interface. The newly added features extend its capacity from responding to individual requests to maintaining a continuous understanding of the user, giving each user their personal financial edge.

Putting the user at the center, Bybit AI is evolving on three pillars:

Personalized: With permissions granted and limits set, Bybit AI analyzes actual account information, including financial behavior and risk profile alongside assets and positions, to generate outputs tailored to the individual.Connected: Bybit AI links Markets, Trading, Earn, Card and other Bybit products, drawing on the full picture of a user’s holdings and activity rather than a single product.Remembered: Users can proactively share their preferences with Bybit AI, which retains this context through long-term memory so that each conversation builds on the previous one.

The release also introduces Featured, a set of customized entry points for specific use cases. Each entry point offers predefined prompts, such as generating a wealth management plan based on a user’s assets and risk tolerance, and returns structured analysis with key data, clear insights and suggested next steps.

Bybit AI supports main account operations while giving users the option to deploy it within a dedicated Bybit AI sub-account. The AI-powered assistant is built on a security-first architecture. Outputs are provided for informational purposes only and do not constitute investment advice. Instructions are executed in chats only after customer authorizations.

Bybit expects to introduce further updates to Bybit AI as it continues to build toward AI-native financial services, with conversational intelligence positioned as core infrastructure.

To explore Bybit AI and learn more about how it works, users may visit: Bybit AI  – Learn how to use Bybit through conversation.

#Bybit  / #NewFinancialPlatform 

About Bybit

Bybit is The New Financial Platform.

We believe every person should have access to every financial opportunity on earth. That’s why we’re building the first intelligent platform that connects anyone, anywhere to the world’s finance.

Trusted by more than 80 million users worldwide, Bybit brings together investing, trading, payments, and wealth-building in a single secure and intelligent ecosystem. Through the combination of AI-powered technology, deep global liquidity, robust security, and transparent operations, Bybit makes global finance more accessible, efficient, and empowering for everyone.

Built for everyone. Powered by intelligence. Open to the world.

Learn more at Bybit.com.

For more details about Bybit, please visit Bybit Press

For media inquiries, please contact: media@bybit.com

For updates, please follow: Bybit’s Communities and Social Media

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Poq is now a Shopify Certified Technology Partner

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LONDON, Oct. 22, 2026 /PRNewswire/ —  poq, the native mobile app platform for retail brands, today announced it has been recognised as a Shopify Certified Technology Partner. Shopify’s certification is reserved for app partners that meet Shopify’s standards for quality, security, performance and support. poq is now listed in the Shopify Technology Partner Directory and the Certified Technology Partner App Store Collection, making it easier for enterprise Shopify merchants to find and adopt a proven native app platform.

poq already powers native iOS and Android apps for joint customers including Ardene, Steve Madden UK, e.l.f. Beauty (globally), Horze (pan-European), Mamas & Papas (UK) and ECO. Modern Essentials (ANZ and UK). Across the poq platform, shoppers convert at 1.8 times the rate of mobile web, based on the median across 21 brands from January 2025 to January 2026.

“Certification from Shopify is independent validation that poq meets the high standard Shopify sets for its technology partners,” said Jay Johnston, CEO of poq. “Our customers use their apps to build loyalty and drive repeat purchases from their most valuable shoppers. This recognition means more Shopify merchants can launch a high-performing native app with confidence, on a platform already proven at scale across four continents.”

Results for Shopify Brands

European equestrian retailer Horze moved to Shopify and chose to stay with poq for its native app. “After choosing to continue working together, I can confidently say that this was absolutely the right decision. The level of motivation, ownership, and commitment the poq team demonstrated throughout the project was truly impressive,” said Dominik Schlag, CFO of Horze.

In the UK, Mamas & Papas uses its poq app to make shopping easier for busy parents. “Our poq app makes shopping with us quick and easy wherever they are, and drives loyalty and repeat purchases,” said Jo Molineux, Digital Director at Mamas & Papas.

About poq

poq is a leading Software-as-a-Service (SaaS) platform that empowers retailers and brands to create and maintain engaging, high-performance native mobile apps. With a focus on driving customer engagement and revenue, poq’s platform enables seamless integration, powerful personalisation, and an enhanced shopping experience for businesses worldwide. Learn more at poqcommerce.com.

Media contact
Emma Williams, Marketing Lead
emma.williams@poqcommerce.com  

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