NVIDIA and SK hynix Forge Multiyear Tech Partnership for AI Memory
Written by Emily J. Thompson, Senior Investment Analyst
Updated: 1 hour ago
0mins
Source: Yahoo Finance
- Technology Partnership: NVIDIA and SK hynix have established a multiyear technology partnership aimed at co-developing next-generation memory to support the global AI factory buildout, which is expected to significantly enhance the efficiency of semiconductor design and manufacturing.
- Market Diversification: Through this collaboration, SK hynix will enter new markets created by NVIDIA, including AI infrastructure and personal AI, co-developing memory products to meet the demands of high-end offerings like NVIDIA Vera Rubin AI supercomputers.
- AI-Driven Design Acceleration: The two companies will leverage NVIDIA's CUDA-X libraries and PhysicsNeMo framework to accelerate semiconductor chip design and manufacturing processes, which is anticipated to shorten development cycles and enhance product performance, driving technological advancements in the industry.
- Digital Twin Technology: SK hynix is developing digital twin technology to enable fully autonomous semiconductor manufacturing, utilizing NVIDIA's Omniverse and cuOpt technologies to optimize factory operations, thereby improving production efficiency and decision-making capabilities.
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Analyst Views on NVDA
Wall Street analysts forecast NVDA stock price to rise
41 Analyst Rating
39 Buy
1 Hold
1 Sell
Strong Buy
Current: 218.660
Low
200.00
Averages
264.97
High
352.00
Current: 218.660
Low
200.00
Averages
264.97
High
352.00
About NVDA
NVIDIA Corporation is an artificial intelligence (AI) infrastructure company. The Company is engaged in accelerated computing to help solve the challenging computational problems. Its segments include Compute & Networking and Graphics. The Compute & Networking segment includes its Data Center accelerated computing and networking platforms and AI solutions and software, and automotive platforms and autonomous and electric vehicle solutions, including software. The Graphics segment includes GeForce GPUs for gaming and personal computers (PCs), and Quadro/NVIDIA RTX GPUs for enterprise workstation graphics. Its technology stack includes the foundational NVIDIA CUDA development platform that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, frameworks, algorithms, software development kits (SDKs), and application programming interfaces (APIs). Its platforms address four markets, which include Data Center, Gaming, Professional Visualization, and Automotive.
About the author
Emily J. Thompson
Emily J. Thompson, a Chartered Financial Analyst (CFA) with 12 years in investment research, graduated with honors from the Wharton School. Specializing in industrial and technology stocks, she provides in-depth analysis for Intellectia’s earnings and market brief reports.
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- High-Performance AI Services: The new AI cloud will focus on GPU computing, supporting training, inference, and agentic AI workloads, which is expected to significantly reduce token production costs per megawatt, thereby improving operational efficiency and profitability for enterprises.
- Expanded Collaborative Research: SK Group and NVIDIA will jointly pursue research on next-generation AI factory architectures, focusing on accelerated computing and memory technologies, aiming to drive innovation and optimization in AI infrastructure, further solidifying their leadership in the AI sector.
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See More
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- Market Diversification: This collaboration allows SK hynix to enter new markets created by NVIDIA, including personal AI and physical AI, co-developing memory for NVIDIA Vera Rubin AI supercomputers and Jetson Thor robotic computing platforms, enhancing its competitive position in the industry.
- Accelerated Semiconductor Design: SK hynix will leverage NVIDIA's CUDA-X libraries and PhysicsNeMo framework to accelerate semiconductor simulations and design processes, improving core workload acceleration across its in-house engineering codes and enhancing the efficiency of technology computer-aided design and computational lithography workflows.
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