The technology industry continues to be a hotbed of innovation. Activity driven by the increasing demand for scalable and cost-effective data storage solutions, the proliferation of big data applications, and the need for real-time analytics, as well as growing importance of technologies such as distributed storage systems, data partitioning techniques, and advanced indexing algorithms distributed storage systems, data partitioning techniques, and advanced indexing algorithms. These technologies enable efficient and intelligent data storage, retrieval, and analysis in the cloud, empowering organisations with enhanced scalability, performance, and decision-making capabilities. In the last three years alone, there have been over 3.6 million patents filed and granted in the technology industry, according to GlobalData’s report on Innovation in Cloud: Neural networks for data storage. Buy the report here.

According to GlobalData’s Technology Foresights, which uses over 2.5 million patents to analyse innovation intensity for the technology industry, there are 300+ innovation areas that will shape the future of the industry.

Neural networks for data storage is a key innovation area in cloud

Neural networks data storage is a form of artificial intelligence (AI) technology that employs interconnected nodes to store and retrieve data. These networks consist of layered nodes that learn from the data they process, allowing for efficient storage of vast amounts of information. Neural networks can be trained to identify patterns within the data, making them well-suited for intricate data storage requirements. Their applications span diverse domains, including image recognition, natural language processing, and predictive analysis.

GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 30+ companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of neural networks for data storage.

Key players in neural networks for data storage – a disruptive innovation in the technology industry

‘Application diversity’ measures the number of different applications identified for each relevant patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.

‘Geographic reach’ refers to the number of different countries each relevant patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.

Patent volumes related to neural networks for data storage

Company Total patents (2010 - 2022) Premium intelligence on the world's largest companies
Intel 64 Unlock Company Profile
International Business Machines (IBM) 45 Unlock Company Profile
SK Square 44 Unlock Company Profile
Samsung Group 33 Unlock Company Profile
Advanced Micro Devices 32 Unlock Company Profile
TDK 23 Unlock Company Profile 18 Unlock Company Profile
Cambricon Technologies 18 Unlock Company Profile
Macronix International 16 Unlock Company Profile
Toshiba 15 Unlock Company Profile
SoftBank Group 14 Unlock Company Profile
Meta Platforms 13 Unlock Company Profile
STMicroelectronics 12 Unlock Company Profile
Microsoft 12 Unlock Company Profile
Tenstorrent 9 Unlock Company Profile
Hewlett Packard Enterprise 9 Unlock Company Profile
NVIDIA 8 Unlock Company Profile
Accenture 8 Unlock Company Profile
Qualcomm 7 Unlock Company Profile
MemryX 7 Unlock Company Profile
Vivante 7 Unlock Company Profile
Cbfi Investment 6 Unlock Company Profile
eMemory Technology 6 Unlock Company Profile
General Motors 6 Unlock Company Profile
Alphabet 5 Unlock Company Profile
Sony Group 5 Unlock Company Profile
Huawei Investment & Holding 5 Unlock Company Profile
China Pacific Insurance 5 Unlock Company Profile
Panasonic 5 Unlock Company Profile
Tesla 5 Unlock Company Profile
Semiconductor Energy Laboratory 5 Unlock Company Profile
Texas Instruments 5 Unlock Company Profile

Source: GlobalData Patent Analytics

Intel is a leading patent filer in neural networks for storage. The company’s patents are aimed at invention describing a computing apparatus to perform machine learning operations.

The apparatus comprises a decode unit to decode a single instruction into a decoded instruction that specifies multiple operands including an input value and a quantized weight value associated with a neural network.

It also includes an arithmetic logic unit including a barrel shifter, an adder, and an accumulator register to execute the decoded instruction. The barrel shifter is used to shift the input value by the quantized weight value to generate a shifted input value and the adder is used to add the shifted input value to a value stored in the accumulator register and update the value stored in the accumulator register.

Other prominent patent filers in the space include IBM and SK Square.

By geographic reach, Semiconductor Energy Laboratory leads the pack, followed by Hewlett Packard Enterprise and TDK. In terms of application diversity, Macronix International holds the top position, followed by Qualcomm and Panasonic.

Neural networks for data storage can efficiently store, process, and retrieve data on a massive scale. It enables scalable, flexible, and cost-effective data storage solutions and empowers organisations to handle big data applications, gain valuable insights, and make data-driven decisions. Neural networks for data storage are transforming the landscape of data storage, enabling businesses to efficiently manage and extract value from their data assets.

To further understand how cloud is disrupting the technology industry, access GlobalData’s latest thematic research report on Cloud Computing – Thematic Intelligence.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.