Neuromorphic Processor Patent Landscape 2026
Neuromorphic Processor Patent Landscape in 2026
The neuromorphic processor patent field is heavily concentrated, with NVIDIA Corp alone holding a commanding lead among the top filers and the top five applicants accounting for 65% of the hundred largest filers’ combined total. Annual volume peaked in 2021 and has since eased, placing the field in a post-peak phase where strategic positioning around adjacent application branches is becoming the key competitive lever.
NVIDIA leads a highly concentrated field with a dominant first-mover position
NVIDIA Corp leads the neuromorphic processor patent landscape with 709 patent families, more than 2.6 times the holdings of the second-ranked Samsung Electronics at 267 patent families. Intel Corp (141), Qualcomm Inc (124), and IBM (105) complete a distinct first tier.
The top five applicants together account for 65% of the hundred largest filers’ combined total, signaling a strongly concentrated competitive structure where the gap between the first tier and the rest is wide. HRL Lab (54 patent families) begins a second tier of specialist players that drops off sharply from the leaders.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | NVIDIA Corporation | 709 | |
| 2 | Samsung Electronics Co., Ltd. | 267 | |
| 3 | Intel Corporation | 141 | |
| 4 | Qualcomm Incorporated | 124 | |
| 5 | International Business Machines Corporation (IBM) | 105 | |
| 6 | HRL Laboratories, LLC | 54 | |
| 7 | Polyn Technology Limited | 40 | |
| 8 | Siemens AG | 39 | |
| 9 | Tata Consultancy Services Ltd. | 29 | |
| 10 | BrainChip Inc. | 28 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | Sony Group Corporation | 26 | |
| 12 | Tsinghua University | 20 | |
| 13 | Lynxi Technologies Co., Ltd. | 19 | |
| 14 | POSTECH Academy-Industry Foundation | 19 | |
| 15 | Syntiant Corp. | 17 | |
| 16 | Toshiba Corporation | 16 | |
| 17 | Innatera Nanosystems B.V. | 15 | |
| 18 | DeepSig Inc. | 14 | |
| 19 | Snap Inc. | 14 | |
| 20 | ELECTRONICS & TELECOMM RES INST | 14 |
NVIDIA’s scale signals deep integration of neuromorphic architectures with AI model inference pipelines. Samsung’s position—bolstered by memory-integrated co-filings—suggests a hardware-software convergence strategy, while Intel and Qualcomm reflect edge-inference commercial motives. IBM’s holdings skew toward research-oriented AI model computing.
Filings from roughly 2024 onward are subject to publication lag and are expected to increase as pending applications publish; the recent-year counts should not be read as final. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Activity peaked in 2021 and is easing; AI model computing dominates the technology mix
The two charts below capture the trajectory of filing activity over time and the distribution of technology classes across the corpus, together revealing where momentum has been and where coverage remains thin.
Annual filing trend
Filings climbed steeply from 80 families in 2017 to a peak of 390 in 2021, then stepped down to 256 in 2022 and further to 158 in 2023. The 2024 and 2025 bars reflect partial publication and should not be read as confirmed declines. The overall multi-year build-up confirms this is a maturing, not nascent, field.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G06N (AI model computing) is the dominant class, reflecting the tight coupling between neuromorphic hardware and neural-network algorithm patents. G06F (digital data processing) is a solid second tier. Image processing (G06T, G06V, G06K), memory devices (G11C), and communications (H04L) each form a meaningful but smaller cluster, and hardware-level classes such as H01L (semiconductor devices) remain comparatively sparse relative to the algorithmic emphasis.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Neuromorphic chip and method and apparatus for det…
Disclosed are a method and an apparatus for detecting spike event or transmitting spike event information generated in a neuromorphic chip. The apparatus for detecting spike event generated in a neuromorphic chip may detect spike event information for a plurality of neurons included in the neuromorphic chip based on a neuron group. (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Operating room black-box device, system, method an… | 492 |
| 2 | Processing of communications signals using machine… | 346 |
| 3 | Processing of communications signals using machine… | 259 |
| 4 | Biomorphic rhythmic movement controller | 202 |
| 5 | System and method for biometric data capture for e… | 200 |
| 6 | Machine Learning to Accelerate Alloy Design | 178 |
| 7 | Robotic control system | 171 |
| 8 | Soft label generation for knowledge distillation | 157 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the competitive structure means for R&D investment decisions
Four structural observations—maturity, concentration, collaboration patterns, and geography—shape where a new entrant or challenger can most efficiently deploy R&D resources.
Post-peak field with consolidation dynamics
The lifecycle evidence places neuromorphic processors in a decline stage, with annual filings easing back from the 2021 peak of 390 families. This signals that broad platform patents have largely been filed, and the competitive frontier is shifting toward application-specific and efficiency-oriented claims. New entrants should expect strong prior-art density in core AI model computing classes and plan accordingly.
Post-peak · 2021 peakThree-tier structure with a wide gap after rank five
NVIDIA’s 709 patent families place it in a tier of its own; Samsung, Intel, Qualcomm, and IBM form a second cohort. Everything below HRL Lab (54 families) represents specialist or research-oriented players. For challengers, this concentration means freedom-to-operate searches are manageable within a small set of blocking portfolios, but licensing or design-around costs in the G06N space will be non-trivial.
Top-5 dominantSamsung anchors the most active co-filing network
Samsung Electronics is the most active co-filer, with 17 joint families alongside POSTECH Academy Industry Foundation, 4 with Sungkyunkwan University, 3 each with the University of Zurich, Seoul National University R&DB Foundation, and KAIST, and 2 each with the University of Montreal and Harvard University. IBM shows a different model, co-filing with its own China and UK subsidiaries (5 families each). This university-industry bridging by Samsung creates a pipeline of research-to-product IP that is difficult to replicate quickly.
Samsung-led ecosystemUS-dominant jurisdiction with PCT and EPO as key protection routes
The United States is the primary filing jurisdiction, followed by WIPO PCT filings and EPO. The United Kingdom, India, and China each hold meaningful counts, while Germany, Australia, and South Korea represent secondary protection markets. The relative sparsity in China (82 records) versus the US (1,234 records) is notable given the field’s commercial importance and may represent either strategic restraint or a coverage gap that competitors could exploit.
US-centric, PCT-broadenedGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
| Applicant | Collaborator | Co-filings |
|---|---|---|
| Samsung Electronics Co., Ltd. | 浦项工科大学校产学协力团 | 17 |
| International Business Machines Corporation (IBM) | IBM China Co., Ltd. | 5 |
| International Business Machines Corporation (IBM) | IBM United Kingdom Ltd. | 5 |
| Samsung Electronics Co., Ltd. | Sungkyunkwan University Industry-Academic Cooperation Foundation | 4 |
| Samsung Electronics Co., Ltd. | University of Zurich | 3 |
| Samsung Electronics Co., Ltd. | Seoul National University R&DB Foundation | 3 |
| Samsung Electronics Co., Ltd. | Korea Advanced Institute of Science and Technology (KAIST) | 2 |
| Samsung Electronics Co., Ltd. | University of Montreal | 2 |
| Samsung Electronics Co., Ltd. | President and Fellows of Harvard College | 2 |
| Samsung Electronics Co., Ltd. | Naboo Inc. | 1 |
Co-filing pairs, ranked by the number of jointly-filed patent families.
NVIDIA and Samsung lead; Siemens and BrainChip show divergent momentum
The leader and closest challenger differ sharply in technology emphasis and recent trajectory. Momentum data (recent three-year window vs. prior three-year window) reveals which players are consolidating versus which are stepping back.
NVIDIA Corp
NVIDIA leads with 709 patent families, concentrated in AI model computing (G06N3, 676 families), image data processing (G06T7, 141), and data recognition (G06K9, 106). This breadth reflects NVIDIA’s strategy of coupling neuromorphic architectures tightly to GPU-accelerated inference pipelines. Recent momentum shows a -58% trend versus the prior period, consistent with the field-wide post-peak easing rather than a strategic retreat.
families: 709Samsung Electronics
Samsung holds 267 patent families and distinguishes itself by pairing AI model computing (G06N3, 241) with memory device integration (G11C11, 51) and digital data processing (G06F7, 43)—a hardware-software stack approach. Recent momentum shows a -52% trend, but Samsung’s active university co-filing network (10 recorded collaboration pairs) maintains a research pipeline that is among the broadest in the corpus.
families: 267| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| NVIDIA Corporation | 197 | ▼ -58% |
| Samsung Electronics Co., Ltd. | 61 | ▼ -52% |
| Intel Corporation | 24 | ▬ +4% |
| International Business Machines Corporation (IBM) | 7 | ▼ -89% |
| Polyn Technology Limited | 19 | ▼ -10% |
| Siemens AG | 29 | ▲ +190% |
| Tata Consultancy Services Ltd. | 13 | ▲ +8% |
| BrainChip Inc. | 26 | ▲ new entrant |
Under-served branches adjacent to the neuromorphic core
The following branches show lower patent density relative to the dominant G06N class. They are observations of relative sparsity; where a branch also has plausible technical coupling and a realistic entry path, that is noted explicitly.
G11C · Static & digital memories
Memory integration is a foundational bottleneck for neuromorphic inference—synaptic weight storage and in-memory computing are active research areas. With 131 records in this branch versus 2,145 in G06N, the hardware-level memory angle is comparatively under-patented. Samsung is the primary incumbent here (G11C11, 51 families); competitors with SRAM, RRAM, or emerging non-volatile memory expertise could find a differentiated entry path by targeting memory-compute co-design claims.
Search this in Eureka →G10L · Speech & audio analysis/synthesis
Spiking neural networks are well-suited to temporal, low-power audio processing—a use case that maps naturally to always-on keyword detection and edge audio AI. With only 85 records in G10L across the corpus, this application branch is sparsely covered relative to the image and general AI classes. Specialist players such as Syntiant and Innatera Nanosystems already address this space, but the overall patent density remains low enough that focused filing around spiking audio architectures could establish meaningful position.
Search this in Eureka →How leading applicants differ by technology route
Strength of each leader across the main technology routes.
| Player | G06N 3 · Computing based on AI models | G06N 20 · Computing based on AI models | G06K 9 · Data recognition & presentation | G06T 7 · Image data processing & generation | G06V 10 · Image/video recognition |
|---|---|---|---|---|---|
| NVIDIA Corporation | Strong · 676 | Emerging · 65 | Emerging · 106 | Moderate · 141 | Emerging · 91 |
| Samsung Electronics Co., Ltd. | Strong · 241 | Emerging · 31 | Emerging · 12 | Emerging · 4 | Emerging · 9 |
| International Business Machines Corporation (IBM) | Strong · 98 | Moderate · 21 | Emerging · 4 | Emerging · 3 | Emerging · 5 |
| Qualcomm Incorporated | Strong · 120 | Absent | Emerging · 5 | Absent | Absent |
| Intel Corporation | Strong · 97 | Emerging · 13 | Absent | Absent | Absent |
| HRL Laboratories, LLC | Strong · 53 | Absent | Moderate · 18 | Emerging · 5 | Emerging · 8 |
| Polyn Technology Limited | Strong · 40 | Absent | Absent | Absent | Absent |
Frequently asked questions
The corpus contains 1,934 patent families in scope for neuromorphic processor technology across the analyzed global dataset.
NVIDIA Corp leads with 709 patent families, more than 2.6 times the holdings of the second-ranked Samsung Electronics (267 patent families).
Annual filings peaked in 2021 at 390 patent families, up from 80 in 2017. Since then, annual volume has eased to 256 in 2022 and 158 in 2023. Counts for 2024 and beyond are subject to publication lag.
G06N (computing based on AI models) is the dominant IPC class, reflecting the tight integration between neuromorphic hardware architectures and neural-network algorithm patents across the corpus.
The United States is the primary filing jurisdiction, followed by WIPO PCT filings and the EPO. The United Kingdom, India, and China also show meaningful filing activity, while Germany, Australia, and South Korea represent secondary protection markets.
Siemens AG shows the strongest upward momentum among established players at +190% in recent filings versus the prior period. Tata Consultancy Services shows a modest +8% increase. BrainChip Inc appears as a new entrant in the recent window. Most other top filers, including NVIDIA and Samsung, show declining recent counts consistent with the post-peak field trend.
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Disclaimer. This page is generated from PatSnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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