BRN Discussion Ongoing

[CHIPS]

Hi @CHIPS,

I think you’re confusing Gabriela Mystkowska, who is a Polish PhD student at the University of Pisa’s Department of Information Engineering as well as a Visiting Researcher at ESA (which also happens to be the organisation that is co-funding her PhD), with Sylvia Traxler, who is a Senior Principal Software Engineer at Raytheon Technologies.

https://www.linkedin.com/in/gabriela-mystkowska/

Sylvia Traxler - Raytheon Technologies | LinkedIn

Experience: Raytheon Technologies · Education: The University of Texas at Austin · Location: Greater Tampa Bay Area · 448 connections on LinkedIn. View Sylvia Traxler’s profile on LinkedIn, a professional community of 1 billion members.

www.linkedin.com

Sylvia Traxler was one of three RTX employees visiting the BrainChip private suite at the Venetian Tower during CES 2025. We know that to be a fact, since she and her colleagues Bryce Nakamori and Geoff Martin were featured in a group photo together with Steve Thorne and JP Wright, which was later posted by BrainChip on LinkedIn. However, that “Day 2: Productive Day at #CES2025” post publicly revealing RTX as a BRN partner vanished into thin air shortly after.

Some of us had long figured out that RTX were likely the subcontractor in question with regards to the AFRL SBIR contract that BRN had been awarded in December 2024, but apparently the negotiations were either not completely cut and dried or there were other reasons why this partnership was not yet supposed to go public. Anyway, IMO a very unprofessional slip-up to completely delete a publicly visible LinkedIn post without a comment. They could have just edited it instead.

Here are several 9 January 2025 posts by @Tothemoon24, @miaeffect, @Quiltman and @SERA2g, which prove that the LinkedIn post in question did exist for a short time - unfortunately, no one that day appears to have posted the actual picture showing the RTX trio…

View attachment 89723
View attachment 89724 View attachment 89725
View attachment 89722

Ah, you are right ... similar looking, but different persons. Sorry.

 

[7für7]

When apple? When META?

Eye Tracking

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brainchip.com

 

[itsol4605]

Which company is a leader in neuromorphic computing that offers a market-ready chip or market-ready IP?

ChatGPT:
In short: BrainChip (Akida) and SynSense are currently the leaders, because they actually offer commercially available neuromorphic products.

• BrainChip – leader in licensable IP: Provides the neuromorphic Akida design as commercially licensable IP (and modules). They already have real licensing deals, e.g. with Frontgrade Gaisler for space applications. If you’re looking for “neuromorphic + market-ready + licensable IP,” BrainChip is the clear choice.
• SynSense – leader in market-ready chips: Sells production chips (Speck, Xylo) and dev kits for vision/audio. Speck is already in mass production, and the Xylo family is on the market with product pages and kits. If you need ready-to-use chips instead of IP, SynSense is at the forefront.

For context:

• Intel (Loihi 2 / Hala Point) and IBM (TrueNorth) are important research platforms, but not available as market-ready, general commercial products or IP.

Bottom line:
If you want licensable IP ⇒ go with BrainChip.
If you want off-the-shelf chips ⇒ go with SynSense.

Do you want me to also compare their ecosystems and developer support (SDKs, toolchains, partner network)? That could help you decide depending on whether you’re aiming for prototyping, product integration, or licensing.

 

[itsol4605]

What is the market potential of neuromorphic computing?

Here’s the market potential of neuromorphic computing summarized in English:

---

Market Size & Growth Outlook​

1) Grand View Research (2023–2030)​

• Market size 2023: USD 5.28 B
• Forecast 2030: USD 20.27 B
• CAGR: 21.2%
• Largest segment: Consumer electronics (~USD 3.05 B)
• Fastest-growing: Automotive
• Leading region: North America (~37.2% share)

2) Persistence Market Research (2024–2031)​

• Market 2024: USD 5.4 B
• Market 2031: USD 20.4 B
• CAGR: 20.9%
• Key use cases: Robotics, autonomous vehicles, healthcare diagnostics
• North America leads (~38.5% in 2023)

3) MarketResearch.biz (2023–2033)​

• Market 2023: USD 5.1 B
• Forecast 2033: USD 35.7 B
• CAGR: 22.1%
• Hardware dominates (76% share)
• Edge computing leads (67.2%)
• Main application: Image processing (48%)

4) Precedence Research (2024–2034)​

• Market 2024: USD 6.9 B
• Forecast 2034: USD 47.3 B
• CAGR: 21.2% (2025–2034)
• Strongest segments: Hardware, image processing, automotive, edge AI

5) MarketResearchFuture (2023–2035)​

• Market 2023: USD 0.59 B
• Forecast 2035: USD 7.5 B
• CAGR: 23.7%
• Growth in both analog and digital neuromorphic systems

---

Regional Insights​

• North America → Market leader (due to research hubs, big tech, and government funding).
• Europe → Strong growth in automotive & healthcare (Germany, France, UK).
• Asia-Pacific → Fastest growth, led by China, Japan, South Korea (supported by policies like Made in China 2025 and Digital India).

---

Innovation & Applications​

• Edge AI & IoT → Energy-efficient local data processing for wearables, sensors, and autonomous systems.
• Automotive & Robotics → Low-power, fast image recognition for autonomous vehicles and robotics.
• Healthcare & Imaging → Medical diagnostics and image analysis.
• Biometrics & Security → Fingerprint, EEG, and pattern recognition for authentication systems.
• Software Ecosystem → Open frameworks and SDKs are key to adoption.

---

Conclusion​

Neuromorphic computing has huge market potential, with forecasts showing 20–24% CAGR through the next decade. Market size estimates for 2033–2035 range between USD 20–35 B, with some optimistic scenarios exceeding USD 45 B.

• Current drivers: Hardware, consumer electronics, and edge computing
• Fastest-growing sectors: Automotive & healthcare
• Regional leaders: North America today, with Asia-Pacific accelerating fastest

---

Would you like me to also break down key players in the market (e.g., Intel, BrainChip, SynSense, IBM) and their strategies?

 

[itsol4605]

Here’s a breakdown of the key players in the neuromorphic computing market and their strategies:

---

1. Intel​

• Flagship product: Loihi (neuromorphic research chip)
• Strategy:
  • Focus on research partnerships and developer ecosystems (Neuromorphic Research Community).
  • Target robotics, edge AI, and autonomous systems for ultra-low-power computation.
  • Roadmap includes scaling Loihi chips and integrating multi-chip neuromorphic platforms.
• Strength: Deep semiconductor expertise and global presence.
• Weakness: Still mostly research-focused; limited commercial products.

---

2. BrainChip​

• Flagship product: Akida Neural Processor
• Strategy:
  • Commercial-grade neuromorphic processor for edge AI applications.
  • Focus on low-power vision, voice, and sensor processing.
  • Expand adoption in automotive, security cameras, robotics, and IoT devices.
• Strength: Early mover in commercial neuromorphic processors.
• Weakness: Smaller scale than Intel; dependent on partnerships for mass deployment.

---

3. SynSense (formerly aiCTX)​

• Flagship product: Dynap-SE / Dynap-CNN
• Strategy:
  • Ultra-low-power spiking neural network (SNN) chips for vision & audio.
  • Target autonomous drones, smart cameras, and IoT devices.
  • Focus on energy-efficient edge computing.
• Strength: Highly specialized SNN expertise and energy-efficient solutions.
• Weakness: Niche market; limited brand recognition outside research community.

---

4. IBM​

• Flagship initiatives: Research on TrueNorth neuromorphic chip
• Strategy:
  • Mainly academic and industrial research partnerships.
  • Explore cognitive computing, AI hardware acceleration, and edge AI.
  • Long-term goal: integrate neuromorphic chips with mainstream AI workflows.
• Strength: Strong research infrastructure, patents, and collaboration network.
• Weakness: Limited commercial product deployment.

---

5. Qualcomm​

• Flagship initiative: Incorporating neuromorphic principles in Snapdragon AI engines
• Strategy:
  • Focus on low-power AI inference for mobile and IoT devices.
  • Integrate neuromorphic-inspired accelerators into existing SoCs.
  • Aim to support on-device AI for smartphones, AR/VR, and wearables.
• Strength: Large-scale mobile ecosystem and supply chain.
• Weakness: Not a pure neuromorphic player; more incremental adoption.

---

6. Research & Startups​

• Examples: aiCTX, Brain-Inspired Computing Labs, SpiNNaker (UK University of Manchester), Loihi-based startups
• Focus:
  • Advancing spiking neural networks and analog neuromorphic chips.
  • Collaborate with universities and edge-AI vendors.
  • Often target specialized markets like robotics, vision, and healthcare.

---

Market Trends Among Players​

1. Edge AI domination: Most companies focus on low-power devices for local inference.
2. Partnerships and ecosystems: Collaboration with universities, cloud providers, and hardware vendors.
3. From research to commercialization: Intel and BrainChip are bridging research prototypes to commercial products.
4. Sector focus: Automotive, robotics, healthcare, and smart sensors are prime adoption areas.

---

If you want, I can also rank these players by estimated market share and technological maturity to give a clearer picture of who’s likely to dominate in the next 5–10 years. Do you want me to do that?

 

[itsol4605]

Certainly! Here's an overview of the market share and technological maturity of key players in the neuromorphic computing industry as of 2025:

---

Neuromorphic Computing Market Share & Technological Maturity​

1. Intel Corporation​

• Market Share: Held a significant share of over 15% in the neuromorphic computing industry in 2023.
• Technological Maturity: Pioneer in neuromorphic computing with the Loihi and Loihi 2 chips. Intel's Hala Point system, featuring 1.15 billion neurons, is among the world's largest neuromorphic systems. (Global Market Insights Inc., Newsroom)

2. BrainChip Holdings Ltd.​

• Market Share: The Consumer Electronics segment accounted for the largest market share, with a revenue of more than 57.9% in 2022.
• Technological Maturity: Offers the Akida neuromorphic processor, focusing on edge AI applications.(BrainChip)

3. SynSense AG​

• Market Share: Specific market share data not readily available.
• Technological Maturity: Specializes in spiking neural networks (SNNs), providing ultra-low-power neuromorphic solutions for robotics and edge AI.

4. IBM Corporation​

• Market Share: Held a significant share of over 15% in the neuromorphic computing industry in 2023.
• Technological Maturity: Developed the TrueNorth chip, focusing on cognitive computing and pattern recognition.(Global Market Insights Inc.)

5. Qualcomm Incorporated​

• Market Share: Specific market share data not readily available.
• Technological Maturity: Offers the Zeroth platform, integrating neuromorphic principles into mobile and IoT devices.(Intel)

---

Summary​

• Intel leads in both market share and technological advancement, with significant investments in neuromorphic computing.
• BrainChip is a strong contender, particularly in the consumer electronics sector, with its Akida processor.
• SynSense offers specialized solutions in the robotics and edge AI domains.
• IBM continues to innovate in cognitive computing but with a more research-focused approach.
• Qualcomm integrates neuromorphic principles into its existing mobile platforms, expanding the reach of neuromorphic computing.(Market.us Scoop)

If you would like a visual comparison of these companies or further details on their specific technologies and market strategies, feel free to ask!

 

[itsol4605]

Here’s a visual comparison of the key neuromorphic computing players in terms of market share and technological maturity:

---

Neuromorphic Computing Key Players: Market & Tech Comparison​

Company	Estimated Market Share	Technological Maturity	Key Strengths	Focus Areas
Intel	~15–20%	Very High	Loihi chips, largest neuromorphic systems	Research & edge AI, robotics, autonomous vehicles
BrainChip	~10–12%	High	Akida processor, edge AI solutions	Consumer electronics, robotics, IoT
SynSense	~5% (niche)	Medium–High	Ultra-low-power SNN chips	Edge AI, robotics, drones, smart cameras
IBM	~15%	High (research focus)	TrueNorth chip, cognitive computing	Pattern recognition, AI research
Qualcomm	~5% (mobile edge)	Medium	Integration in Snapdragon SoCs	Mobile devices, IoT, edge AI

---

Observations​

1. Intel leads both in market share and technology, thanks to its Loihi 2 and large-scale neuromorphic systems.
2. BrainChip is the most commercially advanced in consumer and industrial edge AI applications.
3. SynSense occupies a niche but is highly specialized in energy-efficient SNNs.
4. IBM remains research-focused, contributing innovations but with slower commercial deployment.
5. Qualcomm applies neuromorphic concepts within existing mobile/IoT ecosystems, expanding reach without being a pure neuromorphic chip vendor.

---

If you want, I can also create a graphical chart showing market share vs. technological maturity, which makes the differences even easier to visualize. Do you want me to do that?

 

[Pom down under]

Which company is a leader in neuromorphic computing that offers a market-ready chip or market-ready IP?

ChatGPT:
In short: BrainChip (Akida) and SynSense are currently the leaders, because they actually offer commercially available neuromorphic products.

• BrainChip – leader in licensable IP: Provides the neuromorphic Akida design as commercially licensable IP (and modules). They already have real licensing deals, e.g. with Frontgrade Gaisler for space applications. If you’re looking for “neuromorphic + market-ready + licensable IP,” BrainChip is the clear choice.
• SynSense – leader in market-ready chips: Sells production chips (Speck, Xylo) and dev kits for vision/audio. Speck is already in mass production, and the Xylo family is on the market with product pages and kits. If you need ready-to-use chips instead of IP, SynSense is at the forefront.

For context:

• Intel (Loihi 2 / Hala Point) and IBM (TrueNorth) are important research platforms, but not available as market-ready, general commercial products or IP.

Bottom line:
If you want licensable IP ⇒ go with BrainChip.
If you want off-the-shelf chips ⇒ go with SynSense.

Do you want me to also compare their ecosystems and developer support (SDKs, toolchains, partner network)? That could help you decide depending on whether you’re aiming for prototyping, product integration, or licensing.

Im guessing you’ve finished shorting for now

 

[7für7]

I think this one’s huge. The VR/AR market is still expanding, and one of the reasons it’s struggling is the lack of effective eye tracking. If Akida can solve that, it could be a real game changer for the whole segment, IMO.

Eye Tracking

Next Generation Eye-Tracking with Efficient, Low-Power Edge AI Deliver always-on vision intelligence that enhances safety, interactivity, and user experience. Learn More About Eye-Tracking Technology Why Eye-Tracking Matters More Than Ever In

brainchip.com