CHIPS
Regular
So? Do you want to post all other companies better-managed than BrainChip now? BrainChip is BrainChip and Weebit is Weebit!
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
So? Do you want to post all other companies better-managed than BrainChip now? BrainChip is BrainChip and Weebit is Weebit!
Figure has an cool commercial update dropping in the morning 🦾 Remember,… | Brett Adcock | 20 comments
Figure has an cool commercial update dropping in the morning 🦾 Remember, as more humanoid robots enter the real world, the cheaper + more intelligent they… | 20 comments on LinkedIn
Yes, additional i don’t see actually where they made it better. Share prices is falling too… just a different level
CHIPS
Regular
View attachment 80898 View attachment 80899
Figure has an cool commercial update dropping in the morning 🦾 Remember,… | Brett Adcock | 20 comments
Figure has an cool commercial update dropping in the morning 🦾 Remember, as more humanoid robots enter the real world, the cheaper + more intelligent they… | 20 comments on LinkedInwww.linkedin.com
Tony Lewis comes from a robotics business, of course he likes robots and their development.
Getupthere
Regular
BrainChip and Weebit may both be in the tech sector, but they operate in different niches. BrainChip focuses on neuromorphic computing, while Weebit specializes in next-gen non-volatile memory (ReRAM) however both are listed on the ASX.
The CEO of Weebit is talking about tornadoes, and we haven’t seen any progress with the 2.0 product yet.
One key difference between the two companies is their management style and approach to communication. Weebit’s management is often praised for its transparency, consistent updates, and clear roadmap, which helps maintain investor confidence. In contrast, BrainChip has faced criticism for a lack of regular and clear communication, leaving shareholders uncertain about progress and execution. This difference in approach can impact market perception, investor trust, and overall company momentum.
Hi Fmf,Personally not expecting it to be clear cut as to whether we have been utilised. Be very welcome but don't think we will see it spelt out.
That said, restack.io outlined some neuromorphic gaming thoughts, AI Gen (probs) or authored but either way.
So outside our usual vision / gesture abilities there are a couple of other thoughts where neuromorphic would fit though in the platform examples we don't get a mention. Unsurprising given probs AI generated from other source docs.
I think the 3 example applications would be very exciting for the gaming community, if done well.
Neuromorphic Computing Applications In Gaming | Restackio
Explore how neuromorphic computing enhances gaming experiences through advanced AI and real-time processing capabilities. | Restackiowww.restack.io
Neuromorphic Computing Applications In Gaming
Last updated on 03/24/25
Explore how neuromorphic computing enhances gaming experiences through advanced AI and real-time processing capabilities.
Key Features of Neuromorphic Hardware
- No Separation of Processing and Memory: Unlike traditional architectures, neuromorphic systems allow processing units to access local information directly, reducing latency and improving performance.
- Large-Scale Parallel Computing: This allows for simultaneous processing of multiple tasks, which is essential for complex gaming environments.
- Event-Based Information Processing: Neuromorphic systems utilize spikes for information processing, which can lead to more natural and fluid interactions in games.
Applications in Gaming
Neuromorphic computing applications in gaming are diverse and impactful:
- Realistic NPC Behavior: By leveraging neuromorphic hardware, game developers can create non-player characters (NPCs) that exhibit more lifelike behaviors and adapt to player actions in real-time.
- Enhanced Graphics Rendering: The parallel processing capabilities of neuromorphic systems can significantly improve graphics rendering, allowing for more detailed and immersive environments.
- Adaptive Learning: Games can utilize neuromorphic hardware to learn from player behavior, adjusting difficulty levels and gameplay mechanics dynamically.
Examples of Neuromorphic Platforms
Several neuromorphic platforms are paving the way for advancements in gaming:
- Loihi by Intel: This digital neuromorphic chip is designed for real-time learning and can be used to develop intelligent gaming systems that adapt to player strategies.
- BrainScaleS-2: An analogue platform that implements biological neuron models, offering unique advantages in simulating complex behaviors in gaming AI.
Performance and Energy Efficiency
Neuromorphic hardware not only enhances performance but also improves energy efficiency, making it suitable for edge applications in gaming. For instance, platforms like Loihi have demonstrated energy footprints on the order of microjoules per inference, which is significantly lower than traditional systems. This efficiency allows for more sustainable gaming solutions without compromising on performance.
In conclusion, the integration of neuromorphic hardware in gaming is set to transform the industry, providing developers with the tools to create more engaging, responsive, and intelligent gaming experiences.
As I may have mentioned before, in 2021, Nintendo thought NNs were software:
US2023019874A1 SYSTEMS AND METHODS OF NEURAL NETWORK TRAINING 20210712
[0075] Game device 300 stores (e.g., in volatile or non-volatile storage) and executes a video game application program 308 . Included in the video game application program are a game engine 310 and a neural network 312.
... so that doesn't absoluely rule out Akida, ... but it also does not point to Akida.
If we were in it, I would guess that we would've been paid already or it would've at least been captured as revenue in the last annual statement......... IMO....
CHIPS
Regular
I understand your point, but we do not want to discuss Weebit here. Write Tony a friendly mail and tell him what you think and criticize about BrainChip's management or use the next Annual Meeting for this. Posting it here does not change a bit.
TheUnfairAdvantage
Regular
“As I may have mentioned before, in 2021, Nintendo thought NNs were software:”
One could also say that if all that Nintendo had was software to test the theory and to form the basis of their patent, then I guess that’s what their reference is to in NN’s.
The question would be, At that time, would/could Nintendo have had a AKD1000 reference chip or would they have been working on a software version?
We live in hope whilst we don’t know the answer.
Nintendo Switch 2 leak reveals pre-order date and new button
The console will reportedly be available to pre-order next week, straight after the Nintendo Direct event
"The Nintendo Switch currently uses Nvidia’s (now very old) Tegra X1 chip, which features a 256-core Maxwell GPU. The rumours so far suggest that Nintendo will be sticking with Nvidia for the Nintendo Switch 2, despite stiff competition from AMD, which provided the chip for Valve’s powerful Steam Deck."
FiveBucks
Regular
I don't think so. Nintendo would never go into detail about a supplier of a small part in their hardware.
They will talk about launch dates, launch games, controller gimmicks, price, backwards compatibility/upscaling with switch 1 games and maybe touch on power/graphics but Nintendo don't tend to make power a major selling point of their consoles.
Getupthere
Regular
I understand that you don’t want to discuss Weebit here, and I respect that. However, I have to call out poor management when I see it. At the last AGM, Sean stated that he would improve communication with shareholders, but this has not happened. While he does his quarterly podcast, it often feels repetitive, sticking to the same scripted responses rather than providing real insights or meaningful updates. Compared to Weebit’s more transparent approach, BrainChip’s communication still falls short, leaving investors frustrated and uncertain.
Frangipani
Top 20
Some forum users here and elsewhere keep dissing our competition.
Meanwhile, Socionext hasjust [edited, see my next post] partnered with Innatera:
www.linkedin.com
Embedded World 2025:
www.eu.socionext.com
What happened with our relationship to Socionext?!
Meanwhile, Socionext has
#innatera #socionext #ambientintelligence #presencedetection… | Shreyas Derashri
We are thrilled to partner with Socionext Inc./Socionext Europe to deliver ultra-low-power radar-based presence detection with neuromorphic processing—another…
Embedded World 2025:
Socionext Europe • Socionext Showcased Advanced SoC Technologies at Embedded World 2025
Driving Innovation Across Automotive, Data Center & Networking, Industrial, and IoT Applications From March 11-13, 2025, Socionext was at Embedded…
www.eu.socionext.com
What happened with our relationship to Socionext?!
Last edited:
DingoBorat
Slim
Why has this cat got almost as many followers on LinkedIn, as BrainChip?..#linkedin #linkedinglobal #opentowork #help #knowledge #fundation #dsa… | Rishav Chatterjee 🇮🇳
You’re not a complete Frontend Developer if you can’t make a feature or requirement without a framework or library! If you can build something using…
View attachment 80889
View attachment 80890
View attachment 80888
Happy as Larry (buying more this week)
If he's as good as he says he is, maybe "we" could use him?..
Frangipani
Top 20
Some forum users here and elsewhere keep dissing our competition.
Meanwhile, Socionext has just partnered with Innatera:
#innatera #socionext #ambientintelligence #presencedetection… | Shreyas Derashri
We are thrilled to partner with Socionext Inc./Socionext Europe to deliver ultra-low-power radar-based presence detection with neuromorphic processing—another…
View attachment 80910
Correction: They have already been partnered since at least 2023, but today’s LinkedIn posts and video suggest their collaboration is bearing tasty fruit for both sides:
See my 7 July 2024 post
below:Turns out, Innatera has meanwhile also partnered with one of the companies we have a relationship with, which shouldn’t really come as a surprise, though, given we are targeting the same Edge AI market (although Innatera’s spiking neural processor is of a different architecture and the company does not appear to be aiming for an IP-centred model to date):
“Innatera has partnered with Socionext, a Japanese sensor vendor, to develop an innovative solution for human presence detection. This technology, which Kumar demonstrated at CES in January, combines a radar sensor with Innatera’s neuromorphic chip to create highly efficient, privacy-preserving devices.”
The other day I pointed out that in recent months at least two Mercedes AI engineers have liked LinkedIn posts by Innatera, and so has Sounak Dey from TCS Research - IMO it is naive to just keep on bashing the competition and to repeat the mantra that we are years ahead of them:
View attachment 66095
View attachment 66097
I believe that consulting companies such as TCS or Accenture will happily offer their customers solutions with various providers if they see profitability for themselves - we should move away from the romantic notion that they will work with us exclusively. If they still end up doing so, great! But you shouldn’t get your hopes up that they will ignore our present or future competitors.
Beyond GPUs: Innatera and the quiet uprising in AI hardware
The brain-inspired architecture gives neuromorphic systems distinct advantages, particularly for edge computing applications in consumer devices and industrial IoT.venturebeat.com
Beyond GPUs: Innatera and the quiet uprising in AI hardware
James Thomason@jathomason
July 6, 2024 6:30 AM
While much of the tech world remains fixated on the latest large language models (LLMs) powered by Nvidia GPUs, a quieter revolution is brewing in AI hardware. As the limitations and energy demands of traditional deep learning architectures become increasingly apparent, a new paradigm called neuromorphic computing is emerging – one that promises to slash the computational and power requirements of AI by orders of magnitude.
Mimicking nature’s masterpiece: How neuromorphic chips work
But what exactly are neuromorphic systems? To find out, VentureBeat spoke with Sumeet Kumar, CEO and founder of Innatera, a leading startup in the neuromorphic chip space.
“Neuromorphic processors are designed to mimic the way biological brains process information,” Kumar explained. “Rather than performing sequential operations on data stored in memory, neuromorphic chips use networks of artificial neurons that communicate through spikes, much like real neurons.”
This brain-inspired architecture gives neuromorphic systems distinct advantages, particularly for edge computing applications in consumer devices and industrial IoT. Kumar highlighted several compelling use cases, including always-on audio processing for voice activation, real-time sensor fusion for robotics and autonomous systems, and ultra-low power computer vision.
“The key is that neuromorphic processors can perform complex AI tasks using a fraction of the energy of traditional solutions,” Kumar noted. “This enables capabilities like continuous environmental awareness in battery-powered devices that simply weren’t possible before.”
From doorbell to data center: Real-world applications emerge
Innatera’s flagship product, the Spiking Neural Processor T1, unveiled in January 2024, exemplifies these advantages. The T1 combines an event-driven computing engine with a conventional CNN accelerator and RISC-V CPU, creating a comprehensive platform for ultra-low-power AI in battery-powered devices.
“Our neuromorphic solutions can perform computations with 500 times less energy compared to conventional approaches,” Kumar stated. “And we’re seeing pattern recognition speeds about 100 times faster than competitors.”
Kumar illustrated this point with a compelling real-world application. Innatera has partnered with Socionext, a Japanese sensor vendor, to develop an innovative solution for human presence detection. This technology, which Kumar demonstrated at CES in January, combines a radar sensor with Innatera’s neuromorphic chip to create highly efficient, privacy-preserving devices.
“Take video doorbells, for instance,” Kumar explained. “Traditional ones use power-hungry image sensors that need frequent recharging. Our solution uses a radar sensor, which is far more energy-efficient.” The system can detect human presence even when a person is motionless, as long as they have a heartbeat. Being non-imaging, it preserves privacy until it’s necessary to activate a camera.
This technology has wide-ranging applications beyond doorbells, including smart home automation, building security and even occupancy detection in vehicles. “It’s a perfect example of how neuromorphic computing can transform everyday devices,” Kumar noted. “We’re bringing AI capabilities to the edge while actually reducing power consumption and enhancing privacy.”
Doing more with less in AI compute
These dramatic improvements in energy efficiency and speed are driving significant industry interest. Kumar revealed that Innatera has multiple customer engagements, with traction for neuromorphic technologies growing steadily. The company is targeting the sensor-edge applications market, with an ambitious goal of bringing intelligence to a billion devices by 2030.
To meet this growing demand, Innatera is ramping up production. The Spiking Neural Processor is slated to enter production later in 2024, with high-volume deliveries starting in Q2 of 2025. This timeline reflects the rapid progress the company has made since spinning out from Delft University of Technology in 2018. In just six years, Innatera has grown to about 75 employees and recently appointed Duco Pasmooij, former VP at Apple, to their advisory board.
The company recently closed a $21 million Series A round to accelerate the development of its spiking neural processors. The round, which was oversubscribed, included investors like Innavest, InvestNL, EIC Fund and MIG Capital. This strong investor backing underscores the growing excitement around neuromorphic computing.
Kumar envisions a future where neuromorphic chips increasingly handle AI workloads at the edge, while larger foundational models remain in the cloud. “There’s a natural complementarity,” he said. “Neuromorphics excel at fast, efficient processing of real-world sensor data, while large language models are better suited for reasoning and knowledge-intensive tasks.”
“It’s not just about raw computing power,” Kumar observed. “The brain achieves remarkable feats of intelligence with a fraction of the energy our current AI systems require. That’s the promise of neuromorphic computing – AI that’s not only more capable but dramatically more efficient.”
Seamless integration with existing tools
Kumar emphasized a key factor that could accelerate the adoption of their neuromorphic technology: developer-friendly tools. “We’ve built a very extensive software development kit that allows application developers to easily target our silicon,” Kumar explained.
Innatera’s SDK uses PyTorch as a front end. “You actually develop your neural networks completely in a standard PyTorch environment,” Kumar noted. “So if you know how to build neural networks in PyTorch, you can already use the SDK to target our chips.”
This approach significantly lowers the barrier to entry for developers already familiar with popular machine learning frameworks. It allows them to leverage their existing skills and workflows while tapping into the power and efficiency of neuromorphic computing.
“It is a simple turnkey, standard, and very fast way of building and deploying applications onto our chips,” Kumar added, highlighting the potential for rapid adoption and integration of Innatera’s technology into a wide range of AI applications.
Silicon Valley’s stealth game
While LLMs capture the headlines, industry leaders are quietly acknowledging the need for radically new chip architectures. Notably, OpenAI CEO Sam Altman, who has been vocal about the imminent arrival of artificial general intelligence (AGI) and the need for massive investments in chip manufacturing, personally invested in Rain, another neuromorphic chip startup.
This move is telling. Despite Altman’s public statements about scaling up current AI technologies, his investment suggests a recognition that the path to more advanced AI may require a fundamental shift in computing architecture. Neuromorphic computing could be one of the keys to bridging the efficiency gap that current architectures face.
Bridging the gap between artificial and biological intelligence
As AI continues to diffuse into every facet of our lives, the need for more efficient hardware solutions will only grow. Neuromorphic computing represents one of the most exciting frontiers in chip design today, with the potential to enable a new generation of intelligent devices that are both more capable and more sustainable.
While large language models capture the headlines, the real future of AI may lie in chips that think more like our own brains. As Kumar put it: “We’re just scratching the surface of what’s possible with neuromorphic systems. The next few years are going to be very exciting.”
As these brain-inspired chips make their way into consumer devices and industrial systems, we may be on the cusp of a new era in artificial intelligence – one that’s faster, more efficient, and more closely aligned with the remarkable abilities of biological brains.
Frangipani
Top 20
#linkedin #linkedinglobal #opentowork #help #knowledge #fundation #dsa… | Rishav Chatterjee 🇮🇳
You’re not a complete Frontend Developer if you can’t make a feature or requirement without a framework or library! If you can build something using…
View attachment 80889
View attachment 80890
View attachment 80888
Happy as Larry (buying more this week)
This guy’s post begs the question, though, why he wants to leave TCS?
DingoBorat
Slim
Licence fees have already been captured from MegaChips.
Are you suggesting, that we should have already received royalties, for a product that had not been released or sold yet?..
Yes, it's not a fruit, I am sure they already have a great idea on how many to sell, so I assume they have already manufactured some and is in the process of making more... I hope I am wrong... Maybe they've paid MegaChips and we are waiting for MegaChips to pay us but based on the history, we have never been in the mass produced items so I rather be surprised than disappointed again and again
I remember at one stage, even before Akida, some were suggesting we were in Amazon's Alexa... new phones... etc... lol....still nothing....
Imo only dyor
DingoBorat
Slim
"Product royalties are payments made for the use of a patented product or technology. Typically, these royalties are calculated as a percentage of the sales revenue generated from the product, ensuring that the patent holder receives ongoing compensation for their invention"
"Typically" they work on actual sales of the products, but it depends entirely on how the royalty system was set up.
As we have no information at all about that, I don't know how you could come to the conclusion you have?..
Similar threads
