Fastback6666
Regular
Sorry I didn’t realise you were only talking just short sales…I was thinking just sales. So about a quarter of shorters got out last week alone.
BRN Discussion Ongoing
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Fastback6666
Regular
This is very true.Only 2 ways we are going to see a significant gain with the SP. The reasons we have bought in is clear. All the 1000 eyes and great posts only tells us what we already know, and maybe saves a few retail holders getting nervy hands.
Sean was right when he said watch the financials. The deals that get Ann and the financials are our only way to the gravy train. Sorry, but that is the truth. But still, we are getting great research and posts, which keep us interested
We need dollar attached news.
CHIPS
Regular
This is exactly what I keep saying. In people's thoughts: "How can Akida be so good when it is so cheap compared to others? There must be something wrong with it."
When you don't sell great quality items, usually the price is wrong or you are doing something wrong in sales.
ndefries
Regular
The model is based on 7 figure license fee and royalties. It's about large volume chips. You are over thinking it. That isn't what I would say is cheap!
Fullmoonfever
Top 20
What my conscious sees when I get some spare coin and look at the current SP.
What my subconscious sees.
What ultimately happens.
What my subconscious sees.
What ultimately happens.
Tothemoon24
Top 20
This isn’t anything new from January 2022;
e-nose paper .
Featuring Akida !
Its a reminder to me of the vast variety of applications for this world first technology
www.ncbi.nlm.nih.gov
Based on these results, we can conclude that the classifier model implemented using Akida SNN in conjunction with the AERO encoder provides a promising platform for odor recognition systems. An application targeted towards the identification of malts based on their aroma profile, generally considered a nontrivial classification task using traditional machine learning algorithms, was successfully demonstrated in this work with a classification accuracy greater than 90% under different scenarios. The developed model can be deployed on the Akida NsoC, thus enabling the integration of a bio-inspired classifier model within a commercial e-nose system. A comparative analysis of the proposed approach with statistical machine learning classifiers shows that the SNN-based classifier outperforms the statistical algorithms by a significant margin for both accuracy and processing latency. A performance-based comparison of the neuromorphic model proposed in this work with other neuromorphic olfactory approaches, such as [13,14,26,27,69,70], could not be established as their inherent structures, including spike encoding schemes, neuron models, SNN architectures, and implementation of learning algorithms, vary vastly. The proposed methodology, however, does not require a graphic processing unit (GPU)-based model simulation, unlike in [13], or a complex bio-realistic model, as used in [14]. Furthermore, the SNN-based classifier can be entirely mapped on a single neural processing unit core, as opposed to multiple cores used in [14], leading to a low-power and low-latency implementation.
The application of such real-time and highly accurate e-nose systems can be extended to fields such as food technology, the brewing and wine industries, and biosecurity. Future research in this domain will focus on encoding parameters such as rank-order code within the AERO events to analyze its impact on classification performance.
e-nose paper .
Featuring Akida !
Its a reminder to me of the vast variety of applications for this world first technology
Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts
Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts
Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate feature-rich ...
www.ncbi.nlm.nih.gov
4. Conclusions
This study presents the implementation of a neuromorphic approach towards the encoding and classification of electronic nose data. The proposed approach was used to identify eight classes of malts and has potential as an application for quality control in the brewing industry. Experiments were conducted using a commercial e-nose system to record a dataset consisting of time-varying information of sensor responses when exposed to different malts under semi-laboratory conditions. The classifier proposed in this study utilized the combination of the Akida SNN and the AERO encoder, a neuromorphic approach that has previously delivered highly accurate results on a benchmark machine olfaction dataset [12]. The proposed method successfully classified the dataset with an accuracy of 97.08% and a maximum processing latency of 0.4 ms per inference when deployed on the Akida neuromorphic hardware. A secondary dataset that was used to validate the classifier model in an ‘inference-only’ mode was classified with an accuracy of 91.66%. These results could potentially be further improved by refinements to pre-processing that can enhance informative independent components for malt classes that are misclassified.Based on these results, we can conclude that the classifier model implemented using Akida SNN in conjunction with the AERO encoder provides a promising platform for odor recognition systems. An application targeted towards the identification of malts based on their aroma profile, generally considered a nontrivial classification task using traditional machine learning algorithms, was successfully demonstrated in this work with a classification accuracy greater than 90% under different scenarios. The developed model can be deployed on the Akida NsoC, thus enabling the integration of a bio-inspired classifier model within a commercial e-nose system. A comparative analysis of the proposed approach with statistical machine learning classifiers shows that the SNN-based classifier outperforms the statistical algorithms by a significant margin for both accuracy and processing latency. A performance-based comparison of the neuromorphic model proposed in this work with other neuromorphic olfactory approaches, such as [13,14,26,27,69,70], could not be established as their inherent structures, including spike encoding schemes, neuron models, SNN architectures, and implementation of learning algorithms, vary vastly. The proposed methodology, however, does not require a graphic processing unit (GPU)-based model simulation, unlike in [13], or a complex bio-realistic model, as used in [14]. Furthermore, the SNN-based classifier can be entirely mapped on a single neural processing unit core, as opposed to multiple cores used in [14], leading to a low-power and low-latency implementation.
The application of such real-time and highly accurate e-nose systems can be extended to fields such as food technology, the brewing and wine industries, and biosecurity. Future research in this domain will focus on encoding parameters such as rank-order code within the AERO events to analyze its impact on classification performance.
wilzy123
Founding Member
This is all well in good, but it is ultimately meaningless speculation resemling water cooler conversations by those who are not the target market... which is ok too. Not everyone gets it.
Tothemoon24
Top 20
In adapting and transferring the know-how gained through the era-defining technology programme VISION EQXX, we’re implementing the vision for the future of Mercedes-Benz in this vehicle segment.
But there’s even more technologies that have been transferred from the VISION EQXX to the Concept CLA Class. For example, when it comes to the development approach:
The use of digital engineering techniques was a key element in the speed and efficiency of the VISION EQXX development programme. For the engineering of the Concept CLA Class and MMA platform, we applied an “Inside-out development” approach facilitated by advanced digital simulation techniques.
In adapting and transferring the know-how gained through the era-defining technology programme VISION EQXX, we’re implementing the vision for the future of Mercedes-Benz in this vehicle segment.
The high-voltage electric-drive system and heat pump of the Concept CLA Class deliver outstanding class-defining efficiency – two technologies that have been derived from the VISION EQXX technology programme.
But there’s even more technologies that have been transferred from the VISION EQXX to the Concept CLA Class. For example, when it comes to the development approach:
The use of digital engineering techniques was a key element in the speed and efficiency of the VISION EQXX development programme. For the engineering of the Concept CLA Class and MMA platform, we applied an “Inside-out development” approach facilitated by advanced digital simulation techniques.
In adapting and transferring the know-how gained through the era-defining technology programme VISION EQXX, we’re implementing the vision for the future of Mercedes-Benz in this vehicle segment.
How Does Big Data Solutions Improve Healthcare?
In the digital transformation era, the healthcare industry is experiencing a tremendous process thanks to the beginning of big data solutions. The vast amounts of data generated by healthcare systems, patient records, medical devices, and research studies present an unprecedented opportunity for hea
Neuromorphia
fact collector
interesting video.
KAUST Research Conference on Robotics and Autonomy 2023 Speaker: Jorge Dias, Professor, Khalifa University
Brainchip in slide below.
KAUST Research Conference on Robotics and Autonomy 2023 Speaker: Jorge Dias, Professor, Khalifa University
Brainchip in slide below.
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Tothemoon24
Top 20
Go ahead & ask them yourself , there’s no need to ask for permission from a bunch of believers
I ll mate. I have done in the past dont you worry
Fullmoonfever
Top 20
Anyone seen, looked into or know anything about this company?
Don't think we have anything to do with at this point but
Enabling Intelligence
The Power of Bio-Inspired Artificial Eyes
Experience the future of artificial eyes with AI4IV. We introduce our innovative bio-inspired approach to redefine vision capabilities. Our pioneering technology features an intelligent on-silicon vision unit that overcomes the limitations of current artificial vision systems.
At AI4IV, we have succeeded at closely emulating the complex and fascinating behaviour of the human brain-eye system like never before
September 12, 2023 – AI4IV is happy to announce the successful completion of the test and qualification phase of our innovative FlyEye® Prototype, an important milestone in our journey towards the future of intelligent vision.
The prototype is designed to test the pioneering AI4IV sensing technology, demonstrating the high performance and efficiency of our bio-inspired approach to intelligent vision. Every AI4IV FlyEye® photoreceptor is indeed able to double the dynamic range1 of the photodiodes used to build it.
The FlyEye® Prototype confirms that the AI4IV vision sensor technology can capture in real-time and in single shots extremely high dynamic range and artefact-free images. Its innate ability to adapt to any and every lighting scenario makes it ready for all types of Intelligent Vision applications.
Don't think we have anything to do with at this point but
Enabling Intelligence
in on-silicon Sensing
The Power of Bio-Inspired Artificial Eyes
A Breakthrough in Vision Technology
Experience the future of artificial eyes with AI4IV. We introduce our innovative bio-inspired approach to redefine vision capabilities. Our pioneering technology features an intelligent on-silicon vision unit that overcomes the limitations of current artificial vision systems.
At AI4IV, we have succeeded at closely emulating the complex and fascinating behaviour of the human brain-eye system like never before
Bio-inspired CMOS
Our sensors, built upon arrays of standard CMOS FlyEye Receptors®, revolutionize the way the scene is sensed by preserving the relevant details. With unmatched quality and sensitivity, beyond HDR capabilities, our sensing blocks can be integrated with AI for optimal recognition performance.Unique and Compatible
Thanks to the novel compute paradigm enabled by F Architecture®, the on-sensor processing blocks deliver human-like vision behaviour. This unique design ensures compatibility with the standard approaches to DNNs and seamless porting of existing applications.Digitally Neuromorphic
The fusion of our bio-inspired approach to sensing with the unique processing architecture boosts the quality of the information-extraction process and makes it neuromorphic. At the same time, the use of a pure digital CMOS fabrication technology further improves the final performance and delivers a low-cost, energy-efficient, and small-size Intelligent Vision Sensor.September 12, 2023 – AI4IV is happy to announce the successful completion of the test and qualification phase of our innovative FlyEye® Prototype, an important milestone in our journey towards the future of intelligent vision.
The prototype is designed to test the pioneering AI4IV sensing technology, demonstrating the high performance and efficiency of our bio-inspired approach to intelligent vision. Every AI4IV FlyEye® photoreceptor is indeed able to double the dynamic range1 of the photodiodes used to build it.
The FlyEye® Prototype confirms that the AI4IV vision sensor technology can capture in real-time and in single shots extremely high dynamic range and artefact-free images. Its innate ability to adapt to any and every lighting scenario makes it ready for all types of Intelligent Vision applications.
Colorado23
Regular
I've always hoped to one day witness Akida being used in applications to help address the worlds growing mental health crisis.
Don't believe we are involved in link below but at the moment im feeling like anything is possible with our technology
interestingengineering.com
Don't believe we are involved in link below but at the moment im feeling like anything is possible with our technology
Swiss company's newly developed chip provides imaging much easier
Its technology can connect to thousands of cells at the same time and process bio-signals at 20,000 frames per second.
Heavy lifting with on-chip processing
“The biggest challenges are taking the vast amounts of data coming from cells and processing them without losing critical information in real-time. Accura-3D does a lot of the heavy lifting with on-chip processing, signal amplification, and noise filtering, which makes the chip itself intelligent," Gandolfo explained
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Colorado23
Regular
Apologies if shared in previous thread.
Tothemoon24
Top 20
I like it to Rob Telson
The innovation in TrulyHandsfree 7.0 stems from a new proprietary process, developed at Sensory through years of experience and the deployment of more than 3 billion products in the market. This approach leverages three independent and discreet recognition techniques bringing a game-changing edge over earlier versions by performing recognition with a unique orthogonal approach. TrulyHandsfree 7.0 offers a new standard for voice recognition accuracy while maintaining minimal energy consumption and an ultra-compact footprint.
One of the key highlights of TrulyHandsfree 7.0 is its unparalleled accuracy. The integration of three distinct recognition techniques enables the system to consistently deliver remarkable performance in various real-world scenarios, providing users with an intuitive and reliable voice recognition experience. Whether in noisy environments or challenging acoustic conditions, TrulyHandsfree 7.0 offers industry-leading accuracy that sets a new benchmark for voice-enabled devices. These three orthogonal techniques run below the OS level to allow memory sizes down to 50KB and power consumption under 1 milliwatt. Additional accuracy can be achieved by Sensory through revalidation of larger models that can run on the operating system or SensoryCloud.
For more performance data request the full report.
Despite its exceptional accuracy, TrulyHandsfree 7.0 maintains an incredibly small footprint and low power consumption. Its optimized design ensures minimal impact on system resources, allowing it to function effortlessly within the constraints of modern embedded devices. With this compact size, manufacturers can seamlessly integrate voice recognition capabilities into a wide array of products, from wearables and smartphones to smart appliances and automotive systems. Sensory’s VoiceHub tool streamlines the creation of wake words, commands, and language models across various languages and platforms. Custom-built models featuring TrulyHandsfree 7.0’s innovative and proprietary recognition process are available now, with integration into VoiceHub expected in early 2024.
TrulyHandsfree 7.0 marks a significant leap forward in embedded, far field voice recognition technology, reinforcing Sensory’s position as an industry leader in edge voice AI solutions. The integration of this new proprietary process underscores the company’s dedication to pushing the boundaries of innovation and delivering products that empower manufacturers to create exceptional user experiences.
“We couldn’t be more excited to roll out TrulyHandsfree 7.0, which stands as a testament to our unwavering commitment to lead in low power high accuracy voice recognition technology,” stated Todd Mozer, CEO at Sensory. “This latest update affirms our dedication to deliver advanced, reliable, and energy-efficient solutions that can be effortlessly integrated into a vast array of applications with multiple wake word requirements.”
For additional performance metrics request the latest TrulyHandsfree Performance Report
About Sensory: Sensory, a Silicon Valley-based company, is a pioneer in the field of embedded AI technologies. With a focus on voice recognition and biometric solutions, Sensory empowers consumer electronics manufacturers to create innovative products that enhance user experiences. Backed by decades of experience and a commitment to pushing technological boundaries, Sensory continues to redefine the possibilities of AI integration.
Media Contact: Anu Adeboje, aadeboje@sensory.com
BEST INDUSTRY ACCURACY FOR VOICE WAKE WORDS AND COMMANDS SETS
Santa Clara, September 14, 2023 — Sensory, a pioneer in embedded voice and biometric AI technology, is proud to announce the launch of TrulyHandsfree 7.0, the latest iteration of its groundbreaking voice recognition software for low-power wake words and small command sets. This new version redefines the boundaries of accuracy, size, and power consumption to offer a revolutionary advancement in voice recognition technology.The innovation in TrulyHandsfree 7.0 stems from a new proprietary process, developed at Sensory through years of experience and the deployment of more than 3 billion products in the market. This approach leverages three independent and discreet recognition techniques bringing a game-changing edge over earlier versions by performing recognition with a unique orthogonal approach. TrulyHandsfree 7.0 offers a new standard for voice recognition accuracy while maintaining minimal energy consumption and an ultra-compact footprint.
One of the key highlights of TrulyHandsfree 7.0 is its unparalleled accuracy. The integration of three distinct recognition techniques enables the system to consistently deliver remarkable performance in various real-world scenarios, providing users with an intuitive and reliable voice recognition experience. Whether in noisy environments or challenging acoustic conditions, TrulyHandsfree 7.0 offers industry-leading accuracy that sets a new benchmark for voice-enabled devices. These three orthogonal techniques run below the OS level to allow memory sizes down to 50KB and power consumption under 1 milliwatt. Additional accuracy can be achieved by Sensory through revalidation of larger models that can run on the operating system or SensoryCloud.
For more performance data request the full report.
Despite its exceptional accuracy, TrulyHandsfree 7.0 maintains an incredibly small footprint and low power consumption. Its optimized design ensures minimal impact on system resources, allowing it to function effortlessly within the constraints of modern embedded devices. With this compact size, manufacturers can seamlessly integrate voice recognition capabilities into a wide array of products, from wearables and smartphones to smart appliances and automotive systems. Sensory’s VoiceHub tool streamlines the creation of wake words, commands, and language models across various languages and platforms. Custom-built models featuring TrulyHandsfree 7.0’s innovative and proprietary recognition process are available now, with integration into VoiceHub expected in early 2024.
TrulyHandsfree 7.0 marks a significant leap forward in embedded, far field voice recognition technology, reinforcing Sensory’s position as an industry leader in edge voice AI solutions. The integration of this new proprietary process underscores the company’s dedication to pushing the boundaries of innovation and delivering products that empower manufacturers to create exceptional user experiences.
“We couldn’t be more excited to roll out TrulyHandsfree 7.0, which stands as a testament to our unwavering commitment to lead in low power high accuracy voice recognition technology,” stated Todd Mozer, CEO at Sensory. “This latest update affirms our dedication to deliver advanced, reliable, and energy-efficient solutions that can be effortlessly integrated into a vast array of applications with multiple wake word requirements.”
For additional performance metrics request the latest TrulyHandsfree Performance Report
About Sensory: Sensory, a Silicon Valley-based company, is a pioneer in the field of embedded AI technologies. With a focus on voice recognition and biometric solutions, Sensory empowers consumer electronics manufacturers to create innovative products that enhance user experiences. Backed by decades of experience and a commitment to pushing technological boundaries, Sensory continues to redefine the possibilities of AI integration.
Media Contact: Anu Adeboje, aadeboje@sensory.com
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