AI is one of the most complex technologies embedded developers must tackle. Integrating it into your system brings with it so many questions and not so many answers. In this monthly series, Embedded Computing Design will look to simplify the design process, as much as that’s possible.
Select the session(s) you wish to attend and then complete the registration form on the righthand side of this page.
Select the session(s) you wish to attend and then complete the registration form on the righthand side of this page.
Tue, Jul. 30, 2024 · 11:00 am (PDT)
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This webinar will discuss how AI is used in various smart building/smart home applications—from smart speakers, thermostats, doorbells, shades, to industrial robots, HVAC and more. The presentation will discuss how semiconductors and software can enable more AI at the edge for smart homes and smart buildings, making devices more intelligent, secured and sustainable. The presentation will also discuss how semiconductor implementations will help enable advanced AI in all these IoT devices.
This webinar will discuss how AI is used in various smart building/smart home applications—from smart speakers, thermostats, doorbells, shades, to industrial robots, HVAC and more. The presentation will discuss how semiconductors and software can enable more AI at the edge for smart homes and smart buildings, making devices more intelligent, secured and sustainable. The presentation will also discuss how semiconductor implementations will help enable advanced AI in all these IoT devices.
Wed, Aug. 21, 2024 · 11:00 am (PDT)
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The next “big thing” is quantum computing, and it can have massive effects on AI, as it brings in never before seen levels of compute performance. But how do we manage this new-found power? That’s where this session will go, and we will look at when such systems can expect to become available.
The next “big thing” is quantum computing, and it can have massive effects on AI, as it brings in never before seen levels of compute performance. But how do we manage this new-found power? That’s where this session will go, and we will look at when such systems can expect to become available.
Thu, Sep. 19, 2024 · 8:00 am (PDT)
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Adding AI functionality to your Edge-based design requires a lot of forethought. For example, what exactly am I trying to accomplish using AI? And is that really the best way to achieve my results? Assuming you still want to deploy AI in your design, you can move on to the harder question, how do I do that? These questions and many more will be explored and answered during the AI Day Keynote Address.
Adding AI functionality to your Edge-based design requires a lot of forethought. For example, what exactly am I trying to accomplish using AI? And is that really the best way to achieve my results? Assuming you still want to deploy AI in your design, you can move on to the harder question, how do I do that? These questions and many more will be explored and answered during the AI Day Keynote Address.
Thu, Sep. 19, 2024 · 9:00 am (PDT)
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AI is now all around us. It can be found in nearly every facet of our lives. And the industrial, automation, robotics, and manufacturing sectors are front and center when it comes to AI and ML deployments. As the technology matures, you’ll see huge improvements in productivity, quality, and security. The talks in this session will hone in on these advancements and how they can be deployed in your industrial application.
AI is now all around us. It can be found in nearly every facet of our lives. And the industrial, automation, robotics, and manufacturing sectors are front and center when it comes to AI and ML deployments. As the technology matures, you’ll see huge improvements in productivity, quality, and security. The talks in this session will hone in on these advancements and how they can be deployed in your industrial application.
Thu, Sep. 19, 2024 · 10:30 am (PDT)
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Computer vision, and the algorithms that come with it, can have a huge impact on productivity. But it also significantly increases the amount of data that must be transmitted, processed, and analyzed. In this session, we will look at all the options, from system configuration, to the processing elements that are needed, to how the analysis should be handled, including how and when to act on those outcomes.
Computer vision, and the algorithms that come with it, can have a huge impact on productivity. But it also significantly increases the amount of data that must be transmitted, processed, and analyzed. In this session, we will look at all the options, from system configuration, to the processing elements that are needed, to how the analysis should be handled, including how and when to act on those outcomes.
Thu, Sep. 19, 2024 · 12:00 pm (PDT)
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Vendor A’s AI solution is pretty similar to Vendor B’s solution, yet they are quite different. And then you add in Vendor C, and it gets even murkier. If your task is to choose the right vendor, then implement the solution you’ve chosen, it may be quite difficult to tell them apart. In this session, we will look at the various options that are available to the designer, how they are different, and which makes the most sense based on your application.
Vendor A’s AI solution is pretty similar to Vendor B’s solution, yet they are quite different. And then you add in Vendor C, and it gets even murkier. If your task is to choose the right vendor, then implement the solution you’ve chosen, it may be quite difficult to tell them apart. In this session, we will look at the various options that are available to the designer, how they are different, and which makes the most sense based on your application.
Thu, Sep. 19, 2024 · 4:00 pm (EDT)
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Smart microphones can be very effective with neural networks' capability for pre-processing data. The neural network on the chip provides the advantage for voice processing tasks such as voice detection, voice intelligibility, and voice command processing. At the same time, it supports user privacy and increases the security of smart home solutions, personal communication devices, hearing assistance, robotics, etc. The question is how to find an efficient way to implement it.
Analog circuits excel at accurately representing real-world phenomena and handling continuous signals. They outperform digital circuits for many 1D signal raw data pre-processing near the sensor. Analog saves power consumption of the sensor node and reduces data to be processed on digital CPU/MCU for classification and decision.
POLYN offers an application-specific neuromorphic analog IC for always-on data pre-processing at the sensor. Neuromorphic Analog Signal Processing Front End (NASP NFE) features ultra-low power consumption, low latency, and high accuracy. It needs only 35uW of power for always-on voice detection or up to 120uW to extract a word command from a noisy background. It is a new element in sensor node architecture and the logical continuation of the sensor itself.
Neuromorphic processing of voice solves the problem of communication in a noisy environment through voice extraction, which differs from noise cancellation and works well with irregular noises. It also improves hearing when sound is received over the network with noises mixed at the sender side. Another use case is smart voice controls for Smart Home, Smart Warehouse, headphones, and helmets. The solution improves voice intelligibility in voice management systems, providing high accuracy and robustness even in harsh environments with noise interference and no cloud connectivity.
NASP NFE supports easy integration with existing solutions and new designs operating on batteries or energy harvesting, making the whole solution more sustainable. NASP NFE chips are best suited for smart devices in various AIoT applications.
POLYN invites all parties interested in adding AI to voice-sensing devices to test our neuromorphic voice processing models on the simulation tool.
Smart microphones can be very effective with neural networks' capability for pre-processing data. The neural network on the chip provides the advantage for voice processing tasks such as voice detection, voice intelligibility, and voice command processing. At the same time, it supports user privacy and increases the security of smart home solutions, personal communication devices, hearing assistance, robotics, etc. The question is how to find an efficient way to implement it.
Analog circuits excel at accurately representing real-world phenomena and handling continuous signals. They outperform digital circuits for many 1D signal raw data pre-processing near the sensor. Analog saves power consumption of the sensor node and reduces data to be processed on digital CPU/MCU for classification and decision.
POLYN offers an application-specific neuromorphic analog IC for always-on data pre-processing at the sensor. Neuromorphic Analog Signal Processing Front End (NASP NFE) features ultra-low power consumption, low latency, and high accuracy. It needs only 35uW of power for always-on voice detection or up to 120uW to extract a word command from a noisy background. It is a new element in sensor node architecture and the logical continuation of the sensor itself.
Neuromorphic processing of voice solves the problem of communication in a noisy environment through voice extraction, which differs from noise cancellation and works well with irregular noises. It also improves hearing when sound is received over the network with noises mixed at the sender side. Another use case is smart voice controls for Smart Home, Smart Warehouse, headphones, and helmets. The solution improves voice intelligibility in voice management systems, providing high accuracy and robustness even in harsh environments with noise interference and no cloud connectivity.
NASP NFE supports easy integration with existing solutions and new designs operating on batteries or energy harvesting, making the whole solution more sustainable. NASP NFE chips are best suited for smart devices in various AIoT applications.
POLYN invites all parties interested in adding AI to voice-sensing devices to test our neuromorphic voice processing models on the simulation tool.
Wed, Oct. 16, 2024 · 11:00 am (PDT)
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Machine learning is not new to industrial/automation/robotics equipment. But the capabilities are expanding, and they will continue to do so moving forward. As new algorithms come about and vision system get better, you’ll see huge improvements in productivity, quality, and security. This session will look into some of those applications and where gains can be made thanks to the use of AI.
Machine learning is not new to industrial/automation/robotics equipment. But the capabilities are expanding, and they will continue to do so moving forward. As new algorithms come about and vision system get better, you’ll see huge improvements in productivity, quality, and security. This session will look into some of those applications and where gains can be made thanks to the use of AI.
Tue, Dec. 10, 2024 · 11:00 am (PST)
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Whether they know it or not, consumers have been subjected to various levels of AI for years, a lot longer in some cases. As the processors get more refined and AI can be deployed at the end point, even wearable devices can adapt to their humans. In this session, we will look at some of the very low-power devices and what’s needed to design them into consumer.
Whether they know it or not, consumers have been subjected to various levels of AI for years, a lot longer in some cases. As the processors get more refined and AI can be deployed at the end point, even wearable devices can adapt to their humans. In this session, we will look at some of the very low-power devices and what’s needed to design them into consumer.
