AI Everywhere,
big and small.
AI and IoT will deeply impact every industry on earth, yours included. From AI enabled Call Centers to chicken farms, CBS NEWS Economy 4.0 documentary explores Edge AI and where it is headed.
AI Everywhere,
big and small.
AI and IoT will deeply impact every industry on earth, yours included. From AI enabled Call Centers to chicken farms, CBS NEWS Economy 4.0 documentary explores Edge AI and where it is headed.
Watch Our CBS News Feature
We recently partnered with CBS News for their “Economy 4.0” series, showcasing how AI is reshaping industries. In this exclusive sponsored video, we delve into our role in advancing Edge AI technology
Watch Our CBS News Feature
We recently partnered with CBS News for their “Economy 4.0” series, showcasing how AI is reshaping industries. In this exclusive sponsored video, we delve into our role in advancing Edge AI technology
Only limited by your imagination!
If only it were true that imagination alone could drive innovation. Bringing AI to small, low-powered devices requires more than just big ideas—it demands advanced embedded engineering and Edge AI expertise which is currently in short supply.
Only Limited by your imagination!
If only it were true that imagination alone could drive innovation. Bringing AI to small, low-powered devices requires more than just big ideas—it demands advanced embedded engineering and Edge AI expertise which is currently in short supply.
You Need a Blueprint
Before you start any Edge AI development you need a Blueprint (a structured roadmap), outlining system architecture (hardware and connections), data flow (how data is captured and processed), and the algorithms/models that drive your AI.
AI Blueprints for common functions already exist so you can avoid reinventing the wheel. They are essential for defining the solution components, deployment model and test plan to ensure your system works as expected.
Before you start any Edge AI development you need a Blueprint (a structured roadmap), outlining system architecture (hardware and connections), data flow (how data is captured and processed), and the algorithms/models that drive your AI.
AI Blueprints for common functions already exist so you can avoid reinventing the wheel. They are essential for defining the solution components, deployment model and test plan to ensure your system works as expected.
You Need a Model
Say your application needs some combination of AI vision, sound, language, speech and sensor models. Like the ability to detect a moving object, recognize a face, or identify a sound.
Starting from scratch, models can take months to create and train. For each application it is vital to consider all of the core functions you want, both now and in future, as this wish-list impacts your device’s hardware requirements and roadmap.
Learn more about pre-trained Edge AI Models to shrink R&D.
Say your application needs some combination of AI vision, sound, language, speech and sensor models. Like the ability to detect a moving object, recognize a face, or identify a sound.
Starting from scratch, models can take months to create and train. For each application it is vital to consider all of the core functions you want, both now and in future, as this wish-list impacts your device’s hardware requirements and roadmap.
Learn more about pre-trained Edge AI Models to shrink R&D.
You Need a Dataset
Without high-quality, relevant data, you can’t train your model. A dataset is needed to train AI to recognize patterns, make decisions, and learn from its environment. It should be diverse, covering all potential scenarios your AI will encounter. Quality matters more than quantity—clean, labeled, and balanced data ensures accurate results.
It’s also crucial that your dataset matches the type of AI task in hand (vision, sound, etc.) and your edge device’s constraints. The right dataset accelerates development, improves performance, and reduces the time spent on retraining.
Without high-quality, relevant data, you can’t train your model. A dataset is needed to train AI to recognize patterns, make decisions, and learn from its environment. It should be diverse, covering all potential scenarios your AI will encounter. Quality matters more than quantity—clean, labeled, and balanced data ensures accurate results.
It’s also crucial that your dataset matches the type of AI task in hand (vision, sound, etc.) and your edge device’s constraints. The right dataset accelerates development, improves performance, and reduces the time spent on retraining.
You Need a Platform
2024 is the breakthrough year for new AI chips which incorporate some combination of CPU, NPU, GPU and VPU. They are in short supply too.
Every semi-conductor firm across North America, has some type of AI native chipset in the works, and we have been privileged to get early samples from our partners, with which to develop SDKs for them.
Writing optimized firmware for these chips is vital as the processing demands are intense.
2024 is the breakthrough year for new AI chips which incorporate some combination of CPU, NPU, GPU and VPU. They are in short supply too.
Every semi-conductor firm across North America, has some type of AI native chipset in the works, and we have been privileged to get early samples from our partners, with which to develop SDKs for them.
Writing optimized firmware for these chips is vital as the processing demands are intense.
You Need a Partner
Even with the right models, chips, frameworks and training datasets, navigating the complexities of Edge AI development is a daunting task. That’s where having a seasoned partner is crucial.
Working with an embedded systems expert at the forefront of Edge AI innovation can drastically lower your risks, accelerating your time-to-market while ensuring your solutions are robust and scalable. Only with the right partner can you truly push the boundaries of what’s possible—taking your vision from concept to reality.
Even with the right models, chips, frameworks and training datasets, navigating the complexities of Edge AI development is a daunting task. That’s where having a seasoned partner is crucial.
Working with an embedded systems expert at the forefront of Edge AI innovation can drastically lower your risks, accelerating your time-to-market while ensuring your solutions are robust and scalable. Only with the right partner can you truly push the boundaries of what s possible—taking your vision from concept to reality.
Drive your Edge AI Success by having the right partner
We’ll get your idea to MVP before your competitors
know what’s hit them
Drive your Edge AI Success by having the right partner
We’ll get your idea to MVP before your competitors know what’s hit them
