Intelligent Devices

  • highly optimized AI engines to analyze text, image, video or time series data directly on devices
  • our cloud/ data center and IoT edge devices components enable data-driven proactive operations
  • edge inferencing in real-time and with reduced bandwidth needs
  • AI models training in distributed environments (federated learning)
  • we benchmark edge components (Movidius vs. GPU)

We know leading technologies and both hardware and software components in the space. We can advise about selecting optimal configurations, integrate proper baseline components and help build a final product on top of that.

We know hardware solutions from Xilinx, Intel, NVIDIA, Lenovo, Basler, and many more. We have huge experience in computer vision, machine learning, deep learning and have already delivered a variety of artificial intelligence solutions.

We enable on-device AI (AI on edge) through:

  • Algorithms optimization and fine tuning to take maximum advantage of given processing units, accelerators and overall hardware architecture.
  • Optimum usage of precious resources by selecting appropriate data types.
  • Energy-efficient techniques implementation and development to reduce the energy consumption for real-time data processing.
  • Pre-trained models development and deployment.
  • Implementation of proper deployment strategies: on-device, in the Cloud or data center. Read our guideline here.

Key benefits of deploying AI workloads on the IoT edge devices:

  • Enable Scalability
    (Decentralizes AI services & makes it easier to expand the IoT ecosystems)
  • Enable near-real-time AI experience
    (By using the modern low power, high performance, small form factor accelerators)
  • Solve round-trip latencies
    (Deploying AI directly on the device enables making on-the-spot decisions)
  • Eliminate intermittent connectivity related issues
    (No need for sending the data from the device to external AI services and waiting for results)
  • Reduce costs of bandwidth
    (AI-enabled devices pre-process the data and send the results to external services vs raw data)
  • Data can stay locally on the device
    (Having AI on the device allows for sending the data to external storages selectively)

byteLAKE's and Lenovo's holistic approach to AI 

Let's inject AI into your products!

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