Wrap Up and Next Steps | IoT Developer Show | Ep. 7 | Season 4 | Intel Software

Hello. I’m Martin Kronberg, and
this is the IoT Developer Show, season four. In this wrap-up episode,
we cover everything we explored this season. In episode one, we introduced
the Intel Vision Accelerator Design product solutions. We looked at some
reference limitations and discovered how these
solutions and designs can benefit your
vision applications. In the second episode,
we introduced you to the Intel Neural
Compute Stick 2. We showed off the Intel
Model Zoo on GitHub and looked at a retail
computer vision solution. In the third episode,
we showed you how to use the Intel NCS2
to build low-power embedded computer vision solutions. We also mentioned that the
Raspberry Pi B3 and Intel NCS2 make an awesome
prototyping combination. We then walked you through
a typical prototype pipeline that’s quick and
inexpensive to build. In the fourth episode, we
used a typical video analytics pipeline to understand the
workload balancing concept. We also saw how Intel Vision
Accelerator Design product solutions help manage advanced
computer vision workloads. In the fifth episode,
we learned about FPGAs, or field programmable
gate arrays. You learned what they
are, how they work, and some of the unique
characteristics that make them ideal for AI applications. Finally, in the sixth
episode, we wrap up the series by learning how to use
Intel’s FPGA-based vision accelerator with the Intel
Distribution of OpenVINO toolkit. We also learned a bit more
about the hardware architecture programmed in the FPGA. Now you should understand
typical computer vision pipelines and how to use Intel
Vision Accelerator Design product solutions. Make sure to follow
the links to learn more on the topics
covered this season. Thanks for watching
the IoT Developer Show, and we’ll see you next time. [INTEL THEME PLAYING]

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