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Konten disediakan oleh EdgeCortix Inc.. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh EdgeCortix Inc. atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.
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What is edge AI inference doing for more devices?

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Konten disediakan oleh EdgeCortix Inc.. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh EdgeCortix Inc. atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

By Jeffrey Grosman.
AI inference is a common term - but what is edge AI inference? EdgeCortix provides an answer in terms of workloads, efficiency, and applications.

Artificial intelligence (AI) is changing the rules for many applications. Teams train AI models to recognize objects or patterns, then run AI inference using those models against incoming data streams. When size, weight, power, and time are of little concern, data center or cloud-based AI inference may do. But in resource-constrained edge devices, different technology is needed. What is edge AI inference doing for more devices? Let’s look at differences in AI inference for the edge and how intellectual property (IP) addresses them.
Read the full blog here

  continue reading

6 episode

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iconBagikan
 
Manage episode 367432838 series 3488687
Konten disediakan oleh EdgeCortix Inc.. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh EdgeCortix Inc. atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

By Jeffrey Grosman.
AI inference is a common term - but what is edge AI inference? EdgeCortix provides an answer in terms of workloads, efficiency, and applications.

Artificial intelligence (AI) is changing the rules for many applications. Teams train AI models to recognize objects or patterns, then run AI inference using those models against incoming data streams. When size, weight, power, and time are of little concern, data center or cloud-based AI inference may do. But in resource-constrained edge devices, different technology is needed. What is edge AI inference doing for more devices? Let’s look at differences in AI inference for the edge and how intellectual property (IP) addresses them.
Read the full blog here

  continue reading

6 episode

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