Just got my hands on a Coral TPU, and I have to say. it is actually quite awesome for the price, if only static sized tensors weren't a pain in the ass to work with, as the Project I am porting to work with the edgetpu heavily relies on dynamic-sized tensors
October 3, 2023 at 7:02 PM
Just got my hands on a Coral TPU, and I have to say. it is actually quite awesome for the price, if only static sized tensors weren't a pain in the ass to work with, as the Project I am porting to work with the edgetpu heavily relies on dynamic-sized tensors
Amazing how easy it is to enable even a #RaspberryPI to do #MachineLearning stuff. Just got this in the mail - let the tinkering begin! :3 #GoogleCoral #EdgeTPU #MLAccelerator #AIAccelerator
December 11, 2024 at 11:48 AM
Amazing how easy it is to enable even a #RaspberryPI to do #MachineLearning stuff. Just got this in the mail - let the tinkering begin! :3 #GoogleCoral #EdgeTPU #MLAccelerator #AIAccelerator
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is EmbeddingGemma compared to other models? At just 308 million parameters, EmbeddingGemma is lightweight enough to run on mobile devices and offline environments. Despite its size, it performs competitively with much larger embedding models. Inference latency is low (sub-15 ms for 256 tokens on EdgeTPU), making it suitable for real-time applications.
nexttech-news.com
September 4, 2025 at 11:34 PM
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is EmbeddingGemma compared to other models? At just 308 million parameters, EmbeddingGemma is lightweight enough to run on mobile devices and offline environments. Despite its size, it performs competitively with much larger embedding models. Inference latency is low (sub-15 ms for 256 tokens on EdgeTPU), making it suitable for real-time applications.
nexttech-news.com
September 4, 2025 at 11:33 PM
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
• Tensor G5 (laguna)
• TSMC N3E
• 1x Cortex-X4 (3.4GHz)
• 5x Cortex-A725 (2.86GHz)
• 2x Cortex-A520 (2.25GHz)
• ARM v9.2
• Modem: Samsung S5400
• GPU: PowerVR D-Series DXT-48-1536 1.1GHz.
Integrated Virtualization, Ray Tracing and FSR support
• TPU: Improved version of EdgeTPU (18 / 9 TOPS)
• TSMC N3E
• 1x Cortex-X4 (3.4GHz)
• 5x Cortex-A725 (2.86GHz)
• 2x Cortex-A520 (2.25GHz)
• ARM v9.2
• Modem: Samsung S5400
• GPU: PowerVR D-Series DXT-48-1536 1.1GHz.
Integrated Virtualization, Ray Tracing and FSR support
• TPU: Improved version of EdgeTPU (18 / 9 TOPS)
February 26, 2025 at 1:20 AM
• Tensor G5 (laguna)
• TSMC N3E
• 1x Cortex-X4 (3.4GHz)
• 5x Cortex-A725 (2.86GHz)
• 2x Cortex-A520 (2.25GHz)
• ARM v9.2
• Modem: Samsung S5400
• GPU: PowerVR D-Series DXT-48-1536 1.1GHz.
Integrated Virtualization, Ray Tracing and FSR support
• TPU: Improved version of EdgeTPU (18 / 9 TOPS)
• TSMC N3E
• 1x Cortex-X4 (3.4GHz)
• 5x Cortex-A725 (2.86GHz)
• 2x Cortex-A520 (2.25GHz)
• ARM v9.2
• Modem: Samsung S5400
• GPU: PowerVR D-Series DXT-48-1536 1.1GHz.
Integrated Virtualization, Ray Tracing and FSR support
• TPU: Improved version of EdgeTPU (18 / 9 TOPS)
🚨 EUVD-2026-37171
📊 n/a
🏢 Google
📝 In edgetpu_sync_fence_group_shutdown() of edgetpu-dmabuf.c, there is a possible elevation of privilege due to a use after free. This could lead to local escal...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37171
#cybersecurity #infosec #cve #euvd
📊 n/a
📝 In edgetpu_sync_fence_group_shutdown() of edgetpu-dmabuf.c, there is a possible elevation of privilege due to a use after free. This could lead to local escal...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37171
#cybersecurity #infosec #cve #euvd
June 16, 2026 at 9:00 PM
🚨 EUVD-2026-37171
📊 n/a
🏢 Google
📝 In edgetpu_sync_fence_group_shutdown() of edgetpu-dmabuf.c, there is a possible elevation of privilege due to a use after free. This could lead to local escal...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37171
#cybersecurity #infosec #cve #euvd
📊 n/a
📝 In edgetpu_sync_fence_group_shutdown() of edgetpu-dmabuf.c, there is a possible elevation of privilege due to a use after free. This could lead to local escal...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37171
#cybersecurity #infosec #cve #euvd
🚨 EUVD-2026-37184
📊 n/a
🏢 Google
📝 In ExecuteGraph command handler of EdgeTPU firmware, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation o...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37184
#cybersecurity #infosec #cve #euvd
📊 n/a
📝 In ExecuteGraph command handler of EdgeTPU firmware, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation o...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37184
#cybersecurity #infosec #cve #euvd
June 16, 2026 at 9:00 PM
🚨 EUVD-2026-37184
📊 n/a
🏢 Google
📝 In ExecuteGraph command handler of EdgeTPU firmware, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation o...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37184
#cybersecurity #infosec #cve #euvd
📊 n/a
📝 In ExecuteGraph command handler of EdgeTPU firmware, there is a possible out of bounds write due to an integer overflow. This could lead to local escalation o...
🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-37184
#cybersecurity #infosec #cve #euvd
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is EmbeddingGemma compared to other models? At just 308 million parameters, EmbeddingGemma is lightweight enough to run on mobile devices and offline environments. Despite its size, it performs competitively with much larger embedding models. Inference latency is low (sub-15 ms for 256 tokens on EdgeTPU), making it suitable for real-time applications.
786hz.com
September 4, 2025 at 9:59 PM
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance. How compact is…
(3) role-based group-wise quantization. We implement PointSplit on TensorFlow Lite and evaluate it on a customized hardware platform comprising both mobile GPU and EdgeTPU. Experimental results on representative RGB-D datasets, SUN RGB-D and Scannet [5/6 of https://arxiv.org/abs/2504.03654v1]
April 8, 2025 at 5:56 AM
(3) role-based group-wise quantization. We implement PointSplit on TensorFlow Lite and evaluate it on a customized hardware platform comprising both mobile GPU and EdgeTPU. Experimental results on representative RGB-D datasets, SUN RGB-D and Scannet [5/6 of https://arxiv.org/abs/2504.03654v1]
科学者がAIモデルを騙して秘密を漏らす
Boffins trick AI model into giving up its secrets #Register (Dec 18)
#AIセキュリティ #サイドチャネル攻撃 #ハイパーパラメータ抽出 #EdgeTPU #機械学習
Boffins trick AI model into giving up its secrets #Register (Dec 18)
#AIセキュリティ #サイドチャネル攻撃 #ハイパーパラメータ抽出 #EdgeTPU #機械学習
Boffins interrogate AI model to make it reveal itself
All it took to make an Google Edge TPU give up model hyperparameters was specific hardware, a novel attack technique … and several days
buff.ly
December 20, 2024 at 8:30 AM
科学者がAIモデルを騙して秘密を漏らす
Boffins trick AI model into giving up its secrets #Register (Dec 18)
#AIセキュリティ #サイドチャネル攻撃 #ハイパーパラメータ抽出 #EdgeTPU #機械学習
Boffins trick AI model into giving up its secrets #Register (Dec 18)
#AIセキュリティ #サイドチャネル攻撃 #ハイパーパラメータ抽出 #EdgeTPU #機械学習