Transfer

Optimizing Data Transfer in Distributed AI/ML Training Workloads

a part of a series of posts on optimizing data transfer using NVIDIA Nsight™ Systems (nsys) profiler. Part one focused on CPU-to-GPU data copies, and part two on GPU-to-CPU copies. On this post, we turn our attention...

Optimizing Data Transfer in Batched AI/ML Inference Workloads

is a to Optimizing Data Transfer in AI/ML Workloads where we demonstrated using NVIDIA Nsight™ Systems (nsys) in studying and solving the common data-loading bottleneck — occurrences where the GPU idles while it waits for input...

Optimizing Data Transfer in AI/ML Workloads

a , a deep learning model is executed on a dedicated GPU accelerator using input data batches it receives from a CPU host. Ideally, the GPU — the dearer resource — needs to...

Personal Information Committee “Deep Chic User Information China Transfer Measures”

The Personal Information Protection Committee said that Deep Chic has taken corrective actions for transmitting user information and messages without permission. The Personal Information Committee (Chairman Go Hak -soo) held the ninth plenary session and...

Dubformer Raises $3.6M to Revolutionize AI Dubbing with Emotion Transfer Technology

AI dubbing startup Dubformer has secured a $3.6 million seed funding round to redefine how emotional depth is captured in media localization. The investment, led by Almaz Capital with participation from s16vc and FinSight, in...

Technology sharing event between Ministry of Industry and Samsung Electronics…Free transfer of 123 patents to 86 firms

The Ministry of Trade, Industry and Energy (Minister Lee Chang-yang) and Samsung Electronics held the '2023 Ministry of Trade, Industry and Energy-Samsung Electronics Technology Sharing Event' to share the achievements of technology sharing on...

Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:

Our primary objective is to reinforce the effectiveness of Bayesian Optimisation (BO) by leveraging meta-learning to transfer knowledge across different problem domains, thereby significantly improving sample efficiency.In pursuit of this goal, we introduce the...

Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:

Our primary objective is to boost the effectiveness of Bayesian Optimisation (BO) by leveraging meta-learning to transfer knowledge across different problem domains, thereby significantly improving sample efficiency.In pursuit of this goal, we introduce the...

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