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Researchers from Meta GenAI Introduce Fairy: Fast Parallelized Instruction-Guided Video-to-Video Synthesis Artificial Intelligence Framework

Marktechpost

The Traditional approaches to video editing addressed this issue by tracking pixel movement via optical flow or reconstructing videos as layered representations. However, video editing remains challenging due to the intricate nature of maintaining temporal coherence between individual frames.

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AI News Weekly - Issue #384: Boosting AI-generated content transparency - May 9th 2024

AI Weekly

Powered by ai4.io io In the News OpenAI takes steps to boost AI-generated content transparency OpenAI is joining the Coalition for Content Provenance and Authenticity (C2PA) steering committee and will integrate the open standard’s metadata into its generative AI models to increase transparency around generated content.

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Optimize AWS Inferentia utilization with FastAPI and PyTorch models on Amazon EC2 Inf1 & Inf2 instances

AWS Machine Learning Blog

xlarge 1 2 4 32 Inf2.8xlarge 1 2 32 32 Inf2.24xlarge 6 12 96 192 Inf2.48xlarge 12 24 192 384 Inf2 instances contain the new NeuronCores-v2 in comparison to the NeuronCore-v1 in the Inf1 instances. This won’t be an issue if the model is utilizing the NeuronCores to a large extent.

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Comparison of NVIDIA-A100, H100 and H200 for LLMs

Heartbeat

We will observe the developments on this issue over time. Falcon-40B was trained with 384 A100s. This problem also applies to companies such as OpenAI, and we sometimes see tweets shared by company executives about this issue. “we Which One to Choose? Inflection used 3.5k H100 for its GPT-3.5 equivalent model.

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Use Amazon Titan models for image generation, editing, and searching

AWS Machine Learning Blog

Dr. Kai Zhu currently works as Cloud Support Engineer at AWS, helping customers with issues in AI/ML related services like SageMaker, Bedrock, etc. b64encode(image_file.read()).decode( read()) The following function returns the top similar multimodal embeddings given a query multimodal embeddings. He is a SageMaker Subject Matter Expert.

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Analyze Amazon SageMaker spend and determine cost optimization opportunities based on usage, Part 3: Processing and Data Wrangler jobs

AWS Machine Learning Blog

SageMaker offers two features specifically designed to help with those issues: SageMaker Processing and Data Wrangler. However, you could use two m5.12xlarge instances (2 * 256 GiB = 512 GiB) and reduce the cost by 40% or three m5.4xlarge instances (3 * 128 GiB = 384 GiB) and save 50% of the m5.24xlarge instance cost.

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