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AWS Inferentia: 6 Things You NEED To Know 😇

AWS Inferentia is a custom machine learning chip that you can use for high-performance inference predictions. Hi Guys, this is Abi from GokceDB and in this video you are going to learn 6 things about Inferentia in AWS. Let's get into it. 1. In the training phase of machine learning, you feed your model a curated dataset so that it can learn everything it needs for data analysis. Later, in the inference phase, the model can make predictions or inferences based on live data to produce actionable results. In AWS, you can use Inferentia accelerators to deliver high performance at low cost for your deep learning inference applications. 2. The first-generation AWS Inferentia accelerator powers EC2 Inf1 instances, which deliver up to 2.3x higher throughput and up to 70% lower cost per inference than comparable EC2 instances. 3. The second-generation AWS Inferentia accelerator called Inferentia2 delivers up to 4x higher throughput and up to 10x lower latency compared to the first generation Inferentia. 4. Amazon EC2 Inf2 instances are designed to deliver high performance at the lowest cost. They are optimized to deploy increasingly complex models, such as large language models and vision transformers at scale. 5. By using AWS Neuron SDK with Inferentia, you get native support for popular machine learning frameworks such as PyTorch and TensorFlow. This means you can continue using your existing workflows and get started with AWS Inferentia with only a few lines of code changes. 6. Inf2 instances support scale-out distributed inference with ultra-high-speed connectivity between accelerators. Use cases for inference applications include natural language processing, article summarization, media generation, speech recognition and fraud detection. In summary, Inferentia2 accelerators are purpose built to run deep learning models at scale while offering upto 50% better performance/watt over comparable Amazon EC2 instances. There you have it.