Sign up for the latest Speech AI news from NVIDIA. There is a high chance that you have asked your smart speaker a question like, “How tall is Mount Everest?” If you did, it probably said, “Mount Everest is 29,032 feet above sea level.” Have you ever wondered how it found an answer for you? Question answering (QA) is loosely defined as a system consisting of information retrieval (IR)…
]]>Enterprises across industries are leveraging natural language process (NLP) solutions—from chatbots to audio transcription—to improve customer engagement, increase employee productivity, and drive revenue growth. NLP is one of the most challenging tasks for AI because it must understand the underlying context of text without explicit rules in human language. Building an AI-powered solution…
]]>With the third-generation Tensor Core technology, NVIDIA recently unveiled A100 Tensor Core GPU that delivers unprecedented acceleration at every scale for AI, data analytics, and high-performance computing. Along with the great performance increase over prior generation GPUs comes another groundbreaking innovation, Multi-Instance GPU (MIG). With MIG, each A100 GPU can be partitioned up to seven…
]]>Conversational AI solutions such as chatbots are now deployed in the data center, on the cloud, and at the edge to deliver lower latency and high quality of service while meeting an ever-increasing demand. The strategic decision to run AI inference on any or all these compute platforms varies not only by the use case but also evolves over time with the business. Hence…
]]>Seamlessly deploying AI services at scale in production is as critical as creating the most accurate AI model. Conversational AI services, for example, need multiple models handling functions of automatic speech recognition (ASR), natural language understanding (NLU), and text-to-speech (TTS) to complete the application pipeline. To provide real-time conversation to users…
]]>Natural language processing (NLP) is one of the most challenging tasks for AI because it needs to understand context, phonics, and accent to convert human speech into text. Building this AI workflow starts with training a model that can understand and process spoken language to text. BERT is one of the best models for this task. Instead of starting from scratch to build state-of-the-art…
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