Future challenges in human language understanding
Who is this presentation for?
- CTOs, product managers, and machine learning engineers
The dream of AI is a system that truly understands human speech—in different environments with a variety of accents and languages. For decades, people have tackled this problem with no success. Pinpointing effective strategies for creating such a system seemed impossible.
In the past years, however, breakthroughs in AI have changed everything in the quest for conversational AI, and there’s been a leap forward in development, manifesting in a wide range of products. Yishay Carmiel reviews recent advances in conversational AI, examines the elements that have contributed to the rapid progress and discusses how far we may be from solving the problem completely and what are the near-term and long-term challenges.
- A basic understanding of machine learning terms
What you'll learn
- Understand the basic essentials in building human language understanding, the barrier of entry, and the future challenges still to come
Yishay Carmiel is the founder of IntelligentWire, a company that develops and implements industry-leading deep learning and AI technologies for automatic speech recognition (ASR), natural language processing (NLP), and advanced voice data extraction, and is the head of Spoken Labs, the strategic artificial intelligence and machine learning research arm of Spoken Communications. Yishay and his teams are currently working on bleeding-edge innovations that make the real-time customer experience a reality—at scale. Yishay has nearly 20 years’ experience as an algorithm scientist and technology leader building large-scale machine learning algorithms and serving as a deep learning expert.
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