Published Mar 2, 2023

Ed Grefenstette: Language, Semantics, Cohere

Ed Grefenstette delves into the commercial applications of AI, exploring Cohere's advancements in language technology and the significance of data-driven training. He shares his insights on the role of semantics and pragmatics in AI language processing and offers career advice for budding machine learning researchers, stressing practicality and collaboration.

Episode Highlights

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Episode Highlights

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Dexa/Daniel Bashir

Ed Grefenstette: Language, Semantics, Cohere

Topics covered

Popular Clips

Collaboration and Accessibility

Science and Startups

Unconventional AI Journey

Commercial Applications

Effective Research Lessons

Language Models and Pragmatics

Teaching Machines to Read

Challenging Consciousness

Language Models and Pragmatics

Closing Thoughts

Meaning and Language Usage

Dynamic KMAX Pooling

Training AI Models

Understanding Word Embeddings

Episode Highlights

Machine Learning Applications

Language and Semantics

Career Advice

Related Episodes

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Hugo Larochelle: Deep Learning as Science

Some Changes at The Gradient

Hello World from The Gradient Podcast!

Ted Underwood: Machine Learning and the Literary Imagination

Been Kim: Interpretable Machine Learning

Terry Winograd: AI, HCI, Language, and Cognition

Ted Gibson: The Structure and Purpose of Language

Cameron Jones & Sean Trott: Understanding, Grounding, and Reference in LLMs

Vera Liao: AI Explainability and Transparency

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François Chollet: Keras and Measures of Intelligence

Melanie Mitchell: Abstraction and Analogy in AI

Miles Grimshaw: Benchmark, LangChain, and Investing in AI

Ed Grefenstette: Language, Semantics, Cohere

Topics covered

Popular Clips

Episode Highlights

Machine Learning ApplicationsEd Grefenstette explores the commercial applications of AI models and the innovative training methods that enhance their capabilities. He discusses Cohere's approach to making language technology accessible and the importance of data-driven model training.

Machine Learning Applications

Language and Semantics

Career AdviceEd Grefenstette, Head of Machine Learning at Cohere, discusses his career journey from academia to industry and offers insights for aspiring machine learning researchers. He emphasizes the importance of practical experience, collaboration, and inclusivity in the AI field.

Career Advice

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