Is AGI Just a Fantasy?

The video focuses on Cohere, a Toronto-based company working on language models for practical applications rather than pursuing Artificial General Intelligence (AGI). Cohere’s approach involves retrieval augmented generation, utilizing external knowledge to enhance the reliability and usefulness of language models for real-world business solutions.

In the video, the focus is on Cohere, a company in Toronto that is working on language models for solving real-world problems rather than aiming to create AGI (Artificial General Intelligence). They have recently released new models called command R and command R plus, which are designed for multilingual retrieval augmented generation. This approach involves using a generator to create text and augmenting it with external knowledge from a retrieval database. The co-founder of Cohere, Nick Frost, explains how their technology aims to make large language models useful for businesses by leveraging external knowledge to enhance tasks.

Nick Frost, who previously worked with Google Brain, shares insights about his experience working with Jeff Hinton and his transition into building a language model company. He emphasizes the importance of focusing on real-world Enterprise Business Solutions rather than chasing after AGI. The company’s differentiation lies in their focus on practical applications of language models for businesses rather than building models for general conversational purposes.

The discussion delves into the concept of retrieval augmented generation, which aims to address the issues of hallucination in language models. By providing citations and sources for generated text, the model can ground its answers in external knowledge, making it more reliable and useful for tasks that require accurate information. The conversation also explores the evolution of tool use in language models, where models can utilize external tools like search engines or calculators to enhance their capabilities.

The video touches on the challenges and limitations of benchmarking language models and the importance of developing more robust evaluation methods that align with real-world business use cases. Cohere emphasizes the need for models that can effectively solve business problems rather than focusing solely on performance in artificial benchmarks that may not reflect practical utility. The discussion highlights the shift towards a more software engineering-focused approach in deploying language models, where prompt tuning and infrastructure development play a significant role in getting models into production effectively.

In conclusion, the video showcases Cohere’s commitment to building practical and efficient language models for businesses, leveraging retrieval augmented generation and multilingual capabilities to enhance tasks. The company’s open-source release of the chat toolkit allows developers to explore tool use and multihop interactions in building chat interfaces. Nick Frost’s insights shed light on the evolving landscape of language modeling, emphasizing the importance of aligning technology with real-world applications and the need for robust evaluation methods that prioritize utility over artificial benchmarks.