Radical Reads

This month, Radical Ventures portfolio company Cohere introduced Command R+, a new large language model (LLM) tailored for real-world business applications and workflows. The model has climbed the Arena rankings establishing itself as the best open model today. 

Following the launch of Command R+, Radical Ventures Partner Aaron Brindle spoke with Cohere CEO and Co-founder Aidan Gomez – also an author of the seminal paper that invented the Transformer architecture that underpins Generative AI – about the new model and the future of LLMs. 

Aaron Brindle (AB): Congratulations on the launch of Cohere’s latest large language model, Command R+. What was the ambition behind building this model?

Aidan Gomez (AG): We believe this will be the year that enterprises move beyond proof-of-concept AI projects and into large-scale production. When we designed our latest Command R series of models, we focused on building state-of-the-art large language models that enterprises can efficiently scale into production. We took a customer-first approach and were very intentional about the capabilities we wanted our models to excel at based on real-world business needs for AI.

AB: How is Command R+ different from the latest models released by OpenAI and Google?

AG: Command R+ is the market leader in the emerging scalable model category, which balances high efficiency with strong accuracy to handle enterprise-grade workloads. Our most powerful model to date is best-in-class at business-critical capabilities. Command R+ excels at Retrieval Augmented Generation (RAG) with citations to reduce hallucinations, multilingual coverage in 10 key languages to support global business operations, and Tool Use to automate sophisticated business processes.

AB: What are the critical performance considerations for enterprises looking to deploy LLMs today?

AG: The key considerations for our enterprise partners like Microsoft and Oracle when deploying LLMs are accuracy, efficiency, price point, and data privacy. Enterprises are looking for models with strong out-of-the-box performance that are scalable into production environments. Cohere has been committed to building our technology with data privacy at the core from the beginning and when designing our latest Command R+ model we focused on addressing the right combination of these business needs so that our AI technology can unlock real productivity gains.

AB: Why did Cohere decide to make the weights for Command R available?

AG: We have strongly supported the wider academic AI research community from the start, and that’s why we set up our non-profit research lab Cohere For AI. We released the weights of our Command R model family to help researchers advance breakthroughs for the industry and to allow our models to be independently evaluated. For all enterprise and commercial use our models require a commercial license and will be continually improved for customers.

AB: How does open-source contribute to innovation in the LLM space?

AG: The work of Cohere for AI and the wider research community helps to advance what’s possible with AI technology. We will continue to support the ML ecosystem with initiatives like research compute grants and open-source research releases like Aya that makes LLMs more accessible to cover previously underserved languages and communities.

AB: As you look to what’s next, what are the kinds of innovations we can expect from future LLMs?

AG: LLMs will continue to improve and become core reasoning engines that can automate tasks and take real-world action. We see many promising use cases for enterprises to leverage AI across sectors like financial services, retail, and technology. In particular, we see a lot of opportunity with Tool Use which helps upgrade our model applications from simple chatbots to powerful agents and research tools to increase productivity for businesses.