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Multi-modal Language Models: Expanding the Boundaries of Artificial Intelligence

Summary

In recent years, the field of artificial intelligence (AI) has witnessed significant advancements, thanks to the emergence of multi-modal language models (MLLMs). These sophisticated software models have the ability to process, understand, and draw conclusions from diverse input data such […]

Multi-modal Language Models: Expanding the Boundaries of Artificial Intelligence

In recent years, the field of artificial intelligence (AI) has witnessed significant advancements, thanks to the emergence of multi-modal language models (MLLMs). These sophisticated software models have the ability to process, understand, and draw conclusions from diverse input data such as videos, images, and sounds, going beyond simple textual inputs. This has opened up a whole new set of applications in various sectors, including medicine, law, the automotive industry, and many more.

John Hayes, the founder and CEO of Ghost Autonomy, a pioneer in scalable autonomous software for consumer vehicles, will be sharing his insights on MLLMs at the Financial Times Future of AI summit. The summit, taking place in London from November 15th to November 16th, 2023, will bring together industry leaders in strategy, innovation, technology, and business functions to discuss the integration, scalability, and commercialization of AI.

During his twenty-minute presentation titled “Transforming AI Technologies and Innovations into Marketable Products,” John will delve into the concept of MLLMs, highlighting the areas of technology that are most likely to be impacted by their capabilities. He will also explore the implications of these new models for the application of AI in different use cases. The session will address the major challenges that companies need to overcome when using MLLMs, as well as areas where these models still need improvement.

John will share his insights on the first commercialized applications of MLLMs and how highly regulated industries with potentially critical safety concerns, such as medicine, law, and autonomous driving, can successfully implement them in the market.

Frequently Asked Questions

Q: What are multi-modal language models?
A: Multi-modal language models are sophisticated AI software models that can process and draw conclusions from diverse input data such as videos, images, and sounds. These models expand the capabilities of AI beyond simple textual inputs, opening up new applications in various industries.

Q: Who is John Hayes?
A: John Hayes is the CEO and founder of Ghost Autonomy. Prior to Ghost, he founded and served as CEO of Pure Storage, a publicly traded company. With his expertise in data storage technology, John is applying multi-modal language models to advance autonomous driving.

Q: What is the purpose of using multi-modal language models in autonomous driving?
A: The use of multi-modal language models in autonomous driving enables vehicles to understand and navigate complex driving scenarios, even those they have never encountered before. These sophisticated models apply human-like thinking to driving, creating new possibilities for efficient and safe autonomous driving.

For more information, including videos and integration details, visit Ghost’s blog.