The advent of large language models (LLMs) like GPT-4 has sparked excitement around enhancing them with multimodal capabilities to understand visual data alongside text. However, previous efforts to create powerful multimodal LLMs have faced challenges in scaling up efficiently while maintaining performance. To mitigate these issues, the researchers took inspiration from the mixture-of-experts (MoE) architecture, widely used to scale up LLMs by replacing dense layers with sparse expert modules.

In the MoE approach, instead of passing inputs through a single large model, there are many smaller expert sub-models that each specialize on a subset of the data. A routing network determines which expert(s) should process each input example. It allows scaling up total model capacity in a more parameter-efficient way.

In their approach (shown in Figure 2), CuMo, the researchers integrated sparse MoE blocks into the vision encoder and the vision-language connector of a multimodal LLM. This allows different expert modules to process different parts of the visual and text inputs in parallel rather than relying on a monolithic model to analyze everything.

🤖 🏛️ Have you ever wondered about the connection between AI and Ancient Greek Philosophy?

🧔 📜 The ancient Greek philosophers, such as Aristotle, Plato, Socrates, Democritus, Epicurus and Heraclitus explored the nature of intelligence and consciousness thousands of years ago, and their ideas are still relevant today in the age of AI.

🧠 📚 Aristotle believed that there are different levels of intelligence, ranging from inanimate objects to human beings, with each level having a distinct form of intelligence. In the context of AI, this idea raises questions about the nature of machine intelligence and where it falls in the spectrum of intelligence. Meanwhile, Plato believed that knowledge is innate and can be discovered through reason and contemplation. This view has implications for AI, as it suggests that a machine could potentially have access to all knowledge, but it may not necessarily understand it in the same way that a human would.

At Google I/O, Google previewed a generative AI model that can create videos at 1080p around a minute in length.

Jeff Bezos emailed Amazon execs to ask why more AI firms aren’t using its cloud services, CNBC reported.