
Advancing AI with Multimodal LLMs: Insights from MM1
Explore Apple's MM1 paper on Multimodal Large Language Models (MLLMs). Learn about their architecture, pre-training strategies, and AI potentials.
TOPIC
Foundation models, multimodal LLMs (Gemini, Gemma, Mistral, MM1), prompt engineering, and the open-source releases that shape what banks can build inside their own data perimeter.

Explore Apple's MM1 paper on Multimodal Large Language Models (MLLMs). Learn about their architecture, pre-training strategies, and AI potentials.

Meet Mistral AI's new multilingual Assistant. An advanced AI that can understand and respond in multiple languages, all in one conversation and in real-time.

Explore Google's Gemma AI Model: An open-source project offering ethical AI solutions for both personal and enterprise use.

Gemini 1.5 from Google scales context windows past 1M tokens. What that unlocks for retrieval-augmented finance and the trade-offs worth knowing.

Prompt engineering controls LLM behaviour at inference time. This article covers zero-shot and few-shot prompting, chain-of-thought reasoning, self-consistency sampling, ReAct tool-use architecture, indirect prompt injection risks, and applied patterns from financial services deployments.

AI trends for 2024: generative AI in finance, multimodal models, on-device LLMs and the shifts that will reshape banking and product engineering.

Explore Generative AI in 2023: how it works, where it lands first in financial services, and the ethical and architectural questions worth asking.