GenAI Level UP20 Des 2024

Beyond GPT-4V and Sora: Multi-Modal Generative AI - Level 9

This podcast offers a comprehensive exploration of multi-modal generative AI. We examine the two dominant families of techniques, the multi-modal large language models (MLLM) and diffusion models, covering their probabilistic modeling procedures, multi-modal architecture designs, and advanced applications in image/video large language models, as well as text-to-image/video generation.

We look at how these models are being used in text-to-image/video generation and then dive into the future directions of unified models, controllable generation, and lightweight multi-modal AI.

Online Tutorials:

"Multimodal Generative AI: Vision, Speech, and Assistants " by Coursera: Offered by Codio, this course covers AI applications in image-to-text, text-to-speech, and speech-to-text tasks, along with the Assistant API. It includes practical labs and exercises to enhance learning.
“Technical Fundamentals of Generative AI” by Stanford Online: Developed by the Stanford Institute for Human-Centered Artificial Intelligence (HAI), this course explores the technical aspects of generative AI, including multimodal systems for creating images and videos. It also examines the broader implications of these technologies on society.

#genai #levelup #level9 #learn #generativeai #ai #aipapers #podcast #deeplearning #machinelearning #multimodal

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Episoder(45)

Recursive Self Improvement

Imagine holding a wrench on an assembly line. Suddenly, it leaps from your hand, sprouts its own mechanical arms, and begins forging a faster, lighter wrench without you. You are no longer the creator...

7 Jun 1h

Master the New Physics of AI with Context Graphs & GraphRAG

Stop trying to find the "magic words" to hack your LLM. The era of the Prompt Engineer—tweaking adjectives and hoping for the best—is officially over. We are entering the age of the Context Engineer, ...

1 Feb 17min

Context Graph

Stop feeding your AI static facts in a dynamic world.Most RAG systems and Knowledge Graphs rely on a fundamental unit called the "Triple" (Subject, Verb, Object). It’s efficient, but it’s brittle. It ...

25 Jan 19min

Nested Learning: The Illusion of Deep Learning Architectures

Why do today's most powerful Large Language Models feel... frozen in time? Despite their vast knowledge, they suffer from a fundamental flaw: a form of digital amnesia that prevents them from truly le...

14 Nov 202513min

Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

What if you could build AI agents that get smarter with every task, learning from successes and failures in real-time—without the astronomical cost and complexity of constant fine-tuning? This isn't a...

1 Nov 202518min

MemGPT: Towards LLMs as Operating Systems

Have you ever felt the frustration of an LLM losing the plot mid-conversation, its brilliant insights vanishing like a dream? This "goldfish memory"—the limited context window—is the Achilles' heel of...

1 Nov 202518min

DeepSeek-OCR: Contexts Optical Compression

The single biggest bottleneck for Large Language Models isn't intelligence—it's cost. The quadratic scaling of self-attention makes processing truly long documents prohibitively expensive, a fundament...

24 Okt 202513min

A Definition of AGI

For decades, Artificial General Intelligence has been a moving target, a nebulous concept that shifts every time a new AI masters a complex task. This ambiguity fuels unproductive debates and obscures...

23 Okt 202519min