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1
- Introduction
2
- Multi-Modal/imagery input
3
- Predictable scaling
4
- Performance on exams
5
- Rule-Based Reward Models RBRMs
6
- Spatial Awareness of non-vision GPT-4
7
- Non-multimodel vision ability
8
- Programming
9
- Theory of Mind
10
- Music and Math
11
- Challenges w/ Planning
12
- Hallucinations
13
- Risks
14
- Biases
15
- Privacy
16
- Generative Models used in Training/Evals
17
- Acceleration
18
- AGI
Description:
Dive into an hour-long video analysis of the latest advancements in Generative Pre-trained Transformer (GPT) language models, focusing on OpenAI's GPT-4 Technical Report and Microsoft's "Sparks of AGI" paper. Explore topics such as multi-modal input, predictable scaling, exam performance, rule-based reward models, spatial awareness, programming capabilities, theory of mind, and potential challenges. Examine the implications of these developments, including risks, biases, privacy concerns, and the acceleration towards Artificial General Intelligence (AGI). Gain insights into the current state of GPT and Large Language Models (LLMs) and their potential impact on various fields.

Sparks of AGI - Analyzing GPT-4 and the Latest GPT-LLM Models

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