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LLaMA 4 Uncovers the Activities of Closed Source Models
#LLaMA #Reveals #Closed #Source #Models
Dive into Meta’s latest AI breakthrough with the LLaMA 4 series, setting new benchmarks in democratizing cutting-edge technology. Explore the innovative mixture-of-experts architecture across Scout, Maverick, and Behemoth models, achieving unparalleled efficiency and scalability. The LLaMA 4 boasts incredible context lengths, such as Scout’s 10 million tokens, optimized through new training techniques like Meta P and FP8 precision computing. This video offers a thorough technical analysis, highlighting benchmarks, unique architectural features, and the strategic advantage of open-source AI, setting it apart from leading competitors. Gain insights into how LLaMA 4 promises to redefine AI accessibility and performance.
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🗂 Relevant Links:
🤖 Llama 4: https://ai.meta.com/blog/llama-4-multimodal-intelligence/
🤖 The needle in haystack test: https://medium.com/data-science/the-needle-in-a-haystack-test-a94974c1ad38
🤖 Negative Log Liklyhood: https://medium.com/deeplearningmadeeasy/negative-log-likelihood-6bd79b55d8b6
🤖 Impact of Positional Encoding: https://arxiv.org/pdf/2305.19466
🤖 Scalable Softmax: https://arxiv.org/pdf/2501.19399
🤖 AI Leadboard: https://lmarena.ai/?leaderboard
🤖 Meta AI Chat: https://www.meta.ai/
🤖 Download Models: https://www.llama.com/
🤖 On Github: https://github.com/meta-llama/llama-models/blob/main/models/llama4/MODEL_CARD.md
🤖 On Huggingface: https://huggingface.co/collections/meta-llama/llama-4-67f0c30d9fe03840bc9d0164
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⏰ Chapters:
00:00 Introduction to Llama 4 by Meta
01:31 Overview of the Llama 4 Model Family
04:00 Llama 4 Scout and Maverick Model Specifications
05:50 Performance Benchmarks and Comparisons
08:28 Pre-training Methodology and Mixture of Experts
12:12 Meta P Hyperparameter Technique
15:53 Post-training Pipeline and Curriculum Strategy
19:25 Supervised Fine-tuning and Reinforcement Learning Approach
24:22 Context Window Innovations (10M tokens)
28:59 IROP Architecture for Extended Context Length
33:03 The Behemoth Teacher Model (2T parameters)
36:36 Model Distillation Process
39:19 Conclusion and Open Source AI Benefits
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#GiveMeTheMic #MetaAI #LLaMA4 #OpenSourceAI #MultimodalAI #AIInnovation
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