DeepSeek AI is turning heads, achieving incredible results with older hardware and clever techniques! Join Allen and Roya as they unravel the secrets behind DeepSeek's success, from their unique attention mechanisms to their cost-effective AI training strategies. But is all as it seems? They also tackle the controversies surrounding DeepSeek, including accusations of data plagiarism and concerns about censorship. This episode is a must-listen for anyone interested in the future of AI!

Timestamps:

0:00 Why DeepSeek is creating buzz

1:06 Unveiling DeepSeek's Two Key Models

2:59 Understanding the Power of Attention

4:12 What is the latent space?

5:55 The nail salon example: Multi-Head Attention Explained

10:02 The doctor/cook/police analogy: Mixture of Experts Explained

13:51 AI vs. AI: DeepSeek's Cost-Saving Training Method

16:01 Hallucinations: Is AI Training Too Risky?

20:59 What are Reasoning Models and Why Do They Matter?

26:53 LLMs are pattern systems explained

28:22 How DeepSeek is using old GPUs

32:53 OpenAI vs. DeepSeek: The Data Plagiarism Debate

39:32 Political Correctness: The Challenge of Guardrails in AI

42:16 Why Open Source is Crucial for the Future of AI

43:20 Run DeepSeek locally on OLAMA

43:56 Final Thoughts

Hashtags: #DeepSeek #AI #LLM #Innovation #TechNews #Podcast #ArtificialIntelligence #MachineLearning #Ethics #OpenAI #DataPrivacy #Censorship #TwoVoiceDevs #DeepLearning #ReasoningModel #AIRevolution #ChinaTech