Unlocking Deep Seek R1: Running Advanced Chinese AI Locally
- Authors
- Published on
- Published on
In this riveting episode by David Ondrej, we dive headfirst into the world of AI with the groundbreaking Deep Seek R1 model from China. Surpassing the once-popular Chad GBT, Deep Seek R1 is not only 27 times cheaper than O1 but also boasts a staggering 671 billion parameters. This AI powerhouse has sent shockwaves through the tech industry, causing a massive $600 billion loss for American giants like Nvidia and AMD. But fear not, as Deep Seek R1 offers smaller distilled versions that can run on a variety of computer setups, making its cutting-edge technology accessible to all.
As we witness the global outage at Deep Seek due to its unprecedented popularity, the spotlight shines on the model's reasoning capabilities. Unlike traditional language models, Deep Seek's reasoning models provide insightful responses that outshine the competition. Sam Altman himself acknowledges the impressive feats of Deep Seek, highlighting the healthy competition it brings to the AI arena. But the road ahead is not without its challenges, as OpenAI grapples with adapting to the success of Chinese AI models like Deep Seek.
China's rise in the AI race is no coincidence, fueled by abundant energy resources and top-tier talent. Models like Deep Seek leverage reinforcement learning, a powerful training method that sets them apart in the field. Through a step-by-step guide presented in the video, users can easily run Deep Seek R1 on their computers using tools like Vectal and AMA. By embracing open-source models like Deep Seek, users gain unprecedented insight into the inner workings of AI decision-making, ushering in a new era of adaptability and learning in the tech landscape.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Watch How to run DeepSeek on your computer (100% private) on Youtube
Viewer Reactions for How to run DeepSeek on your computer (100% private)
Running smaller than 671b parameter model is not running R1
Different base models for various sizes of models
DeepSeek allows running own AI model on own hardware
Interest in building a modular system for AI
Reinforced learning with AI models
Comparison between OpenAI and DeepSeek
Concerns about privacy and data security
Questions about feeding large data to DeepSeek
Interest in setting up text generation tasks with DeepSeek
Concerns about speed and complexity of explanations
Related Articles
Revolutionize Coding with Ultra Search AI Tool and Browser Tools mCP
Discover how David Ondrej introduces Ultra search AI tool for mCP in cursor, streamlining coding tasks. Set up GitHub and Browser Tools mCP for enhanced functionality and seamless debugging. Subscribe for cutting-edge AI tutorials and revolutionize your coding experience.
Unveiling GPT 4.5: Costs, Access, and Performance Comparisons
Discover the groundbreaking GPT 4.5 AI model, boasting 5-15 trillion parameters. Despite high costs, its unique capabilities shine. Learn how to access GPT 4.5 affordably and explore its strengths and weaknesses compared to other AI models.
Revolutionizing AI: Claude 3.7 Sonet Dominates Benchmarks and Sets New Standards
David Ondrej introduces the groundbreaking AI model Claude 3.7 Sonet, showcasing its superior performance in software engineering benchmarks and agentic tool use. The model's reduced censorship and practicality set it apart from competitors, offering a glimpse into the future of AI technology.
Logan Kilpatrick: Building AI Agents at Google Deep Mind
AI expert Logan Kilpatrick discusses coding skills, building AI agents, and the future of AI products at Google Deep Mind on the David Ondrej podcast.