Podcast
Questions and Answers
Which of the following best describes Deepseek's approach to AI model development?
Which of the following best describes Deepseek's approach to AI model development?
- Focusing on closed-source models to ensure proprietary advantages.
- Offering an open-source, cheaper alternative with comparable or superior accuracy. (correct)
- Relying solely on supervised learning techniques for all training phases.
- Prioritizing extremely large datasets for training to achieve the highest accuracy.
What is a key difference between Deepseek and OpenAI models regarding their accessibility?
What is a key difference between Deepseek and OpenAI models regarding their accessibility?
- Deepseek uses a more complex API that restricts access.
- Deepseek is open source, whereas OpenAI is not, making Deepseek more available to the public. (correct)
- OpenAI models are cheaper to use, making them more accessible to the average user.
- Deepseek models are only available to large corporations, while OpenAI models are more widely accessible.
In terms of training data, how does Deepseek differ from many other AI models?
In terms of training data, how does Deepseek differ from many other AI models?
- It relies on synthetic data rather than real-world data.
- It uses a significantly larger dataset than other models.
- It employs multiple datasets using a combination of supervised and unsupervised learning.
- It uses a smaller training dataset, yet achieves comparable capabilities. (correct)
Which feature allows users to directly observe Deepseek's reasoning process when running the model locally?
Which feature allows users to directly observe Deepseek's reasoning process when running the model locally?
A significant cost difference between Deepseek and OpenAI was mentioned. What are costs per million tokens?
A significant cost difference between Deepseek and OpenAI was mentioned. What are costs per million tokens?
Which of the following can be used to run Deepseek on a local machine?
Which of the following can be used to run Deepseek on a local machine?
Besides answering questions, what is another capability of Deepseek that was highlighted?
Besides answering questions, what is another capability of Deepseek that was highlighted?
What has been stated as a primary goal of Deepseek's entry into the AI market?
What has been stated as a primary goal of Deepseek's entry into the AI market?
Flashcards
What is Deepseek?
What is Deepseek?
Deepseek is an open-source AI model that offers a cost-effective alternative to models like ChatGPT, primarily known for its powerful capabilities in code generation and question answering.
How does Deepseek's transparency differ from other AI models?
How does Deepseek's transparency differ from other AI models?
Unlike many AI models, Deepseek allows users to see the model's thought process through the "think" tag when running it locally, providing transparency and insights into its workings.
What are the size variations of Deepseek?
What are the size variations of Deepseek?
Deepseek models are available in different sizes, ranging from 1.5 billion to 671 billion parameters, allowing users to choose a model that best suits their needs and computing resources.
How is Deepseek trained?
How is Deepseek trained?
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How can I run Deepseek locally?
How can I run Deepseek locally?
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How does Deepseek compare in cost to OpenAI models?
How does Deepseek compare in cost to OpenAI models?
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What is the significance of Deepseek's availability?
What is the significance of Deepseek's availability?
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How does Deepseek compare in performance to other AI models?
How does Deepseek compare in performance to other AI models?
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Study Notes
Deepseek AI
- Deepseek is an open-source, free-to-use AI model.
- Deepseek offers a more affordable alternative to models like ChatGPT.
- Deepseek addresses the high pricing of companies like OpenAI, fostering a more competitive AI market.
- Deepseek's accuracy is comparable to other AI models; sometimes it surpasses them.
- Deepseek R1 is the latest model version.
- Deepseek costs approximately $0.14 per million tokens, significantly less than OpenAI's $7.50 per million tokens.
- Deepseek uses reinforcement learning for training.
- Deepseek R1 was trained on a smaller dataset than typical models, yet demonstrates impressive thinking capabilities.
- Deepseek comes in various sizes, ranging from 1.5 billion to 671 billion parameters.
- Users can run Deepseek locally using AMA (a machine learning toolkit).
- Deepseek models are downloadable and executable using AMA.
- Users can observe Deepseek's thought processes through the "think" tag when running locally.
- Deepseek applications include code generation and answering questions.
- Deepseek democratizes AI model access and affordability.
Deepseek vs OpenAI Models
- Deepseek is open-source; OpenAI is closed-source.
- Deepseek is a more budget-friendly choice compared to OpenAI models.
- Deepseek's accuracy rivals and sometimes exceeds OpenAI's.
Training Deepseek
- Deepseek training leverages reinforcement learning.
- Deepseek training uses a smaller dataset, still achieving effective responses and revealing thought processes.
Availability and How to Access Deepseek
- Deepseek is freely available and open-source.
- Users can run Deepseek locally by downloading and installing AMA.
- The command "AMA run Deepseek" initiates the process, specifying the desired model size.
Significance of Deepseek
- Deepseek represents a significant advancement in AI, enhancing accessibility and affordability.
- Deepseek is a powerful and cost-effective alternative to other AI models for users and developers.
- Deepseek's goal is to foster a more competitive AI market.
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