Skill Leap AI - DeepSeek R1 vs ChatGPT o3 Mini vs Gemini Flash Thinking - Ultimate Test
The video evaluates the reasoning capabilities of Chat GPT, Deep Seek, and Google Gemini by testing them with a series of prompts that increase in complexity. The reasoning models are designed to break down questions into smaller parts and think through them before responding, a process known as 'chain of thoughts.' The tests include logical deduction, creative problem-solving, and coding tasks. Chat GPT generally performs well, providing accurate answers quickly, while Deep Seek, although slower, offers detailed reasoning. Google Gemini is the fastest but sometimes lacks detailed reasoning. In a coding test, Chat GPT successfully creates a chess game with modified rules, while Deep Seek struggles with execution errors, and Gemini fails to run the game. The models are also tested on their ability to solve unsolved mathematical problems, with none able to provide a solution. The video concludes that while each model has strengths, Chat GPT often provides the most reliable and accurate responses.
Key Points:
- Reasoning models break down questions into smaller parts for better accuracy.
- Chat GPT is generally faster and more accurate in providing answers.
- Deep Seek offers detailed reasoning but is slower in response time.
- Google Gemini is the fastest but sometimes lacks detailed reasoning.
- None of the models can solve unsolved mathematical problems.
Details:
1. 🚀 Introducing Advanced AI Models
- Chad GPT, Deep Seek, and Google Gemini have newer reasoning models that outperform older models in nearly every benchmark.
- The evaluation was conducted using 10 different prompts, beginning with simpler ones.
- The benchmarks included tests on reasoning, comprehension, and adaptability, providing a comprehensive assessment of each model's capabilities.
- Chad GPT showed a 30% improvement in reasoning tasks compared to its predecessors.
- Deep Seek excelled in comprehension, outperforming older models by 25%.
- Google Gemini demonstrated superior adaptability, showing a 35% increase in performance metrics.
- These advancements highlight a significant leap in AI capabilities, setting new standards for future developments.
2. 🧠 Understanding Reasoning Models
- Chat GPT O3 mini, Deep Seek R1, and Google Gemini's Flash thinking models are key reasoning models discussed, providing a foundation for understanding how machines can replicate human reasoning processes.
- These models are crucial for advancements in AI, offering insights into how machines can process information and make decisions akin to human reasoning.
- HubSpot is mentioned as a sponsor, indicating potential integration or applications of these models within business ecosystems to enhance customer engagement and operational efficiency.
3. 🔍 Comparative Testing of AI Capabilities
- AI models now employ reasoning models that break down questions into smaller parts, resulting in a more thoughtful response. This approach, known as 'chain of thoughts,' allows for some questions to take several minutes of processing.
- Different AI models, such as Chat GPT 3.5 and Google Gemini Advanced, include reasoning functionalities and search capabilities, enhancing their ability to provide up-to-date information.
- The use of reasoning models in AI demonstrates a shift from instant answers to more calculated responses, potentially improving the accuracy and relevance of AI-generated information.
- Chat GPT 3.5 has improved its reasoning capabilities by integrating search functions, which helps in accessing the latest data and providing more accurate answers.
- Google Gemini Advanced distinguishes itself with its advanced reasoning algorithms, allowing it to handle more complex queries effectively.
- Both models show a trend towards more deliberative processing, which may lead to longer response times but improved accuracy and depth in responses.
4. 🕵️♂️ Unpacking AI's Thought Process
- An AI model, Deep Seek, took 88 seconds to solve a problem with detailed reasoning breakdowns, in contrast to ChatGPT's 5-second solution time for the same task.
- Deep Seek, although slower, provides a more elaborate reasoning breakdown, which potentially enhances accuracy, crucial for complex reasoning tasks.
- The comparison highlights a trade-off between speed and accuracy, suggesting that in scenarios demanding nuanced understanding, models like Deep Seek could be more beneficial despite their slower processing times.
5. 🔗 Tackling Complex Problem-Solving
- The Gemini model is the fastest among the models tested, providing instant answers in about two seconds, although it does not specify thinking time like other models.
- The Gemini model and the chat GPT model demonstrated similar speeds, with Gemini using a straightforward thinking process to solve basic reasoning questions.
- In the prompt where the question was 'which came first, the chicken or the egg,' both Deep Seek and Gemini provided the scientifically accepted answer that 'the egg came first,' indicating consistency in reasoning.
- For a creative problem-solving task involving measuring the height of a building with only a rope and body height, chat GPT's answer was impractical, suggesting using one's body as a ruler in an infeasible manner.
- Deep Seek and Gemini used a similar triangles method for the building height problem, showcasing a logical and feasible approach, which was more effective than chat GPT's suggestion.
6. 🧩 Logic and Deduction Challenges
6.1. Logic Question Description
6.2. AI Response Analysis
7. 💼 Applying AI to Practical Tasks
- Reasoning models for AI tasks require simple prompts, breaking down questions into smaller components for effective problem-solving.
- HubSpot offers a resource with over a thousand expertly crafted prompts, aiding in productivity, strategy, content creation, and branding, especially useful for marketers, entrepreneurs, and content creators.
- The HubSpot resource's marketing strategy and brand pricing strategy sections are particularly useful, providing organized categories that simplify application.
- Reasoning models excel in strategic tasks, offering advantages over standard models like ChatGPT-4, suggesting their suitability for complex applications.
- Utilizing these resources can streamline content creation and strategic planning, enhancing overall productivity.
8. ♟️ Coding and Chess Game Challenges
- A custom chess game was developed where the king moves like a queen, testing AI models' adaptability to rule changes.
- Initial results showed models could execute basic movements correctly, adjusting to the king's enhanced movement rule.
- The AI demonstrated flexibility in adapting to modified piece movement, handling the changes with relative ease.
- However, the models struggled with understanding complex end conditions like checkmate, revealing a significant limitation in game logic comprehension.
- This highlights the need for improvements in AI's ability to recognize and process advanced game scenarios beyond basic movement rules.
9. 🔧 Debugging and Code Evaluation
9.1. Deep Seek Evaluation
9.2. Gemini Evaluation
9.3. Code Debugging and Interaction
10. 🖼️ Vision and Reasoning Integration
- The updated code resolved the crashing issue encountered by Gemini, allowing the game to operate without errors, but the chess game logic still allows the King to move like a Queen, suggesting a need for improved rule implementation.
- Deep Seek successfully ran the game, fixing the initial crashing issue, yet faced the same logic error with the King’s movements, highlighting persistent challenges in rule-based logic.
- AI models were tested for identifying the creators of digital images: ChatGPT failed to identify the AI model creator, Deep Seek couldn't succeed due to a lack of text extraction capabilities, whereas Gemini successfully identified Mid Journey as the likely creator, demonstrating its advanced reasoning capabilities.
11. 🌐 AI Search Abilities and Summarization
- ChatGPT identified ChatGPT 4.0 and 3.0 as the best models for general-purpose and conversational use, while Google Gemini was recommended for multimodal and deep reasoning tasks.
- Different AI models were evaluated: ChatGPT for general use, Google Gemini for deep reasoning, and Deep Seek R1 for cost efficiency, highlighting the strengths and ideal use cases for each model.
- The importance of AI models utilizing up-to-date information was emphasized, particularly for applications requiring current data.
- Initial responses from AI were critiqued for being outdated, suggesting a reliance on internal knowledge rather than current search results.
- Subsequent improvements in search results were noted, but initial responses often relied on outdated mid-2024 data.
- ChatGPT initially provided correct information, while Google Gemini's response was lengthy and not current, indicating a need for balance between detail and timeliness.
12. 🔄 Consistency in Follow-up Prompts
- Deep Seek R1 scores 89 out of 100 in quality metrics, outperforming GPT-4.0.
- GPT-4.0 is selected as the best model for general purpose and reasoning, with justification provided for this choice.
- The importance of enabling search to avoid outdated information from training data.
- A detailed comparison between Deep Seek R1 and GPT-4.0 could enhance understanding of their respective strengths.
- More specific examples or data points could improve the comprehensiveness of the evaluation.