|
86 | 86 | }, |
87 | 87 | "outputs": [], |
88 | 88 | "source": [ |
89 | | - "%pip install -q -U \"google-genai>=1.0.0\"" |
| 89 | + "%pip install -q -U \"google-genai>=1.19.0\"" |
90 | 90 | ] |
91 | 91 | }, |
92 | 92 | { |
|
133 | 133 | }, |
134 | 134 | "outputs": [], |
135 | 135 | "source": [ |
136 | | - "MODEL_ID = \"gemini-2.5-flash-preview-05-20\" # @param [\"gemini-2.0-flash-lite\",\"gemini-2.0-flash\",\"gemini-2.5-flash-preview-05-20\",\"gemini-2.5-pro-preview-05-06\"] {\"allow-input\":true, isTemplate: true}" |
| 136 | + "MODEL_ID = \"gemini-2.5-flash-preview-05-20\" # @param [\"gemini-2.0-flash-lite\",\"gemini-2.0-flash\",\"gemini-2.5-flash-preview-05-20\",\"gemini-2.5-pro-preview-06-05\"] {\"allow-input\":true, isTemplate: true}" |
137 | 137 | ] |
138 | 138 | }, |
139 | 139 | { |
|
439 | 439 | "outputs": [ |
440 | 440 | { |
441 | 441 | "data": { |
442 | | - "text/markdown": "Here is a summary of the YouTube video content based on the provided information:\n\n1. **Main Thesis/Claim:** The creator claims that Google's newly released Gemini 2.5 Pro (specifically the experimental 03-25 version tested) is the best coding AI they have ever used, demonstrating impressive capabilities in generating and refactoring code across various languages and tasks, often outperforming other models.\n2. **Key Topics:**\n * Evaluation of Gemini 2.5 Pro's coding abilities.\n * Attempted coding projects:\n * Generating an Ultimate Tic-Tac-Toe game (Java using Swing) - successful one-shot.\n * Generating a Kitten Cannon-style game (`p5.js`/JavaScript) - required multiple prompts/corrections to fix errors (a \"three-shot\").\n * Building a landing page (Vite/React/Tailwind CSS) from a mockup image - generated code and instructions, but required manual setup and the resulting UI wasn't a perfect match (\"garbage\" UI according to the creator).\n * Recreating the X (Twitter) website UI (HTML) - generated a static visual representation.\n * Refactoring existing Rust code using iterators - produced cleaner, more idiomatic code.\n * Comparison of Gemini 2.5 Pro's performance on various benchmarks (Reasoning & knowledge, Science, Mathematics, Code generation - LiveCodeBench v5, Code editing - Aider Polyglot, Agentic coding - SWE-bench verified, Factuality - SimpleQA, Visual reasoning - MMMU, Image understanding - Vibe-Eval (Reka), Long context - MRCR, Multilingual performance - Global MMLU (Lite)), highlighting its strong performance, particularly in areas beyond simple code generation compared to competitors like OpenAI, Claude, Grok, and DeepSeek.\n * Discussion of Gemini's training data knowledge date (mentioned as March 2025, although a test for the current React version required Google Search).\n3. **Call to Action:** The creator asks viewers to subscribe, like the video, and hit the notification bell (11:15). He also asks for comments on the refactored Rust code (10:58).\n4. **Summary:** This video tests Google's Gemini 2.5 Pro AI model for its coding capabilities by attempting several distinct projects: generating games in Java/Swing and p5.js, building front-end applications with Vite/React/Tailwind, recreating a website UI with HTML, and refactoring Rust code. While some projects were successfully generated or significantly improved (Ultimate Tic-Tac-Toe, Rust refactoring), others required iteration or manual fixes (Kitten Cannon, Landing Page UI). The creator also reviews benchmark data comparing Gemini 2.5 Pro to competing models, showing its strong performance across various AI tasks, especially in mathematics and reasoning. He concludes that Gemini 2.5 Pro is an impressive and powerful tool for coding, particularly highlighting its potential when integrated into development workflows like Windsurf.", |
| 442 | + "text/markdown": [ |
| 443 | + "Here is a summary of the YouTube video content based on the provided information:\n", |
| 444 | + "\n", |
| 445 | + "1. **Main Thesis/Claim:** The creator claims that Google's newly released Gemini 2.5 Pro (specifically the experimental 03-25 version tested) is the best coding AI they have ever used, demonstrating impressive capabilities in generating and refactoring code across various languages and tasks, often outperforming other models.\n", |
| 446 | + "2. **Key Topics:**\n", |
| 447 | + " * Evaluation of Gemini 2.5 Pro's coding abilities.\n", |
| 448 | + " * Attempted coding projects:\n", |
| 449 | + " * Generating an Ultimate Tic-Tac-Toe game (Java using Swing) - successful one-shot.\n", |
| 450 | + " * Generating a Kitten Cannon-style game (`p5.js`/JavaScript) - required multiple prompts/corrections to fix errors (a \"three-shot\").\n", |
| 451 | + " * Building a landing page (Vite/React/Tailwind CSS) from a mockup image - generated code and instructions, but required manual setup and the resulting UI wasn't a perfect match (\"garbage\" UI according to the creator).\n", |
| 452 | + " * Recreating the X (Twitter) website UI (HTML) - generated a static visual representation.\n", |
| 453 | + " * Refactoring existing Rust code using iterators - produced cleaner, more idiomatic code.\n", |
| 454 | + " * Comparison of Gemini 2.5 Pro's performance on various benchmarks (Reasoning & knowledge, Science, Mathematics, Code generation - LiveCodeBench v5, Code editing - Aider Polyglot, Agentic coding - SWE-bench verified, Factuality - SimpleQA, Visual reasoning - MMMU, Image understanding - Vibe-Eval (Reka), Long context - MRCR, Multilingual performance - Global MMLU (Lite)), highlighting its strong performance, particularly in areas beyond simple code generation compared to competitors like OpenAI, Claude, Grok, and DeepSeek.\n", |
| 455 | + " * Discussion of Gemini's training data knowledge date (mentioned as March 2025, although a test for the current React version required Google Search).\n", |
| 456 | + "3. **Call to Action:** The creator asks viewers to subscribe, like the video, and hit the notification bell (11:15). He also asks for comments on the refactored Rust code (10:58).\n", |
| 457 | + "4. **Summary:** This video tests Google's Gemini 2.5 Pro AI model for its coding capabilities by attempting several distinct projects: generating games in Java/Swing and p5.js, building front-end applications with Vite/React/Tailwind, recreating a website UI with HTML, and refactoring Rust code. While some projects were successfully generated or significantly improved (Ultimate Tic-Tac-Toe, Rust refactoring), others required iteration or manual fixes (Kitten Cannon, Landing Page UI). The creator also reviews benchmark data comparing Gemini 2.5 Pro to competing models, showing its strong performance across various AI tasks, especially in mathematics and reasoning. He concludes that Gemini 2.5 Pro is an impressive and powerful tool for coding, particularly highlighting its potential when integrated into development workflows like Windsurf." |
| 458 | + ], |
443 | 459 | "text/plain": [ |
444 | 460 | "<IPython.core.display.Markdown object>" |
445 | 461 | ] |
|
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