Summary
The Deep Seek team unveiled the new Deep Seek Version 3.1 model, featuring enhanced features and exceptional performance in coding benchmarks. The upcoming R2 launch introduces a mixture of experts model praised for its innovation in the open-source coding community. This AI model showcases its capabilities in writing code, managing personal finances, solving complex mathematical equations, generating symmetrical designs, and understanding text-based queries with precision and efficiency.
Chapters
Deep Seek Version 3.1 Model Release
R2 Launch - A Mixture of Experts Model
AI Newsletter and Models Testing
Monthly Incomes Tracking App and Finance Management
Game of Life in Python and SVG Generation
Logical Problem-Solving and Python Bug Fix
Product Combination Assessment
Reading Comprehension and Recall
Deep Seek Version 3.1 Model Release
The Deep Seek team quietly launched the new Deep Seek Version 3.1 model, a massive model with enhanced features under the MIT license. Users are raving about its performance and it outperforms previous versions in coding benchmarks.
R2 Launch - A Mixture of Experts Model
The Deep Seek team is gearing up for the R2 launch, introducing a mixture of experts model that has been receiving positive feedback from users. This model is set to be a game-changer in the open-source coding community.
AI Newsletter and Models Testing
Discussion about the world of AI newsletter and model testing, showcasing a model's ability to flawlessly write code and solve complex mathematical equations. The model is praised for outperforming others in various tasks.
Monthly Incomes Tracking App and Finance Management
Exploration of a monthly incomes tracking app that efficiently manages finances by displaying expenses and balances. The AI model successfully generates financial summaries, demonstrating its useful application in personal finance management.
Game of Life in Python and SVG Generation
Testing the AI model's ability to implement complex simulations by creating an SVG representation of a prompt. The model performs well in generating symmetrical designs, showcasing its capability in solving intricate problems.
Logical Problem-Solving and Python Bug Fix
Solving a logical problem using multiple steps and fixing a Python bug that involves summing even numbers. The AI model efficiently resolves the issues and provides explanations for fixing the bug.
Product Combination Assessment
Assessment of an AI model's ability to determine valid combinations of product purchases within a given budget constraint. The model successfully identifies valid product combinations, showcasing its capability in problem-solving.
Reading Comprehension and Recall
Testing the model's reading comprehension by providing prompts. The model recalls and responds accurately to the prompts, demonstrating its effectiveness in understanding and responding to text-based queries.
Get your own AI Agent Today
Thousands of businesses worldwide are using Chaindesk Generative
AI platform.
Don't get left behind - start building your
own custom AI chatbot now!