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Artificial Intelligence & ChatGPT Prompts

Artificial Intelligence & ChatGPT Prompts

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🔓Unlock Your Coding Potential with ChatGPT 🚀 Your Ultimate Guide to Ace Coding Interviews! 💻 Coding tips, practice questions, and expert advice to land your dream tech job. For Promotions: @love_data

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📈 Analytical overview of Telegram channel Artificial Intelligence & ChatGPT Prompts

Channel Artificial Intelligence & ChatGPT Prompts (@curiousprogrammer) in the English language segment is an active participant. Currently, the community unites 42 288 subscribers, ranking 3 088 in the Technologies & Applications category and 8 926 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 42 288 subscribers.

According to the latest data from 03 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 35 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.60%. Within the first 24 hours after publication, content typically collects 0.66% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 677 views. Within the first day, a publication typically gains 278 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as learning, algorithm, detection, llm, pattern.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
🔓Unlock Your Coding Potential with ChatGPT 🚀 Your Ultimate Guide to Ace Coding Interviews! 💻 Coding tips, practice questions, and expert advice to land your dream tech job. For Promotions: @love_data

Thanks to the high frequency of updates (latest data received on 04 September, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

42 288
Subscribers
+724 hours
+247 days
+3530 days
Posts Archive
OpenAI New Model-01 Don't let snake-oil salesmen fool you. This new model released by OpenAI today doesn't "think." It just generates an extensive "chain of thought", which is just a discussion of the model with itself that looks like a person talking to themselves. Previous models were trained to be used in one-shot. You ask a question, you get an answer. Because of randomness in next token generation, if you were unlucky, your answer might be wrong. This model was finetuned to generate a long (and hidden from the user by the UI) discussion on how to better solve the problem, what facts are known, what assumptions need to be made, and what constraints should be respected. If you explicitly asked previous models to generate this discussion before answering your question, you would get a better quality result, because the final answer would be conditioned on the information contained in this discussion. They seemingly optimized their model to generate good quality discussions (without the user asking for it) by using reinforcement learning on various problems that have a verifiable solution, so that a reward for finding the right answer could be automatically assigned. For example: Question: 1+1 = ? Discussion: we have 1 and we have 1 more. And we have a plus sign, so it's an addition. What happens if we add 1 and 1? It means 1 is incremented by 1. When we increment 1 by 1, what do we get? Let's count: 1, 2, 3, 4,... Ok, 2 comes after 1, so 1 + 1 must be 2. Answer: 2 Reward: 1 Question: 1+1 = ? Discussion: It's easy. 1+1=11 Answer: 11 Reward: 0 Once the model is trained, what the user sees: Question: 1+1 = ? (Discussion happens behinds the scenes.) Answer: 2 Sure! Here's a more polished version of the statement: Don't get swept away by the hype around AI; Stay grounded and approach it thoughtfully. 💯

HIGH-INCOME SKILLS TO LEARN💰 1. Artificial Intelligence 2. Cloud Computing 3. Data Science 4. Machine Learning 5. Blockchain 6. Data Analytics 7. Data Engineering 8. Applications Engineering 9. Web Development 10. Software Development 11. UX Design 12. Web Design 13. Graphic Design 14. Video Editing 15. Content Marketing 16. Digital Marketing

8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the
8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the main function when the user clicks "Get Answer"

7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays indi
7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays individual responses in expandable sections • Aggregates responses using the aggregator model • Streams the aggregated response.

6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its re
6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its response

5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the agg
5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the aggregator model and its system prompt

4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and a
4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and asynchronous Together clients

3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API
3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API key

2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM i
2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM interactions

1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:
1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:

🧠 Build your own ChatGPT
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Keyboard shortcuts for Telegram Desktop ⌨️ Action : Command • Move to next chat : Ctrl + Tab • Move to next chat : Ctrl + PageDown • Move to next chat : Alt + Arrow Down • Move to previous chat : Ctrl + Shift + Tab • Move to previous chat : Ctrl + PageUp • Move to previous chat : Alt + Arrow Up • Go to Previous Folder : Ctrl + Shift + Arrow Up • Go to Next Folder : Ctrl + Shift + Arrow Down • Search selected chat : Ctrl + F • Exit selected chat and search Telegram : Esc • Exit display of current chat/channel   : Esc • Delete currently selected message : Delete • Quit Telegram : Ctrl + Q • Lock Telegram (if Local Password is set) : Ctrl + L • Iconify (Minimize) Telegram : Ctrl + M • Iconify (Minimize) Telegram to System Tray : Ctrl + W • Edit Previous Message : Arrow Up • Start New Line in Input Area : Ctrl + Enter or Shift + Enter • Move Cursor to Start of Multi-line Message : Ctrl + Home • Make Text Italic : Ctrl + I • Make Text Bold : Ctrl + B • Make Text Underline : Ctrl + U Make Text Striketrough : Ctrl + Shift + X • Make Text Monospace : Ctrl + Shift + M • Remove Text Formatting (Make Selection Plain Text) : Ctrl + Shift + N • PH4N745M • Add URL to Selected Text (Make Link) : Ctrl + K • Send File : Ctrl + O • Open Contacts : Ctrl + J • Fast Scroll : Scroll with Ctrl or Shift pressed. • Reply in another chat : Ctrl+Click on Reply in the menu. • Jump to a message from the reply panel : Ctrl + LMB. • Open conversation in a separate tab : Ctrl + click. • Jump between Folders :  Ctrl + 1,2,3... #Desktop #Shortcuts #Tips

List of top 10 hard skills: 1. Cloud Computing 2. Data Analysis 3. Digital Marketing 4. Cybersecurity 5. Artificial Intelligence (AI) and Machine Learning (ML) 6. Web Development 7. Database Management 8. Networking 9. Software Development 10. Graphic Design

How to Master Networking Looking to expand your connections? Use these tips! 1. Be genuine and approachable in conversations. 2. Prepare a brief, engaging introduction about yourself. 3. Follow up with new contacts to build lasting relationships. 4. Offer help and value to others without expecting immediate returns. 5. Attend industry events and stay active on professional platforms.

Data Science Essentials in Python.pdf5.01 MB

Preparing for a data science interview can be challenging, but with the right approach, you can increase your chances of success. Here are some tips to help you prepare for your next data science interview: 👉 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL. 👉 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning. 👉 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice. 👉 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects. 👉 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms. 👉 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve. Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 ENJOY LEARNING 👍👍

Complete Roadmap to learn SQL in 2024 👇👇 1. Basic Concepts - Understand databases and SQL. - Learn data types (INT, VARCHAR, DATE, etc.). 2. Basic Queries - SELECT: Retrieve data. - WHERE: Filter results. - ORDER BY: Sort results. - LIMIT: Restrict results. 3. Aggregate Functions - COUNT, SUM, AVG, MAX, MIN. - Use GROUP BY to group results. 4. Joins - INNER JOIN: Combine rows from two tables based on a condition. - LEFT JOIN: Include all rows from the left table. - RIGHT JOIN: Include all rows from the right table. - FULL OUTER JOIN: Include all rows from both tables. 5. Subqueries - Use nested queries for complex data retrieval. 6. Data Manipulation - INSERT: Add new records. - UPDATE: Modify existing records. - DELETE: Remove records. 7. Schema Management - CREATE TABLE: Define new tables. - ALTER TABLE: Modify existing tables. - DROP TABLE: Remove tables. 8. Indexes - Understand how to create and use indexes to optimize queries. 9. Views - Create and manage views for simplified data access. 10. Transactions - Learn about COMMIT and ROLLBACK for data integrity. 11. Advanced Topics - Stored Procedures: Automate complex tasks. - Triggers: Execute actions automatically based on events. - Normalization: Understand database design principles. 12. Practice - Use platforms like LeetCode, HackerRank, or learnsql for hands-on practice. Here are some free resources to learn  & practice SQL 👇👇 Udacity free course- https://imp.i115008.net/AoAg7K SQL For Data Analysis: https://t.me/sqlanalyst For Practice- https://stratascratch.com/?via=free SQL Learning Series: https://t.me/sqlspecialist/567 Top 10 SQL Projects with Datasets: https://t.me/DataPortfolio/16 Join for more free resources: https://t.me/free4unow_backup ENJOY LEARNING 👍👍

Confused about which field to dive into—Front-End Development (FE), Back-End Development (BE), Machine Learning (ML), or Blockchain? Here's a concise breakdown of each, designed to clarify your options: ### Front-End Development (FE) Key Skills: - HTML/CSS: Fundamental for creating the structure and style of web pages. - JavaScript: Essential for adding interactivity and functionality to websites. - Frameworks/Libraries: React, Angular, or Vue.js for efficient and scalable front-end development. - Responsive Design: Ensuring websites look good on all devices. - Version Control: Git for managing code changes and collaboration. Career Prospects: - Web Developer - UI/UX Designer - Front-End Engineer ### Back-End Development (BE) Key Skills: - Programming Languages: Python, Java, Ruby, Node.js, or PHP for server-side logic. - Databases: SQL (MySQL, PostgreSQL) and NoSQL (MongoDB) for data management. - APIs: RESTful and GraphQL for communication between front-end and back-end. - Server Management: Understanding of server, network, and hosting environments. - Security: Knowledge of authentication, authorization, and data protection. Career Prospects: - Back-End Developer - Full-Stack Developer - Database Administrator ### Machine Learning (ML) Key Skills: - Programming Languages: Python and R are widely used in ML. - Mathematics: Statistics, linear algebra, and calculus for understanding ML algorithms. - Libraries/Frameworks: TensorFlow, PyTorch, Scikit-Learn for building ML models. - Data Handling: Pandas, NumPy for data manipulation and preprocessing. - Model Evaluation: Techniques for assessing model performance. Career Prospects: - Data Scientist - Machine Learning Engineer - AI Researcher ### Blockchain Key Skills: - Cryptography: Understanding of encryption and security principles. - Blockchain Platforms: Ethereum, Hyperledger, Binance Smart Chain for building decentralized applications. - Smart Contracts: Solidity for developing smart contracts. - Distributed Systems: Knowledge of peer-to-peer networks and consensus algorithms. - Blockchain Tools: Truffle, Ganache, Metamask for development and testing. Career Prospects: - Blockchain Developer - Smart Contract Developer - Crypto Analyst ### Decision Criteria 1. Interest: Choose an area you are genuinely interested in. 2. Market Demand: Research the current job market to see which skills are in demand. 3. Career Goals: Consider your long-term career aspirations. 4. Learning Curve: Assess how much time and effort you can dedicate to learning new skills. Each field offers unique opportunities and challenges, so weigh your options carefully based on your personal preferences and career objectives. Here are some telegram channels to help you build your career 👇 Web Development https://t.me/webdevcoursefree Jobs & Internships https://t.me/getjobss Blockchain https://t.me/Bitcoin_Crypto_Web Machine Learning https://t.me/datasciencefun Artificial Intelligence https://t.me/machinelearning_deeplearning Join @free4unow_backup for more free resources. ENJOY LEARNING 👍👍

Join @pythony Telegram channel for all your programming needs! Get access to a wealth of resources, materials, and tips to he
Join @pythony Telegram channel for all your programming needs! Get access to a wealth of resources, materials, and tips to help you become a coding expert! 😍😎💪🏻