Artificial Intelligence - ChatGPT & AI Tech News

AI/ML roadmap Topic: Mathematics - Subtopic: Linear Algebra - Vectors, Matrices, Eigenvalues and Eigenvectors - Subtopic: Calculus - Differentiation, Integration, Partial Derivatives - Subtopic: Probability and Statistics - Probability Theory, Random Variables, Statistical Inference Topic: Programming - Subtopic: Python - Python Basics, Libraries like NumPy, Pandas, Matplotlib Topic: Machine Learning - Subtopic: Supervised Learning - Linear Regression, Logistic Regression, Decision Trees - Subtopic: Unsupervised Learning - Clustering, Dimensionality Reduction[1](https://i.am.ai/roadmap) - Subtopic: Neural Networks and Deep Learning - Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks Topic: Specializations - Subtopic: Natural Language Processing - Text Preprocessing, Topic Modeling, Word Embeddings - Subtopic: Computer Vision - Image Processing, Object Detection, Image Segmentation - Subtopic: Reinforcement Learning - Markov Decision Processes, Q-Learning, Policy Gradients Join for more: https://t.me/machinelearning_deeplearning

🧠 How to Build an AI Agent

🚨 Google dropped a 68-page whitepaper on Prompt Engineering — perfect for API users! It’s packed with advanced tips, techniques, and real examples. Super useful if you're working with LLM APIs or building AI apps! PDF below 👇

7 out of 10 businesses are missing the AI automation opportunity. (𝗜 𝘀𝗲𝗲 𝘁𝗵𝗶𝘀 𝗮𝗹𝗹 𝘁𝗵𝗲 𝘁𝗶𝗺𝗲 𝗶𝗻 𝗺𝘆 𝘀𝗮𝗹𝗲𝘀 𝗰𝗮𝗹𝗹𝘀.) So many are stuck in manual processes. Wondering why competitors are suddenly 10x faster. But this 5-step AI automation process will help you out. Here’s what business leaders should be implementing: STEP 1: IDENTIFY AI USE CASES ↳ Content Creation with Jasper, Copy(.)ai ↳ Data Analysis with Julius AI, Code Interpreter ↳ Customer Support with Retell AI, Vectorshift AI STEP 2: SELECT AI MODEL/TOOL ↳ ChatGPT for conversations & images ↳ Claude for analysis & coding ↳ n8n for workflow automation STEP 3: DESIGN AGENT WORKFLOW ↳ Map the process with clear inputs/outputs ↳ Define decision logic ↳ Set up error handling STEP 4: CONNECT APIs & DATA ↳ Zapier for app connections ↳ Make for workflow automation ↳ Langchain for AI frameworks STEP 5: DEPLOY & MONITOR ↳ Track performance metrics ↳ Optimize based on results ↳ Scale what works KEY TECH SKILLS YOU NEED: - API Integration & Webhooks - Prompt Engineering (ChatGPT, Claude) - No-Code Platforms (Lovable, n8n) - Vector Databases - AI Agent Architecture

🤖 9 Free Al Testing Platforms

Two powerful open-source tools to master Local AI efficiently 1️⃣ LEANN: Extreme Compression for RAG

This open-source repo compresses 60 million text chunks from approximately 201 GB to about 6 GB 🤯 That's about 97% less, while the quality of the retrieval remains very close to standard setups. • No cloud • No GPU • Runs locally on a regular laptop • Full privacy • 100% open source LEANN achieves this by not storing embeddings permanently. Instead, it uses a compact graph and recalculates embeddings only when they are actually needed.

GitHub 2️⃣ Transformer Lab: All-in-One set of tools for working with LLMs.

☞ Allows you to train, fine-tune, and communicate with any LLM locally. ☞ One-click model loading, Simple drag-and-drop interface for RAG. ☞ Completely open sourced.

GitHub ••••••••••••••••••••••••••••••••• 🤖 Data Science, ML & Big Data with @DataXplore

🌐 AI Frameworks & Their Use Cases 🤖🔬 🔹 TensorFlow ➜ Scalable deep learning for production ML models and distributed training 🔹 PyTorch ➜ Dynamic neural networks for research, prototyping, and flexible AI experiments 🔹 Keras ➜ High-level API for quick neural network building on TensorFlow backend 🔹 Scikit-learn ➜ Classical ML algorithms like classification, regression, and clustering 🔹 Hugging Face Transformers ➜ Pre-trained models for NLP tasks like translation and generation 🔹 XGBoost ➜ Gradient boosting for structured data with high accuracy and speed 🔹 LangChain ➜ Building LLM-powered apps with chaining, memory, and tool integration 🔹 JAX ➜ High-performance numerical computing with auto-differentiation for research 🔹 AutoGen ➜ Multi-agent systems for collaborative AI workflows and automation 🔹 LlamaIndex ➜ RAG pipelines and knowledge bases for context-aware AI apps 🔹 CrewAI ➜ Orchestrating multi-agent teams for complex task decomposition 🔹 Semantic Kernel ➜.NET-based AI orchestration for enterprise plugins and planning 🔹 MLflow ➜ ML lifecycle management with tracking, deployment, and reproducibility 🔹 FastAPI ➜ Building efficient APIs for serving AI models in production 🔹 Apache MXNet ➜ Lightweight deep learning with multi-GPU support for scalability 💬 Tap ❤️ if this helped!

Google and OpenAI employees revolt: "We will not be divided" The Pentagon's war with Silicon Valley is escalating fast. Over 500 verified employees from Google and OpenAI just dropped a massive open letter titled "We Will Not Be Divided," urging their CEOs to stand with Anthropic and refuse to build AI for mass domestic surveillance or fully autonomous weapons. The letter accuses the Department of War of trying to play the top AI labs against each other threatening Anthropic with the Defense Production Act while negotiating with Google and OpenAI behind closed doors. Source. @aipost 🏴

⚠️ AI Mistakes Developers Make ❌ Trusting output blindly ❌ Skipping code review ❌ Using AI instead of thinking ❌ Shipping untested AI code ❌ Ignoring edge cases React ❤️ for more like this #techinfo

🤖 DeepSeek Al Prompt Hacks

Copy & paste these 7 ChatGPT prompts to create an irresistible Resume/CV 👇 Showcase your strengths. Turn applications into interview invites! Use these 10 proven ChatGPT prompts: 📈 Prompt 1: ATS Keyword Optimizer Analyze the job description for [Position] and my resume. Identify 10 crucial keywords. Suggest natural placements in my resume, ensuring ATS compatibility. Present results as a table with Keyword, Relevance Score (1-10), and Suggested Placement. My resume: [Paste Resume]. Job description: [Paste Description]. 📈 Prompt 2: Experience Section Enhancer Optimize the bullet points for my most recent role as [Job Title]. Focus on achievements, skills utilized, and quantifiable results. Use strong action verbs. Present a before/after comparison with explanations for changes. Current job description: [Paste Current Bullets].  📈 Prompt 3: Skills Hierarchy Creator Evaluate my skills for [Job Description]. Create a skills hierarchy with 3 tiers: core, advanced, and distinguishing skills. Suggest how to demonstrate each skill briefly. Present a visual skills pyramid with examples. My resume: [Paste Resume]. Job requirements: [Paste Requirements]. 📈 Prompt 4: Professional Summary Crafter Write a compelling professional summary for my resume for [Job Title]. Incorporate my unique value proposition, key skills, and career experience. Limit to 3-4 sentences. Provide 3 versions: conservative, balanced, and bold. My resume: [Paste Resume]. Job description: [Paste Description]. 📈 Prompt 5:  Education Optimizer Refine my education section for [Job Title]. Highlight relevant coursework, projects, or academic achievements. Suggest how to present ongoing education/certifications effectively. Provide a before/after version with explanations. My resume: [Paste Resume]. Job description: [Paste Description]. 📈 Prompt 6: Technical Skills Showcase List my technical skills for [Industry/Role]. Create a visual representation (Described in Text) that organizes these skills by proficiency level and relevance to [Target Role]. Suggestion skills to acquire/improve. My resume: [Paste Resume]. Job description: [Paste Description]. 📈 Prompt 7:  Positive Career Gap Framing Write an explanation for my [X months/years] career gap between [Start Date] and [End Date]. Focus on growth, skills gained, and valuable experiences. Show how these enhance my fit for [Target Job Title]. Create 3 versions for resume, cover letter, and interview response. My resume: [Paste Resume]. Job description: [Paste Job Description]. Join for more: https://t.me/aiindi #aiprompt

Kandinsky 5.0 Video Lite and Kandinsky 5.0 Video Pro generative models on the global text-to-video landscape 🔘Pro is currently the #1 open-source model worldwide 🔘Lite (2B parameters) outperforms Sora v1. 🔘Only Google (Veo 3.1, Veo 3), OpenAI (Sora 2), Alibaba (Wan 2.5), and KlingAI (Kling 2.5, 2.6) outperform Pro — these are objectively the strongest video generation models in production today. We are on par with Luma AI (Ray 3) and MiniMax (Hailuo 2.3): the maximum ELO gap is 3 points, with a 95% CI of ±21. Useful links 🔘Full leaderboard: LM Arena 🔘Kandinsky 5.0 details: technical report 🔘Open-source Kandinsky 5.0: GitHub and Hugging Face

🔸 Claude Code is coming to Slack and it could quietly reshape developer workflows Anthropic is bringing its coding assistant Claude Code directly into Slack, letting teams trigger code generation, bug fixes, or feature implementations straight from chat threads. 🔸 Once enabled, developers can tag @Claude in a conversation and the assistant will analyze the thread, pull context, choose the right repo, and start working including creating branches, writing code, and posting updates as it progresses. 🔸 Unlike traditional coding assistants that sit inside an editor, Claude Code in Slack moves the entire workflow to where teams already discuss bugs and features, reducing context switching and speeding up decision-to-implementation cycles. 🔸 The integration arrives as a beta, but Anthropic says it aims to turn Slack into a central automation hub where code reviews, pull requests, and task execution originate directly from team chat.

If this model sticks, Slack could become the place where software planning, discussion, and actual code execution merge into one continuous loop.

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OnSpace Mobile App builder: Build AI Apps in minutes 👉https://www.onspace.ai/agentic-app-builder?via=tg_aisigma With OnSpace, you can build AI Mobile Apps by chatting with AI, and publish to PlayStore or AppStore. What will you get: - Create app by chatting with AI; - Integrate with Any top AI power just by giving order (like Sora2, Nanobanan Pro & Gemini 3 Pro); - Download APK,AAB file, publish to AppStore. - Add payments and monetize like in-app-purchase and Stripe. - Functional login & signup. - Database + dashboard in minutes. - Full tutorial on YouTube and within 1 day customer service