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India banned Telegram after the NEET paper leak led to a retest for 2.28 million students. Class Central studied the scam, the money trail, and other platforms the leaks could move to.
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Master building a RAG-powered chat application using LangFlow and Streamlit, focusing on minimal code implementation and creating an AI system capable of explaining other AI models.
Discover how to build a Mario game using Cursor AI without writing code - perfect for beginners transitioning from VS Code, featuring FastAPI implementation and prompt-based development.
Explore multi-agent systems fundamentals and build hierarchical agents with LangGraph through hands-on coding, covering limitations of single agents and collaboration structures.
Dive into CrewAI's flow functionality and learn to build a meeting assistant through hands-on development, focusing on state management and seamless agent communication.
Discover how to build AI agents and develop games using Crew AI framework, from basic concepts to practical implementation with a hands-on game development demonstration.
Explore DeepSeek's Janus Pro 7b architecture, training strategies, and capabilities in unified vision-language processing for both image understanding and generation in AI systems.
Discover how to leverage tools in CrewAI framework for developing and orchestrating AI agents, building upon core concepts of Crew, Flow, and Knowledge components.
Discover the groundbreaking Singular Value Fine-tuning (SVF) approach for LLMs, offering superior performance to LoRA through self-adaptive weight modifications and dynamic model adjustments.
Dive into a comprehensive comparison of DeepSeek r1 and OpenAI o1 models, examining their capabilities in mathematical reasoning, logic, and visual problem-solving through practical demonstrations.
Explore DeepSeek R1's groundbreaking approach to training language models through reinforcement learning, eliminating the need for supervised fine-tuning while achieving superior reasoning capabilities.
Explore Gemini 2.0's multi-modal capabilities through real-world demonstrations and comparisons with leading AI models like Claude 3.5 and GPT-4, evaluating its strengths and limitations.
Dive into vector databases for RAG systems, exploring indexing methods like LSH, HNSW, and IFI, while learning how to choose and implement the right approach for efficient similarity search and retrieval.
Explore Meta's Mixture-of-Transformers (MoT) architecture, a revolutionary approach to handling multi-modal AI tasks combining text, speech, images, and videos with enhanced efficiency and performance.
Dive into Meta's MovieGen AI model's architecture, training pipeline, and innovative features for revolutionary video generation, including temporal auto-encoding and superresolution techniques.
Dive into Kolmogorov-Arnold Networks (KAN), a groundbreaking alternative to Multi-Layer Perceptrons, exploring its architecture, implementation, and potential advantages in neural network development.
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