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AI in Healthcare: Beyond the Buzzword AI in healthcare is more than just hype. Peel back the layers, and you'll find biostatistics at its core. ⚠️How valid is this point? 🟥 AI in healthcare often gets attention for its transformative potential, b

Many argue that Data Engineering is a part of data science and analytics. It's different from data science, but they work together closely. Data Engineers come first in the process. They gather and organize data. This data is then used by Data Scien

Google DeepMind’s CaMeL: A Breakthrough in Stopping AI’s "Prompt Injection" Problem? For years, prompt injection attacks (where hidden instructions trick AI models into bypassing safeguards) have haunted developers. Despite countless fixes, no solut

Retrieval-Augmented Generation (RAG) is a GenAI framework that enhances large language models (LLMs) by incorporating information from external knowledge bases, improving accuracy, relevance, and reliability of generated responses. Here's a more det

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How AI Works 1. Neural Networks – AI’s Brain AI’s neural networks consist of three layers: Input Layer: Takes in raw data (e.g., an image). Hidden Layers: Process data to find patterns (e.g., detecting edges, shapes). Output Layer: Produces the fi

Startup Idea: PureAir Grid – AI-Powered Outdoor Air Filtration 🔴 Problem: Rising air pollution in cities causes severe health issues. 🟢 Solution: Smart AI-driven filtration towers that: ✅ Detect & clean air using real-time sensors. ✅ Run on solar

🚀 For the first time in LLM History! Introducing Agentic Compound LLMs in AnyLLM. What are agentic LLM's ? Agentic LLMs have access to all the 10+ llms in anyllm and know when you use any one of them to perform a specific task. They also have acces

Many people are not clear or don't know the difference between business analyst and data analyst... Ofc they sound the same, they analyse the data, duh...🤷🏻‍♂️ But there is a major difference in both of them, if you want to become any one of the

how to prompt like a pro 1. first: share your raw idea 2. ask: “what’s unclear, risky, or missing?” 3. then: “make this resonate with [my audience/customer/community]” insert data about them 4. finally: “what would [0.01% top expert in my field] do