Ch 3 explores cutting-edge technologies shaping the future — AI, ML, NLP, robotics, IoT, cloud computing, big data analytics, blockchain, and immersive technologies (AR/VR).
Artificial Intelligence: systems that simulate human intelligence — perception, reasoning, learning, problem-solving. Machine Learning: subset of AI — algorithms improve through experience (data). Types: supervised (labelled data), unsupervised (find patterns), reinforcement (reward/penalty). Natural Language Processing: AI understanding human language — chatbots, translation, voice assistants. Robotics: AI-powered machines for manufacturing, surgery, exploration. Sensors and actuators enable interaction with physical world.
Internet of Things (IoT): network of smart devices (sensors + connectivity + processing). Smart homes, wearables, smart agriculture, industrial IoT. Cloud Computing: on-demand IT resources via internet. IaaS (infrastructure: VMs, storage), PaaS (platform: development tools), SaaS (software: Gmail, Google Docs). Models: public, private, hybrid cloud. Big Data: datasets too large for traditional tools. 5 Vs: Volume, Velocity, Variety, Veracity, Value. Blockchain: distributed, immutable ledger. Each block has data, hash, previous hash. Applications: cryptocurrency, supply chain, smart contracts, digital identity.
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Each block contains: data, its own hash (unique fingerprint), and the hash of the previous block — forming a chain. If someone changes data in one block, its hash changes, which breaks the link with the next block — invalidating all subsequent blocks. Plus, blockchain is distributed across many computers (nodes). To tamper, you'd need to alter all copies simultaneously, which is computationally infeasible. Consensus mechanisms (Proof of Work, Proof of Stake) add further security by requiring network agreement before adding new blocks.
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