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    04 - Literacia em IA

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    Ramon Barbosa
    The document discusses various perspectives on artificial intelligence including technological, economic, and philosophical views. It outlines different areas of AI such as machine learning, deep learning, neural networks, computer vision, natural language processing, and generative AI. It also references specific AI models like GPT-3, DALL-E, BERT, and Transformer models. The focus is on literacy around AI and how machines can learn in similar ways as humans through techniques like supervised and unsupervised learning.

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    04 - Literacia em IA

    Uploaded by

    Ramon Barbosa
    27 views9 pages
    The document discusses various perspectives on artificial intelligence including technological, economic, and philosophical views. It outlines different areas of AI such as machine learning, deep learning, neural networks, computer vision, natural language processing, and generative AI. It also references specific AI models like GPT-3, DALL-E, BERT, and Transformer models. The focus is on literacy around AI and how machines can learn in similar ways as humans through techniques like supervised and unsupervised learning.

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    The document discusses various perspectives on artificial intelligence including technological, economic, and philosophical views. It outlines different areas of AI such as machine learning, deep learning, neural networks, computer vision, natural language processing, and generative AI. It also references specific AI models like GPT-3, DALL-E, BERT, and Transformer models. The focus is on literacy around AI and how machines can learn in similar ways as humans through techniques like supervised and unsupervised learning.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    27 views9 pages

    04 - Literacia em IA

    Uploaded by

    Ramon Barbosa
    The document discusses various perspectives on artificial intelligence including technological, economic, and philosophical views. It outlines different areas of AI such as machine learning, deep learning, neural networks, computer vision, natural language processing, and generative AI. It also references specific AI models like GPT-3, DALL-E, BERT, and Transformer models. The focus is on literacy around AI and how machines can learn in similar ways as humans through techniques like supervised and unsupervised learning.

    Copyright:

    © All Rights Reserved
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    Download as pdf or txt
    of 9

    LITERACIA EM IA

    INTELIGÊNCIA ARTIFICIAL É A NOVA ELETRICIDADE


    LITERACIA EM INTELIGÊNCIA ARTIFICIAL
    DIVERSAS PERSPECTIVAS
    Artificial Intelligence
    Artificial Narrow Intelligence
    Machine Learning
    Artificial General Intelligence
    Deep Learning
    Artificial Super Intelligence
    Supervised Artificial Neural Nets
    Technological Singularity
    Unsupervised Transformers
    ...
    Reinforcement Foundation Models (LLMs)
    Semi-supervised Quantum AI
    Self-supervised ...
    Multi-Instance Learning
    One shot Learning PERSPECTIVAS
    Few shots Learning
    TECNOLÓGICA
    AI
    ...
    ECONÔMICA
    FILOSÓFICA
    Inductive Learning
    Deductive Inference
    Computer Vision
    Transductive Learning
    Natural Language Processing
    Multi-Task Learning
    Conversational (Text, Voice, Speech)
    Active Learning
    AI Math Cognitive Robotics
    Online Learning
    AI Computation Experts Systems
    Transfer Learning
    AI Processors Conversational AI
    Ensemble Learning
    AI Platforms Generative AI
    ...
    AI Frameworks ...
    ...
    LITRACIA
    EM IA AGI ASI

    GENERAL SUPER
    GENERATIVE AI INTELLIGENCE INTELLIGENCE
    A democratização do “impossível”?
    OpenAI: chatGPT, Whisper, Dalle-2, Jukebox GitHub
    Autopilot, Midjoousrney, Stable Diffusion
    WOW! Um tsunami de novas Apps & Tools

    AI FOUNDATION MODELS
    As novas plataformas de serviços digitais?
    Huge Models to reinvent Cloud Computing?
    GPT-X (OpenAI), LaMDA (Google), BERTLarge, DALLE-E
    Bloom (HuggingFace), ESMFold (Meta), Gato (Deepmind)

    NEURAL NETWORKS
    AS máquinas podem aprender como o cérebro?
    Deep Learning, ANN, RNN, CNN
    Backprop, Fwd-Fwd, Transformers, Diffusion

    MACHINE LEARNING
    As máquinas podem aprender?
    Un / Semi / Supervised Learning
    Reinforcement, Transferable Learning

    ...
    LITRACIA
    EM IA
    GENERATIVE AI

    ELI5
    A democratização do “impossível”?
    OpenAI: chatGPT, Whisper, Dalle-2, Jukebox GitHub
    Autopilot, Midjoousrney, Stable Diffusion
    WOW! Um tsunami de novas Apps & Tools

    AI FOUNDATION MODELS
    As novas plataformas de serviços digitais?
    Huge Models to reinvent Cloud Computing?
    GPT-X (OpenAI), LaMDA (Google), BERTLarge, DALLE-E
    Bloom (HuggingFace), ESMFold (Meta), Gato (Deepmind)

    NEURAL NETWORKS
    AS máquinas podem aprender como o cérebro?
    Deep Learning, ANN, RNN, CNN
    Backprop, Fwd-Fwd, Transformers, Diffusion

    MACHINE LEARNING
    As máquinas podem aprender?
    Un / Semi / Supervised Learning
    Reinforcement, Transferable Learning

    ...
    ELI5
    EXPLAIN LIKE
    I’M 5 YEARS OLD

    Richard Feynman
    Feynman

    Feynman

    Feynman

    Feynman

    Source: Calltech; Unicamp Nightfall (>)


    ELI5 : EXPLAIN LIKE I’M 5 YEARS OLD
    COMO AS MÁQUINAS APRENDEM?

    COMO AS CRIANÇAS APRENDEM?


    COMO NASCEM AS CRIANÇAS?

    BERT DALL-E
    LaMDA chatGPT MidJourney
    Foundation Models
    ELI5 Generative AI
    Transformers Models
    Artificial Neural Networks Diffusion Models

    Machine Learning Generative Adversarial Networks

    INTELIGÊNCIA ARTIFICIAL
    CRISTIANO KRUEL

    KRUEL @ STARTSE.COM
    IN / CRISTIANOKRUEL
    @ CRISKRUEL

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