What is Generative AI ? Video

Generative Artificial Intelligence, or generative AI, refers to a set of systems that use machine learning to produce results that are not merely predictions or decisions based on incoming data, but rather new data or information that was not explicitly present in the input data.

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Generative artificial intelligence refers to

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a set of systems that use machine learning.

00:00:09

Generative AI systems go

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beyond making predictions or

00:00:13

decisions based on received data.

00:00:15

Instead, they analyze patterns

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in the data and use them to

00:00:19

generate new original information,

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surpassing mere data-driven

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responses or predictions.

00:00:24

Rather than merely processing

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and reacting to input data,

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generative AI systems create new

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information that was not explicitly

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contained in the original data.

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Identifying patterns in incoming data.

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They produce original outputs,

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such as a new musical composition

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from a collection of existing

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pieces showcasing their creativity.

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Generative AI finds applications

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in numerous fields,

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yielding impressive and

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sometimes unexpected results.

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Here are some examples.

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Text synthesis.

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It generates new and original text,

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ranging from simple sentences to poems,

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stories, or even entire novels.

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Image creation.

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It produces new images or artworks.

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Often by imitating the styles

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of famous artists or generating

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images based on specific styles.

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Music composition.

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It composes new musical pieces

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by analyzing and learning from

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various existing compositions.

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These examples illustrate the

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versatility and power of generative AI.

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By understanding and manipulating

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patterns in data,

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it can create new information in

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various formats and contexts,

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even generating things we

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hadn't previously imagined.

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Generative AI expands the traditional

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capabilities of AI by creating new data

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going beyond simple analysis and prediction.

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It allows AI to enter realms

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associated with human creativity,

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such as art and music.

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When we say that generative AI promises

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a future filled with creativity,

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we refer to its innovation potential.

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For instance, it could compose unique music,

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create original artworks,

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or propose novel solutions to

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complex problems by generating new

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ideas or solutions that wouldn't

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have been conceived otherwise.

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In the field of medical research,

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for example,

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generative AI could be used to generate

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new molecular structures for drugs.

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Helping accelerate the discovery

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of new treatments.

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As a result,

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generative AI has the potential

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to transform various domains

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and industries by fostering

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innovation and creativity.

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Prepare for the future of AI.

00:02:27

Continue our training to understand,

00:02:29

master and apply generative AI

00:02:31

in your professional domain.

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Don't miss this opportunity

00:02:34

to stay at the forefront of

00:02:36

technological innovation.

00:00:04

A inteligência artificial generativa refere-se a:

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um conjunto de sistemas que utilizam aprendizagem automática.

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Sistemas de IA generativa vão

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além de fazer previsões ou

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decisões baseadas nos dados recebidos.

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Em vez disso, eles analisam padrões

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nos dados e utilizá-los para

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gerar novas informações originais,

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superando o mero orientado por dados

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respostas ou previsões.

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Em vez de apenas processar

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e reagindo aos dados de cálculo,

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sistemas generativos de IA criam novos

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informações que não foram explicitamente

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contidos nos dados originais.

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Identificação de padrões nos dados recebidos.

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Produzem resultados originais,

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como uma nova composição musical

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de uma coleção de

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peças que mostram a sua criatividade.

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IA generativa encontra aplicações

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em numerosos domínios,

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rendendo impressionante e

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por vezes, resultados inesperados.

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Eis alguns exemplos.

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Síntese de texto.

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Gera texto novo e original,

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variando de frases simples a poemas,

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histórias, ou mesmo romances inteiros.

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Criação de imagem.

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Produz novas imagens ou obras de arte.

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Muitas vezes imitando os estilos

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de artistas famosos ou geradores

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imagens baseadas em estilos específicos.

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Composição musical.

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Compõe novas peças musicais

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analisando e aprendendo com

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várias composições existentes.

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Estes exemplos ilustram a

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versatilidade e poder da IA generativa.

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Compreendendo e manipulando

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padrões nos dados,

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pode criar novas informações em

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vários formatos e contextos,

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mesmo gerando coisas que nós

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não tinha imaginado anteriormente.

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A IA generativa expande o tradicional

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capacidades da IA através da criação de novos dados

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indo além da simples análise e previsão.

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Permite que a IA entre em reinos

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associada à criatividade humana,

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como a arte e a música.

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Quando dizemos que a IA generativa promete

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um futuro cheio de criatividade,

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referimo-nos ao seu potencial de inovação.

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Por exemplo, poderia compor música única,

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criar obras de arte originais,

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ou propor soluções inovadoras para

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problemas complexos, gerando novos

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ideias ou soluções que não o fariam

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foram concebidos de outra forma.

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No domínio da investigação médica,

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Por exemplo

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IA generativa pode ser usada para gerar

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novas estruturas moleculares para fármacos.

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Ajudando a acelerar a descoberta

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de novos tratamentos.

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Como resultado,

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a IA generativa tem o potencial

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para transformar vários domínios

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e indústrias, fomentando

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inovação e criatividade.

00:02:25

Prepare-se para o futuro da IA.

00:02:27

Continue a nossa formação para compreender,

00:02:29

dominar e aplicar IA generativa

00:02:31

no seu domínio profissional.

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Não perca esta oportunidade

00:02:34

para se manter na vanguarda da

00:02:36

inovação tecnológica.

DiLeaP AI: THIS MIGHT BE HELPFUL

Keys to Success, Pitfalls to Avoid, and Best Practices

We dive here into the heart of Generative Artificial Intelligence, this revolutionary technology that shapes the digital landscape. We start by exploring the essential foundations of its success, highlighting the importance of data quality, model choice, and required resources. Then, we address the challenges faced illustrated by poignant examples of errors and limitations highlighting potential biases and ethical dilemmas. Finally, the video concludes with a series of practical recommendations, offering valuable advice for successfully integrating generative AI into various projects. This immersion offers a balanced perspective on the immense potential and inherent challenges of generative AI.

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Generative AI Prompts : Harnessing the Power of Models

In this video titled "Prompts in Generative AI: Harnessing the Power of Models," we delve into the mechanisms guiding the powerful algorithms of generative artificial intelligence. We begin by explaining the crucial role of prompts, those compasses that direct computational capacity towards specific areas of interest. Then, the complex nature of prompts is described, highlighting their essential characteristics: Contextualization, which anchors AI in a specific framework; Specificity, which sharpens the accuracy of results; and Stimulation, awakening the model's creativity. We conclude by illustrating the dynamic evolution of prompts in interactions, where a prompt shapes and is influenced by the previous output, evoking an interaction between the user and the model. Here is an in-depth overview of the art and science of prompts, revealing their invaluable importance in the rapidly expanding field of generative AI.

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Writing with Intelligence : Exploring GPT-4's Capabilities in Generative Writing

Discover the revolutionary potential of generative AI in the world of writing with our course titled "Writing with Intelligence: Exploring the Capabilities of GPT-4 in Generative Writing". In this video, we begin by introducing the fascinating world of AI-generated texts, from movie scripts to poems. Highlighting GPT-4's ability to produce compelling writings. We then delve into the inner workings of these technologies. Showing how they learn from vast datasets to mimic human style. While acknowledging the undeniable benefits of AI, we also discuss its limitations. Particularly the lack of authentic emotion and human context. The most captivating part is undoubtedly when we unveil GPT-4's ability to engage in conversations. Instead of a simple response, we show how this AI can engage in continuous dialogue. Allowing for in-depth exchanges. In conclusion, we discuss the promising collaboration between AI and humanity in the creative field of writing. Join us for this enriching exploration and discover how the future of writing is being shaped by technological advancements.

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History of Generative AI

Let's explore together the captivating evolution of generative AI. From its humble beginnings in the 1950s, through the era of neural networks in the 1980s, the explosion of Big Data at the turn of the millennium, to the rise of GANs and major advancements in the 2020s.

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From Data to Discoveries : The Art of Innovation with Generative AI

This video provides a methodological roadmap for brainstorming future applications of generative AI. It begins with an introduction to the basics of generative AI and its relevance in the current technological ecosystem. The method uses proven techniques such as Mind Mapping to map out ideas, the Six Thinking Hats method to consider various perspectives and the Future Scenario Technique to project visions of AI's future. These methods will help participants navigate, collaborate, and envision innovative applications of generative AI across various sectors, while considering the ethical and societal implications.

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