Generative AI and how it adapts to the Individual

AI is constantly creating new content by training data from existing content, yes on the content we are providing it. This excites many businesses and individuals due to its exceptional possibilities. AI today can help build services, solve problems, and predict crises. An estimated $8 trillion per year is the projected boost AI could provide to the global economy. It's revolutionizing how we live and work.

AI is learning to think, see, listen, and speak like a human

Understanding Gen AI

Below is the model equation

y = f(x), {x is input, f is function, y is output}

y is considered Generative AI when y is any of the following types — Natural Language, Image, and Audio resulting in text-to-text, text-to-image/video, or text-to-task model types.

Test-to-text models: These models take text as input and produce text as output. A common example is a translation model, which takes text in one language and outputs the same in another.

Text-to-Image/video model: These models input text and generate videos/images as output.

Text-to-Task: Here the input is text, and the output is generated by specifying tasks. For example, performing a search, asking a question, or even sentiment analysis.

How personalization is achieved?

According to a study, 1788 participants showed that generative AI could automate and scale personalized influence, making it more effective.

Unlike traditional machine learning that processes training and labeled data — to build a model, Gen AI uses Training code, labeled and unlabeled data as input — to build a model — and generate new content.

Gen AI uses a Pattern-matching system to generate new data that resembles the training data it was provided.

For example, when giving a prompt to replicate a specific style that’s unique to an artist, AI can use it to generate a new image without the original artist knowing or approving.

Remember a prompt is a small description(input) that helps improve the output quality.

Example: AI trying to classify the image of an animal as a dog

In traditional programming, we would build a set of rules for distinguishing a dog — type: animal, legs: 4, ears: 2, fur: yes, likes: bones, Sound: Bhow!!.

Using the descriptive model on unstructured data , AI will classify the image as

• Dog or
• Not Dog

Output will be Yes or No.

Example: AI trying to generate the image of an animal called "dog"

In Gen AI programming, this is how the learning model works

• Data Collection and Processing — AI learns from large datasets.
• Training ANN — To generate a dog image based on the given features using AI, we can utilize a Generative Adversarial Network (GAN) trained on dog images GANs are a type of neural network architecture; fed on interconnected patterns to generate new data instances.
• Output generation — The output is generated and depends on the network architecture.

Now when we type the prompt “Tell me what’s a dog” —the model will generate everything it has learned about dogs.

Benefits across industries

1. Everyday tool: As AI algorithms are integrated with everyday software, gen AI has the power to become an everyday tool for all.
2. For everyone: Providing a platform to explore creativity, Gen AI is for all and is being used in every aspect of life.
3. Health: Gen AI can analyze vast amounts of medical data and use them in drug discovery and creating treatment plans.
4. Transportation: Automated vehicles can rely on AI algorithms for navigation and decision-making.

Likewise, the future of Gen AI holds immense promise across various fields. Its ability to generate novel content opens up possibilities for problem-solving, creativity, and decision-making processes, leading to innovation and advancements in society.

Can AI take over everything??????

We will discuss in the next article.

Sources :

The potential of generative AI for personalized persuasion at scale (nature.com)

Personalization and Customization of AI-generated Content: Exploring the Role of Consumer Devices, Edge Devices, and Data Centers | Frontiers Research Topic (frontiersin.org)

https://www.cloudskillsboost.google/

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