What Is Generative AI and How Can You Use It in 2023

Last Updated on August 9, 2023 by Leave a Comment

What Is Generative AI and How Can You Use It in 2023
Blog / Business / What Is Generative AI and How Can You Use It in 2023
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The realm of artificial intelligence (AI) technology is expanding at an unprecedented rate. What was once considered the stuff of science fiction is now becoming an integral part of our everyday lives. From voice assistants and recommendation algorithms to cyber-security and advanced healthcare diagnostics, generative AI is reshaping the world as we know it.

One way to grasp this rapid progression is by the sheer volume of research being produced in the field.

“We are seeing 500,000 new AI research papers per year.”
Joelle Pineau, VP of AI Research at Meta

This all-in mindset for the technology shows the intense interest and investment in AI across academia, private industry, and government. But what about you? How can you use Gen AI for your business, hobbies, and personal life? We’ve collected all our best articles on different categories of generative AI products that will make it easy for you to see how AI can directly impact your day-to-day.

But first, what is Generative AI?

What is Generative AI?

Generative AI is a branch of artificial intelligence that focuses on creating unique content based on training data and neural networks. This can range from creating text content to images, music, and even video.

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To understand generative AI, it’s helpful first to understand what AI is. Artificial Intelligence, or AI, is a broad term that refers to machines or software mimicking human intelligence. It’s about creating systems that can understand, learn, and apply knowledge, handle new situations, and carry out tasks that would typically require human intelligence. AI isn’t on par with human intelligence, but it is phenomenal at what it can do.

Generative AI takes AI a step further. It doesn’t just mimic human intelligence; it creates like a human might. This happens using machine learning models. These are like rules that get better over time through practice and training. The more data and training these models see the better they get at making high-quality, relevant content.

Development of Generative AI

Generative AI developed slowly, building on previous AI advancements. It began with machine learning. This kind of AI lets systems learn and improve from experience without specific programming.

As machine learning techniques evolved, we saw the development of neural networks, which are computing systems loosely inspired by the human brain. These networks can learn from vast amounts of data, making them incredibly powerful tools for tasks like image recognition, natural language processing, and content generation.

AI Generative Models Image by Pro_Vector

Image by Pro_Vector / shutterstock.com

Generative AI made significant strides with the advent of Generative Adversarial Networks, or GANs. A GAN is made up of two competing parts: a generator and a discriminator. These two parts work together to create very realistic “synthetic data.”

The generator’s job is to create new outputs. The discriminator’s job is to compare the output to trained data and attempt to fail it. When the discriminator doesn’t approve, the generator is tasked with trying again. Both parts keep this up until there is an approved output. This process helps the generator learn and refine itself. Over time, it improves at making data that looks much like the training data.

With all of this working under the hood, AI has been able to creep into several types of use cases for the average person. You don’t need to be an expert in programming GANs to leverage the technology fully.

 

Applications of Generative AI

Generative AI has flooded many digital tools, providing practical solutions for everyday tasks.

“In 12 months, call it next year this time (Mid-2024), I really think every company, every marketing team, every sales team, this generative and predictive AI is going to be a core part of every tool that they use. I just cannot see technology in the next year not incorporating this capability.”
Joyce Kim Chief Marketing Officer, Board Member at Twilio

If Joyce is correct, you’ll be using these tools in your professional life before you know it (if you haven’t already).

Let’s explore some of the key domains where generative AI is making a significant impact.

Language Processing and Writing

Generative AI is revolutionizing the field of language processing and writing. AI tools like ChatGPT (based on the GPT-3 model) and Copy.ai are becoming indispensable for creating content, streamlining tasks, drafting emails, writing articles, and answering questions. These tools dramatically enhance productivity and boost creativity.

Throughout our research on the state of AI writing and natural language processing (NLP), we’ve found some of the best tools that leverage these text-based AI models. These include:

As you can clearly see, Natural Language Processing (NPL) and language-based AI models are seeing some of the swiftest adoptions by businesses. Their use cases span many different types of tasks and tools. But language is far from the only thing that generative AI is capable of.

Visual Art and Enhancement

Generative AI is reshaping the landscape of visual creativity and enhancement. With foundation models like Stable Diffusion, products can generate unique images and art using text prompts. AI is now creating stunning artwork, creating realistic videos, and helping with photo editing. Tools like Midjourney and Photoshop are paving the way with this type of AI. We’ve written extensively about the best AI tools for creating visuals. These include:

Audio Generation and Speech Processing

Generative AI is transforming the auditory landscape as well. It can generate music in a specific style. Or you can use it as a text-to-speech tool to convert written text into spoken words. That opens up content to be more accessible for visually impaired users. On the other hand, speech-to-text tools can transcribe audio files, making them searchable and easier to analyze. Some of the best audio-centric AI tools include:

How to Use Generative AI Responsibly

Generative AI, with its ability to produce human-like content, offers a multitude of opportunities. However, the power of this technology also introduces a range of ethical considerations and potential for misuse. It’s crucial to navigate these challenges responsibly to harness the full potential of generative AI while minimizing harm. Whether you are using consumer-level AI tools, developing off the back of a broader AI model, or creating your own, we each have our roles in responsibly using AI.

Aside from the sky-is-falling forecasts about what AI could cause, tangible yet elusive risks are involved in using it.

Inherent Risks and Criticisms of Using Generative AI

As with any powerful technology, generative AI comes with its own set of challenges and potential pitfalls. One of the primary concerns is that generative AI models do not inherently fact-check the information they generate. They may produce content based on inaccurate or misleading data, leading to the propagation of false information. Worse still is that when they make an error, it isn’t obvious or always easy to figure out that they did.

This is particularly concerning in areas like journalism or academia, where the accuracy of information is paramount. Even in casual writing, AI “hallucinates” or invents facts (especially when it has a hard time finishing its output).

Another potential risk lies in the realm of content authenticity. As AI-generated content becomes more prevalent, AI detection tools are being developed to detect and flag such content. Publishers or individuals using AI-wholesale may experience great reputational damage, especially if the AI-generated content is not clearly labeled as such.

What Experts Are Saying About Gen AI Risks

There is no doubt that LLM training data includes copyrighted material, content that was added against website TOSs, and harmful and potentially defamatory information.

Use of AI Rules of Conductx1800

Image by designium / shutterstock.com

It’s still to be seen what legal ramifications exist for using AI. Whether you are developing a model or using one as a service in your own business.

“Serious legal issues exist around of using training data involving materials with copyright, TOS violation, reputational harm issues.”
Regina Sam Penti, Partner at Ropes and Gray

Bias (of each and every kind) is a part of generative AI training data. Collecting, cleaning, and keeping up with data are the biggest jobs for generative AI systems in the future.

“Bias will continuous problem because the data it was trained on human generated data…guardrails will need to be continue to be refined”
Eric Boyd, CVP of AI Platform at Microsoft

Even as a consumer, it’s important to know the risks that exist, even in the products we use. That doesn’t mean that you shouldn’t use these tools—it just means you should be careful about the information you feed these tools and what you ultimately expect from them.

Where Do We Go From Here?

As we stand on the brink of a new era in digital innovation, generative AI’s potential is only beginning to be realized. It’s not just about the technology itself. It’s also about how people and businesses can use it to change their everyday jobs and creative work.

Imagine using AI chatbots to handle customer service inquiries, providing immediate responses and support. Or using AI to transcribe audio, making content more accessible to a wider audience. Generative AI can even assist in writing, from drafting email responses and resumes to creating compelling marketing copy. And on and on.

For a deeper dive into the topic, check out our comprehensive post on the best available AI tools today. It provides a detailed overview of the top AI tools across various categories, helping you choose the right tool for your needs.

Generative AI is not just a technological advancement; it’s a tool for creativity, efficiency, and innovation. As we explore its potential, one thing is clear: generative AI is not just shaping our future; it’s here and now.

Frequently Asked Questions (FAQs)

Before we wrap up, let’s answer some of your most common questions about generative AI. Did we miss one? Leave a question below and we will respond!

What is generative AI?
Generative AI is a subset of artificial intelligence that crafts unique content by harnessing neural networks and training data. It encompasses text, images, music, and videos. Unlike traditional AI, which mimics human intelligence, generative AI goes beyond creating content akin to human creativity. It employs machine learning models that improve through practice and training, producing increasingly high-quality and relevant outputs as they encounter more data.
How can I use generative AI?
Generative AI holds vast potential across various fields, from creative content and content enhancement to engineering and design. It aids in generating written content, answering questions, manipulating text tone, summarizing and simplifying content, classifying data, and improving chatbot performance. Long-term applications include medical image prediction, synthetic data augmentation, proactive suggestions, and legacy code modernization. As generative AI advances, its impact on scientific discovery, technology, and numerous sectors will continue to evolve rapidly, shaping the future of innovation.
What kinds of output can a generative AI model produce?
Generative AI models can produce various outputs based on their training data. These include:
  • Text such as news articles, product descriptions, or creative writing
  • Images from realistic portraits and landscapes to abstract art
  • Audio outputs like music, speech, or sound effects
  • Video including product videos, 3D animation, and realistic human avatars
  • Code outputs for software applications, websites, or custom apps
What are the limitations of AI models?
AI models, while powerful, have certain limitations:
  • Bias: AI models can reflect biases in training data, leading to potentially unfair or inaccurate predictions.
  • Complexity: The intricate nature of AI models can make them hard to understand, debug, or improve.
  • Data requirements: AI models need large amounts of data for training, which can be costly to collect and prepare.
  • Creativity: AI models lack human-like creativity and can only generate content based on their training data.
  • Emotion: AI models don't possess or comprehend emotions.
Despite these limitations, AI models are instrumental in solving many problems, and ongoing advancements may help overcome these challenges.
What is ChatGPT?
ChatGPT is an AI chat experience developed by OpenAI, leveraging the company's Generative Pre-trained Transformer (GPT) series of large language models (LLMs). It's built on OpenAI's GPT-3.5 and GPT-4 models and fine-tuned for conversational applications using supervised and reinforcement learning techniques. Launched on November 30, 2022, ChatGPT quickly gained recognition for its articulate responses across various knowledge domains. However, it has been noted for occasionally providing inaccurate information with confidence. Key features of ChatGPT include:
  • Natural Conversations: ChatGPT can engage in natural human-like conversations, employing various conversational techniques such as questioning, clarifying, and making statements.
  • Comprehensive Answers: It can provide detailed and informative answers to a wide range of questions, even those that are open-ended or complex.
  • Creative Text Generation: ChatGPT can generate diverse formats of text content, including poems, code, scripts, emails, and letters.
Could generative AI replace jobs?
Generative AI, while potentially automating certain roles, is also expected to create new job opportunities. For instance, it could automate customer service, marketing, content creation, and data entry tasks, potentially impacting roles such as customer service representatives, graphic designers, writers, and data entry clerks. However, the rise of generative AI also necessitates skilled professionals to develop and maintain these systems, creating new roles. Furthermore, as generative AI is used in innovative ways, it's likely to open up new job opportunities. While generative AI may transform specific jobs, it also presents new career paths, underscoring the importance of adaptability and continuous learning in the evolving job market. This is all still speculative and could go any number of directions.
What is Auto-GPT?
Auto-GPT, an open-source, autonomous AI tool, leverages OpenAI's GPT-4 and GPT-3.5 text-generating models to execute tasks. Developed by Toran Bruce Richards and released on March 30, 2023, Auto-GPT is speculated to have the following features:
  • Autonomy: Auto-GPT is designed to carry out tasks independently, minimizing the need for human intervention.
  • Versatility: It's believed to handle many tasks, from debugging code and writing emails to craft presentations, blog posts, and marketing materials.
  • User-Friendly: Auto-GPT is expected to be easy to use, making it accessible to individuals regardless of their technical expertise.
Given these potential capabilities, Auto-GPT could significantly transform our work processes, though its full impact remains to be seen.
What is Google's Search Generative Experience?
Google's Search Generative Experience (SGE) is an innovative feature currently under testing. It employs generative AI to generate summaries of search results, providing a comprehensive overview of the topic alongside the traditional list of links. This helps users quickly locate the information they're seeking. SGE operates by generating a summary of search results when a user initiates a search. The summary, influenced by factors like the user's location and search history, is displayed alongside the traditional list of links. Users can delve deeper by clicking on the summary or the original source links. Benefits of SGE include a more comprehensive topic overview, improved user experience by facilitating information discovery, and reduced reliance on traditional search results. As such, SGE represents a potential enhancement to the user search experience.
How can AI generate images?
AI art generators utilize neural networks and machine learning to interpret text prompts, generating diverse digital images and art forms like music, collages, and 3D renderings. Jasper Art, for instance, employs AI to analyze text descriptions and produce customizable, high-quality digital art. These tools expedite creative processes, providing logos, flyers, and other designs, saving time and cost for individuals and organizations in various artistic endeavors.
How can I use generative fill in Photoshop?
Photoshop AI's generative fill tools offer versatile applications, including creating images, removing objects/backgrounds, extending canvases, and generating realistic objects. To extend a canvas, select the marquee tool, make selections around the canvas edges, and apply the generative fill. Select and invert the subject for background replacement, use generative fill with a background prompt, and generate. To add objects, select an area, use generative fill with a relevant prompt, and generate. Object removal involves selecting the area to be replaced and generating. Photoshop's generative fill can create composite images by choosing and generating elements based on prompts. However, it's limited to images below 1024 pixels for quality reasons.
How can AI generate music?
AI music generators employ intricate algorithms and vast music databases to compose original pieces, analyzing rhythm, melody, and harmony patterns. They revolutionize the music industry, offering solutions for background music, soundtracks, and sound effects. Content creators, advertisers, filmmakers, and gamers benefit from AI's ability to produce diverse music, enhancing videos, podcasts, commercials, presentations, and entertainment experiences. AI-driven music creation opens new possibilities, from customized jingles to elaborate orchestrations, making it a versatile tool for various industries and personal enjoyment.
Are AI-generated images copyrighted?
AI-generated images are not eligible for copyright protection as per the U.S. Copyright Office, as these works are created by non-humans and are based on learned patterns from human-made data. The AI systems' outputs are derived from copyrighted material, making them a culmination of human work. The challenge lies in aligning AI advancements with copyright law.
What is the best AI voice generator?
Play.ht is a robust AI voice generator offering efficient text-to-voice conversion for professional-grade audio. It boasts diverse synthetic voices, ideal for podcasts, videos, and articles. The online editor simplifies conversion, enabling customization of speech styles and pronunciations. Real-time synthesis swiftly produces high-quality audio. Play.ht securely manages files, allowing export in MP3/WAV formats, team collaboration, and podcast distribution. Its WordPress plugin enhances website accessibility and engagement, benefiting SEO. With 907 AI voices, emotion-rich styles, and customization options, Play.ht is a top-tier text-to-voice solution.
What is the best AI logo generator?
The Wix Logo Generator, part of the Wix suite, is a top AI logo generator and a versatile addition to its website-building tools. Beyond creating logos, Wix offers deep editing capabilities post-AI generation, providing exceptional flexibility. With over 40 color palettes, 100+ fonts, and diverse icons and geometric shapes, it empowers users to craft unique logos. Multiple file formats, including SVG, for advanced editing and enhanced usability. Wix Logo Generator stands apart by granting users robust graphic design tools to create personalized, AI-informed logos, setting it as a premium logo creation solution.
What is the best AI writing tool?
Rytr is a robust AI writing platform. With a vast array of copywriting frameworks, templates, and use cases, it caters to diverse marketing needs. Rytr employs AI technology to swiftly produce high-quality content, making it valuable for various industries like marketing and eCommerce. Its user-friendly interface ensures accessibility for all, even those new to AI writing. Rytr Chat facilitates human input for specific content generation, while a Chrome extension and Semrush integration enhance usability and effectiveness, making Rytr a top-tier AI writing tool.
What is the best AI video generator?
Pictory is the premier AI video generator, offering rapid video creation from scripts, articles, or image assets. With a vast repository of 3+ million royalty-free visuals, including images, gifs, stickers, and emojis, Pictory empowers users to craft compelling videos effortlessly. It enables seamless editing or complete video generation, making it a versatile tool for efficient and creative video production.

Featured image by Doloves / shutterstock.com

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