Generative AI: What Is It, Tools, Models, Applications and Use Cases

They can use such models for virtual try-on options for customers or 3D-rendering of a garment. Generative AI offers teachers a practical and effective way to develop massive amounts of unique material quickly. Whether it’s quiz questions, reviews of concepts or explanations, this technology can generate brand-new content from existing information to help educators easily create diverse teaching materials for their classes. From designing syllabi and assessments to personalizing course material based on students’ individual needs, generative AI can help make teaching more efficient and effective. Furthermore, when combined with virtual reality technology, it can also create realistic simulations that will further engage learners in the process.

This is accomplished by generating a comprehensive image of a passenger’s face utilizing photographs captured from various angles, streamlining the process of identifying and confirming the identity of travelers. It can be used to analyze player data, such as gameplay patterns and preferences, to provide personalized game experiences. Generative AI can improve the quality of outdated Yakov Livshits or low-quality learning materials, such as historical documents, photographs, and films. By using AI to enhance the resolution of these materials, they can be brought up to modern standards and be more engaging for students who are used to high-quality media. It can allow students to interact with a virtual tutor and receive real-time feedback in the comfort of their home.

Finally, the technology’s adaptability and interactivity could encourage preventive care, wellness, and healthy behaviors via personalized nudges on mobile apps, wearables, and monitoring devices. Predictive AI forecasts Yakov Livshits future events by analyzing historical data trends to assign probability weights to the models. GPT-3 in particular has also proven to be an effective, if not perfect, generator of computer program code.

Image Resolution Increase (Super-Resolution)

Tools like ChatGPT can assist in creating content structure by generating outlines and organization suggestions for a given topic. This can be useful for SEO maximization because a well-structured and organized content not only provides a better user experience but also helps search engines understand the context and relevance of the content. When a customer leaves a review or comment on online review platforms or your website, ChatGPT or other tools can be used to generate a response that addresses the customer’s concerns and offers potential solutions or assistance. Generative AI models can simulate various production scenarios, predict demand, and help optimize inventory levels. It can use historical customer data to predict demand, thereby enabling more accurate production schedules and optimal inventory levels.

Still, our research indicates the technology could deliver productivity with a value ranging from 10 to 15 percent of overall R&D costs. In other cases, generative AI can drive value by working in partnership with workers, augmenting their work in ways that accelerate their productivity. Its ability to rapidly digest mountains of data and draw conclusions from it enables the technology to offer insights and options that can dramatically enhance knowledge work.

Data privacy protection for analytical models

Maket is an AI tool that empowers architects, designers, builders, contractors, and developers in the residential industry. Additionally, Maket assists users in navigating zoning codes and offers a wide range of styles to explore. Tidio is a customer support AI software that empowers small and medium-sized organizations with real-time chat, personalized recommendations, and task automation. This AI app leverages extensive data collected from diverse sensors and sources to construct a digital replica of a facility or factory. By utilizing real-world information, it can create simulations that provide predictive insights into product performance and process outcomes. One example of how media outlets can utilize generative AI for their content is BuzzFeed.

For customers who need additional resources to get started, Synthesia offers a library of example videos, a help center, and Synthesia Academy tutorials. Bard, considered Google’s response to ChatGPT, is a chatbot and content generation tool that runs on LaMDA, a transformer-based model that Google launched a couple of years ago. The tool is currently considered a Google Experiment and is only available to a limited number of users in the United States and the United Kingdom. Worse, sometimes it’s biased (because it’s built on the gender, racial, and myriad other biases of the internet and society more generally) and can be manipulated to enable unethical or criminal activity. For example, ChatGPT won’t give you instructions on how to hotwire a car, but if you say you need to hotwire a car to save a baby, the algorithm is happy to comply. Organizations that rely on generative AI models should reckon with reputational and legal risks involved in unintentionally publishing biased, offensive, or copyrighted content.

Generative AI outputs are carefully calibrated combinations of the data used to train the algorithms. Because the amount of data used to train these algorithms is so incredibly massive—as noted, GPT-3 was trained on 45 terabytes of text data—the models can appear to be “creative” when producing outputs. What’s more, the models usually have random elements, which means they can produce a variety of outputs from one input request—making them seem even more lifelike.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Pharmaceuticals and medical products could see benefits across the entire value chain

And medtech company Implicity is using the technology to incorporate remote monitoring in pacemakers and implantable defibrillators. Generative AI could help companies create more personalized and patient-centered devices—incorporating software that allows for preventive maintenance and repairs, for example. Generative AI could support applications like conversational AI to deliver personalized messages based on member health needs and preferences.

• A 2022 McKinsey survey shows that AI adoption has more than doubled over the past five years, and investment in AI is increasing apace.
• These deep generative models were the first able to output not only class labels for images, but to output entire images.
• But once a generative model is trained, it can be “fine-tuned” for a particular content domain with much less data.
• Generative AI can analyze historical sales data and generate forecasts for future sales.

Training GANs for the purpose of fraud detection, by utilizing it with a training set of fraudulent transactions, helps identify underrepresented transactions. Generative AI can be used to automate the process of refactoring code, making it easier to maintain and update over time. One of the most straightforward uses of generative AI for coding is to suggest code completions as developers type. GAN-based video predictions can help detect anomalies that are needed in a wide range of sectors, such as security and surveillance.

Marketing Applications

All of us are at the beginning of a journey to understand generative AI’s power, reach, and capabilities. This research is the latest in our efforts to assess the impact of this new era of AI. It suggests that generative AI is poised to transform roles and boost performance across functions such as sales and marketing, customer operations, and software development. In the process, it could unlock trillions of dollars in value across sectors from banking to life sciences. To grasp what lies ahead requires an understanding of the breakthroughs that have enabled the rise of generative AI, which were decades in the making.

Using generative models, AI can suggest new or alternative products to customers that they might be interested in, based on their buying history and preferences. It can also anticipate their future needs and preferences, thereby improving the shopping experience. Generative AI can create new product designs based on the analysis of current market trends, consumer preferences, and historic sales data. The AI model can generate multiple variations, allowing companies to shortlist the most appealing options.

Code

The process of including related keywords to a content is crucial for a successful SEO strategy as it helps determine the terms and phrases that potential customers use when searching for products or services related to the website’s offerings. Conversational tools can be trained to recognize and respond to common customer complaints, such as issues with product quality, shipping delays, or billing errors. When a customer sends a message with a complaint, the tool can analyze the message and provide a response that addresses the customer’s concerns and offers potential solutions. Generative AI models can generate personalized insurance policies based on the specific needs and circumstances of each customer.

Generative AI can create realistic and dynamic NPC behavior, such as enemy AI and NPC interactions. ChatGPT code interpreter can convert files between different formats, provided that the necessary libraries are available and the operation can be performed using Python code. To achieve realistic outcomes, the discriminators serve as a trainer who accentuates, tones, and/or modulates the voice. One example of such a conversion would be turning a daylight image into a nighttime image. This type of conversion can also be used for manipulating the fundamental attributes of an image (such as a face, see the figure below), colorize them, or change their style. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Some generative models like ChatGPT can perform data visualization which is useful for many areas. It can be used to load datasets, perform transformations, and analyze data using Python libraries like pandas, numpy, and matplotlib. You can ask ChatGPT Code Interpreter to perform certain analysis tasks and it will write and execute the appropriate Python code. These can be useful for mitigating the data imbalance issue for the sentiment analysis of users’ opinions (as in the figure below) in many contexts such as education, customer services, etc.