2306 02781 A survey of Generative AI Applications

Generative AI models combine various AI algorithms to represent and process content. Similarly, images are transformed into various visual elements, also expressed as vectors. One caution is that these techniques can also encode the biases, racism, deception and puffery contained in the training data. Yakov Livshits for developing chatbots and virtual assistants help in ensuring that users can obtain relevant information in a timely manner. The generative AI applications focus on offering customer service or helping users with multiple tasks, such as playing videos or scheduling appointments.

Up until recently, machines had no chance of competing with humans at creative work—they were relegated to analysis and rote cognitive labor. But machines are just starting to get good at creating sensical and beautiful things. This new category is called “Generative AI,” meaning the machine is generating something new rather than analyzing something that already exists. Banks and alternative financial service providers leverage deep learning models like GAN for credit scoring and fraud detection.

Personalized customer responses

Simplifying the traditionally complex process of video editing, Runway provides an accessible and cost-effective solution for enhancing video footage. ChatGPT, developed by OpenAI, is a renowned web-based chatbot that rapidly gained traction after its launch in November 2022. Its interface emulates a traditional chatbot, enabling users to pose questions and receive prompt, detailed responses. Generative AI provides new and disruptive opportunities to increase revenue, reduce costs, improve productivity and better manage risk. In a recent Gartner webinar poll of more than 2,500 executives, 38% indicated that customer experience and retention is the primary purpose of their generative AI investments.

• Provide powerful google-like search capabilities to your internal documents which are not publicly available.
• The generative AI model lets you reach more audiences in a short period because of its results.
• Many early users have praised Claude’s abilities when it comes to comedy, creative content generation, and generally absorbing feedback about communication style.
• Generative AI can be used to analyze customer data, such as past bookings and preferences, to provide personalized recommendations for travel destinations, accommodations, and activities.
• Generative AI aims to utilize generative AI models to inspect data and produce new and original content based on that data.

Such types of use cases can find different types of applications in advertising, education, and marketing. Examples of generative AI for voice generation would include Replica Studios, Lovo, and Synthesys. The potential of generative AI for creating works of art is also useful for game developers. Generative AI can help game developers by supporting the creation of different aspects of a video game by leveraging AI algorithms. The use cases of generative AI in game development focus on creating game levels, objects, characters as well as narratives for the entire game.

Customer service chatbot

This also raises the issue of it replacing humans when it comes to many creative workforces, such as freelancers or commercial artists who work in publishing, entertainment, and even advertising. Our platform now also allows you to generate synthetic data, which you can use as an addition to your existing datasets. For more on which Python tools to use for generative AI application building, check out our latest cheat sheet. There are far more than we have captured on this page, and we are enthralled by the creative applications that founders and developers are dreaming up. They are large and difficult to run (requiring GPU orchestration), not broadly accessible (unavailable or closed beta only), and expensive to use as a cloud service. Despite these limitations, the earliest Generative AI applications begin to enter the fray.

Such solutions are also effective in simulating and testing potential ideas to predict outcomes, enabling organizations to make informed decisions when pursuing specific objectives. With the right partner capable of developing a tailored generative AI-based system to meet the organization’s needs, any business can elevate its actions and gain a competitive advantage. A company “brain” powered by generative AI serves as a valuable tool for employees at all levels, from newly hired staff to CEOs, as well as other stakeholders. It acts as a knowledge hub accessible from anywhere, swiftly retrieving and presenting information in the desired format. For instance, a sales manager can ask the app to provide the latest statistics from their department and present them as a graph to demonstrate the sales team’s performance to superiors.

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.

User interface design

Journalists, social media influencers, YouTube podcasters, and movie script writers are already using generative artificial intelligence systems to create ideas, gather information, and draft their texts. On top of the two models used by ML, Generative AI can also use Yakov Livshits the semi-supervised model learning characteristic of the DL algorithms. This semi-supervised learning model suggests that a system is given a small amount of tagged data and a large amount of untagged data to build an understanding of how they relate to each other.

Inspired by the human brain, neural networks do not necessarily require human supervision or intervention to distinguish differences or patterns in the training data. Generative AI holds immense promise for unlocking creativity across various industries. With generative AI applications and the correct data, companies can explore more possibilities, minimize risk, optimize production and automate tasks, leading to breakthrough solutions and cost savings. Style transfer models allow users to manipulate and transform an input image or video style while preserving its content. These models employ convolutional neural networks (CNNs) and feature-matching techniques to separate content and style representations.

By analyzing X-rays or MRIs and comparing them to extensive databases of other medical images, AI can quickly and precisely detect anomalies. For such businesses, staying informed about market trends, seasonal fluctuations, customer preferences, and potential risks is crucial to keep their operations running smoothly. With generative AI, they can improve performance, identify areas that require improvement, reduce costs, and proactively prevent potential malfunctions. Some individuals express concerns that ChatGPT and other artist-dedicated solutions might eventually replace humans. Creatives who harness the power of algorithms will be able to elevate their art and build businesses around it.

Notion has launched an Alpha of Generative AI Copywriting Tool that can assist users in generating outlines for blogs, social media posts, and other content pieces. Notion AI can also produce drafts for various types of documents such as meeting agendas, press releases, brainstorms, and even poems upon request. On top of that it could work with your text to fix spelling & grammar, summarize the idea of the text, or translate it. Telecom virtual assistants can assist customers with inquiries, billing, and account management, providing a personalized experience. Virtual assistant analyze data on usage patterns, device type, and location, Generative AI in Telecom personalized recommendations based on customer behavior.

EXPLORING POPULAR GENERATIVE AI APPLICATIONS IN 2023

Generative AI Tools can be useful in a variety of industries, including advertising, entertainment, design, manufacturing, healthcare, and finance. Generative Adversarial Networks (GANs) are capable of producing lifelike audio speech. In order to achieve this, discriminators act as trainers, emphasizing, toning, and/or modulating the voice to create a convincing output. It’s not surprising that generative AI is a crucial tool that organizations across industries must adopt.