What Is Generative AI? Meaning & Examples

OpenAI, an AI research and deployment company, took the core ideas behind transformers to train its version, dubbed Generative Pre-trained Transformer, or GPT. Observers have noted that GPT is the same acronym used to describe general-purpose technologies such as the steam engine, electricity and computing. Most would agree that GPT and other transformer implementations are already living up to their name as researchers discover ways to apply them to industry, science, commerce, construction and medicine.

OpenAI’s Dall-E 2 and other products — Midjourney, Deep Dream Generator, Big Sleep, etc. — use AI to create pictures based on text descriptions. If you tell one to create a ridiculous picture of 14 lemmings and a talking cantaloupe wearing a trench coat and pretending to be a private investigator, it will do so. Dall-E and its many competitors have taken a huge leap forward, in both their image quality and their ability to translate arbitrary text into images. For example, in a few months they overcame severe shortcomings, such as an inability to generate realistic human hands. Such systems are finding their way into advertising, product design, set design, film and other industries. The benefits of generative AI include faster product development, enhanced customer experience and improved employee productivity, but the specifics depend on the use case.

What are ChatGPT and DALL-E?

For example, you can enter a prompt into a chatbot and the algorithm will give you brand-new content based on that prompt. Other use cases include generating branded images to use in ads, developing content ideas based on SEO keywords, writing shareable summaries for long-form articles and even translating advertisements. Additionally, tools are also growing, as developers work to evolve the original technology to create new software. Building a generative AI model has for the most part been a major undertaking, to the extent that only a few well-resourced tech heavyweights have made an attempt.

Understanding the search intent behind a query is crucial in creating content that accurately and effectively addresses the needs of the customers, which can lead to higher engagement and conversions. The video below is generated by AI and shows its visual potentials to be used for marketing purposes. For more, check our article on the use and examples of generative AI in the retail industry.

Creating interview questions

Boost.ai is an AI-powered conversation builder that delivers accurate responses to customers using advanced natural language processing and your customized training inputs. It seamlessly operates across various platforms, including websites, Slack channels, Zendesk, and Teams. ChatBot is an AI customer support tool that improves service by streamlining processes and offering support across various channels and languages. It leverages large language models to enhance the user experience with visual explanations and interactive forms.

Marketing chief Fab Dolan, whose departure was announced on the earnings call, spent just over two months in the position. The departure of Chief Product Officer Sujatha Sagiraju was also just announced. Despite Appen’s enviable client list and its nearly 30-year history, the company’s struggles have intensified this year. Revenue in the first half of 2023 tumbled 24% to $138.9 million, amid what it called a “broader technology slowdown.” The company said its underlying loss widened to $34.2 million from $3.8 million a year earlier.

Generative AI techniques

This can be a big problem when we rely on generative AI results to write code or provide medical advice. Many results of generative AI are not transparent, so it is hard to determine if, for example, they infringe on copyrights or if there is problem with the original sources from which they draw results. If you don’t know how the AI came to a conclusion, you cannot reason about why it might be wrong. The AI-powered chatbot that took the world by storm in November 2022 was built on OpenAI’s GPT-3.5 implementation. OpenAI has provided a way to interact and fine-tune text responses via a chat interface with interactive feedback.

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.

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. Another use case of generative AI involves generating responses to user input in the form of natural language. This type is commonly used in chatbots and virtual assistants, which are designed to provide information, answer questions, or perform tasks for users through conversational interfaces such as chat windows or voice assistants. Music-generation tools can be used to generate novel musical materials for advertisements or other creative purposes. In this context, however, there remains an important obstacle to overcome, namely copyright infringement caused by the inclusion of copyrighted artwork in training data.

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Generative AI applications produce novel and realistic visual, textual, and animated content within minutes. Tools called AI detectors are designed to label text as AI-generated or human. AI detectors work by looking for specific Yakov Livshits characteristics in the text, such as a low level of randomness in word choice and sentence length. These characteristics are typical of AI writing, allowing the detector to make a good guess at when text is AI-generated.

The models do this by incorporating machine learning techniques known as neural networks, which are loosely inspired by the way the human brain processes and interprets information and then learns from it over time. As we continue to advance these models and scale up the training and the datasets, we can expect to eventually generate samples that depict entirely plausible images or videos. This may by itself find use in multiple applications, such as on-demand generated art, or Photoshop++ commands such as “make my smile wider”. Additional presently known applications include image denoising, inpainting, super-resolution, structured prediction, exploration in reinforcement learning, and neural network pretraining in cases where labeled data is expensive. Researchers appealed to GANs to offer alternatives to the deficiencies of the state-of-the-art ML algorithms.

• Generative AI describes situations in which the computer creates something new rather than evaluating something already existing.
• In 2023, the rise of large language models like ChatGPT is indicative of the explosion in popularity of generative AI as well as its range of applications.
• Generative AI also raises numerous questions about what constitutes original and proprietary content.
• Generative AI has a variety of different use cases and powers several popular applications.

Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data. The recent buzz around generative AI has been driven by the simplicity of new user interfaces for creating high-quality text, graphics and videos in a matter of seconds. You’ve probably seen that generative AI tools (toys?) like ChatGPT can generate endless hours of entertainment.

How will generative AI contribute business value?

Such models can help fintech companies produce innovative trading strategies and predict future market trends. For example, Markov chain models can analyze past purchase histories to provide product recommendations customized to each customer’s preferences. Moreover, these tools can also help create text-based reports and perform complex business calculations. Simform provides top AI/ML development services which integrate generative AI capabilities for NLP-based solutions across business domains. The adoption of generative AI is increasing across business domains, and why not? After all, if harnessed well, it can significantly reduce the overall time, effort, and cost needed to run the business.

From creating innovative styles to refining and optimizing existing looks, the technology helps designers keep up with the latest trends while maintaining their creativity in the process. This can be done by a variety of techniques such as unique generative design or style transfer from other sources. By leveraging generative AI, personalized lesson plans can provide students with the most effective and tailored education possible.

Moreover, generative AI can assist artists and animators by providing them with new ideas and exhaustive features to enhance their artwork. One easy but very useful use case is generating many variations of an artwork. A one-stop destination to help you identify and understand the complexities and opportunities that AI surfaces for your business and society. Users can simply insert queries into the Bing search box and receive answers instantly on the search results page. ChatGPT can be used for simple queries such as “who signed the Declaration of Independence” or for more complex tasks such as finding errors in code.