Top 35 Generative AI Tools by Category Text, Image 2023

Creating dialogues, headlines, or ads through generative AI is commonly used in marketing, gaming, and communication industries. These tools can be used in live chat boxes for real-time conversations with customers or to create product descriptions, articles, and social media content. Generative AI tools are trained by natural language processing, neural networks, and/or deep learning AI algorithms to ingest, “understand,” and generate responses based on input data. Successful generative AI models are only possible with massive amounts of relevant, clean, ethical, and unbiased training data.

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 thousands of potential scenarios from historical trends and data. The insurance companies can use these scenarios to understand potential future outcomes Yakov Livshits and make better decisions. Generative AI can be used to generate synthetic customer profiles that help in developing and testing models for customer segmentation, behavior prediction, and personalized marketing without breaching privacy norms. Generative AI offers teachers a practical and effective way to develop massive amounts of unique material quickly.

Applying Generative AI to product design with BigQuery DataFrames

Developers using generative AI–based tools were more than twice as likely to report overall happiness, fulfillment, and a state of flow. They attributed this to the tools’ ability to automate grunt work that kept them from more satisfying tasks and to put information at their fingertips faster than a search for solutions across different online platforms. Our latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists—all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.

Generative AI models can be employed to streamline the often complex process of claims management. They can generate automated responses for basic claim inquiries, accelerating the overall claim settlement process and shortening the time of processing insurance claims. Generative programming tools can be used to automate game testing, such as identifying bugs and glitches, and providing feedback on gameplay balance. This can help game developers to reduce testing time and costs, and improve the overall quality of their games. It can be used to analyze player data, such as gameplay patterns and preferences, to provide personalized game experiences.

Video related applications

These tools enable text-to-image conversions that can be used commercially in areas such as advertising, publishing, and the film industry. Based on a function-based classification, we will examine the top generative AI tools in this article. AI can be used to generate onboarding materials for new employees, such as training videos, handbooks, and other documentation. ChatGPT can be used in generating sitemap codes producing an XML file that lists all the pages and content on a website. ChatGPT can be used in creating effective meta descriptions by generating summaries of the content that accurately and concisely describe the main topic of a page.

• The customer doesn’t even need to provide the new product name—they can just upload an image and let the agent guide them through the rest.
• In turn, the CEO said, “Great!” and explained that the programming language’s “simplicity and readability make it a popular choice for beginners and experienced developers alike.”
• The majority of genAI users work with public-facing applications (e.g., ChatGPT, DALL-E).
• As you can see above most Big Tech firms are either building their own generative AI solutions or investing in companies building large language models.

The multilingual support offered by generative AI tools like ChatGPT for customer service involves using the large language model capabilities of the system to provide support to customers who speak different languages. Conversational AI tools can be trained on a variety of languages, and it can translate messages from one language to another in real-time. Generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it.

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.

Compared to DALL-E, DALL-E 2 is said to be generating more photorealistic imagery that better matches user requests. An additional plus, DALL-E 2 appears to have received more training than its predecessor on how to decline inappropriate inputs and avoid creating inappropriate outputs. Synthesia is an AI video creation platform that allows users to create videos based on their own scripted prompts.

Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. Heathrow Airport is another organization already experiencing the benefits of Einstein Copilot, using it to create personalized interactions based on real-time data of millions of passengers. “For example, a marketer could ask Prompt Builder to generate a personalized message and discount for a new product based on the customer’s purchase history and location. Einstein Copilot will then auto-generate personalized messages that align with individual customer preferences, reference past purchases, and demographic information,” Salesforce’s press release states. With these integrations, users will be able to seamlessly work across platforms through Salesforce and Google Workspace’s generative AI assistants, Salesforce’s Einstein Copilot, and Duet AI in Google Workspace. Humans are still required to select the most appropriate generative AI model for the task at hand, aggregate and pre-process training data and evaluate the AI model’s output.

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. Generative AI provides banks with a powerful tool to detect suspicious or fraudulent transactions, enhancing the ability to combat financial crime. 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 improve the quality of outdated 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 offers a highly informative and integrated conversation to users, like philosophical discussions.

This flexibility allows for a better experience than the “Sorry, I can’t answer that” responses we have come to expect from bots. When applicable, these types of responses include citations so the user knows what source content was used to generate the answer. Google today announced the launch of AlloyDB AI, an integrated set of capabilities built into AlloyDB for PostgreSQL to support developers in building generative AI apps using their own data. AlloyDB AI, available in preview via AlloyDB Omni (which is moving from a technical preview to public preview), provides built-in support for vector embeddings — delivering the foundation for AI search apps and more. By using machine learning algorithms, manufacturers can predict equipment failures and maintain their equipment proactively.

Step GenAI growth guideline for businesses

Do you have historic family photographs of distant relatives or ancestors who you’d like to see in motion? This innovative tool lets you animate the faces in family photos so you can see them smile, blink, and laugh, just as if you had recorded a video of them back in the day. Automated music generator – create royalty-free Yakov Livshits AI music by simply making decisions about the genre of music you want to create, the instruments that will be used, the mood you want to create, and the length of the track. So, what are the tools that everyone should be getting to grips with to ensure they understand exactly what AI is capable of today?