Blog: Generative AI in action: real-world applications and examples

The app provides diverse plans with options for various body sizes, hairstyles, body shapes, custom poses, and more. Lokalise AI is an automated localization and translation platform designed for various applications, including web apps, customer service, documents, mobile apps, games, and marketing assets. With its advanced features like contextual translation, alternative variants, rephrasing, and concise adaptations, it enables seamless communication with global audiences in different languages.

• He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
• Others are working to improve resource utilization by both clinical and administrative staff.
• AI can be used to generate interview questions that are relevant to the job position and that assess the candidate’s qualifications, skills, and experience.
• Generative AI has many use cases that can benefit the way we work, by speeding up the content creation process or reducing the effort put into crafting an initial outline for a survey or email.

A generative AI system is constructed by applying unsupervised or self-supervised machine learning to a data set. The capabilities of a generative AI system depend on the modality or type of the data set used. However, keep in mind that it is important for your company to establish usage rules ahead of time, especially as it relates to data security and uploading proprietary information into any of these tools. Though some of its features are relatively limited compared to ChatGPT, the tool is quickly growing its capabilities.

generative AI solutions?

An audio-related application of generative AI involves voice generation using existing voice sources. With STS conversion, voice overs can be easily and quickly created which is advantageous for industries such as gaming and film. With these tools, it is possible to generate voice overs for a documentary, a commercial, or a game without hiring a voice artist.

GPT-3, for example, was initially trained on 45 terabytes of data and employs 175 billion parameters or coefficients to make its predictions; a single training run for GPT-3 cost $12 million. Most companies don’t have the data center capabilities or cloud computing budgets to train their own models of this type from scratch. As a result, generative AI is likely to have the biggest impact on knowledge work, particularly activities involving decision making and collaboration, which previously had the lowest potential for automation (Exhibit 10). Our estimate of the technical potential to automate the application of expertise jumped 34 percentage points, while the potential to automate management and develop talent increased from 16 percent in 2017 to 49 percent in 2023. Our previously modeled adoption scenarios suggested that 50 percent of time spent on 2016 work activities would be automated sometime between 2035 and 2070, with a midpoint scenario around 2053.

View All Financial Services & Investing

AI is providing a significant upgrade to banking operations by automating tasks that were previously performed manually, resulting in more efficient processes. Traditional methods have been replaced by digital strategies, personalized messaging, and interactive experiences that businesses must navigate in order to connect and resonate with their target audiences. From the Mad Men era to the age of the internet, social media, and hyperconnectedness, marketing has undergone a remarkable transformation. It efficiently grades both digital and paper-based assignments, providing quick and accurate results. Additionally, Gradescope offers valuable insights into students’ knowledge levels across various subjects.

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.

Even when a source is provided, that source might have incorrect information or may be falsely linked. Submit a text prompt, and the generator will produce an output, whether it is a story or outline from ChatGPT or a monkey painted in a Victorian style by DALL-E2. It’s also worth noting that generative AI capabilities will increasingly be built into the software products you likely use everyday, like Bing, Office 365, Microsoft 365 Copilot and Google Workspace. This is effectively a “free” tier, though vendors will ultimately pass on costs to customers as part of bundled incremental price increases to their products. If the company is using its own instance of a large language model, the privacy concerns that inform limiting inputs go away.

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

One advantage of using generative AI to create training data sets is that it can help protect student privacy. A data breach or hacking incident can reveal real-world data containing personal information about school age children. By leveraging generative AI, personalized Yakov Livshits lesson plans can provide students with the most effective and tailored education possible. These plans are crafted by analyzing student data such as their past performance, skillset, and any feedback they may have given regarding curriculum content.

ChatGPT and other similar generative tools with their natural language processing (NLP) can generate personalized content for your customers based on their preferences, past behavior, and demographics. This can help you create targeted content that resonates with your audience, which can lead to higher engagement and conversion rates. By learning from images of products in the past and identifying those that were defective, generative AI tools can generate a model to predict whether a newly manufactured product is likely to be defective. Using synthetic data, which is created by AI models that have learned from real-world data, can provide anonymity and protect students’ personal information. Synthetic data sets produced by generative models are effective and useful for training other algorithms, while being secure and safe to use. Data augumentation is a process of generating new training data by applying various image transformations such as flipping, cropping, rotating, and color jittering.

Generative AI applications in business

These deep generative models were the first able to output not only class labels for images, but to output entire images. Cohere Generate is a text generation solution from Cohere, a fast-growing AI startup with leadership members that previously wrote and worked on Google’s now-famous Transformer paper. Many of the use cases advertised on Cohere’s site focus on product management and sales, digital marketing, and similar Yakov Livshits goals, but the tool can be used for software development tasks and other business requirements as well. AI encompasses many techniques for developing software models that can accomplish meaningful work that only humans could perform previously. AI developers build different AI models embodying a variety of techniques, including neural networks, genetic algorithms, deep or machine learning and reinforcement learning.

Marketing functions could shift resources to producing higher-quality content for owned channels, potentially reducing spending on external channels and agencies. For one thing, mathematical models trained on publicly available data without sufficient safeguards Yakov Livshits against plagiarism, copyright violations, and branding recognition risks infringing on intellectual property rights. A virtual try-on application may produce biased representations of certain demographics because of limited or biased training data.