Generative AI Use Cases in Data Analytics and BI

A large part of the success of a product lies in the hands of the sales and sales team. Salespeople must understand the customer, be strong enough to observe the customer and be willing to listen to their customer. The success of a product lies not only in building a product but also getting it to the masses, and popularizing it plays a huge role. Marketing is not just about advertising or convincing people instead, it’s about messaging, positioning, brand story, and interaction with customers.

Stay up-to-date on topics such as Blockchain, Artificial Intelligence, and much more. Generative AI enables sales teams to focus on quality and personalization without sacrificing efficiency. Data privacy is critical to keeping confidential data secure from unauthorized access or misuse. As companies’ collection of personal data increases, it is crucial to ensure data security. Companies must adhere to data privacy laws to avoid legal penalties and reputational damage.

See the image above? That’s a generative AI use case. It’s created using Picsart, an app that generates pictures based…

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. Wizdom is an AI solution that analyzes vast amounts of data from the global research ecosystem to offer valuable insights for decision-making. With its comprehensive approach, it empowers users to make informed decisions and stay at the forefront of advancements in their field.

When we think of AI in the education industry, we tend to think of students using AI tools to cheat for assignments. Semantic Scholar is an invaluable resource for researchers seeking expedited access to emerging scientific knowledge. With a comprehensive index of over 2 million academic research papers, this AI-powered application swiftly extracts key insights, enabling users to stay abreast of the latest trends in their respective fields. However, by harnessing advanced technologies, including the integration of generative AI, farmers can overcome these hurdles and achieve optimized crop production, efficient resource management, and sustainable practices.

Use these amazing Deep Learning Models to automate tasks and get ahead. 2022 has been a crazy year for Machine Learning…

Once the foundational activities are in place, it is critical to develop a clear understanding of the core Generative AI technologies. At the center of this are the generative foundation models – including the well-known large language models (LLMs). And we are not just talking about text (which is the basis for ChatGPT); it’s also about generating and managing images, videos, structures (e.g. DNA), audio and software code. The model lifecycle including ingesting, training, tuning, inferring, and running these models is hugely important, and will determine their quality over time. The way these models are being infused in custom applications, generic enterprise applications, and other software development platforms are critical ‘sub-paths’ to impact that also need to be explored.

The outcome is a QA system that can handle intricate, image-based testing scenarios, identifying bugs that would be challenging for traditional automation tools to catch. RedBlink’s Artificial Intelligence Consulting Services offer unmatched expertise in harnessing the potential of this technology. From enhancing creative processes to automating content generation, their solutions drive innovation across industries. Discover how RedBlink can empower your business with cutting-edge AI strategies.

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.

Similarly, this marketing strategy can be used on social and websites to get customers’ attention and increase sales. Using these tools, a person can draw sketches and get the realistic images he wants. For instance, healthcare professionals can use this tool to diagnose a patient, and police can use this tool to get variations of real images of a criminal to hunt him down.

To ensure a successful journey through the slope of enlightenment, you must establish an ecosystem of three robust business capabilities that provide a fertile ground for generative AI to flourish. ChatGPT, or similar software, can identify the positive areas and the problem areas within a piece of content. This simply provides the data that a teacher needs to make their assessment of a student’s assignment. This ensures that students are still receiving the same level of feedback, but reduces the time spent for teaching or assessment staff. We’re just beginning to find new ways to use generative AI in the education sector, and teachers, leaders and students around the globe continue to experiment. The key is to find safe ways to use these tools, while also reaping their benefits.

Gartner earlier this year reported that 38% of respondents consider customer experience/retention as their primary focus of generative AI investments. That was No. 1, ahead of revenue growth (26%), cost optimization (17%) and business continuity (7%). Marketing and customer care continue to play a prominent role in the use of generative artificial intelligence. Organizations need a data lakehouse to target data challenges that come with deploying an AI-powered knowledge management system.

Code Conductor empowers users to create applications without writing a single line of code. Its intuitive drag-and-drop interface and extensive library of pre-built components make it easy to design and deploy various applications. When comparing ChatGPT 3.5 and ChatGPT 4, it becomes evident that these advanced language models have revolutionized content generation. If you’re interested in diving deeper into the topic, I recently came across a fascinating analysis comparing the capabilities of ChatGPT 3.5 vs. ChatGPT 4, you must checkout. The technological landscape is in a constant state of evolution and is leading us toward a new industrial environment where humans are working with intelligent machines. These smart machines are embedded with various cognitive technologies such as artificial intelligence and machine learning.

How to benefit your business whether it’s big or small, these potential use cases of generative AI will help you take it to even greater heights. NLP, or Natural Language Processing, is a field in Artificial Intelligence that allows computers to understand and comprehend the languages that are written by Humans. In this article, we will unravel the multiple use cases of LLMs and uncover their immense potential in countless domains. With over a decade of premier partner status, 66degrees aligns with Google Cloud to ensure a seamless experience for our clients — from our shared vision to the way we organize our teams. Dive seamlessly integrates with popular video conferencing platforms, revolutionizing your meeting experience.

Whether you are using Power BI or another
self-service BI tool, generative AI models can come in handy on many occasions. Present-day generative AI models can
automate work activities that consume 60%-70% of employees’ Yakov Livshits time. These research developments highlight LLMs’ ongoing evolution and increasing versatility in tackling complex tasks. However, it’s important to note that we are still in the early days of using generative AI.

• This can reduce time and money, increase efficiency and improve the quality of content generated.
• The TTS generation has multiple business applications such as education, marketing, podcasting, advertisement, etc.
• Generative AI is now being used to code various kinds of apps and write product documentation for these apps.
• Most generative AI models are based on diffusion/transformer (another explanation) architecture.
• There was still a considerable amount of manual input required, and the method lacked the ability to autonomously account for entirely new scenarios or changes in application behavior.
• Like image generation, generative AI tools for video production can create videos from scratch, which can be used for enhancing video resolution, video manipulation, and completion.