Insights

How to get started in Generative AI

Adnan Masood, PhD. Chief AI Architect, UST

2023 will increasingly likely be known as the year of “Generative AI.” Executive enthusiasm about the promise of Generative AI to transform their business dominates the news, and we continually see new applications or development in the space.

A Salesforce survey of over 500 senior IT leaders found that two-thirds were prioritizing Generative AI for their business over the next year and a half; one-third of them said it was a top priority. It is abundantly clear that Generative AI is poised to transform many businesses and industries as we know them.

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Introduction to Generative AI

As we explained in our first blog, Generative AI is a form of applied artificial intelligence based on algorithms trained on existing content to create “new” forms of content, such as images, text, or video, resembling human-generated content. Developers train these Generative AI tools on a vast array of content to parse the data sets quickly and answer prompts. Recent public launches of OpenAI’s ChatGPT, Google’s Bard, and Stable Diffusion’s visual-based AI have captured the public’s attention. As the field matures, there will be more entrants and each model will seek to differentiate itself from the competition.

Generative AI is one of the most powerful technologies to be developed in the 21st century. It promises to remake business, creating new opportunities for startups and established enterprises, and has the power to shuffle the current pecking order of industry leaders. The topic has captured the attention of consumers and business executives alike, driving many to say we’re at the forefront of a Generative AI revolution.

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Why is Generative AI important for businesses?

Generative AI creates many business opportunities for companies of all sizes and across different industries. GPT-4, for instance, can generate human-like text that can replace human effort for various tasks, such as creating new product descriptions, composing messages, generating customer service responses, and even writing code.

Generative AI will minimize the need for employees to engage in repetitive tasks better suited to computers and code, freeing up those workers to pursue more meaningful projects that contribute to the bottom line and drive greater job satisfaction.

Some examples of repetitive tasks now handled by humans that Generative AI will transform:

1. Generating reports: It can take volumes of data, make sense of it, and create a persuasive and beautiful presentation or PDF.
2. Research assistant: Generative AI can help identify reading material, surface insights, and pour through emails to help busy executives find exactly what they need to find.
3. Composing emails: Indeed, many email platforms already use a form of AI to auto-suggest words, phrases or sentences based on what a user has already written. Generative AI goes beyond this, making it possible to draft an entire email based on a few cues.
4. Generating customer service responses: Companies have used chatbots for many years to answer the most common customer questions, alleviating the need for additional human customer service representatives and ensuring those customers receive accurate information immediately. But they are limited in that they have a specific script to follow and do not parse the nuances of human language and Generative AI. Using the latter to power responses to a broader array of human questions will yield more personalized responses.
   
   These are just some simple ways Generative AI can transform businesses. It is set to have a broader impact on business intelligence, creative decision-making, and product strategy.

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How to get started in Generative AI

Identify the opportunity: One of the reasons why Generative AI is so powerful is because it holds the promise of transforming so many things. That can become overwhelming. The first step is identifying a problem/opportunity that Generative AI can help solve. This could be anything from creating new product designs to automating customer service interactions. Understanding the problem and opportunity is essential before moving forward. As with other major digital transformation efforts, you should pick one manageable opportunity for a trial run. But ensure it will have a meaningful and demonstrable impact on your business.

1. Gather and prepare data: As the famous saying goes: bad data in, bad data out. Generative AI models are only as good as the information they're trained on. Your company will need to gather and prepare data that will be used to train the model. The more data you can feed into the tool, the better the results will be. This includes cleaning and pre-processing the data and formatting it for the model to understand.
2. Choose your platform: There are a variety of platforms and tools available for training and deploying Generative AI models, such as OpenAI’s GPT-4, Google’s Bard, HuggingFace’s Transformers, or TensorFlow. All have different approaches, feature different inputs and outputs, and are trained on different datasets. Knowing what each one excels at and placing it in context with your business will help your organization select the right one.
3. Understand the legal risks and ethics: Companies must comply with relevant laws and regulations regarding AI and data, such as ensuring the data used to train the model is legally obtained and the company has the necessary permissions to use it. Additionally, Generative AI presents several ethical implications, such as the potential for biases based on race, religion, or gender and the potential for misuse. Companies must spend considerable time exploring the model used, who will have access to it, and what kind of content it will generate, and establish safeguards to minimize potential harm.
4. Selecting the right team and resources: UST helps you choose a platform appropriate for your specific use case and has the necessary features to train the model. The right partner can help you collect and pre-process the right data, select and fine-tune the right model for your business, and perfect the integration and launch.
5. Deploy the model: Once fine-tuned, it can be deployed in a production environment. This could involve integrating the model into an existing application or creating a new application that utilizes the model’s capabilities.

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Key considerations for implementing Generative AI in your business

Could you not do it alone? Generative AI is too important to get wrong. The right partner puts you on the right track right away. Working with Generative AI requires significant effort, and businesses cannot afford to go down the wrong path, especially in uncertain economic times.

1. Put in the work before launching: That includes ensuring your data is clean, legally obtained, and usable for AI.
2. Communicate clearly to the C-suite: Generative AI available today is impressive but will be far from what it will be in five years or even five months. Don't oversell the promise of Generative AI; it will only lead to confusion and disappointment if not set up correctly.
3. Fine-tune the model: Creating a Generative AI model usually begins by training it on a smaller, specialized dataset to adapt it to a specific task or domain. This allows the model to improve performance in a particular task or domain while leveraging the general knowledge and capabilities learned during pre-training.
4. Monitor and maintain: Generative AI models require ongoing monitoring and maintenance to perform as expected and adjust as needed. This includes monitoring the model's performance, updating the model with new data, and retraining the model as needed.
   
   UST collaborates with clients to create a Generative AI approach that meets their business needs. Most importantly, we identify specific use cases to drive business results by improving employee productivity and satisfaction and creating new and dynamic revenue streams.
   
   With our team of experts in natural language processing, machine learning, and enterprise software development, we can help you unlock the full potential of your business with Generative AI. From data collection and preprocessing to model deployment and integration, we provide end-to-end solutions customized to your needs. Learn more here.

Unlock the power of Generative Al as a visionary CIO with a free guide

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Case Studies: Real-World Applications of Generative AI

To help illustrate the impact of Generative AI on various industries, let's explore some real-world applications and case studies:

1. Marketing and Advertising: Companies use Generative AI to create personalized marketing campaigns based on user data, preferences, and behaviors. By generating tailored content, businesses can engage their audience more effectively and increase conversion rates.
2. Entertainment and Media: Generative AI has been used to create music, movies, and even video games. For instance, AIVA Technologies uses AI to compose original music scores for films, video games, and commercials. This technology can help artists and creators generate new content more quickly, enhancing creativity and productivity.
3. Manufacturing and Design: Generative AI can help design and optimize products more efficiently by exploring thousands of possible design variations. For example, Autodesk's Dreamcatcher software uses Generative AI to create optimized designs based on specific constraints, such as weight, strength, and materials.
4. Healthcare and Medical Research: Generative AI analyzes vast amounts of medical data to identify patterns, make predictions, and generate insights. This technology can help researchers discover new drugs, optimize treatment plans, and improve patient outcomes.
5. Finance and Investment: Generative AI is applied to financial data analysis and investment decision-making. AI-powered platforms can analyze market trends, news, and other relevant data to make more informed decisions, manage risks, and optimize returns.

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Conclusion

Generative AI is revolutionizing industries across the board and has the potential to reshape the way businesses operate. By understanding the technology, its benefits, and implementation strategies, companies can harness the power of Generative AI to drive innovation, improve efficiency, and stay competitive in an ever-changing business landscape.

As you embark on your Generative AI journey, remember to identify specific opportunities, invest in the right team and resources, and collaborate with experienced partners. With the right approach, Generative AI can unlock unprecedented growth and success for your business.

In the era of digital dominance, business intelligence is the ace up your sleeve. Our AI experts, here at UST, aim to empower enterprises and accelerate innovation while keeping pace with a fast-changing world. Visit UST Alpha AI to explore tailored solutions for your businesses.