Generative AI vs Predictive AI: The power of Artificial Intelligence

In our last post we talked about what Artificial Intelligence is and went into the study of Generative AI, what it is and how it works. Now let's understand the differences between Generative AI vs Predictive AI. But, before we see the differences, let's understand a little more about Predictive AI.

What is Predictive AI?

Predictive AI is the ability to use statistical analysis to identify patterns, anticipate behaviors, and predict future events. We are talking about a field of statistics that has been used for a long time to make predictions of the future, as the use of Predictive AI makes analysis much faster and theoretically more accurate through Machine Learning and access to large amounts of data. .

It is not possible to guarantee that predictions are correct, but Predictive AI can help companies prepare for the future and most importantly, personalize experiences for their consumers.

Predictive AI is another field of study in Artificial Intelligence, as is Generative AI. In Predictive AI we are talking about a set of skills that computers can have and that imitate human cognition. We still remain in the field of Weak AI or Limited Artificial Intelligence at the Limited Memory level (Read my previous post to better understand the levels of Artificial Intelligence) .

How does Predictive AI work?

Big Data - The more data we have, the more accurate analysis we generally have. Predictive AI requires access to large amounts of data, we can even talk about Big Data here. The more data we have, the better the predictions will be. A practical example: An opinion poll needs a minimum number of people interviewed to have a certain level of confidence and provide a certain prediction. Using Predictive AI we can take not just one survey, but thousands of opinion polls carried out in the past to make predictions about public opinion.

Machine Learning - a subset of AI, a method for training a computer program to identify data without any human intervention. In Predictive AI, Machine Learning is applied to Big Data so that it can quickly process and find existing patterns without supervision.

Predictive AI can analyze hundreds or thousands of factors to identify patterns that indicate possible events in the future.

Some use cases of Predictive AI

Having an idea of what may come in the future can be a great advantage for business, even if predictions are not accurate. The application of Predictive AI is vast and comprehensive, but here are some possible ideas:

• Inventory management Predictive AI can help identify inventory demand within the company through historical consumption analysis.

• Supply chain management It's not just about demanding the purchase in the correct way according to consumer demand. But with Predictive AI we can determine possible periods of problems, such as congestion on the roads and heavy periods of rain that will affect deliveries.

• User Experience (UX) One of the main applications of artificial intelligence. Predictive AI can analyze a customer's entire history, behavior and activities to help predict their next steps. Based on this, Predictive AI can even help predict what types of content or products customers may be interested in, optimizing marketing campaigns.

• Financial Forecasting Predictive AI improves forecasting by leveraging broader financial information data with other business data to anticipate market trends and investment opportunities.

• Fraud Predictive AI has been widely used by Banks and Anti-Fraud Platforms in e-commerce to detect potential fraudulent activities. Behaviors such as unusual login locations or suspicious IP addresses are analyzed in real time.

Now that we understand more about Predictive AI, let's analyze Generative AI vs Predictive AI.

Generative AI focuses on content creation, bringing new ideas and forms to life. It is the creative force in the world of artificial intelligence. Now Predictive AI is about predicting the future and avoiding adverse outcomes through data analysis.

Within business, both forms of AI have significant implications. Generative AI, as we have already seen, is opening up new possibilities for creativity, allowing people together with machines to create. Predictive AI is transforming the way we make decisions within companies, allowing us to predict the future with an accuracy that has increasingly increased.

Talking about challenges and limitations, we see both Generative AI and Predictive AI need large volumes of data and the difficulty in interpreting their results, often the data is not properly structured. In the case of Generative AI, we have some ethical issues, as we have already seen the creation of several deepfakes or Fake News, which is why we are studying a way for everything generated via AI to have a “certificate” or “seal” to inform that it work was generated by artificial intelligence.

In the case of Predictive AI, the quality of the data affects even more as it becomes more difficult and complex to understand the patterns on an unstructured basis to be able to predict something.

Although Generative AI and Predictive AI play different roles, the future will unite these boundaries, combining the use of both. More advanced artificial intelligence systems will be able to combine the two approaches, thus generating an integration between predictive algorithms for recognizing patterns and trends with generative algorithms to create new content based on what can be most successful.

The advances in Artificial Intelligence are great, to give you an idea, ChatGPT 3.5 is 10 times better than version 3.0 and consequently 4.0 is 10 times better than 3.5. As evolution continues, both Generative AI and Predictive AI will increasingly play pivotal roles in reshaping our future and that of the industry. We are living in the Artificial Intelligence Revolution.

"The Artificial Intelligence Revolution will be bigger than the creation of the Internet" Jeetu Patel - Vice President of Cisco at the Cisco Live 2023 event

By integrating predictive and generative capabilities, we will have advanced artificial intelligence systems that are ready to deliver value to companies and society as a whole. Both intelligences are transforming the business world and challenging the logic of many processes, reinventing people, professions and businesses. It is important to understand both, understand their essences and invest in training to seek to use AI to boost positively.