What are the risks of generative AI? The risks associated with generative AI are significant and rapidly evolving. A wide array of threat actors have already used the technology to create “deep fakes” or copies of products, and generate artifacts to support increasingly complex scams. ...
Figure 1: The three requirements of a successful generative AI model. How to Develop Generative AI Models? There are multiple types of generative models, and combining the positive attributes of each results in the ability to create even more powerful models. ...
Of course, the ability to classify and predict data accurately is a critical element to successful generative AI: The product is only as good as the data it has to work with. “AI is only as good as the data you give it and you have to make sure that the datasets are representative....
So, while generative AI has the “sizzle” here in mid-2023, it’s still only a part of the whole AI “steak.” But every action has an equal and opposite reaction. So, along with its remarkable productivity prospects, generative AI brings new potential business risks—such as inaccuracy,...
Generative AI is a technology to produce various types of content. Learn about what is generative AI, how it works, and some of the most exciting applications of generative AI today.
. Modern AI is no longer confined to the realm of speculation; widely available and increasingly powerful, automation and AI are changing the way that people across all walks of life approach tasks, get information, and share ideas. At the forefront of this revolution is generative AI....
What’s The Future Of Generative AI? The future of GenAI is fascinating, and it’s full of possibilities: Simulations and Made-Up Data: GenAI can create computer simulations and made-up data that are very realistic. This is useful when real data is hard to get. For example, it can help...
Generative AI exposes the gaps in the data management practices within the organization. You can compare this to the concept of security by obscurity - so far even if the data management practices were not mature, it was difficult to detect/identify it. Now with generative AI s...
What are some Examples of generative AI? Let’s look at an example, traditional AI models have been defined around predicting an outcome. Traditional AI is deterministic; it has a set of rules that are defined and it will tell you the outcome of something based on those rules. Traditional ...
Generative AI systems are more flexible because they rely on machine learning, which doesn’t require explicit programming. Instead, humans give computers access to large amounts of data. The machines train themselves to recognise patterns in that data and, most importantly, to draw conclusions from...