2 Minute Read - Genrative AI With Simon Bliss
As technology people, we find customers, and our family expect us to be able to explain the newest cutting-edge technology at the drop of a hat. Often, we feel like we understand it, but could we explain it?
So, if you are asked, what is Generative AI (you might be!), how could you answer? Here is your 2-minute read.
Generative AI is a particular field of artificial intelligence focused on creating new data, such as text, images, or even music. It is different from traditional AI, which typically makes predictions based on existing data.
Generative AI isn't entirely new. It began over 100 years ago with the Markov process (enough material for a future 2-minute read). This theory was used more recently to provide next-word prediction tools.
Today, generative AI is much more sophisticated. It is built on large, complex models with billions of parameters and is trained on vast amounts of data. This allows it to generate highly realistic and contextually relevant output.
The applications for generative AI are wide and diverse. The general opinion is, that there is no industry, vertical, company, or organisation where generative AI can’t add value. But it does have its limitations and its challenges. It is not suitable for all tasks. It is less effective than traditional methods for analysing and making predictions on structured data. It also raises concerns about job losses, bias, and copyright issues. Think Hollywood strikes and Elon Musk saying ‘it will take everyone’s job’ etc.
In summary, generative AI, with its ability to create brand new stuff, represents a significant leap in AI's evolution. It's not just about understanding or processing data or making predictions based on what happened in the past. It has become more about contributing original, creative output. AI is now our office workmate and a collaborator in our creative and analytical activities.
Acknowledgments: MIT News
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