What is Generative AI and why it is so popular?
What is Generative AI?
Generative artificial intelligence?(AI) is a subset of artificial intelligence that holds the ability to generate many different types of content, including but not limited to text, images, audio and synthetic data. Rather than simply analyzing or classifying data, generative AI uses patterns in existing data to create entirely new content.
The most powerful generative AI algorithms are built on top of foundation models that are trained on a vast quantity of data to identify underlying patterns for a wide range of tasks. For example, GPT-3, or Generative Pretrained Transformer 3, is a model trained on large volumes of text, can be adapted for answering questions, summarize text and language translation and carry out many more tasks.
Why is it a hot topic?
The term generative AI created a huge buzz and became a hot topic because of the popularity of generative AI models, particularly, OpenAI's?ChatGPT. ChatGPT is an AI chatbot with natural language processing (NLP) that enables human-like conversations to complete various tasks. ChatGPT became extremely popular in no time, accumulating over one million users a week after its launch. Many companies witnessed this success and started trying their hands at building generative AI models to harness the benefits of this technology.
The statistics around the current use of generative AI and how it will look by the end of this decade is mind-blowing. Over 100 million people are expected to start making use of generative AI by 2025. This number and buzz around generative AI is not going to slow down or end anytime soon. It is likely to grow further with more & more companies entering into this space, identifying new use cases and creating generative AI systems designed for specific verticals. The major benefits that companies see in generative AI making it a hot favourite topic include expansion of workforce productivity, emergence of new business models and personalization of customer experience among others.
How does Generative AI work?
Generative AI?technology typically uses?large language models (LLMs), which are powered by?neural networks. These LLMs are trained on a huge quantity of data (e.g., text, images, audios, videos etc.) to identify patterns and structured within the existing data that they then follow to generate new or original content. The training process for a generative model involves feeding it a large dataset of images, text, audio, or videos. The model then analyzes the patterns, structures and relationships within the input data to understand the underlying rules governing the content. Then, it generates new data by sampling from a probability distribution it has learned and continuously adjusts its parameters to maximize the probability of generating accurate output.
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As an example, popular?chatbots?like?ChatGPT, based on GPT-3, has been trained on massive amounts of data it is fed to make predictions and generate answers in future scenarios and has “learned” what words are likely to appear, in what order, in each context. ChatGPT can even generate an essay from a basic text request.
Generative AI models have the ability to leverage different learning approaches, including unsupervised or semi-supervised learning for training. This enables leveraging a large amount of unlabeled/unstructured data to create foundation model which are then used as a base for Generative AI systems to be able to perform multiple tasks.
Conclusion
On the flip side, generative AI tools are not fully accurate in certain cases. These have good success rate because of the large amount of data they are trained on, but they can and do go wrong. As an example, ChatGPT is prone to “hallucinations,” or output that deviates from its training data. There is another risk of plagiarism and copyright infringement, as these tools often repeat or paraphrase data sourced from elsewhere on the Internet and therefore pose data security risks.
Despite these shortcomings, generative AI has been one of the most important technological development of the last several years. It will be a game changer for business as it has the potential to redefine the way organizations work. Given the pace at which generative AI is advancing, business leaders in every industry should consider adoption of generative AI into their processes and systems as early as possibly with an aim to innovate and grow. Companies that don’t embrace the disruptive power of generative AI will find themselves at a major disadvantage in time to come. It remains critical, though, that generative AI is used responsibly and governed in the most rightful manner to prevent it from becoming disruptive.
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