Business and AI

  Before making predictions about stock price movements, an expert will consider various economic indicators, market sentiment, past performance and trading volume. An effective generative AI tool must take into account all these important factors before recommending a stock for investment. These AI-based predictive models are built on historical data, but should also be equipped to conduct sentiment analysis based on current market conditions – one of the most essential elements in share market trading. These GenAI models learn from historical data fed into them to recognise the complex patterns such as market trends, and other factors to establish their correlation with the price movements. They also perform sentiment analysis by extracting important information from news articles and social media posts for better forecast. The models, thus trained on the training data (historical data) and enhanced with sentiment analysis, can show whether a stock will move upwards or will go ...

Data science with artificial intelligence (AI) as its backbone, which was just an option, has turned out to be a crucial support system for financial services industry. Be it decision making for granting loans or issuing credit cards to a prospective customer, ensuring cyber security, making recommendations or offering advice on where to invest, predicting market, or understanding the sentiments of customers, data science is everywhere. Data science is an integral part of almost every department in financial industry. The organizations, if there are any, that choose not to invest in AI are left far behind in the competition with the likelihood of going under. Well, this may sound overstatement or a bit of exaggeration, nonetheless, it does make a point that how important it is for a financial organization to consider data science as its significant ally. When it comes to granting loans or issuing credit cards to prospective customers, banks usually, in traditional approach, follow ...

Generative AI has been making buzz in almost every industry and there is no surprise that it has already made its foray into marketing and branding, to be specific, in digital marketing industry. It is not unknown what generative AI can do. It generates original content without any plagiarism or copyright infringement. Its capability is not limited to text, but it can generate images, music, and much more. Digital marketing is a content driven industry and it heavily relies on high volume of text, visuals and background scores for different marketing activities. Therefore, scalability has always been a matter of concern considering high competition and ever-changing dynamics of digital space. To make the matter worse, in the recent past, the business world has witnessed a constant and drastic change in consumer behaviour which keeps shifting from one extreme to another. Social media consumes the major portion of time spent by the target audience and companies or marketing and brand...

No doubt, generative AI or generative artificial intelligence has become a new standard in today’s business world. It is taking almost every industry by storm. Be it IT, software development, healthcare, finance, art, writing, fashion, gaming or marketing, generative AI has a significant role to play in almost every industry. But how does it work? Generative AI finds its roots in advance level of data science which uses algorithms such as deep learning. Deep learning is nothing but multi-layered neural network also known as deep neural network. Some of the examples of such algorithms are recurrent neural network (RNN) and convolution neural network (CNN). These deep learning algorithms are used by some of the sophisticated and high performing computers and cloud networks to train models on a large amount of historical data, also known as training data. These trained models are then used to produce desired output. The trained models then predict or rather generate content which are ...