Since its release, the artificial intelligence chatbot known as ChatGPT has swept the globe.

Good morning tech fam, here are some quick tech updates for you to catch on to!

What's New Today: Microsoft recently laid off 10,000 workers, including Indian workers in the United States.

Fast-Track Insights: After a tumultuous year marked by numerous high-profile mishaps, the digital asset market is currently experiencing a boom.

Andreas Braun, Chief Technology Officer at Microsoft Germany, disclosed at an event that Microsoft will launch GPT 4 this week with AI video capabilities. Since its release at the end of last year, the artificial intelligence chatbot known as ChatGPT has swept the globe. ChatGPT has received a lot of praise, even though some users haven't liked the ethical considerations. This is despite the fact that ChatGPT has helped researchers make diet plans and help researchers write abstracts for their research papers. However, Microsoft will still release a new, more robust version of ChatGPT.

Business intelligence (BI) and Artificial intelligence (AI) are advancing daily, allowing organizations to employ Machine learning algorithms to spot innovative data trends and swiftly decide how to present them in real-time. But how AI and ML are revolutionizing Business Intelligence? Businesses and other organizations that are undergoing a digital transformation are confronted with a mounting data tsunami that is both extremely valuable and becoming more and more difficult to gather, handle, and analyze. To handle the enormous amount of data being collected, mine it for insights, and act on those insights when they are discovered, new tools and approaches are required. Data is king in the contemporary corporate world.

Data is used by businesses of all sizes and in all sectors to help them make decisions that will ultimately lead to success. Unfortunately, it can be difficult to glean significant insights and analyses from the vast amount of data that is already available. Artificial intelligence (AI) and machine learning (ML) can assist firms in sorting through the data noise and obtaining useful insights in this situation. Read more

After digital-asset giant Circle Internet Financial Corp., one of the largest issuers of the widely used tokens known for their perceived safety, revealed it had $3.3 billion of reserves with the bank, SVB's failure triggered a knock-on effect in the crucial market for stablecoins. The news caused USD Coin, Circle's token, to fall below its intended one-to-one peg with the dollar, shocking the market.

Over-the-counter trading desks, hedge funds, and other investors who wanted to get into crypto at the beginning had to go through expensive, time-consuming, and difficult maneuvers just to move money between digital assets and banks because the two types of infrastructure weren't connected. If an investor wanted to send money from their bank account to an exchange, traditional banking methods could take days, making it often too late to take advantage of the latest market movement. Because banks were closed during crypto trades, it was impossible to move funds quickly or on weekends.