We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself. Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts. Without further ado, generative AI as explained by generative AI.
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more. Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data. Generative AI has a wide range of applications, including:
Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
Disrupting Industries
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry. Generative AI has the potential to disrupt several industries, including:
Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy. In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information. In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future. on But fast forward to the end of last week, and SVB was shuttered by regulators after a panic-induced bank run. So, how exactly did this happen? We dig in below.
Road to a Bank Run
SVB and its customers generally thrived during the low interest rate era, but as rates rose, SVB found itself more exposed to risk than a typical bank. Even so, at the end of 2022, the bank’s balance sheet showed no cause for alarm.
As well, the bank was viewed positively in a number of places. Most Wall Street analyst ratings were overwhelmingly positive on the bank’s stock, and Forbes had just added the bank to its Financial All-Stars list. Outward signs of trouble emerged on Wednesday, March 8th, when SVB surprised investors with news that the bank needed to raise more than $2 billion to shore up its balance sheet. The reaction from prominent venture capitalists was not positive, with Coatue Management, Union Square Ventures, and Peter Thiel’s Founders Fund moving to limit exposure to the 40-year-old bank. The influence of these firms is believed to have added fuel to the fire, and a bank run ensued. Also influencing decision making was the fact that SVB had the highest percentage of uninsured domestic deposits of all big banks. These totaled nearly $152 billion, or about 97% of all deposits. By the end of the day, customers had tried to withdraw $42 billion in deposits.
What Triggered the SVB Collapse?
While the collapse of SVB took place over the course of 44 hours, its roots trace back to the early pandemic years. In 2021, U.S. venture capital-backed companies raised a record $330 billion—double the amount seen in 2020. At the time, interest rates were at rock-bottom levels to help buoy the economy. Matt Levine sums up the situation well: “When interest rates are low everywhere, a dollar in 20 years is about as good as a dollar today, so a startup whose business model is “we will lose money for a decade building artificial intelligence, and then rake in lots of money in the far future” sounds pretty good. When interest rates are higher, a dollar today is better than a dollar tomorrow, so investors want cash flows. When interest rates were low for a long time, and suddenly become high, all the money that was rushing to your customers is suddenly cut off.” Source: Pitchbook Why is this important? During this time, SVB received billions of dollars from these venture-backed clients. In one year alone, their deposits increased 100%. They took these funds and invested them in longer-term bonds. As a result, this created a dangerous trap as the company expected rates would remain low. During this time, SVB invested in bonds at the top of the market. As interest rates rose higher and bond prices declined, SVB started taking major losses on their long-term bond holdings.
Losses Fueling a Liquidity Crunch
When SVB reported its fourth quarter results in early 2023, Moody’s Investor Service, a credit rating agency took notice. In early March, it said that SVB was at high risk for a downgrade due to its significant unrealized losses. In response, SVB looked to sell $2 billion of its investments at a loss to help boost liquidity for its struggling balance sheet. Soon, more hedge funds and venture investors realized SVB could be on thin ice. Depositors withdrew funds in droves, spurring a liquidity squeeze and prompting California regulators and the FDIC to step in and shut down the bank.
What Happens Now?
While much of SVB’s activity was focused on the tech sector, the bank’s shocking collapse has rattled a financial sector that is already on edge.
The four biggest U.S. banks lost a combined $52 billion the day before the SVB collapse. On Friday, other banking stocks saw double-digit drops, including Signature Bank (-23%), First Republic (-15%), and Silvergate Capital (-11%).
Source: Morningstar Direct. *Represents March 9 data, trading halted on March 10.
When the dust settles, it’s hard to predict the ripple effects that will emerge from this dramatic event. For investors, the Secretary of the Treasury Janet Yellen announced confidence in the banking system remaining resilient, noting that regulators have the proper tools in response to the issue.
But others have seen trouble brewing as far back as 2020 (or earlier) when commercial banking assets were skyrocketing and banks were buying bonds when rates were low.
