5 Stocks That Will Make You Rich in 5 Years According to ChatGPT

4. NVIDIA Corp (NASDAQ:NVDA)

Number of Hedge Fund Investors: 180

Gaming and AI. These are the two growth catalysts for NVIDIA Corp (NASDAQ:NVDA) that make it a suitable stock to buy and hold to get rich in the next five years, according to ChatGPT.

NVIDIA Corp (NASDAQ:NVDA) shares have skyrocketed by 236% in 2023 through December 21.

Dawn Hudson, a director and 10% owner of NVIDIA Corp (NASDAQ:NVDA) shares, sold 1,000 shares on Dec. 15 for a price of $494.525, worth $492,525.

As of the end of the third quarter of 2023, 180 hedge funds tracked by Insider Monkey had stakes in NVIDIA Corp (NASDAQ:NVDA).

Blue Tower Asset Management made the following comment about NVIDIA Corporation (NASDAQ:NVDA) in its Q3 2023 investor letter:

“In addition to the use of larger datasets, the training speed of AI models has increased dramatically. NVIDIA Corporation (NASDAQ:NVDA)’s stock almost tripled in the first 3 quarters of this year with a 197% gain, and a large reason for this is the huge role they have played in recent AI improvements. Nvidia’s single GPU AI training speed performance has increased by a dramatic 1000x in 10 years with only 2.5x coming from Moore’s Law3 driven increases in chip density. Besides better chip manufacturing, there were three other improvement factors at play: simplifications in number representation for the weights of the neural networks, more complex mathematical instructions for reducing the computational overhead involved in mathematical calculations, and increased neuron sparsity (in neural networks, some neurons are useless and can be pruned from the network without reducing performance significantly). In addition to these single GPU improvements, Nvidia also made improvements in data center scale architecture that allows groups of GPUs to work more efficiently together.

It is noteworthy that the vast majority of the improvement came from hardware architectural and software data improvements, rather than transition density. These improvements were likely the low-hanging fruit of training speed improvements as researchers will eventually converge on an ideal architecture. The simplification of going from 32-bit to 8-bit floating point numbers for measuring weights is a one-time gain that can’t be repeated again. I expect the rate of improvement to slow down over the next ten years and eventually approach the levels of Moore’s Law improvements in chip efficiency. The historical trend for computer hardware is for it to eventually be commoditized, and I believe this will eventually occur for Nvidia’s GPUs as well.”