5 Set-It-and-Forget-It Stocks to Buy According to Financial Media

3. Meta Platforms, Inc. (NASDAQ:META)

Number of Hedge Fund Holders: 234

Meta Platforms, Inc. (NASDAQ:META) is headquartered in California and owns and runs multiple social networking platforms and apps, including Facebook, Instagram, Threads, and more.

Of the 38 Wall Street analysts that covered Meta Platforms, Inc. (NASDAQ:META), 37 maintained a Buy rating on the stock. As of the December 22 market close, the average price target of $389.57 had an upside of 10.24%.

On December 20, Raymond James initiated coverage of Meta Platforms, Inc. (NASDAQ:META)’s stock with a Strong Buy rating and a $425 price target.

Meta Platforms, Inc. (NASDAQ:META) was mentioned in Blue Tower Asset Management’s third-quarter 2023 investor letter. Here is what it said:

“On February 24, 2023, Meta Platforms, Inc. (NASDAQ:META) released Llama, their LLM project, with the code being open-source but the training weights being kept proprietary. Nonetheless, within a week the training weights were leaked for the project. This release of the weights for 65 billion parameter model was a huge gift for open-source programmers to begin experimenting upon. Within weeks, other developers were creating innovations building on the model. There has been a race towards developing low-budget fine-tuning projects that can be trained for specific applications at the cost of a few hundred dollars in some cases. Some of these LLM projects can even be run on individual computers rather than data centers.

After the voluntary release of Llama’s architecture as open-source, the leak of the model weights ended up being a blessing in disguise for Meta. The innovation and improvements that followed were all built on Meta’s AI codebase. They were able to get these innovations without needing to pay any of the open-source developers for their efforts. This also demonstrates that the business advantage of the large tech companies is not in their models or AI codebase. Any innovations that the companies develop are unlikely to stay within the walls of the companies due to the mobility of researchers being poached between companies by recruiters. However, as these new model improvement technologies are made, the big tech companies have a scale advantage. They will be able to employ it into models that have more data, more compute budget, more parameters and therefore more intelligence in the resulting neural net.”