Meta Platforms Inc (NASDAQ: META) stock rose 0.89% (As on April 6, 11:57:14 AM UTC-4, Source: Google Finance) after an Argus analyst upgraded the company from Hold to Buy with a price target of $270.00. Argus Research analyst Joseph Bonner upgraded by writing that “the cost cuts do demonstrate prudence by management and should improve profitability,” even though Meta continues to face challenges related to the advertising market and Apple Inc.’s privacy-related changes. Meta is in the process of making “some of the deepest cost cuts in the tech sector,” in Bonner’s view, as the company has announced two sizable rounds of layoffs. Beyond Twitter, which slashed more than half its staff as Elon Musk took over the company, Meta’s headcount reduction is “significantly greater than at most peers.” Besides the cost cuts, Meta has other factors working in its favor as well, Bonner wrote, especially as some of its competitors experience problems. TikTok faces pushback from the U.S. government, while Twitter “has made a series of erratic strategic moves” under Musk’s leadership “that have hobbled the company.”

“We believe that challenges at TikTok and Twitter could benefit Meta, which continues to add users to its platform,” Bonner wrote, noting that “an outright ban of TikTok is by no means certain, any regulatory trouble for this disruptive upstart would be a positive for Meta.” Meta “is almost entirely dependent on advertising revenue,” Bonner noted, and like other social-media players, it’s tried to diversify a bit. One new initiative is a subscription program that lets creators and others verify their identities.

On the other hand, the company is releasing both its new Segment Anything Model, known as “SAM,” and a Segment Anything 1-Billion mask dataset, called SA-1B, to the research community. The intention is to encourage further research into the foundation models required to make computer vision. These are the problems that Meta says it can overcome with SAM and SA-1B, which is the largest ever segmentation dataset to be released. The SA-1B dataset is being made available for research purposes, while SAM is being released under a permissive open license. The Segment Anything project, as the initiative is known, is all about helping researchers by reducing the need for task-specific modeling expertise, training compute and custom data annotation. SAM was built to serve as a foundational model for image segmentation.