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Alphabet shares tumbles on mixed earnings results, but Goldman sees 25% upside ahead on AI strength

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Shares of Alphabet, which includes Google, fell on Wednesday as investors digested second-quarter results that beat profit estimates but fell short in other key areas, Business Insider reports, UNN writes.

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The mixed results, as indicated, led to a 5% drop in shares in afternoon trading on Wednesday, but Goldman Sachs analysts say they remain optimistic about the company's artificial intelligence capabilities.

Last quarter, the company's earnings per share amounted to $1.89 against estimates of $1.85. Nevertheless, YouTube's advertising revenues were lower than Wall Street expected, amounting to $8.66 billion against estimates of $8.95 billion. Capital expenditures for the quarter were also higher than expected, reaching $13.2 billion.

Goldman Sachs was upbeat in its analysis, raising its target price on Alphabet from $211 to $217 after the company released its earnings report. This is a 25% increase from Wednesday afternoon's price of $172.80.

Goldman says that its optimism is largely due to Alphabet's artificial intelligence capabilities.

"While we can't refute the ongoing investor debate about the future of search, we still believe Alphabet is positioned to be the first company to pioneer artificial intelligence," the analysts said, adding that the company has existing applications into which it can further integrate its AI tools.

The company's executives on Tuesday were quoted as saying that the tech giant's ambitions in artificial intelligence will bring long-term returns.

"I think it will become an important factor over time," said Alphabet CEO Sundar Pichai regarding the integration of AI into its cloud division.

Pichai also said that the company has "over 2 million developers playing with these things.

Goldman analysts are not focused on the potentially long timeline for AI gains, but say they expect investors to continue to focus on future search, operating margin results, and long-term investments in data centers and technical infrastructure to drive AI, the publication notes.

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