Meta, the company that runs Facebook and Instagram, announced that it made more money than people expected in the last three months. They made $39.07 billion, which is a lot of money. They also said that they think they will make between $38.5 billion and $41 billion in the next three months.

One of the reasons they made so much money is because they sold more advertisements on their websites and apps. Advertisements are the little pictures and videos that you see when you use Facebook or Instagram. Companies pay Meta to show their ads to people like you.

Meta is also spending a lot of money to make their AI, or artificial intelligence, better. AI is like a smart computer that can do things like talk to people or understand what they are saying. Meta wants to be a leader in AI, so they are spending money to make their AI smarter than other companies' AIs. Read from source...

- He claims that Meta is spending a lot on AI but does not provide any numbers or sources to support this claim.
- He says that Meta's AI push is driven by concerns about being late, but does not explain why being late would be so bad or how it would affect Meta's competitiveness or market share.
- He implies that Meta's AI investments are risky and may not pay off, but does not provide any evidence or analysis to back this up.
- He mentions that Meta is boosting spending on AI infrastructure, but does not compare this to spending by other tech companies or explain how this will impact Meta's overall financial performance.
- He cites Zuckerberg's reasoning for investing in AI infrastructure as preferring to risk building capacity before it is needed, rather than risk being too late, but does not explain why this is a better strategy or how it differs from Google's approach.
- He acknowledges that Meta's financials are benefiting from cost-cutting efforts, but does not explain how these efforts are being implemented or what impact they are having on the company's operations or bottom line.
- He concludes by suggesting that Meta's AI ambitions are unclear and unproven, but does not provide any concrete examples or data to support this claim.