According to Visible Alpha consensus, Amazon's total revenue for North America of $113.8 billion expected for Q2 edged upward since the February 2026 release. The International operating profit margin range is more extreme at 1.7% to 13.4%, with consensus settling at 4.2%. Given the current backdrop and increasing energy and chip prices, there are questions about whether the Company will raise its full year CapEx guidance.
Artificial intelligence has become the biggest growth story in global technology, but this week's earnings from Alphabet and Tesla have reminded investors that building the infrastructure behind that boom is becoming increasingly expensive. And, investors are not okay with this.
Amazon's explosive cash-flow growth has compressed its valuation multiple, potentially undervaluing the stock. Customer spending on Amazon Bedrock, an AI-powered application and agent buidling tool, grew 170% last quarter.
If you've been an Amazon Prime member at some point in the past several years, you have until Monday to file a claim to be included in a $2.5 billion settlement.
Amazon is closing its San Francisco AGI site as part of the layoffs it made this week in its artificial general intelligence organization, but said its frontier model research lab will continue.
CNBC's Seema Mody and MacKenzie Sigalos report on trends regarding AI's capex concerns.
Magnificent Seven stocks lost $787 billion in a single day as Alphabet and Tesla earnings revealed massive AI infrastructure capex that spooked investors.
The AI buildout is eroding the free cash flow and increasing balance-sheet risk at hyperscalers like Alphabet and Microsoft, warned Moody's Ratings. In a research note released this week, Moody's highlighted stock sales and off-balance-sheet moves that "threaten credit quality.
I keep hitting the buy button on Amazon (NASDAQ:AMZN | AMZN Price Prediction) for a reason that barely makes the headlines: the custom silicon business sitting inside AWS.
Artificial intelligence (AI) infrastructure is hitting a physical wall. As large language models grow exponentially in size, the legacy approach of throwing large, monolithic graphics processing units at the problem breaks down during the inference phase.