Nvidia Earnings Seen as Next Big AI Stock Catalyst

S&P 500 earnings are expected to increase by +24% from the same period last year in the third quarter, the 8th straight quarter of double-digit earnings growth for the index, according to Zacks Investment Research. Earnings are expected to be above the year-earlier level for 14 of the 16 Zacks sectors, with 5 sectors expected to enjoy double-digit growth: Aerospace up +159.3%, Energy up +111.9%, Tech up +41.9%, Basic Materials up +31.2%, and Transportation up +15.1%. The Conglomerates sector is the only one expected to have lower earnings in Q3 relative to the same period last year, down 35.4%, while Consumer Staples earnings are expected to be flat. Excluding the Energy sector, Q3 earnings growth for the S&P 500 drops to +20% from +24%, and excluding the Tech sector, growth for the rest of the index drops to +14.4%. Nvidia's Q3 earnings are expected to increase +90% year-over-year on +91.2% higher revenues, while Micron's year-over-year earnings and revenue growth rates are expected to be +938% and +348.6%, respectively, and Tech sector earnings growth gets cut by slightly more than half once contributions from Nvidia and Micron are excluded. The Q3 earnings season will get the spotlight when the big banks report on October 13th, but the reporting cycle actually got underway with the September 10th quarterly releases from Oracle and Adobe, followed by homebuilder Lennar as the third S&P 500 member to report such Q3 results, with an additional six index members on deck this week including Costco, AutoZone and Darden. Total Q3 earnings for the three S&P 500 members that have reported results already are up +22.6% from the same period last year on +14.9% higher revenues, with 33.3% beating EPS estimates and 66.7% besting revenue estimates.

Humanoid robots are making meaningful progress in autonomy, dexterity and repetitive real-world tasks, but widespread commercial deployment remains a work in progress, according to a report published Wednesday by Citrini Research. After a week meeting robotics labs, engineers and investors across the San Francisco Bay Area, the firm found most humanoid robots remain in development, training and tele-operated demonstrations, with real-world deployments closer to pilots than clear return-on-investment opportunities. The report examined whether robotics is approaching its own ChatGPT moment and highlighted advances from GeneralistAI and Skild AI, along with Figure AI's demonstration involving 250,000 packages, suggesting the field may advance through a mosaic of signals rather than one defining breakthrough. Basic humanoid locomotion is effectively a solved problem while complex dexterity remains more difficult, and simple repetitive tasks are already trainable. Investment in the broader robotics infrastructure is keeping pace: Tesla Inc has been preparing production lines for Optimus, XPeng Inc has launched an automated production line for its IRON humanoid robot, and Figure AI is securing access to up to 100,000 Vera Rubin GPUs from NVIDIA Corp to train the models powering its humanoid robots. The report concluded robotic autonomy is developing along a curve rather than arriving through one decisive breakthrough, with broad generalizability remaining the longer-term goal.

Nvidia CEO Jensen Huang said the company expects to sell roughly twice as many chips next year as it does this year, calling it one of his strongest signals yet that AI demand remains far from exhausted. Speaking to reporters Thursday at a summit in Scotland with King Charles III, Huang said the reason is AI's contribution to different industries and economies, and that people in almost every country Nvidia operates in want to invest in AI. The forecast adds to Nvidia's increasingly aggressive outlook: the company recently said it expects roughly 70% growth in the fiscal year ending January 2028, which would put annual revenue around $673 billion. Nvidia does not disclose total chip unit shipments, making Huang's volume forecast difficult to translate directly into revenue, though its most important products include data-center GPUs, particularly Blackwell and next-generation Rubin systems; Huang said last fall that Nvidia had shipped about 6 million Blackwell GPUs over four quarters. The comments come as investors debate whether hyperscaler spending and model-training demand can keep growing at the breakneck pace seen during the first phase of the AI buildout, with the key question being not simply whether Nvidia can double chip volumes but what that mix looks like, since higher shipments of premium Blackwell and Rubin systems could support enormous revenue growth while greater unit volume at lower average selling prices would produce a different margin outcome.