A company reports 30% revenue growth. Net income is rising. Demand appears strong. Yet operating cash flow is falling. That combination may look contradictory, but it can happen when growth requires a business to put increasing amounts of cash into receivables and inventory before that cash returns. This is the working capital trap investors can
When a company reports earnings, investors often focus on one number: earnings per share, or EPS. A higher EPS sounds like good news. If EPS increased from $5 to $6, it is easy to assume that the company became more profitable. But that is not always what happened. A company can increase EPS even when
For much of the AI boom, the investment story has centered on GPUs. That makes sense. Advanced AI models require enormous amounts of computing power, and GPUs have become one of the most visible bottlenecks in the AI infrastructure buildout. But as more GPUs enter data centers, another constraint is becoming increasingly important: electricity. The
Alphabet reported strong headline numbers.But the figure that caught my attention was $44.9 billion. The connection between Google earnings and semiconductor stocks is becoming harder to ignore as Alphabet spends more heavily on AI infrastructure. According to Alphabet’s Q2 2026 earnings release, the company reported $119.8 billion in second-quarter 2026 revenue, while Google Cloud revenue
Every AI prompt feels almost weightless. A question is typed, and an answer appears within seconds. From the user’s perspective, artificial intelligence looks like pure software. Behind that simple interaction, however, is a physical system of GPUs, servers, networking equipment, cooling systems, backup power, and data centers connected to the electricity grid. This is why
AI vs IT is often framed as a comparison between two generations of computing technology. Both eras are built around software, data, semiconductors, and global networks. The internet connected people and information, while artificial intelligence adds a new layer capable of generating text, images, code, analysis, and decisions. But similar technologies do not always produce
