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Benchmark Raises $2B Growth Fund, Breaks 20-Year Tradition
The legendary abandons its more than 20 year tradition of keeping its funds to about $425 million.
Convective Capital Raises $85M for Disaster Resilience
After launching to invest in fire tech, Convective is broadening its mandate to disaster resilience.
Meridian Ventures Launches $35M Fund for MBA-Deferred Founders
This new fund will back founders building enterprise technology in the United States. Meridian is agnostic, co-founder Devon Gethers said, noting that the firm has already invested in companies in fintech, logistics, healthcare, and of course, AI.
Coatue's New Venture: AI Data Centers Near Power Sources
Coatue, one of the biggest names in venture capital, has a new venture that is reportedly buying land near large power sources.
Amazon's AWS Surges, Drives Massive Cloud Spending
The e-commerce giant is making more money than expected from AWS but it's also spending a lot, and will continue to do so in the near term, its chief executive said.
Nvidia Exec: AI Currently More Expensive Than Human Workers
Nvidia’s vice president of applied deep learning, Bryan Catanzaro, recently stated that for his team, “the cost of compute is far beyond the costs of the employees,” highlighting that AI is currently more expensive than human workers. This challenges the narrative that widespread tech layoffs (including Meta’s planned cut of \~8,000 jobs and Microsoft’s voluntary buyouts) signal an imminent replacement of humans by AI. An MIT study from 2024 supports this, finding that AI automation is economically viable in only 23% of roles where vision is central, and cheaper for humans in the remaining 77%. Despite heavy AI investment—Big Tech has announced $740 billion in capital expenditures so far this year, a 69% increase from 2025—there is still no clear evidence of broad productivity gains or job displacement from AI. AI spending is driving up costs, with some executives like Uber’s CTO saying their budgets have already been “blown away.” Experts describe the situation as a short-term mismatch: high hardware, energy, and inference costs make AI less efficient than humans right now, though future improvements in infrastructure, model efficiency, and pricing models could tip the balance toward greater economic viability in the coming years.