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SpaceX, Reflection AI Sign $150M Monthly Compute Deal
Reflection AI will pay $150 million a month beginning July 1, 2026 through 2029 for immediate access to Nvidia's latest GB300 AI chips and supporting hardware across SpaceX's Colossus 2 data center near Memphis, Tennessee.
Groq Aims to Raise $650M for AI Inference Focus After Nvidia Deal
Chipmaker Groq is looking to raise $650 million in internal funding as it pivots from hardware to focus more on AI inference, the process of refining the way AI models respond to prompted requests, per Axios.
AionOS: Self-Healing Microkernel in Zig for Real Hardware
AionOS: A Self Healing Microkernel Powered by Zig for Actual Hardware AionOS stands out as a groundbreaking self healing microkernel, uniquely developed in the …
Cerebras Systems: The AI Chip Startup That Almost Failed
Cerebras Systems was 2026's biggest tech IPO so far. But years ago, it burned through hundreds of millions working on a chip many believed impossible.
Cerebras IPO: Benchmark's Billion-Dollar Bet on AI Hardware
Benchmark almost never backs hardware startups. So Eric Vishria dragged his feet 10 years ago before agreeing to hear Cerebras' pitch.
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.
AMDXDNA Driver Enhances Ryzen AI Multi-User Fairness
AMDXDNA Driver Enhances Ryzen AI Multi User Fairness The AMDXDNA driver is designed to improve the performance and efficiency of AMD Ryzen processors, particula…