For more than three decades, modern CPUs have relied on speculative execution to keep pipelines full. When it emerged in the 1990s, speculation was hailed as a breakthrough — just as pipelining and superscalar execution had been in earlier decades. Each marked a generational leap in microarchitecture. By predicting the outcomes of branches and memory loads, processors could avoid stalls and keep execution units busy. But this architectural shift came at a cost: Wasted energy when predictions failed, increased complexity and vulnerabilities such as Spectre and Meltdown. These challenges set the stage for an alternative: A deterministic, time-based execution model. As David Patterson observed in 1980, “A RISC potentially gains in speed merely from a simpler design.” Patterson’s prin [...]
It's refreshing when a leading AI company states the obvious. In a detailed post on hardening ChatGPT Atlas against prompt injection, OpenAI acknowledged what security practitioners have known fo [...]
It's not just Google's Gemini 3, Nano Banana Pro, and Anthropic's Claude Opus 4.5 we have to be thankful for this year around the Thanksgiving holiday here in the U.S.No, today the Germ [...]
“When you get a demo and something works 90% of the time, that’s just the first nine.” — Andrej KarpathyThe “March of Nines” frames a common production reality: You can reach the first 90% [...]
The buzzed-about but still stealthy New York City startup Augmented Intelligence Inc (AUI), which seeks to go beyond the popular "transformer" architecture used by most of today's LLMs [...]
As generative AI matures from a novelty into a workplace staple, a new friction point has emerged: the "shadow AI" or "Bring Your Own AI (BYOAI)" crisis. Much like the unsanctioned [...]