Why measuring tokens per second, NCCL behavior, and communication exposure together tells a much more useful story than GPU utilization alone. The easiest way to misunderstand distributed AI performan
“Don’t ask the model to guess, design the system to retrieve and compute what’s true.” That idea sits at the core of how modern AI should be applied in financial systems. In equity research, speed mat
By Anton R Gordon
By Anton R Gordon Understanding both hardware efficiency and answer quality is essential for building high-performance, trustworthy AI systems. CUDA workloads rely heavily on GPU utilization and kernel design, while retrieval-augmented generation (RA...
Training large language models is expensive. Deploying them efficiently is even harder. As models like Llama 3, Mixtral, or Nemotron grow in size, the ability to optimize inference and training workflows determines whether they can be realistically u...
Real-time decisioning in financial services—especially for macro events like yield-curve inversions and fast FX exposures—demands an architecture that combines ultra-low latency market data ingest, high-throughput model inference, robust risk control...
In the evolving world of artificial intelligence and cloud computing, Anton R Gordon, an accomplished AI Architect and Cloud Specialist, continues to pioneer frameworks that make AI deployment faster, scalable, and cost-efficient. One of his most inf...