inference
Enhancing AI Inference: Advanced Techniques and Best Practices
When it comes to real-time AI-driven applications like self-driving cars or healthcare monitoring, even an extra second to process an input could have serious consequences. Real-time AI applications require reliable GPUs and processing power, which has been very expensive and cost-prohibitive for many applications – until now. By adopting an optimizing inference process, businesses can…
LLMs Can Now Reason in Parallel: UC Berkeley and UCSF Researchers Introduce Adaptive Parallel Reasoning to Scale Inference Efficiently Without Exceeding Context Windows
Large language models (LLMs) have made significant strides in reasoning capabilities, exemplified by breakthrough systems like OpenAI o1 and DeepSeekR1, which utilize test-time compute for search and reinforcement learning to optimize performance. Despite this progress, current methodologies face critical challenges that impede their effectiveness. Serialized chain-of-thought approaches generate excessively long output sequences, increasing latency and…
DeepSeek jolts AI industry: Why AI’s next leap may not come from more data, but more compute at inference
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The AI landscape continues to evolve at a rapid pace, with recent developments challenging established paradigms. Early in 2025, Chinese AI lab DeepSeek unveiled a new model that sent shockwaves through the AI industry and resulted…