Guide to freezing layers in AI models
Master the art of freezing layers in AI models to optimize transfer learning, save computational resources, and achieve faster training with better results.
Master the art of freezing layers in AI models to optimize transfer learning, save computational resources, and achieve faster training with better results.
Welcome to the series of articles on the secrets of time series modeling. Today’s edition features the nested cross-validation — a lesser-known technique that mitigates some of… Read More »Secrets of time series modeling: Nested cross-validation
Intuition alone is no longer enough for effective leadership in the modern business world. Business leaders increasingly rely on data to guide strategic decisions. Research… Read More »How business leaders are using AI to make data-driven decisions
Discover how purpose-built AI factories are transforming on-premises GPU data centers for high-performance AI workloads, offering cost efficiency, security, and scalability for enterprises.
A radiologist looks at hundreds of CT images to find a tiny shadow that could be cancer. At these moments, every pixel matters. AI can… Read More »How diagnosis image annotation turns scans into insights
The dialogue surrounding AI often raises anxiety: Will I be automated out of a job? The fact is, things are far more optimistic; AI is… Read More »How AI shapes the future of work with superworkers
AI benchmarks have created a false impression about how to evaluate AI models: test AI for complex questions that several humans can’t answer. Even if AI… Read More »Ranking GPT-5 against LLMs
Explore the critical computing infrastructure challenges in AI workloads, from scalability and storage to network performance and compliance requirements.
Technical debt occurs when best practices are ignored as IT solutions are built. In a survey of 500+ IT pros conducted by CompTIA, approximately three-quarters… Read More »A tech debt fighting champion for developers