Purpose: Is used to train the machine learning model. Function: Think of it as the study material for the model. It provides examples and patterns for the model to learn from and build its internal ...

MIT researchers achieved 61.9% on ARC tasks by updating model parameters during inference. Is this key to AGI? We might reach the 85% AGI doorstep by scaling and integrating it with COT (Chain of ...

AI training uses large datasets to teach algorithms, increasing AI capabilities significantly. Better-trained AI models respond more accurately to complex prompts and professional tests. Evaluating AI ...

Test automation and DevOps play a major role in today's quality assurance landscape. As we know, software development is evolving at a rapid pace. This requires finding robust ways to invest in ...

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...