In my earlier articles about ITOps 4.0, we established the case for “run driven change or transformation” and how that enables a “composition of services,” making infrastructure invisible. In this ...

Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...

Founder and Managing Principal of DBP Institute. I consult companies on how to transform technology and data into a valuable business asset. Today, every company is looking at data and analytics to ...

The process of updating deep learning/AI models when they face new tasks or must accommodate changes in data can have significant costs in terms of computational resources and energy consumption.

DCF model estimates stock value by discounting expected future cash flows to present value. Using multiple valuation methods with DCF can enhance accuracy in stock evaluations. DCF's effectiveness is ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

A common criticism of fundamentals models is that they are extremely easy to “over-fit”—the statistical term for deriving equations that provide a close match to historical data, but break down when ...