The financial landscape of 2026 is defined by a paradox: machine learning systems are now more powerful and autonomous than ever, yet they operate under the strictest regulatory scrutiny in history.

Unlike traditional systems that produce a single output, ML-driven tax planning generates a set of ranked strategies.

Jonathan D. Uslaner and Matthew Goldstein of Bernstein Litowitz Berger & Grossmann LLP examine the proposed new Federal Rule of Evidence 707, which addresses the admissibility of machine-generated ...

In 2026, neural network research is advancing in efficiency, adaptability, and workflow reasoning, yet the MLRegTest benchmark shows persistent weaknesses in rule generalization. Researchers are ...