SPM Articles

Abstract: Powerful artificial intelligence (AI) tools that have emerged in recent years—including large language models (LLMs), automated coding assistants, and advanced image and speech generation technologies—are the result of monumental human achievements. These breakthroughs reflect mastery across multiple technical disciplines and the resolution of significant technological challenges. However, some of the most profound challenges may still lie ahead.

Abstract: This article argues that the quest for brain-mimicking artificial intelligence is no longer limited by algorithms or transistor counts, but by the philosophical assumptions embedded in modern electronics. Today’s AI systems, despite their impressive performance, remain rooted in a worldview shaped by the historically inherited and largely unquestioned digital reductionism and Cartesian dualism: one that fragments signals, separates mind from matter, and treats intelligence as an abstract computation detached from physical embodiment.

Fractional programming (FP) is a branch of mathematical optimization that deals with the optimization of ratios. It is an invaluable tool for signal processing and machine learning, because many key metrics in these fields are fractionally structured, e.g., the signal-to-interference-plus-noise ratio (SINR) in wireless communications, the Cramér-Rao bound (CRB) in radar sensing, the normalized cut in graph clustering, and the margin in support vector machine (SVM).

With the advent of large language models (LLMs), the concept of artificial intelligence (AI) agents capable of decision making and action execution has gained prominence, particularly as LLMs demonstrate increasing proficiency in tool use and task planning. Following these advancements, the established methods used for task-oriented dialogue (TOD) systems have undergone a paradigm shift by integrating LLMs’ revolutionary language understanding and reasoning skills with enhanced instruction following and response generation abilities.

The Golden Jubilee edition of the IEEE Signal Processing Society’s (SPS’s) flagship conference, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), was held on 6–11 April 2025 at the Hyderabad International Convention Center in Hyderabad, India. This was the first time an ICASSP was organized in India. Here, we provide a brief summary of the event. The goal of the organizers was to provide an affordable, inclusive, memorable, and sustainable (AIMS) event that lived up to the lofty technical standards of an ICASSP.

The tutorial “Introducing Information Metrics for Statistical Signal Processing,” [A1] provided the inspiration for our cover in this issue. In their “Lecture Notes” column, Steve Kay and Kaushallya Adhikari invite us to “a leisurely stroll through the garden of the beautiful information-theoretic flowers that have blossomed over the years.” This ends up being not only a pleasant stroll, but also an enriching one with useful insights into these measures and their interrelationships recounted with precision.

One year has passed since I began my term as the editor-in-chief (EiC) of IEEE Signal Processing Magazine (SPM). It has been a busy first year, with a rich set of challenges that go beyond those I have experienced in previous volunteer positions. This is welcome: with giving back to our community comes the desire to grow through new challenges and experiences, especially for those of us approaching our wiser years.

As we enter the new year, I would like to take a moment to reflect on our achievements from the past year and celebrate our successes. I am naming this “President’s Message” column the “State of the Society,” which will serve as a platform to share updates about our Society, including our activities, successes, and challenges.