This article critically examines the foundational principles of contemporary AI methods, exploring the limitations that hinder its potential. We draw parallels between the modern AI landscape and the 20th-century Modern Synthesis in evolutionary biology, and highlight how advancements in evolutionary theory that augmented the Modern Synthesis, particularly those of Evolutionary Developmental Biology, offer insights that can inform a new design paradigm for AI. By synthesizing findings across AI and evolutionary theory, we propose a pathway to overcome existing limitations, enabling AI to achieve its aspirational goals.

Scientists have developed the most accurate computing method to date to reconstruct the patchwork of genetic faults within tumors and their history during disease development, in new research funded by Cancer Research UK and published in Nature Genetics. Their powerful approach combines artificial intelligence with the mathematical models of Charles Darwin's theory of evolution to analyze genetic data more accurately than ever before, paving the way for a fundamental shift in how cancer's genetic diversity is used to deliver tailored treatments to patients. Applying these new algorithms to DNA data taken from patient samples revealed that tumors had a simpler genetic structure than previously thought. The algorithms showed that tumors had fewer distinct subpopulations of cells, called "subclones," than previously suggested. The scientists, based at The Institute of Cancer Research, London, and Queen Mary University of London, could also tell how old each subclone was and how fast it was growing.

In this paper, we make a review on the concepts of rationality across several different fields, namely in economics, psychology and evolutionary biology and behavioural ecology. We review how processes like natural selection can help us understand the evolution of cognition and how cognitive biases might be a consequence of this natural selection. In the end we argue that humans are not irrational, but rather rationally bounded and we complement the discussion on how quantum cognitive models can contribute for the modelling and prediction of human paradoxical decisions.

They're regularly depicted in science fiction blockbusters as other-worldly, monster-like beings. But a new study suggests that in reality, aliens could be more similar to us than thought. The research indicates that aliens are potentially shaped by the same processes that shaped humans, such as natural selection, and that they may even'look like us.' They're regularly depicted in science fiction blockbusters as other-worldly, monster-like beings. Researchers have shown for the first time how evolutionary theory can be used to predict alien behaviour. Their theory supports the argument that foreign life forms undergo natural selection, and like us, are evolving to be stronger over time.

This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. Get ready for game bots with a mind of their own. It is the year 2002. After an explosion of R&D funded by software giants and startups, more than a third of US households are populated by sophisticated artificial intelligence bots – their decisionmaking guided by complex neural nets and simulated emotions, their perceptual systems honed to detect subtle changes in their environment. Every day millions of Americans interact with these creatures, encountering advanced technology from nuanced natural language routines to gesture recognition to machine learning.