This article presents a white paper summarizing current knowledge on quantum gravity phenomenology and its multi-messenger signals. It provides an overview of the field, discusses experimental and observational signatures, and identifies key questions and challenges.
Excavations in Turkey have revealed a previously unknown Anatolian-Indo-European language, Kalašma, dating back around 3,000 years. The language is similar to Luwian and has been deciphered by researchers from the University of Worzburg and Istanbul University.
Explores the dynamic relationship between language, cognition, and the role of Large Language Models (LLMs) in expanding our understanding of the functional significance of language.
Astrophysicists have detected subtle hints that the mysterious 'dark energy' that drives the universe's expansion may be slightly weakening over time.
The article discusses the limitations of Large Language Models (LLMs) in planning and self-verification tasks, and proposes an LLM-Modulo framework to leverage their strengths in a more effective manner. The framework combines LLMs with external model-based verifiers to generate, evaluate, and improve plans, ensuring their correctness and efficiency.
"Simply put, we take the stance that LLMs are amazing giant external non-veridical memories that can serve as powerful cognitive orthotics for human or machine agents, if rightly used."
"Simply put, we take the stance that LLMs are amazing giant external non-veridical memories that can serve as powerful cognitive orthotics for human or machine agents, if rightly used."
Our study demonstrates that sperm whale vocalisations form a complex combinatorial communication system: the seemingly arbitrary inventory of coda types can be explained by combinations of rhythm, tempo, rubato, and ornamentation features. This study shows that these vocalisations have a significantly greater information capacity than was previously known.
Researchers led by Nigel Goldenfeld and Björn Hof offer new insights into the transition from laminar to turbulent water flow, solving a 150-year-old mystery. The interdisciplinary team applied statistical mechanics to reveal that the phenomenon behaves like directed percolation.
Recent volumetric brain reconstructions reveal high anatomic complexity. Research shows brain anatomy satisfies universal scaling laws, implying criticality in the cellular brain structure. Findings enable comparisons of structural properties across different organisms.
Last week, Anthropic announced a significant breakthrough in our understanding of how large language models work. The research focused on Claude 3 Sonnet, the mid-sized version of Anthropic’s latest frontier model. Anthropic showed that it could transform Claude's otherwise inscrutable numeric representation of words into a combination of ‘features’, many of which can be understood by human beings. The vectors Claude uses to represent words can be understood as the sum of ‘features’—vectors that represent a variety of abstract concepts from immunology to coding errors to the Golden Gate Bridge. This research could prove useful for Anthropic and the broader industry, potentially leading to new tools to detect model misbehavior or prevent it altogether.
The paper proposes the "law of increasing functional information," a new law of nature that could help explain the evolution of complex systems across multiple scales in the universe, from atoms and molecules to stars and brains.
These systems are characterized by three attributes: they form from numerous components, processes generate numerous configurations, and configurations are preferentially selected based on function.
The law suggests that functional information of a system will increase over time when subjected to selection for function(s). The authors argue this law could help predict the behavior of these systems and provide a unified framework for understanding their evolution.
They suggest it could be a missing piece in our understanding of the universe.
These systems are characterized by three attributes: they form from numerous components, processes generate numerous configurations, and configurations are preferentially selected based on function.
The law suggests that functional information of a system will increase over time when subjected to selection for function(s). The authors argue this law could help predict the behavior of these systems and provide a unified framework for understanding their evolution.
They suggest it could be a missing piece in our understanding of the universe.
