The origins of aptly named supermassive black holes—which can weigh in at more than a million times the mass of the sun and reside in the center of most galaxies—remain one of the great mysteries of the cosmos.
Researchers from LMU, the ORIGINS Excellence Cluster, the Max Planck Institute for Extraterrestrial Physics (MPE), and the ORIGINS Data Science Lab (ODSL) have made an important breakthrough in the analysis of exoplanet atmospheres.
As Shumer told VentureBeat over DM: “I’ve been thinking about this idea for months now. LLMs hallucinate, but they can’t course-correct. What would happen if you taught an LLM how to recognize and fix its own mistakes?”
Hence the name, “Reflection” — a model that can reflect on its generated text and assess its accuracy before delivering it as outputs to the user.
The model’s advantage lies in a technique called reflection tuning, which allows it to detect errors in its own reasoning and correct them before finalizing a response.
Scientists have finally figured out a way to connect the dots between the macroscopic and the microscopic worlds. Their magical equation might provide us answers to questions like why black holes don’t collapse and how quantum gravity works.
Why a blog post and not a proper response in a philosophy journal? My very first journal submission is still in the review process, close to two months later, for one. Secondly, blogging allows me to be pedantic, to be human, that is, to express frustration, to show anger, to be candid; in other words, blogging allows me to be myself. Probably of highest priority is the fact that I do not want my first publication in the philosophy of mind to be a response. I want to eventually outline my own theory of consciousness, which is strongly hinted at here, and I prefer for that to be my first contribution to the philosophy of mind. I do not find panpsychism convincing and I think there is another theory of consciousness, similar to panpsychism in ways, that is much more cogent. I have outlined some qualms I have with panpsychism before; to people new to the blog, you can read here.
Researchers from the University of Pisa developed a quantum subroutine to improve matrix multiplication for AI and machine learning applications.
When you multiply two large matrices—this is a common task in fields like machine learning, but it can be time-consuming, even for powerful computers…
In a recent study published in IEEE Access, a team of researchers from the University of Pisa introduced a quantum subroutine designed to streamline matrix multiplication. This subroutine is a new feature in the toolbox of matrix multiplication that could improve computational efficiency, particularly in applications like machine learning and data processing.
Imagine you’re sitting across from a friend, having a conversation.
I’m a die-hard Beach Boys fan. In one of their most famous songs, they sing about “pickin’ up good vibrations” from a girl. We’ve all felt those “good vibes” when we’re connecting with someone new. I used to think that feeling was a mysterious, mystical experience — something I couldn’t fully explain that bonded me with some friends and strangers more easily than others.
It turns out that “good vibes” aren’t as mysterious as I thought.
Continue reading “Picking up good vibes from a stranger? That might be your neurons aligning” »
Android users have been warned that a dangerous new hack attack uses optical character recognition to grab passphrases from your smartphone.
Google has built a quantum computer that makes fewer errors as it is scaled up, and this may pave the way for machines that could solve useful real-world problems for the first time.
Learning and a spectrum of other behavioral competencies allow organisms to rapidly adapt to dynamically changing environmental variations. The emerging field of diverse intelligence seeks to understand what systems, besides ones with complex brains, exhibit these capacities. Here, we tested predictions of a general computational framework based on the free energy principle in neuroscience but applied to aneural biological process as established previously, by demonstrating and manipulating pattern recognition in a simple aneural organism, the green algae Volvox. Our studies of the adaptive photoresponse in Volvox reveal that aneural organisms can distinguish between patterned and randomized inputs and indicate how this is achieved mechanistically.
