Many AI models fail to recognise negation words such as “no” and “not”, which means they can’t easily distinguish between medical images labelled as showing a disease and images labelled as not showing the disease
Category: robotics/AI
Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve researchers’ ability to detect complex genetic alterations in cancer genomes. However, the complex structure of cancer genomes means that standard analysis tools, including existing methods specifically developed to analyze long-read sequencing data, often fall short, leading to false-positive results and unreliable interpretations of the data.
These misleading results can compromise our understanding of how tumors evolve, respond to treatment, and ultimately how patients are diagnosed and treated.
To address this challenge, researchers developed SAVANA, a new algorithm which they describe in the journal Nature Methods.
A “fine-tuned” artificial intelligence (AI) tool shows promise for objective evaluation of patients with facial palsy, reports an experimental study in the June issue of Plastic and Reconstructive Surgery.
“We believe that our research offers valuable insights into the realm of facial palsy evaluation and presents a significant advancement in leveraging AI for clinical applications,” comments lead author Takeichiro Kimura, MD, of Kyorin University, Mitaka, Tokyo.
Patients with facial palsy have paralysis or partial loss of movement of the face, caused by nerve injury due to tumors, surgery, trauma, or other causes. Detailed assessment is essential for evaluating treatment options, such as nerve transfer surgery, but poses difficult challenges.
While there are many potential uses for soft-bodied robots, the things are still typically only built in small experimental batches. Scottish scientists are out to change that, with a mass-production-capable soft bot that is 3D-printed in a single piece which then walks off of the print bed.
Before we go any further, this isn’t the first time we’ve heard about a soft robot that was printed in one piece.
It was just this March that we told you about a hexapod bot created at UC San Diego, which was 3D-printed in one continuous 58-hour step. That robot was powered not by a motor but by compressed air, which sequentially moves its legs forward.
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Why is there something rather than nothing? Robert Lawrence Kuhn, creator of Closer To Truth, joins John Michael Godier to explore one of the most profound questions in science and philosophy. The discussion moves through materialism, idealism, panpsychism, and quantum perspectives, asking whether consciousness is merely a byproduct of evolution or a fundamental aspect of reality, and what that could mean for the universe, artificial intelligence, and the nature of mind. Kuhn discusses his recent paper, A Landscape of Consciousness: Toward a Taxonomy of Explanations and Implications, which maps the full range of consciousness theories and explores their broader significance.
Links:
Closer to Truth.
https://www.youtube.com/c/CloserToTruthTV
A landscape of consciousness: Toward a taxonomy of explanations and implications by Robert Lawrence Kuhn https://www.sciencedirect.com/science/article/pii/S0079610723001128?via%3Dihub.
Seeing the consciousness forest for the trees by Àlex Gómez-Marín.
https://iai.tv/articles/seeing-the-consciousness-forest-for-the-trees-auid-2901
00:00:00 Introduction to Robert Lawrence Kuhn and consciousness.
Today we introduced Flow, a new AI filmmaking tool built with and for creatives for the next wave of storytelling.
The Right must find out what ‘winning an AI race’ means, how much jobs matter, and who to trust.
In this episode of The Moss Report, Ben Moss sits down with Dr. Ralph Moss to explore the real-world pros and cons of using artificial intelligence in cancer research and care.
From AI-generated health advice to PubMed citations that don’t exist, this honest conversation covers what AI tools are getting right—and where they can dangerously mislead.
Dr. Moss shares the results of his own AI test across five major platforms, exposing their strengths and surprising failures.
Whether you’re a cancer patient, caregiver, or simply curious about how AI is shaping the future of medicine, this episode is essential listening.
Links and Resources:
🌿 The Moss Method – Fight Cancer Naturally – (Paperback, Hardcover, Kindle) https://amzn.to/4dGvVjp.
The advancement of artificial intelligence (AI) and the study of neurobiological processes are deeply interlinked, as a deeper understanding of the former can yield valuable insight about the other, and vice versa. Recent neuroscience studies have found that mental state transitions, such as the transition from wakefulness to slow-wave sleep and then to rapid eye movement (REM) sleep, modulate temporary interactions in a class of neurons known as layer 5 pyramidal two-point neurons (TPNs), aligning them with a person’s mental states.
These are interactions between information originating from the external world, broadly referred to as the receptive field (RF1), and inputs emerging from internal states, referred to as the contextual field (CF2). Past findings suggest that RF1 and CF2 inputs are processed at two distinct sites within the neurons, known as the basal site and apical site, respectively.
Current AI algorithms employing attention mechanisms, such as transformers, perceiver and flamingo models, are inspired by the capabilities of the human brain. In their current form, however, they do not reliably emulate high-level perceptual processing and the imaginative states experienced by humans.
There’s a deep human desire to know, to better understand the world, and for decision-makers within organizations to do that in a way that’s grounded in data and grounded in fact.