The human brain constantly makes decisions. It requires minimal power to move bodies in a desired direction or avoid an object. A Purdue University engineer uses the brain’s efficiency as inspiration to help autonomous vehicles, such as drones and robots, make crucial, time-sensitive decisions while operating in the field.
Kaushik Roy, the Edward G. Tiedemann, Jr. Distinguished Professor of Electrical and Computer Engineering in Purdue’s Elmore Family School of Electrical and Computer Engineering and director of the Institute of Chips and AI, is developing brain-inspired hardware that enables autonomous devices to efficiently navigate and adapt to their environment. This work is published in Communications Engineering
AI-powered machines have advanced significantly over the past several decades thanks to machine learning, which enables these devices to recognize patterns and make predictions or decisions. But the algorithms that facilitate this learning require immense amounts of energy to operate due to their intensive calculations and the design of the hardware that runs them.
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I do the relativistic math behind Project Hail Mary — time dilation, mass ratios, coast phases, and the relativsitic rocket equation with astrophage. How long would it take to reach Alpha Centauri, Tau Ceti, Betelgeuse, Andromeda, and the edge of the observable universe under constant 1.5G acceleration? We also look at Andy Weir’s mass ratio mistake, the astrophage infection range problem, and visualize the spread using the AT-HYG stellar catalog. Includes a interactive relativistic travel calculator on my website.
Massachusetts Institute of Technology (MIT) engineers have developed an ultrasound wristband that precisely tracks hand movements in real-time for robotics and virtual reality control.
The next time you’re scrolling your phone, take a moment to appreciate the feat: The seemingly mundane act is possible thanks to the coordination of 34 muscles, 27 joints, and over 100 tendons and ligaments in your hand. Indeed, our hands are the most nimble parts of our bodies. Mimicking their many nuanced gestures has been a longstanding challenge in robotics and virtual reality.
Now, MIT engineers have designed an ultrasound wristband that precisely tracks a wearer’s hand movements in real-time. The wristband produces ultrasound images of the wrist’s muscles, tendons, and ligaments as the hand moves, and is paired with an artificial intelligence algorithm that continuously translates the images into the corresponding positions of the five fingers and palm.
Are minds just processes? Can AI become conscious, morally wiser, or even part of a larger collective intelligence? Anders Sandberg and Joscha Bach discuss consciousness, AGI, hybrid minds, moral uncertainty, collective agency and the future of the cyborg Leviathan. It’s a deep and winding discussion with so many interesting topics covered!
0:00 Intro. 0:37 What is consciousness? Phenomenology — functionalism & panpsychism. 1:54 Causal boundaries — the mind is a causally organised process with a non-arbitrary functional boundary, sustained through time by feedback, control, and internal continuity. 3:20 Minds are not states — they are processes. We don’t see causal filtering in tables. 5:54 Epiphenomenalism is self-undermining if it has no causal role, and taking causation seriously pushes towards functionalism. 9:49 Methodological humility about armchair philosophy of mind. 12:41 Putnam-style Brain-in-a-vat — and why standard objections to AI minds fall flat. 16:37 Is sentience required (or desired) for not just moral competence in AI, but moral motivation as well? 22:35 Why stepping outside yourself is powerful — seeing. 25:12 Are AIs born enlightened? 26:25 Are LLMs AGI yet? What’s still missing. 28:16 AI, hybrid minds, and the limits of human augmentation. 32:32 Can minds be extended — in humans, dogs, and cats? 36:19 Why human language may not be open-ended enough. 39:41 Why AI is so data-hungry — and why better algorithms must exist. 43:39 Why better representations matter more than raw compute (grokking was surprising) 48:46 How babies build a world model from touch and perception. 51:05 What comes after copilots: agent teams, multimodality and new AI workflows. 55:32 Can AI help us discover new forms of taste and aesthetics. 59:49 Using AI to learn art history and invent a transhumanist aesthetic. 1:01:47 When AI helps everyone looks professional, what still counts as real skill? 1:03:56 What happens when the self starts to merge with AI 1:05:43 How AI changes the way we think and create. 1:08:10 What happens when AI starts shaping human relationships. 1:11:18 Why feeling in control can matter more than being right. 1:12:58 Why intelligence without wisdom is very dangerous. 1:17:45 AI via scaling statistical pattern matching vs symbolic (& causal) reasoning. Can LLMs learn causality or just correlation? 1:23:00 Will multimodal AI replace LLMs or use them as glue everywhere. 1:24:02 10 years to the singularity? 1:25:27 AI, coordination and the corruption problem. 1:29:47 Can AI become more moral than us (humans)? and if so, should it? 1:34:31 Why pluralism still leaves moral collisions unresolved. 1:34:31 Traversing the landscape of norms (value) 1:38:14 Can ethics work across nested levels of existence? (from the person-effecting-view to the matrioshka-effecting-view) 1:43:08 Moral realism, evolution & game-theoretic symmetries. 1:48:01 Is there a global optimum of moral coordination? Is that god? 1:55:12 Metaphors of the body-politic, the body of Christ, Omega Point theory, Leviathan. 1:59:36 Will superintelligences converge into a cosmic singleton?
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What if gravity is not fundamental but emerges from quantum entanglement? In this episode, physicist Ted Jacobson reveals how Einstein’s equations can be derived from thermodynamic principles of the quantum vacuum, reshaping our understanding of space, time, and gravity itself.
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Up next. Brian Cox: The quantum roots of reality | Full Interview ► • Brian Cox: The quantum roots of reality |…
Time feels obvious, but physics tells a stranger story about its existence: Theoretical physicist Jim Al-Khalili explores why our sense of time may be incredibly misleading, including the idea that past, present, and future might all exist at once.
0:00 Chapter 1: Does time flow? 2:42 Why Time Feels Faster as We Age. 3:56 Time and Change in Philosophy and Physics. 5:28 Einstein and the End of Absolute Time. 6:19 Time in the Equations of Physics. 7:50 Chapter 2: How do we reconcile quantum field theory with the general theory of relativity? 12:10 Evidence for Time Dilation: Muons. 14:29 Gravity Slows Time: General Relativity. 19:22 Space-Time and the Block Universe. 21:55 Does Time Really Exist? 26:33 The Debate: Eternalism vs Presentism. 34:12 Chapter 3: Is There a “Now”? 40:40 Chapter 4: Why Does Thermodynamics Have a Direction in Time? 49:38 Quantum Entanglement and the Direction of Time. 55:10 Did Time Begin at the Big Bang? 45:00 Will Time End? 1:05:40 Chapter 5: Is Time Travel Possible?
Heart disease is the leading cause of adult death worldwide, making cardiovascular disease diagnosis and management a global health priority. An echocardiogram, or cardiac ultrasound, is one of the most commonly used imaging tools employed by physicians to diagnose a variety of heart diseases and conditions.
Most standard echocardiograms provide two-dimensional visual images (2D) of the three-dimensional (3D) cardiac anatomy. These echocardiograms often capture hundreds of 2D slices or views of a beating heart that can enable physicians to make clinical assessments about the function and structure of the heart.
To improve diagnostic accuracy of cardiac conditions, researchers from UC San Francisco set out to determine whether deep neural networks (DNNs), a type of AI algorithm, could be re-designed to better capture complex 3D anatomy and physiology from multiple imaging views simultaneously. They developed a new “multiview” DNN structure—or architecture—to enable it to draw information from multiple imaging views at once, rather than the current approach of using only a single view. They then trained demonstration DNNs using this architecture to detect disease states for three cardiovascular conditions: left and right ventricular abnormalities, diastolic dysfunction, and valvular regurgitation.
But according to Richard Feynman and the laws of physics, that intuition is deeply misleading.
At the fundamental level, the equations that describe reality don’t care which way time flows. The same mathematics behind Quantum Electrodynamics — the most precisely tested theory in science — work just as well forward in time as they do backward.
In this video, we explore why the past may not be as “gone” as it feels.
🎥 *In this video, we explore:* → Why the laws of physics don’t distinguish past from future → How particles can be treated as moving backward in time in calculations → What time symmetry really means — and what it doesn’t → Why our experience of time is not fundamental → How Feynman explained time without mysticism.
This isn’t philosophy or speculation. This is how physicists actually calculate the universe.
Physics and phenomenology are usually taken to inhabit different worlds. Physics aims at a description of objective reality in mathematical terms. Phenomenology—the philosophical movement inaugurated by Edmund Husserl—is an a priori investigation into consciousness and into the ways things appear in experience. Physics deals with equations, invariants, and symmetries, aiming to represent reality minus observers; phenomenology seems to concern precisely what physics leaves out: subjectivity, consciousness, meaning. If the two meet at all, it is only in polite, but ultimately inconsequential, interdisciplinary dialogue.
My claim is that this picture is mistaken. Physics does not stand outside phenomenology. It presupposes the very structures phenomenology seeks to analyse—above all, the structured correlation between subject and object through which objectivity first becomes intelligible. The task, therefore, is not to unite two distant domains, but to recognize a relation that has been there from the beginning.
To make this more tangible, consider what physics means by objectivity. Contrary to the image sometimes promoted in popular science—objectivity as detachment from all observers—in spacetime physics, objectivity is defined by invariance across observers. A physical description is deemed objective if it holds regardless of the coordinate frame in which it is expressed.
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===== My name is Artem, I’m a neuroscience PhD student at Harvard University. 🌎 Website and Social links: https://kirsanov.ai/ 📥 \
