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Category: information science – Page 47

How An Algorithm Feels From Inside

“If a tree falls in the forest, and no one hears it, does it make a sound?” I remember seeing an actual argument get started on this subject—a fully naive argument that went nowhere near Berkeleyan subjectivism. Just:

“It makes a sound, just like any other falling tree!” “But how can there be a sound that no one hears?”

The standard rationalist view would be that the first person is speaking as if “sound” means acoustic vibrations in the air; the second person is speaking as if “sound” means an auditory experience in a brain. If you ask “Are there acoustic vibrations?” or “Are there auditory experiences?”, the answer is at once obvious. And so the argument is really about the definition of the word “sound”

Researchers Propose a Smaller, more Noise-Tolerant Quantum Circuit for Cryptography

Researchers Propose a #Smaller, more #Noise-#Tolerant #Quantum #Circuit for #Cryptography.

MIT researchers new algorithm is as fast as Regev’s, requires fewer qubits, and has a higher tolerance to quantum noise, making it more feasible to implement…

The most recent email you sent was likely encrypted using a tried-and-true method that relies on the idea that even the fastest computer would be unable to efficiently break a gigantic number into factors.

Quantum computers, on the other hand, promise to rapidly crack complex cryptographic systems that a classical computer might never be able to unravel. This promise is based on a quantum factoring algorithm proposed in 1994 by Peter Shor, who is now a professor at MIT.

But while researchers have taken great strides in the last 30 years, scientists have yet to build a quantum computer powerful enough to run Shor’s algorithm.

Prospective multicenter study using artificial intelligence to improve dermoscopic melanoma diagnosis in patient care

Outperforms dermatologists in detecting melanoma, offering better diagnosis for challenging cases and improving patient care. 🩺🖥️

Heinlein, Maron, Hekler et al. evaluate an AI algorithm for detecting melanoma and compare its performance to that of dermatologist on a prospectively collected, external, heterogeneous dataset. The AI exhibits a significant performance advantage, especially in diagnosing challenging cases.

Will Machines Ever Become Conscious?

AI may equal human intelligence without matching the true nature of our experiences.

By Christof Koch

A future where the thinking capabilities of computers approach our own is quickly coming into view. We feel ever more powerful machine-learning (ML) algorithms breathing down our necks. Rapid progress in coming decades will bring about machines with human-level intelligence capable of speech and reasoning, with a myriad of contributions to economics, politics and, inevitably, warcraft. The birth of true artificial intelligence will profoundly affect humankind’s future, including whether it has one.

Harnessing Automated Insulin Delivery: Case Reports from Marathon Runners with Type 1 Diabetes

How can machine learning help individuals with type 1 diabetes (T1D)? This is what a study presented at this year’s Annual Meeting of the European Association for the Study of Diabetes (EASD) hopes to address as a team of researchers have developed a system using machine learning capable of managing blood sugars levels with such proficiency that those using system were able to lead lives far more active than the average T1D patient.

For the study, the researchers developed the AID system, which uses closed-loop technology that delivers insulin based on readings from the machine learning algorithm, resulting in a 50-year-old man, a 40-year-old man, and a 34-year-old woman with T1D being able to run hours-long marathons in Tokyo, Santiago, and Paris, respectively. This study holds the potential to help develop better technology capable of allowing T1D diabetes patients to stay in shape without constantly fearing for their blood sugar levels, which can lead to long-term health problems, including hyperglycemia, nerve damage, or a heart attack.

“Despite better systems for monitoring blood sugars and delivering insulin, maintaining glucose levels in target range during aerobic training and athletic competition is especially difficult,” said Dr. Maria Onetto, who is in the Department of Nutrition at the Pontifical Catholic University of Chile and lead author of the study. “The use of automated insulin delivery technology is increasing, but exercise continues to be a challenge for individuals with T1D, who can still struggle to reach the recommended blood sugar targets.”

Wormhole: A wormhole is a hypothetical structure connecting disparate points in spacetime, and is based on a special solution of the Einstein field equations

A wormhole is a hypothetical structure connecting disparate points in spacetime, and is based on a special solution of the Einstein field equations. [ 1 ]

A can be visualized as a tunnel with two ends at separate points in spacetime (i.e., different locations, different points in time, or both).

Wormholes are consistent with the general theory of relativity, but whethers actually exist is uncertain. Many scientists postulate thats are merely projections of a fourth spatial dimension, analogous to how a two-dimensional (2D) being could experience only part of a three-dimensional (3D) object. [ 2 ] A well-known analogy of such constructs is provided by the Klein bottle, displaying a hole when rendered in three dimensions but not in four or higher dimensions.

Einstein’s famous equation first demonstrated the creation of matter from light

Scientists Create Matter from Pure Light, Demonstrating Einstein’s E=mc² Equation in Action.

Physicists at Brookhaven National Laboratory have achieved a groundbreaking experiment, creating matter from light by demonstrating the Breit-Wheeler process. Using the Relativistic Heavy Ion Collider, they accelerated heavy ions to generate nearly real photons, leading to the formation of electron-positron pairs. This experiment showcases Einstein’s E=mc² equation in action, aligning with predictions for transforming energy into matter. While these virtual photons act similarly to real ones, the experiment is a crucial step towards proving the process with real photons when technology advances to create gamma-ray lasers. Don’t forget to comment your thought about this!

Combining existing sensors with machine learning algorithms improves robots’ intrinsic sense of touch

A team of roboticists at the German Aerospace Center’s Institute of Robotics and Mechatronics finds that combining traditional internal force-torque sensors with machine-learning algorithms can give robots a new way to sense touch.

In their study published in the journal Science Robotics, the group took an entirely new approach to give robots a that does not involve artificial skin.

For living creatures, touch is a two-way street; when you touch something, you feel its texture, temperature and other features. But you can also be touched, as when someone or something else comes in contact with a part of your body. In this new study, the research team found a way to emulate the latter type of touch in a robot by combining internal force-torque sensors with a machine-learning algorithm.

Procedural Road Network Made With Unreal Engine 5

Game Developer jourverse, who is currently working on a tutorial series focused on building a traffic system in Unreal Engine 5, shared a demo project file for this procedural road network integrated with vehicle AI for obstacle avoidance, using A* for pathfinding.

The developer explained that both the A* algorithm and the road editor mode are implemented in C++, with no use of neural networks. Vehicle AI operations like spline following, reversing, and performing 3-point turns are handled through Blueprints. The vehicle AI navigates using two paths: the green spline for the main route and the blue spline for obstacle avoidance. The main spline leverages road network nodes to determine the path to the target via A* on FPathNode, which includes adjacent road nodes.

For obstacle detection, the vehicle employs polynomial regression to predict its future position. Upon detecting an obstacle, a grid of sphere traces is generated to map the obstacle’s location, and another A* algorithm is employed to create a path around the obstacle.