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Category: robotics/AI

Can AI build a machine that draws a heart? What automated mechanism design could mean for mechanical engineering

Can you design a mechanism that will trace out the shape of a heart? How about the shape of a moon, or a star? Mechanism design—the art of assembling linkages and joints to create machines with prescribed motion—is one of the quintessential activities of mechanical engineers, but has resisted automation for almost two centuries.

In his seminal 1841 book Principles of Mechanisms, Oxford professor Robert Willis famously noted, “When the mind of a mechanician is occupied with the contrivance of a machine, he must wait until, in the midst of his meditations, some happy combination presents itself to his mind which may answer his purpose.”

Almost 200 years later, we still teach machine design mostly by apprenticeship. While we can simulate machines of almost any complexity, systematic methods for design are known only for the most trivial contraptions.

Machine learning helps solve a central problem of quantum chemistry

Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that it delivers precise results and reliably establishes a physically meaningful solution. The findings are published in the Journal of the American Chemical Society.

Why molecular electron densities matter

How electrons are distributed in a molecule determines its chemical properties—from its stability and reactivity to its biological effect. Reliably calculating this electron distribution and the resulting energy is one of the central functions of quantum chemistry. These calculations form the basis of many applications in which molecules must be specifically understood and designed, such as for new drugs, better batteries, materials for energy conversion, or more efficient catalysts.

How Artificial Intelligence Is Creating New Job Opportunities

Artificial Intelligence (AI) has become a buzzword in recent years. We’ve heard countless stories about how AI could potentially eliminate jobs, particularly in the engineering and contracting realm. However, we tend to forget that AI is also capable of creating new opportunities for employment and growth. I’d like to explore exactly how AI can help create jobs for engineers and other professionals in the contracting industry.

AI Enhances Demand for Skilled Workers

One of the most significant ways that AI can create jobs is by enhancing efficiency and productivity. By reducing manual labor and streamlining processes, organizations are able to focus their energy on more complex tasks that require human expertise. This shift means a greater need for skilled labor, which means more job openings for engineers and other professionals. For example, AI can be used to automate mundane tasks such as data entry or administrative work, allowing humans to focus their attention on more technical projects – and this means engineers have more time to create solutions that change the world.

Personalization features can make LLMs more agreeable, potentially creating a virtual echo chamber

Many of the latest large language models (LLMs) are designed to remember details from past conversations or store user profiles, enabling these models to personalize responses. But researchers from MIT and Penn State University found that, over long conversations, such personalization features often increase the likelihood an LLM will become overly agreeable or begin mirroring the individual’s point of view.

This phenomenon, known as sycophancy, can prevent a model from telling a user they are wrong, eroding the accuracy of the LLM’s responses. In addition, LLMs that mirror someone’s political beliefs or worldview can foster misinformation and distort a user’s perception of reality.

Unlike many past sycophancy studies that evaluate prompts in a lab setting without context, the MIT researchers collected two weeks of conversation data from humans who interacted with a real LLM during their daily lives. They studied two settings: agreeableness in personal advice and mirroring of user beliefs in political explanations.

Why Cybersecurity Strategies and Frameworks Must Be Recalibrated in the Age of AI and Quantum Threats

#cybersecurity #ai #quantum

Artificial intelligence and quantum computing are no longer hypothetical; they are actively altering cybersecurity, extending attack surfaces, escalating dangers, and eroding existing defenses. We are in a new ear of emerging technologies that are directly impacting cybersecurity requirements.

As a seasoned observer and participant in the cybersecurity domain—through my work, teaching, and contributions to Homeland Security Today, my book “Inside Cyber: How AI, 5G, IoT, and Quantum Computing Will Transform Privacy and Our Security”, — I have consistently underscored that technological advancement is outpacing our institutions, policies, and workforce preparedness.

Current frameworks, intended for a pre-digital convergence era, are increasingly unsuitable. In order to deal with these dual-use technologies that act as force multipliers for both defenders and enemies, we must immediately adjust our strategy as time is of the essence.

UT San Antonio to launch nation’s first open-access neuromorphic computing hub

To tackle this challenge, the MATRIX AI Consortium for Human Well-Being at UT San Antonio plans to launch a new initiative that establishes a national hub for “neuromorphic” computing available for public use.

Neuromorphic computing is a revolutionary approach that mimics the human brain’s structure to process information with a fraction of the energy used by traditional computers. Unlike standard processors that crunch data in a fixed sequence, neuromorphic chips operate like biological neurons. They are event-based, meaning that they activate only when there is something new to process, saving energy between events.

The initiative, called THOR: The Neuromorphic Commons, is funded by the National Science Foundation. THOR will make the promising technology available for researchers nationwide to explore and conduct experiments, serving as the largest-ever full-stack neuromorphic platforms to be open to the public.

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