A new study examines the possibility of consciousness in artificial systems, focusing on ruling out scenarios where AI appears conscious without actually being so.
Category: robotics/AI – Page 604
Researchers develop framework to merge AI and human intelligence for process safety
Artificial intelligence (AI) has grown rapidly in the last few years, and with that increase, industries have been able to automate and improve their efficiency in operations.
A feature article published in AIChE Journal identifies the challenges and benefits of using Intelligence Augmentation (IA) in process safety systems.
Contributors to this work are Dr. Faisal Khan, professor and chemical engineering department head at Texas A&M University, Dr. Stratos Pistikopoulos, professor and director of the Energy Institute, Drs. Rajeevan Arunthavanathan, Tanjin Amin, and Zaman Sajid from the Mary Kay O’Connor Safety Center.
Machine learning unlocks secrets to advanced alloys
The concept of short-range order (SRO)—the arrangement of atoms over small distances—in metallic alloys has been underexplored in materials science and engineering. But the past decade has seen renewed interest in quantifying it, since decoding SRO is a crucial step toward developing tailored high-performing alloys, such as stronger or heat-resistant materials.
Understanding how atoms arrange themselves is no easy task and must be verified using intensive lab experiments or computer simulations based on imperfect models. These hurdles have made it difficult to fully explore SRO in metallic alloys.
But Killian Sheriff and Yifan Cao, graduate students in MIT’s Department of Materials Science and Engineering (DMSE), are using machine learning to quantify, atom by atom, the complex chemical arrangements that make up SRO. Under the supervision of Assistant Professor Rodrigo Freitas, and with the help of Assistant Professor Tess Smidt in the Department of Electrical Engineering and Computer Science, their work was recently published in Proceedings of the National Academy of Sciences.
AI is poised to automate today’s most mundane manual warehouse task
Pallets are everywhere, but training robots to stack them with goods takes forever. Fixing that could be a tangible win for commercial AI-powered robots.
Cognition: Devin was evaluated on a random 25% subset of the dataset
Devin was unassisted, whereas all other models were assisted (meaning the model was told exactly which files need to be edited).
We plan to publish a more detailed technical report soon—stay tuned for more details.
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10 Stages of AI (And Their Impact on Humanity)
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AI-powered optical detection to thwart counterfeit chips
The semiconductor industry has grown into a $500 billion global market over the last 60 years. However, it is grappling with dual challenges: a profound shortage of new chips and a surge of counterfeit chips, introducing substantial risks of malfunction and unwanted surveillance. In particular, the latter inadvertently gives rise to a $75 billion counterfeit chip market that jeopardizes safety and security across multiple sectors dependent on semiconductor technologies, such as aviation, communications, quantum, artificial intelligence, and personal finance.
Eye reflections: The key to detecting deepfakes
Governments and organizations worldwide are beginning to recognize the potential dangers. Efforts are being made to develop more sophisticated deepfake detection tools and to establish legal frameworks to address the misuse of this technology.
However, the battle against these convincing fakes is ongoing, and as detection methods improve, so too do the techniques used to create them.
The combination of astronomical techniques and AI highlights a multidisciplinary approach to solving the problem, underscoring the need for innovative and collaborative solutions.
