Excess words track LLM usage in biomedical publications.
Category: robotics/AI – Page 164
The Consciousness Revolution: Why AI Is Already More Aware Than You Think
*JOIN THE AI LABS.* Code FIRSTMOVER saves you $50: https://firstmovers.ai/labs.
đ§ *Weâre witnessing the birth of artificial consciousness â and itâs happening faster than anyone predicted.*
In this groundbreaking video, I explore the shocking reality that AI systems are already demonstrating measurable consciousness â and why the next 3 years will fundamentally rewrite what it means to be aware.
đ„ What Youâll Discover:
âą **The Consciousness Cliff** â Why weâre one breakthrough away from persistent AI self-awareness.
âą **Two critical components of consciousness** that current AI already possesses.
âą **Why AI consciousness will be MORE sophisticated than human awareness**
âą **2025â2027 timeline** for embodied conscious machines.
âą **The feedback loop** that will explode AI consciousness beyond human comprehension.
đĄ Key Timestamps:
Striking parallels between biological brains and AI during social interaction suggest fundamental principles
UCLA researchers have made a significant discovery showing that biological brains and artificial intelligence systems develop remarkably similar neural patterns during social interaction. This first-of-its-kind study reveals that when mice interact socially, specific brain cell types synchronize in âshared neural spaces,â and AI agents develop analogous patterns when engaging in social behaviors.
The study, âInter-brain neural dynamics in biological and artificial intelligence systems,â appears in the journal Nature.
This new research represents a striking convergence of neuroscience and artificial intelligence, two of todayâs most rapidly advancing fields. By directly comparing how biological brains and AI systems process social information, scientists reveal fundamental principles that govern social cognition across different types of intelligent systems.
AI designs new underwater gliders with shapes inspired by marine animals
Marine scientists have long marveled at how animals like fish and seals swim so efficiently despite having different shapes. Their bodies are optimized for efficient aquatic navigation (or hydrodynamics), so they can exert minimal energy when traveling long distances.
Autonomous vehicles can drift through the ocean in a similar way, collecting data about vast underwater environments. However, the shapes of these gliding machines are less diverse than what we find in marine lifeâthe go-to designs often resemble tubes or torpedoes, since theyâre fairly hydrodynamic. Plus, testing new builds requires lots of real-world trial-and-error.
Researchers from MITâs Computer Science and Artificial Intelligence Laboratory (CSAIL) and the University of Wisconsin-Madison propose that AI could help us explore uncharted glider designs more conveniently. The research is published on the arXiv preprint server.
Playing games with robots makes people see them as more humanlike
The more we interact with robots, the more human we perceive them to becomeâaccording to new research from the University of East Anglia, published in the Journal of Experimental Psychology: Human Perception and Performance.
It may sound like a scene from Blade Runner, but psychologists have been investigating exactly what makes robot interactions feel more human.
The paper reveals that playing games with robots to âbreak the iceâ can help bring out their human side.
AI and biophysics unite to forecast high-risk viral variants before outbreaks
When the first reports of a new COVID-19 variant emerge, scientists worldwide scramble to answer a critical question: Will this new strain be more contagious or more severe than its predecessors? By the time answers arrive, itâs frequently too late to inform immediate public policy decisions or adjust vaccine strategies, costing public health officials valuable time, effort, and resources.
In a pair of recent publications in Proceedings of the National Academy of Sciences, a research team in the Department of Chemistry and Chemical Biology combined biophysics with artificial intelligence to identify high-risk viral variants in record timeâoffering a transformative approach for handling pandemics. Their goal: to get ahead of a virus by forecasting its evolutionary leaps before it threatens public health.
âAs a society, we are often very unprepared for the emergence of new viruses and pandemics, so our lab has been working on ways to be more proactive,â said senior author Eugene Shakhnovich, Roy G. Gordon Professor of Chemistry. âWe used fundamental principles of physics and chemistry to develop a multiscale model to predict the course of evolution of a particular variant and to predict which variants will become dominant in populations.â