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Experts believe that with new AI and metaverse technologies, humans could upload to their brain to the web and potentially live longer.
Local consciousness, or our phenomenal mind, is emergent, whereas non-local consciousness, or universal mind, is immanent. Material worlds come and go, but fundamental consciousness is ever-present, according to the Cybernetic Theory of Mind. From a new science of consciousness to simulation metaphysics, from evolutionary cybernetics to computational physics, from physics of time and information to quantum cosmology, this novel explanatory theory for a deeper understanding of reality is combined into one elegant theory of everything.
#CyberneticTheoryofMind #Consciousness #Evolution #Mind #Documentary
Why do industrial robots require teams of engineers and thousands of lines of code to perform even the most basic, repetitive tasks while giraffes, horses, and many other animals can walk within minutes of their birth?
My colleagues and I at the USC Brain-Body Dynamics Lab began to address this question by creating a robotic limb that learned to move, with no prior knowledge of its own structure or environment [1,2]. Within minutes, G2P, our reinforcement learning algorithm implemented in MATLABÂź, learned how to move the limb to propel a treadmill (Figure 1).
System sidesteps computing bottleneck in tuning artificial intelligence algorithms.
Closing Gaps in Geometrically Frustrated Symmetric Clusters: Local Equivalence between Discrete Curvature and Twist Transformations.
Siemens and Roboze have announced that they are collaborating to develop workflows dedicated to the industrialization of 3D printing. This includes an emphasis on expanding the use of the technology in energy, mobility, and aerospace. Though the exact nature of the agreement isnât fully elucidated, it marks a significant shift for both firms.
Siemens is the largest industrial manufacturer in Europe, with a storied history spanning nearly two centuries and annual revenues totaling âŹ62.3 billion, as of 2021. In contrast, Roboze is a comparatively new firm, established in Italy in 2013. The company has since built itself up into a leader in industrial-grade material extrusion 3D printers, earning such customers as Ducati, GE, and the U.S. Army.
The partners do not exactly clarify their intent except to say that they will work together to âincrease the productivity, competitiveness and efficiency of manufacturers that have embarked on the path to the future of industry.â They do mention focusing on âdigitalization and automation projectsâ.
Reward maximisation is one strategy that works for reinforcement learning to achieve general artificial intelligence. However, deep reinforcement learning algorithms shouldnât depend on reward maximisation alone.
Identifying dual-purpose therapeutic targets implicated in aging and disease will extend healthspan and delay age-related health issues.
AI is all that matters now, and reaching Agi before 2030 is all that matters for this decade.
A substantial percentage of the human clinical trials, including those evaluating investigational anti-aging drugs, fail in Phase II, a phase where the efficacy of the drug is tested. This poor success is in part due to inadequate target choice and the inability to identify a group of patients who will most likely respond to specific agents. This challenge is further complicated by the differences in the biological age of the patients, as the importance of therapeutic targets varies between the age groups. Unfortunately, most targets are discovered without considering patientsâ age and being tested in a relatively younger population (average age in phase I is 24). Hence, identifying potential targets that are implicated in multiple age-associated diseases, and also play a role in the basic biology of aging, may have substantial benefits.
Identifying dual-purpose targets that are implicated in aging and disease at the same time will extend healthspan and delay age-related health issues â even if the target is not the most important in a specific patient, the drug would still benefit that patient.
Now, an intelligent robotic fruit packing machine is able to automate the most labor-intensive job in the packhouse. For post-harvest operators, this robot could prove to be a game-changer in the industry.
The Aporo II robotic produce packaging machine by Globe Pac Technologies builds on the proven technology of the original Aporo I Produce Packer. First developed in 2018, the latest model can now accommodate twice the throughput, packing 240 fruit per minute, saving between two and four labor units per double packing belt.
Continue reading “Fruit packing robot dramatically cuts packhouse labor needs” »
