The article provides an overview of approaches to modeling the human psyche in the perspective of building an artificial one. Based on the review, a concept of cognitive architecture is proposed, where the psyche is considered as an operating system of a living or artificial subject, including a space of needs that determines its life meanings in connection with stimuli from the external world, and intelligence as a decision-making system for actions in relation to this world in order to satisfy these needs. Based on the concept, a computational formalization is proposed for creating artificial intelligence systems through learning from experience in the space of a space of needs, taking into account their biological or existential significance for an intelligent agent. Thus, the problem of building general artificial intelligence as a system for making optimal decisions in the space of agent-specific needs under conditions of uncertainty is formalized, with maximization of success in achieving goals, minimization of existential risks and maximization of energy efficiency. A minimal experimental implementation of the model is also provided.

The computer scientist and CEO who popularized the term'artificial general intelligence' (AGI) believes AI is verging on an exponential'intelligence explosion.' The PhD mathematician and futurist Ben Goertzel made the prediction while closing out a summit on AGI this month: 'It seems quite plausible we could get to human-level AGI within, let's say, the next three to eight years.' 'Once you get to human-level AGI,' Goertzel, sometimes called'father of AGI,' added, 'within a few years you could get a radically superhuman AGI.' While the futurist admitted that he'could be wrong,' he went on to predict that the only impediment to a runaway, ultra-advanced AI -- far more advanced than its human makers -- would be if the bot's'own conservatism' advised caution. Mathematician and futurist Ben Goertzel made the prediction while closing out a summit on AGI las week: 'we could get to human-level AGI within, let's say, the next three to eight years' Goertzel made his predictions during his closing remarks last week at the '2024 Beneficial AI Summit and Unconference,' partially sponsored by his own firm SingularityNET where he is CEO.

To come up with the new definition, the Google DeepMind team started with prominent existing definitions of AGI and drew out what they believe to be their essential common features. The team also outlines five ascending levels of AGI: emerging (which in their view includes cutting-edge chatbots like ChatGPT and Bard), competent, expert, virtuoso, and superhuman (performing a wide range of tasks better than all humans, including tasks humans cannot do at all, such as decoding other people's thoughts, predicting future events, and talking to animals). They note that no level beyond emerging AGI has been achieved. "This provides some much-needed clarity on the topic," says Julian Togelius, an AI researcher at New York University, who was not involved in the work. "Too many people sling around the term AGI without having thought much about what they mean."

Ben Goertzel said the sky's "not even the limit" when it comes to the potential impact of artificial general intelligence. The co-creator of the social humanoid robot Sophia says artifical general intelligence (AGI) and super AGI are mere decades away, and he warns that the subsequent disruption from these artificial intelligence (AI) models will cause a significant amount of political and economic "mayhem" before massive benefits to humanity are seen. Speaking with Fox News Digital on the global aspects of the transition from the present day to AGI, Dr. Ben Goertzel highlighted the need to develop a beneficial, compassionate super general intelligence model to ensure humanity flourishes. Often referred to as the "singularity" – the point AGI exceeds human intelligence and reasoning – humankind will be at the whim of the AI model's motivations and behaviors. AI researchers and futurologists have repeatedly said that this inflection point is still decades away. Given the current timeline of AI acceleration, Goertzel concurred with friend and computer scientist Ray Kurzweil, calling it a "fair approximation" that human-level AGI will be created around 2029.

Artificial intelligence scientist Ben Goertzel said that generative AI models and tools like ChatGPT could replace many tasks performed by humans. Most people's jobs do not require'incredible' creativity or innovation, added Goertzel, who is also the co-developer of Sophia, the humanoid robot. He said that AI could be used for tasks like copy editing, writing sport score summaries, and weather reports, as reported by ZDNet. He further said with these tools automating major portions of people's jobs would lead to industry reshuffling and reassigning job duties. He, however, said that AI will not be able to replace jobs that rely on human interaction and the ones that require creativity. Generative AI replacing or automating tasks has been a hot topic of discussion.

SingularityNET CEO Ben Goertzel teased some of the company's new plans. In detail, Geortzel shared that SingularityNET is aiming to launch projects much smarter than ChatGPT on its network. Furthermore, Goertzel believes that an AI revolution in the blockchain space would transform peoples' perceptions towards crypto. However, Goertzel also shared that it will take a while to launch these projects. "It's going to take a little while, but we know how to do it. We're working on it," he said during an interview with Crypto Influencer Ben "BitBoy Crypto" Armstrong.

As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60 % of the Mizar theorems in the hammer setting. We also automatically prove 75 % of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growing a corpus of millions of ATP proofs with training increasingly strong AI/TP systems on them. We also present a selection of Mizar problems that were proved automatically.

We describe a cognitive architecture intended to solve a wide range of problems based on the five identified principles of brain activity, with their implementation in three subsystems: logical-probabilistic inference, probabilistic formal concepts, and functional systems theory. Building an architecture involves the implementation of a task-driven approach that allows defining the target functions of applied applications as tasks formulated in terms of the operating environment corresponding to the task, expressed in the applied ontology. We provide a basic ontology for a number of practical applications as well as for the subject domain ontologies based upon it, describe the proposed architecture, and give possible examples of the execution of these applications in this architecture.

Artificial intelligence (AI) has become an integral part of our everyday lives, found in everything from social media algorithms to e-commerce and navigation, but not everyone is comfortable with the idea. The key to winning over a skeptical public could be a family of robot "sisters." Sophia, Grace and Desdemona are humanoid robots, each programmed with sophisticated AI. The oldest of the three, Sophia, was first activated in 2016 and gained widespread attention, mostly for her looks. Whereas most artificial intelligence operates discretely out of sight, powering things like software and smartphones, Sophia is designed to look like a young woman and gained celebrity status as the face of AI.

Humanoid robots have long been a common staple of science fiction. Arnold Schwarzenegger killing machines and synthethics like Bishop from the Aliens movies have long been confined to realms of fantasy. However, a wave of innovative tech companies are actively trying to make those visions a reality. "There is a chance that one day life will imitate art and robots and people will look alike," according to a recent report from research firm GlobalData. "If and when that happens, societies will face an ethical conundrum: what rights to give to non-human creatures that look like us?"