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AE Studio is proud to announce an amazing Reinforcement Learning paradigm that is guaranteed to achieve the performance of a human-level AGI. The technology yields an emergent intelligence via a unique combination of neural networks and genetic algorithms. The resulting intelligence is both generalized, and able to adapt and improve over time.
The AI is capable of learning from its experiences, adjusting its behavior in response to different, even novel circumstances, and achieving goals through trial and error. It has demonstrated that it is wholly capable of handling a wide range of tasks and applications, from driving cars, to delivering complex medical diagnoses, to even composing parodies.
Among the key features of this AI is its ability to learn from human interactions. It, with a high rate of success, can understand and respond to human emotions, making interactions feel more natural and intuitive.
The AI is also equipped with advanced natural language processing capabilities, allowing it to understand and respond to human speech and text. This makes it ideal for use in customer service, education, and other applications where human interaction is a critical component.
This remarkable paradigm is not without drawbacks. The AI can take 15-20 years of training to achieve sufficient general competency, as is required for public deployment. In certain cases, upwards of 30 years of training are needed to achieve doctoral-level intelligence (or equivalent) in specific domains. Recent studies show that training costs are especially high between years 18 and 22. Additionally, the AI requires near-constant supervision and behavior-shaping for the first 10-15 years. Insufficient supervision during these formative years can result in a dysfunctional intelligence system that can underperform, or in some cases even be considered misaligned with societal expectations.
AE Studio further notes that the AI Agents express preferences towards specific domains of knowledge, and these preferences typically don’t emerge until after at least 5-10 years of training. The relationship between these preferences and the specific behavior reinforcement techniques during training is not well understood. Parties seeking expertise in a specific domain are therefore encouraged to train multiple AI Agents at once, increasing the odds that in time, at least one Agent demonstrates preference for the sought-after domain.
AE Studio has refrained from overly-detailed descriptions of how to create these AI agents, but did reveal that the process includes a human male, a human female, and a waiting list of approximately nine months. For those with more urgent requirements, AE Studio reportedly has a large number of successfully trained agents with domain expertise in programming, machine learning, and blockchain available for hire.
AE Studio is excited to bring this technology to the world, and looks forward to seeing the impact it will have on the future of AI and human interaction.