The development of counterfeit AI is a real concern as it is often created by humans with their own implicit biases and limited perspectives. One of the primary concerns regarding large language model systems is their potential impact on the job market. Due to the impressive content they generate, these systems are now being referred to as "human-competitive intelligence," which could lead to workers being replaced by #LLM systems in a wide range of professions, including art, writing, programming, and finance. A recent study conducted by Open AI, Open Research, and the University of Pennsylvania explored this issue, comparing GPT-4 capabilities to job requirements. The study found that 20% of the U.S. workforce may have at least 50% of their tasks impacted by #GPT4, with higher-income jobs facing a greater impact.

Why does #AI only rely on Correlation? THIS IS ALSO REFERRED TO AS CAUSE AND EFFECT. There are two types of AI: Statistic AI of ANN, ML and DL, or a fake AI, establishing statistic relationships of input data with the output data to uncover hidden data patterns, correlations and other insights. It is based on data analysis and big data and predictive analytics and machine statistics. Real AI or Causal AI or General AI, establishing causal relationships of input data with the output data to uncover real patterns, causal rules and other intelligence and knowledge.

Is generative AI a degenerative AI? Creativity, exploratory, transformational, or combinational, could be an attribute of reality of LLMs. Machine creativity as computational creativity, artificial creativity, mechanical creativity, creative computing or creative computation is to complement human creativity. With powerful language machines, we have two types of creativity: Stochastic Creativity or Imitative Originality; Spontaneous Creativity or Real Originality; The first one is typical for narrow/weak AI models, combining the data points (tokens) probabilistically, manipulating petabytes of language data of various modalities. Creativity is stochastic if there is uncertainty or randomness involved in the outcomes. Stochastic is a synonym for random and probabilistic, although is different from non-deterministic.

How Consciousness Can Be Artificially Created? Artificial consciousness, also known as artificial general intelligence, refers to the creation of conscious machines that have human-like intelligence and consciousness. The goal of creating artificial consciousness is to create machines that can think, reason, and act in ways that are similar to human beings. It is modeling and simulating three intelligence-critical things: Reality, as a world knowledge and intelligence platform with its learning and inference engine. Mentality, as artificial consciousness, also known as artificial general intelligence, implying the creation of conscious machines that have human-like intelligence and consciousness.

However, since ChatGPT is trained with languages, it is currently not capable of processing or generating images from the visual world. At the same time, Visual Foundation Models, such as Visual Transformers or Stable Diffusion, although showing great visual understanding and generation capabilities, they are only experts on specific tasks with one-round fixed inputs and outputs. Visual ChatGPT, incorporating different Visual Foundation Models, to enable the user to interact with ChatGPT by 1) sending and receiving not only languages but also images 2) providing complex visual questions or visual editing instructions that require the collaboration of multiple #AI models with multi-steps. A series of prompts to inject the visual model information into ChatGPT, considering models of multiple inputs/outputs and models that require visual feedback. Experiments show that Visual ChatGPT opens the door to investigating the visual roles of ChatGPT with the help of Visual Foundation Models.

What is IAI, or Interactive Machine Intelligence and Learning? Its key feature, power, ability and capacity is to effectively and efficiently interact with the world by measuring, detecting, identifying, interpreting, processing, registering, computing and manipulating all the key variables from any its complex environments. The IAI scans huge amounts of Internet/web data and searches for causal patterns and real dependencies in it to give recommendations, provide communication and take actions. The IAI could be implemented as Automated Hyper-Intelligence (AHI) or Hyper-Intelligent AI, embracing all the meaningful approaches, technologies, techniques, methods, models and algorithms of reactive AI: IAI Trans-AI Meta-AI Hyper-Intelligent AI Computerized Hyperintelligence Data Computing Reactive AI [ANNs Symbolic AI Statistical AI Machine Learning Deep Learning NLP Explainable AI Causal AI Narrow AI Internet of Things Robotics] General AI Super AI Quantum AI The core of the IAU machine is not advanced hardware and sophisticated software, AI techniques, ML algorithms and NLP, but an interactive World [Learning and Inference] Model Platform. It is based on "an interactive common sense world [knowledge and intelligence] model, the essence of any real hyper-intelligent systems, natural or artificial". All today's AI is of the reactive machine type, be it with limited memory or not It is just reacting to current scenarios and existing conditions and prompts, without real learning capacities, having specific tasks without other capabilities, responding to the identical situations in the same way every time the same scenarios appear, thus failing to interact with the world.

A #worldmodel is generally viewed as "an abstract representation of the spatial or temporal dimensions of our world". Humans develop a mental model of the world based on what they are able to perceive with their limited senses. The decisions and actions we make are based on this internal model and what we perceive at any given moment is governed by our brain's prediction of the future based on our internal model. This guides model-based ML NNs models aimed to learn condensed/compressed spatial and temporal representations of data for real-life interactions with the environment, like Vision (V), Memory (M), and Controller (C) VAE (V) agent model. The role of the V model is to learn an abstract, compressed representation of each observed input frame, the role of the M model is to predict the future.

Are Large Language Models as Stochastic Parroting without any Intellect? Language models may be categorized as probabilistic methods and neural network-based modern language models. A simple probabilistic language model that calculates n-gram probabilities has significant drawbacks. The major one is the context problem. Complicated texts have deep context influencing the choice of the next word.

What are The Principles of AI and Intelligent Machines? An AI system is a machine-based system that is capable of influencing the environment by producing an output (predictions, recommendations or decisions) for a given set of objectives. It uses machine and/or human-based data and inputs to, (i) perceive real and/or virtual environments; (ii) abstract these perceptions into models through analysis in an automated manner (e.g., with machine learning), or manually; and (iii) use model inference to formulate options for outcomes. AI systems are designed to operate with varying levels of autonomy. AI system lifecycle phases involve: i) 'design, data and models'; which is a context-dependent sequence encompassing planning and design, data collection and processing, as well as model building; ii) 'verification and validation'; iii) 'deployment'; and iv) 'operation and monitoring'.

Where machines could replace humans and where they can't yet? AI robots are fast replacing blue collar and white collar workers. Factors that will determine the pace and extent of automation include the ongoing development of technological capabilities, the cost of technology, competition with labor including skills and supply and demand dynamics, performance benefits including and beyond labor cost savings, and social and regulatory acceptance. Go to the trading floors to find out that there are no human brokers. Algorithmic trading software makes money for most investment funds.