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.

The metaverse is a novel concept that seems to often be misunderstood by the investment community. Although most notably discussed in the context of virtual reality and its associated hardware, the metaverse is actually a much broader concept than what it may seem to be. The metaverse today refers to the totality of digital worlds in which people both participate and create. The first credible metaverse products were MMORPGs (Massive Multiplayer Online Role-Playing Games) such as World of Warcraft. These were'first-generation' metaverse products owing to the fact that users were strictly limited to participation. Nonetheless, real world economics – and real world value – were created as a direct result of this extremely successful game.

Theoretical physics is to understand the natural world or universe by making a model of reality, to describe, explain, and predict physical phenomena by means of physical theories or models, as mainstream theories, proposed theories and fringe theories. Today's theoretical #physics is no more natural philosophy trying to embrace the whole nature and the physical universe. In essence, theoretical physics is largely mathematical physics intersecting ontology or metaphysics, #mathematics and physics itself. Theoretical physics and mathematical physics is a great training for your mind to develop an extraordinary intelligence, both general and specific. Without such a fundamental pre-training, it would be impossible to create the Real #AIModel as integrating most of human-like AI modalities, as Trans-AI Science.

The Jobs and Skills Summit being convened this week in Canberra sets out to address the employment challenges that Australia currently faces. But even as we respond to today's skills shortage, we must also keep an eye on the long-term consequences of Artificial Intelligence (AI) and machine learning on jobs. Fantasies in which AIs advance to the point of doing all of our jobs are seductive in some tech circles. Elon Musk has long promised fully driverless cars that will be safer than cars driven by humans. When these vehicles do arrive, they may delete the human Uber driver.

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner Human and machine powers are most productively harnessed by designing hybrid human- machine superintelligence (HMSI) cyber-physical networks in which each party complements each other's strengths and counterbalances each other's weaknesses. Software universe, as the web applications, application software and system software, source or machine codes, as AI/ML codes, programs, languages, libraries; V. Hardware universe, as the Internet, the IoT, CPUs, GPUs, AI/ML chips, digital platforms, supercomputers, quantum computers, cyber-physical networks, intelligent machinery and humans; How it is all represented, mapped, coded and processed in cyberspace/digital reality by computing machinery of any complexity, from smartphones to the internet of everything and beyond. AI is the science and engineering of reality-mentality-virtuality [continuum] cyberspace, its nature, intelligent information entities, models, theories, algorithms, codes, architectures and applications. Its subject is to develop the AI Cyberspace of physical, mental and digital worlds, the totality of any environments, physical, mental, digital or virtual, and application domains. AI as a symbiotic hybrid human-machine superintelligence is to overrule the extant statistical narrow AI with its branches, as machine learning, deep learning, machine vision, NLP, cognitive computing, etc. #machinelearning #deeplearning #artificialintelligence #nlp #algorithms #dataengineering

The number of variables is virtually numberless, all being studied in both functional roles, like vector-valued functions or y f(x) or x g (y), or both causal directions, direct and reverse. In an undirected simple graph of order n, the maximum degree of each vertex is n 1 and the maximum size of the graph is n(n 1)/2, and n(n 1)/2, if to include loops, what is responsible for the network effects.

"All men by nature desire to know." - Aristotle "He who does not know what the world is does not know where he is." - Marcus Aurelius "If I have seen further, it is by standing on the shoulders of giants." "The universe is a giant causal machine. The world is "at the bottom" governed by causal algorithms. Our bodies are causal machines. Our brains and minds are causal AI computers". The 3 biggest unknown unknowns are described and analyzed in terms of human intelligence and machine intelligence. A deep understanding of reality and its causality is to revolutionize the world, its science and technology, AI machines including. The content is the intro of Real AI Project Confidential Report: How to Engineer Man-Machine Superintelligence 2025: AI for Everything and Everyone (AI4EE). It is all a power set of {known, unknown; known unknown}, known knowns, known unknowns, unknown knowns, and unknown unknowns, like as the material universe's material parts: about 4.6% of baryonic matter, about 26.8% of dark matter, and about 68.3% of dark energy. There are a big number of sciences, all sorts and kinds, hard sciences and soft sciences. But what we are still missing is the science of all sciences, the Science of the World as a Whole, thus making it the biggest unknown unknowns. It is what man/AI does not know what it does not know, neither understand, nor aware of its scope and scale, sense and extent. "the universe consists of objects having various qualities and standing in various relationships" (Whitehead, Russell), "the world is the totality of states of affairs" (D. "World of physical objects and events, including, in particular, biological beings; World of mental objects and events; World of objective contents of thought" (K. How the world is still an unknown unknown one could see from the most popular lexical ontology, WordNet,see supplement. The construct of the world is typically missing its essential meaning, "the world as a whole", the world of reality, the ultimate totality of all worlds, universes, and realities, beings, things, and entities, the unified totalities. The world or reality or being or existence is "all that is, has been and will be". Of which the physical universe and cosmos is a key part, as "the totality of space and times and matter and energy, with all causative fundamental interactions".

If you ever get a chance, I HIGHLY recommend talking to people. Not just people around you *most* of the time, like your immediate or extended family, or the nosy neighbor, or the mail professional who happily delivers package upon package of online orders to your porch on what seems to be an hourly basis. No, I mean different people, ones you've never met before, especially around the world. I have had the unique opportunity to visit many countries in my still short life, and experienced several cultures, several languages, several routines and rites. I've broken bread around the world, and visited hundreds of heritage sites learning about the past and present of the indigenous.

The AI field needs major breakthroughs in its thinking to achieve continuous, sensory-gathered, machine learning from the environment on unlimited subjects. The way to motivate such dramatic progress is to articulate and endorse research goals for machine behavior so ambitious that limited-domain, problemsolving knowledge representation methods are disqualified at the outset, thus forcing ourselves to produce valuable new "thoughtware". After exploring why the tendency to associate intelligence with problem-solving may be a mental roadblock to further progress in AI science, some preliminary thinking tools are introduced more suitable for sensory learning machine rcscarch These include lifelong sensorimotor data streams, representation as a symbolic recording process, knowledge transmission, and the totality of knowledge. One day, Professor Nokemoff, a distinguished AI professor of robotics at a leading institution, called in a grad student to hand out a thesis project. "Build me a robot that can sort two different parts coming down a conveyor belt.

I was 8-years-old and remember being both terrified and intrigued about something that was being talked about everywhere. This wasn't a storyline out of a science fiction movie or novel, this was real, and happening here on Earth. Millions of people were going to witness something that maybe happens a couple of times in our lifetime: A total solar eclipse. Our teachers were planning lessons about this incredible celestial event. Chalkboard diagrams, planetary mobiles and handmade viewing devices were being created out of shoe boxes.