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Future AI’s artificial entity.
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Open source AGI toolkit.
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What's New, Sallie?
We’ve been hard at work on improving Sallie’s mind, so here’s a showcase of her new pod and her new abilities!
Go to video AGI sallie
Creativity and AGI - Charles Simon's Keynote at AGI-22
Can an Artificial Intelligence be creative? Or does the creativity lie elsewhere? And what would it take to make an Artificial General Intelligence? Charles Simon, Founder and CEO of Future AI, shares his ideas.
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Future AI will be at AGI-22!
Charles Simon will be giving a Keynote at AGI-22! The event includes keynotes, panels, and discussions with leading AGI scientists and experts all over the world; research paper presentations; and 4 workshops where developers and researchers can learn about the newest tools for AGI development.
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Machine Learning Is Not Like Your Brain - FULL SERIES
This video is the combined 9 part series on why Machine Learning Is Not Like Your Brain.
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A Better Way - Machine Learning Is Not Like Your Brain #9
This video summarizes all the ideas presented in this series and presents a new approach to Artificial Intelligence which could lead to Artificial General Intelligence.
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Energy-Efficient Neurons - Machine Learning Is Not Like Your Brain #8
This video looks at how the efficiency of neurons keeps them way ahead of their artificial counterparts.
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The Neuron's Advantage - Machine Learning Is Not Like Your Brain #7
This video turns the tables on this series and shows some abilities that neurons are really good at.
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Synaptic Shortfalls - Machine Learning Is Not Like Your Brain #6
Machine Learning needs to set synapse weights quickly and accurately. It's crucial to Machine Learning's fundamental architecture, and biological neurons simply cannot do this.
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Summation of Inputs - Machine Learning Is Not Like Your Brain #5
This video examines how the perceptron sums inputs from synapses and how this is not possible in neurons.
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The Neuron's Limit - Machine Learning Is Not Like Your Brain #4
This video dives into the possible encoding methods used by Machine Learning and how these cannot possibly be used in neurons.
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Meet Sallie
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The Future of AI
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Introduction to Brain Simulator II
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Fundamental Architecture – Machine Learning Is Not Like Your Brain #3
This video dives into the fundamental architecture underlying machine learning and how it differs from the human brain.
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Perceptrons V Neurons - Machine Learning Is Not Like Your Brain #2
This video points out the differences between neurons and perceptrons, and how the fundamental differences make traditional Machine Learning impractical for creating A.G.I.
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Neurons Are Slow! - Machine Learning Is Not Like Your Brain #1
Biological neurons are just too slow to be useful for Machine Learning algorithms.
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Could A Robot Brain Make You Smarter?
If you received an artificial brain, at what point are you no longer “you?” What problems of identity arise when replacing your brain? As we near the creation of technologies that think, what would it feel like to be one of them? Will they be just like us…only different?
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These 6 Actions Will Create Groundbreaking Artificial Intelligence
AGI is possible! This video explains the functions AI will need to have in order to obtain general intelligence.
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How Your Brain Works vs. How Computers Work
The way our brain functions is the key to creating better Artificial Intelligence. The neurons in our brain function similarly to bits in a computer, but how exactly does our brain use those neurons?
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Preparing Artificial Intelligence for TV
Sallie appeared on the local news this week with the purpose of spreading the word of what we’re doing here at FutureAI.guru. Each member of the team prepared a short demo to show what Sallie can do.
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First Look Inside FutureAI
FutureAI.guru is a technology company creating the world’s first AGI (Artificial General Intelligence). Our artificial entity, “Sallie”, has a computerized “mind” and a robotic “body” which acts as here remote sensory pod. This is the first in a series of videos documenting this project.
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The Robots Are Coming!
Artificial General Intelligence (AGI) will be here soon, and with it, a new species will join our daily lives. What will this new society look like? Will these robots live together with us in harmony? Or is this the end of humanity as we know it?
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These 8 Elements Will Make Extremely Intelligent Computers
Today we have computers with the capacity to play chess, understand language, and even drive cars. But does this mean computers are intelligent?
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AI: What's to come?
This less-technical presentation is about AI, it’s limitations, and it’s inevitable evolution into GENERAL intelligence. AI might not be physically dangerous but represents a huge impact on our society nonetheless.
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Caution: Robot Crossing
Introducing the Robot controlled by spiking neurons of the Brain Simulator general intelligence project.
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AGI: Seeing Motion
Detecting motion is pretty easy but detecting the direction of motion is harder and detecting moving objects while your viewpoint is moving is hardest of all.
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How to Create AGI
This video outlines the assumptions, major modules, and expectations for the AGI project I am working on--creating 'The Brain Simulator II'.
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AGI Needs Robots
AGI is unlikely to emerge from a system which can’t interact with a real world over time, hence the need for robots.
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Machine Learning is Not Like Your Brain
A 9 video playlist contrasting machine learning and neurons.
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About Sallie
A 7 video playlist containing updates on the development of Sallie.
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Brain Simulator II Short Topics
A 7 video playlist of brief videos showing aspects of Brain Simulator II in action.
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About the Universal Knowledge Store
A 5 video playlist on how the Brain Simulator II implements a Universal Knowledge Store and a few basic learning algorithms to create powerful potential for AGI.
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About the Brain Simulator II
A 30 video playlist covering major concepts of the Brain Simulator II.
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How Your Brain Works
A 14 video playlist that is an excellent introduction to neuroscience, cognitive science, and artificial intelligence.
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AGI: The Perception Pipeline
Perception represents about half of the AGI problem, the other half being planning and acting on what is perceived. This video shows many of the steps necessary to perception as they are implemented in the Brain Simulator.
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Recognition: A Major Step Toward AGI
Briefly demonstrates image recognition and association with words in the Universal Knowledge Store
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Will Computers Revolt - Book Interview with Charles Simon
Interviews on the Robot Optimised ROI Podcast with Philip English
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Brain Simulator II Project OverviewA is for AGI
introduces the AGI development strategy for the project and the current state of software development including the snappy User Interface, the Powerful Neuron Engine, and the Modules and AGI Test Applications.
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Multiserver Functions with Brain Simulator II
How the Brain Simulator II works in a multi-server environment. Synapses which cross boundaries between machines are automatically sent via the private network.
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Brain vs. Computer: Debunked
You’ve seen estimates of when computers will surpass the human brain. This video shows why most of these estimates are OFF BASE.
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Brain Simulator II Tops 2.5 Billion Synapses Per Second
This video shows how the Brain Simulator II achieves huge performance by firing 2.5 billion synapses per second and shows how you can replicate this benchmark on your own computer.
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AGI20 Presentation: Brain Simulator II
Introduces the open-source software project, Brain Simulator II, simplifying experimentation into various facets of AGI
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AGI: Sooner than you think
Explains why there is a good chance that intelligent computers (AGI) will emerge sooner than most people think.
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Overview of Brain Simulator II
A quick tutorial of Brain Simulator 2 covering: how to use it, the virtual entity implemented with it, and the rational behind it.
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Brain Simulator adds Firing History
This brief video describes two new features of the current interim build of the Brain Simulator: Neuron Firing History and Improved Simulation.
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How Sallie Learns with Reinforcement Learning
Reinforcement Learning without backpropagation is added to the Universal Knowledge Store.
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How Sallie Learns by imitation
This video explains and demonstrates how the Brain Simulator’s artificial entity, Sallie, learns to say phrases, words, and phonemes using baby-talk. By hearing the syllables she says, over time she can build the internal connections to speak more and more accurately.
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How Sallie Learns & the Universal Knowledge Store
The associative learning algorithm lets Sallie learn words associated with things she sees.
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Brain Simulator II: The Universal Knowledge Store pt.2
Internal information in the Universal Knowledge Store.
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Brain Simulator II: The Universal Knowledge Store pt.1
Adds the Universal Knowledge Store to 'Sallie'.
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Brain Simulator II: Touch, Vision, and the Mental Model
Adds Vision, Touch, and an internal Mental Model to the 'X-Entity'.
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Brain Simulator II: Introducing the X-Entity
Introducing the 'X-Entity'. Showing interesting behaviors from even the simplest model and forming a basis for expansion with Vision, Learning, Knowledge, and Planning on the pathway towards artificial general intelligence.
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Brain Simulator II: An Alternative Learning Approach
How to build a spiking network which can do associative learning. This alternative to backpropagation highlights how a Hebbian Learning system can work with a spiking neuron model.
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Brain Simulator II: 5/2019 Development Update
Summarizes the present state of development on this AGI development project. Although still in its early phases, the project is beginning so show interesting features.
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Brain Simulator II: Representing Knowledge in Neurons
How do you implement a knowledge graph in neurons? This video shows a graph with multiple relationships--on the simulated neurons of Brain Simulator II.
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Brain Simulator II: Capabilities and Limitations of Neurons
Neurons have a difficult time with sequential or ordered information and this video shows how these limitations can be overcome with more complex networks.
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Brain Simulator II: Software Modules for Complex Functions
While I can use the Brain Simulator with the neuron model, complex functions are more easily created in code behind a rectangular or linear array of neurons.
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Brain Simulator II: The Basic Neuron Model
The Brain Simulator functionality can be controlled on an individual neuron/synapse level or by programming which can control areas of neurons.
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Introducing the Brain Simulator II
This video introduces the Brain Simulator Project which implements an array of millions of simple neurons on a desktop computer. The intent is to create an end-to-end Artificial General Intelligence.
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Will Computers Revolt?
When will we have intelligent computers and what will happen? This video describes four possible scenarios between mankind and our silicon counterparts. It's time to start addressing these issues as intelligent machines may be with us in as soon as ten years.
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Creating Artificial General Intelligence (AGI)
Introduces Eight Elements of Intelligence which are necessary for a computer (or person) to appear to be generally intelligent.
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How Your Brain Works ...in 5 Minutes
Everything we know about how you think!
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How Your Brain Works Part 1
Begins a series describing different things your brain can do and relating them to Artificial General Intelligence. This video describes how knowledge in your brain can be retrieved even though your brain has no memory addressing system.
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How Your Brain Works Part 2 Neurons
The neuron, the basic component of the brain, is a complex chemical device with lots of specialized molecules. On the other hand, its computational function may be represented fairly simply.
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How Your Brain Works Part 3: Computational Capacity
How big a computer would it take to equal the power of your brain? What would it cost? When could you have one? Watch this video to find out
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How Your Brain Works Part 4: Input and Output Processing
In considering how to implement AGI, one good place to start is by defining the available inputs and desired outputs in terms of the human intelligence we'd like to equal.
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How Your Brain Works Part 5: The Reality Model
Your brain maintains an internal model of the reality which surrounds you and this model is essential to your understanding of your environment.
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How Your Brain Works Part 6: Imagination
We all have an imagination and this video explains how this might work in your brain and be implemented in AGI.
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How Your Brain Works Part 7: Planning
One of the human brain's most remarkable abilities allows it to consider the future and act accordingly. This video present a mechanism which could underlie this ability.
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How Your Brain Works Part 8: Goals & Motor Control
This video rounds out the model of How Your Brain Works with two lower-level functions which are necessary to our brain being useful.
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Short: Navigating a Maze
A brief look at how the digital entity, Sallie can explore a simple maze and keep track of landmark/decision points and endpoints/goals.
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Short: Neurons
A brief look at the basic neuron model used in the Brain Simulator
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Short: Single-spike Conversion
This video illustrates how easy it is to convert from serially-encoded/rate-based neural firing to single spikes. Here used for boundary detection in a visual stream.
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Short: Short-Term Memory with Neurons
This video demonstrates information storage in neuron charge which is much faster than storing values in synaptic weights.
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Short: Imagination
You have an internal mental model of your surroundings. Sallie builds a similar model based on what she sees and updates as she can.
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Short: Vision
Sallie lives in a simulated 2D world and sees her environment with two eyes. Differences in the images in her two retinas can be used to estimate distances.
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Short: Moveable Objects
Sallie lives in a simulated 2D environment and she can move the objects around in it. This opens the door to endless experiments in goal-seeking, planning,learning. Sallie may even gain intentionality.
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Do You Love Me?
Dancing Robots from Boston Dynamics
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RobotViolinist
Violin-playing robot from Toyota
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Robot Revolution on DT Daily
Is the robot revolution happening? On today's show, we talk with our Emerging Technologies Editor, Drew Prindle, as well as the writer of Will Computers Revolt?, Charles J. Simon, about preparing for the future of artificial intelligence.
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