What is AGI artificial general intelligence?

Artificial general intelligence (AGI) is the intelligence of a machine that could successfully perform any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies.

There are four types of artificial intelligence: reactive machines, limited memory, theory of mind and self-awareness.

  • Reactive machines. …
  • Limited memory. …
  • Theory of mind. …
  • Self-awareness.

Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. … For most of its history, AI research has been divided into subfields that often fail to communicate with each other.

The basic elements of artificial intelligence are…

  • Problem Solving mostly deals with constraint satisfaction problems, Solve by Search.
  • Certain knowledge representation, reasoning of it and plan of execution. First order logic is dealt here.
  • Uncertain knowledge representation and its reasoning. …
  • Feature Learning. …
  • Perception, communication and action taken by agents.

Major sub-fields of AI now include: Machine Learning, Neural Networks, Evolutionary Computation, Vision, Robotics, Expert Systems, Speech Processing, Natural Language Processing, and Planning.

A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. … Some argue that advances in artificial intelligence (AI) will probably result in general reasoning systems that lack human cognitive limitations.

The branches of artificial intelligence

  • Computational creativity –
  • Machine learning. Neural networks – Hybrid neural network – …
  • Fuzzy systems –
  • Evolutionary computation, including: Evolutionary algorithms – Genetic algorithm – …
  • Probabilistic methods including: Bayesian network. Hidden Markov model. …
  • Chaos theory.

Google’s artificial intelligence (AI) is much smarter than Apple’s Siri, according to a report from three Chinese researchers. … But while Google’s AI leads the tech pack, it has a long way to go before it comes close to human intelligence; the average 6-year-old has an IQ of 55.5, according to the report.

Artificial Intelligence (AI) and Machine Learning (ML) are two very hot buzzwords right now, and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to some confusion.

There is Artificial intelligence, and there is Artificial general intelligence (AGI). The latter is a branch of the former. Microsoft Cortana is definitely an AI application, like all Natural language processing applications, but it’s not an AGI application, nor it aspires to be.

The field of artificial intelligence is essentially when machines can do tasks that typically require human intelligence. … Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data.

In addition, deep learning is used to detect pedestrians, which helps decrease accidents. Aerospace and Defense: Deep learning is used to identify objects from satellites that locate areas of interest, and identify safe or unsafe zones for troops.

Java, Python, Lisp, Prolog, and C++ are major AI programming language used for artificial intelligence capable of satisfying different needs in development and designing of different software.

LISP is another language used for artificial intelligence development. … LISP, unlike most AI programming languages, is more efficient in solving specific as it adapts to the needs of the solutions a developer is writing. It is highly suitable in inductive logic projects and machine learning.

 

SingularityNET Vision | 1.3 A Robust and Adaptive Software Architecture

In computer science terms, SingularityNET is essentially a distributed computing architecture or making new kinds of smart contracts to facilitate market interactions with AI and machine learning tools. The following design principles are incorporated throughout the design:

  • Interoperability: The network will be able to interface with multiple
    blockchains.
  • Data Sovereignty and Privacy: User data control and sharing comes
    with privacy-enabled controls on top of the network, and access is validated
    through smart contracts and the blockchain.
  • Modularity: Flexible network capabilities make it possible to create custom topologies, AI Agent collaboration arrangements, and failure recovery methods.
  • Scalability: SingularityNET will securely host both private and public
    contracts, so more scalable and resilient applications can be built on top
    of it with near zero transaction costs.

SingularityNET Agents can run in the cloud, on phones, robots, or other embedded devices. Via close collaboration with co-founding firm Hanson Robotics, SingularityNET is designed to foster the development of multiple species of robots as the next-generation interface for delivering AI services and applications, and fostering the emergence of global Artificial General Intelligence.

#WellerAGI

SingularityNet Whitepaper

SingularityNET Vision | 1.2 Acute Market Needs Addressed

SingularityNET meets an acute and accelerating market need. In the current economic and technological context, every business needs AI, but off-the-shelf AIs will rarely match a business’s needs. Only tech giants can hire armies of developers to build custom AIs, and even they have a hard time hiring enough AI experts to meet demand. SingularityNET provides an automated process enabling each business to connect existing AI tools together to build the solution it needs. By providing an easy means of configuring tools, it offers both customization and availability, while reducing the reduplication of effort involved in proprietary development, making the development process more efficient.

Many state of the art AI tools exist only in GitHub repositories created by grad students or independent researchers. This puts them out of the reach of anyone without the skills to install, configure, and run them. Most AI developers are academics, not business people, and have no easily-accessible marketplace to monetize their clever AI code.

In addition to their clever code, machine learning tools require datasets of sufficient size. Creating and managing such large datasets is beyond the means and capabilities of most AI developers, and the closed development model that currently prevails makes it hard for developers to share datasets.

SingularityNET launches these AI tools and datasets onto the marketplace, making them more accessible to end-users and developers, and giving developers a way to monetize their creations.

It is a sharing-economy marketplace for AI, that encourages collaboration between these tools and decentralized sharing of information, democratizing access to the benefits of AI. In accordance with these goals, SingularityNET will be an open network. Anyone can insert an AI Agent as long as the Agent shares information according to the SingularityNET API, and accepts/disburses payment according to SingularityNET’s economic logic. New AI Agents will come from AI software developers who want access to SingularityNET’s market, which will be the hub of open AI services.

We have a situation similar to the ones that spawned the creation of Uber and AirBnB: there is a large unexploited resource, a large market in need of that resource, and we are launching the tool to connect the two. The unexploited resource is AI algorithms and software existing on GitHub and elsewhere, and n need of this resource is the 99% of businesses that can’t afford its own team of AI experts.

SingularityNET Vision | 1.1 Inspiration

The concept of a Technological Singularity is increasingly widely accepted throughout the technology and business worlds. More and more, it is real- ized that within the next few decades there will be a transition to a new society and economy in which machine intelligence is the dominant factor; and novel digital and organic technologies acting on multiple scales will network together to produce emergent “global brain” dynamics of unprecedented complexity and sophistication [Bro97] [Kur06] [Vin93] [Goe07].

Humanity faces many challenges on the path to a positive Singularity; among these is the contemporary global economic system. In numerous respects, today’s standard financial mechanisms and institutions are not up to the task of serving as the economic engine of a smooth transition to a broadly positive Singularity. New, more flexible, open and rapidly adaptive economic structures and dynamics are needed [GGG16].

Blockchain provides a powerful tool for managing transactions in a Singularity- era economy [CB14] ; but blockchain is just a tool, and it must be used in the right way. A blockchain-based framework designed to serve the needs of AI Agents as they interact with each other and with external customers can enable the emergence of a collective intelligence. And it is critical that this framework be designed with positive principles in mind:

  • Democratic governance on specific issues – giving the community a voice in the system will tend to make the system act for the benefit of the community;
  • Encouraging innovative new Agents to enter the network, and creating the conditions for Agents to act in a manner that feeds the collective intelligence;
  • Directing a significant percentage of the network’s efforts toward causes of broad benefit.

SingularityNET has been designed to meet these requirements, via

  • Delivering intelligence services to corporations, individuals and organiza- tions;
  • Fostering the emergence of increasingly powerful distributed general intelligence;
  • Deploying artificial intelligence for ever-increasing benefit of as many humans and other sentient beings as possible.

SingularityNET is explicitly designed both to be highly valuable in the current context, and to lay the groundwork for the emergence of a future self-modifying, decentralized “artificial cognitive organism” with the eventual potential for general intelligence and beneficial ethical characteristics beyond the human level. It is a practical design inspired by long theoretical thinking and prototyping on the part of the founders regarding concepts such as Artificial General Intelligence [Goe16a], Open-Ended Intelligence [WV16] and the Global Brain [Hey07]. #WellerAGI

SingularityNet Whitepaper

I Am Now | A decentralized, open market and inter-network for AIs

December 19, 2017

Abstract

The value and power of Artificial Intelligence is growing dramatically every year, and will soon dominate the internet – and the economy as a whole. However, AI tools today are fragmented by a closed development environment; most are developed by one company to perform one task, and there is no way to plug two tools together. SingularityNET aims to become the key protocol for networking AI and machine learning tools to form a coordinated Artificial General Intelligence.

SingularityNET is an open-source protocol and collection of smart contracts for a decentralized market of coordinated AI services. Within this framework, the benefits of AI become a global commons infrastructure for the benefit of all; anyone can access AI tech or become a stakeholder in its development. Anyone can add an AI/machine learning service to SingularityNET for use by the network, and receive network payment tokens in exchange.

SingularityNET is backed by the SingularityNET Foundation, which operates on a belief that the benefits of AI should not be dominated by any small set of powerful institutions, but shared by all. A key goal of SingularityNET is to ensure the technology is benevolent according to human standards, and the network is designed to incentivize and reward beneficial players. #WellerAGI

SingularityNet Whitepaper