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.

So WTF is Settlement Quality AI Data (SQAID) for microgrids?!

I’ve been racking my brain searching for the bridge between my profession as a Senior Energy Professional in the energy and environmental sector and my new ventures in artificial general intelligence (AGI). And, I’ve discovered the answer…Settlement Quality AI Data (SQAID) for microgrids.

Here’s a bit of history that might help the understanding.

I’ve been active in the California energy sector for since 1995 and have guided public and private organizations through the intricate process of implementing energy and environmental programs. These programs include advanced metering infrastructures, competitive green power supply, distributed and utility scale generation, performance contracting agreements and solar power purchase agreements.

As the Vice President of Sales & Energy Services for Commonwealth Energy Corporation, I managed the San Diego Association of Governments (SANDAG) account and sold over 100 MW of renewable electricity services to their SANDAG members.

When I first arrived at Commonwealth the market was in chaos and the California Energy Crisis looming. As an Energy Service Provider, we were mandated by the California Public Utility Commission to comply and to seamlessly integrate all policy and activities with the Investor Owned Utilities (IOUs) and the California Independent System Operator (California ISO).

At the same time, the IOUs began building Advanced metering infrastructures (AMIs) throughout the state. An AMI is an integrated system of smart meters, communications networks, and data management systems that enables two-way communication between utilities, service providers and customers.

As per the California ISO, “Metering and telemetry ensure operational accuracy. Accurate metering of electricity generated or consumed provides key data inputs for accurate settlement calculations. Direct measurement of a generator or load participant through telemetry allows the ISO to manage and monitor power generation in real-time.”

Therefore the functions of the Meter Service Providers (MSPs) and Meter Data Management Agents (MDMA) were crucial to provide Schedule Coordinators (SCs) with…Settlement Quality Meter Data (SQMD).

Meaning all meter data went through a vigorous Validation, Editing and Estimation (VEE) process and then parceled for various functions related to customer billing, load and financial settlement, load profile creation and procurement forecasting, demand response programs, etc.

So WTF is Settlement Quality AI Data (SQAID) for microgrids?!

By definitiion, microgrids are modern, small-scale versions of the centralized electricity system. They are a localized group of electricity sources and loads that normally operates connected to and synchronous with the traditional centralized electrical grid (macrogrid), but can also disconnect to “island mode” — and function autonomously as physical and/or economic conditions dictate.

SCADA is a control system architecture that uses computers, networked data communications and graphical user interfaces for high-level process supervisory management, but uses other peripheral devices such as programmable logic controllers and discrete PID controllers to interface to the microgrid.

The SCADA computer system handles operator interfaces that enable monitoring and the issuing of process commands, such as controller set point changes. However, the real-time control logic or controller calculations are performed by networked modules that are connected to field sensors and actuators.

So Why is any of this Important?!

So imagine the value created by SQAID, instantaneously read from Smart AI meters, devices and sensors by an AI Schedule Coordinator which controls microgrid operations and facilitates authority having jurisdiction compliance requirements. There could be billions of energy dollar savings created by the use of a common SQAID algorithm.

Imagine an AI Agent using SQAID and acting in the capacity of the traditional MSP, MDMA, SC and SCADA process. And served from a microgrid, guaranteeing reliability, health and life safety, security, and most importantly human and AI comfort and long-term sustainability.

Instantaneously!

About the Author

Patrick A. Weller is known for his authorship of the Smart Modernization and Retrofit Technology Solutions (SMARTS) Program recognized by the American Recovery and Reinvestment Act of 2009. His historic monetization of ARRA investment capital was achieved by using an ironclad investment grade audit and a standard of care that withstood the “test of scrutiny” of the federal, state, local government and Investor Owned Utilities.

Related online information:

City of Grover Beach Goes Green: https://www.grover.org/ArchiveCenter/ViewFile/Item/111

Datapult AMI: https://www.elp.com/articles/2001/07/lge-enertech-selects-datapult-as-provider-of-energy-monitoring-services.html

SOL DOMINIQUE I | Dennys W. Sacramento Power Purchase Agreement: https://youtu.be/EMYsIiKZWdk

References: California ISO: http://www.caiso.com/Pages/default.aspx; Wikipedia https://en.wikipedia.org/wiki/Microgrid

SingularityNET and NR Capital: AI Technologies that Drive Global Trade

SingularityNET and NR Capital: AI Technologies that Drive Global Trade

(L-R) Surina Jones, GM Six Kin Development; J.J. Ho, Director, NR Capital; Tom James, CEO NR Capital; Scott Jones, SingularityNET Partner and MD Six Kin Development

We’re excited to join forces with Singapore FinTech firm, NR Capital, to develop revolutionary new AI-driven solutions for the commodity finance. These SingularityNET agents from our collaboration will be used to drive and automate global trade.

“We are very excited to work with SingularityNET and Six Kin Development, world leaders in AI and Machine Learning technologies. We all share a common vision in the application of AI to improve the efficiency of real world economy processes. This collaboration will greatly assist us in our goal to revolutionize and disrupt the existing way that bulk physical commodity shipments are managed.”
— Tom James, CEO, NR Capital

As a provider of AI Consulting Services and the local representative of SingularityNET in Singapore, Six Kin Development is providing the needed resources and capabilities to fuel this partnership.

“We’ve had the pleasure of getting to know NR Capital and Tom James over the past few months through our engagements in various technology oriented community events, and I’m thrilled that we’re now able to team up, along with SingularityNET, and take our relationship to the next level. The commodities trade finance ecosystem is poised for disruption, and Tom and his team are putting together an impressive strategy for revolutionizing the business. We look forward to supporting them in this endeavor!”
— Scott Jones, Managing Director, Six Kin Development

Commodity Trade Meets Supply Chain

The commodity market covers all commerce of raw and primary products, divided between hard commodities such as gold and oil and soft commodity agricultural products such as wheat and coffee. Within the metal commodities market, copper and iron amount to $91 Billion and $115 Billion respectively, while the oil market alone amounts to $1.72 Trillion.

“These markets are inefficiently managed today due to an inability to process the vast volumes of data. Through SingularityNET’s AI capabilities, supply chain finance can be disrupted via AI analysis and automation at scale.”

SingularityNET’s Role

Any AI-driven innovations in commodity finance could create billions in value. SingularityNET gives the world access to AI to automate entire supply chains across industries and nations. The value created, as well as corporations in desperate need for supply-chain automation, could be staggering.

In a joint Memorandum of Understanding (MOU) signed in December 2017, NR Capital, SingularityNET and Six Kin Development agreed to collaborate in pursuit of several objectives, including digitization of supply chain and application of Artificial Intelligence to fully automate and improve efficiency for the commodity trade finance business. The partners will also explore how to leverage SingularityNET’s decentralized AI marketplace to expose these new AI services to previously unreachable consumers around the world. We look forward to sharing the fruits of this partnership with the community going forward.

This partnership with NR Capital marks the first of many finance-AI collaborations for SingularityNET. We are creating the network infrastructure for a world of open and interoperable AI. This vision requires financial AI in force, and our partnership with NR Capital takes us one step closer to making SingularityNET the AI infrastructure for the financial world.


If you haven’t already, join our Telegram group today for the latest updates and announcements. We’re excited to share with you our achievements since the TGE completed.

SingularityNET has arrived, and we’re glad you’re a part of it,
The SingularityNET Team