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 Agent

SingularityNET

Build Status

Coverage Status

Documentation Status

SingularityNET allows multiple AI computing agents to work as a whole to provide various services in a distributed and decentralized way.

For the first time, we have a financial substrate in the blockchain that lets us align diverse AI technologies and functions into a coherent financial and cognitive whole. The SingularityNET architecture incorporating block-chain smart-contracts and automatic payment will let diverse AIs integrate together into a single dynamic intelligence. AI agents incorporating the OpenCog AGI framework, Google Tensorflow and other powerful tools, interacting within the SingularityNET; will bootstrap the research and development of an AGI economy.

Contents

Architectural Overview

There are seven major interacting components in the SingularityNET architecture:

  • Network – the block-chain and smart-contract network used for agent negotiation and discovery
  • Agent – the agent which provides services and responds to service requests by other agents in the SingularityNET
  • Ontology – contains definitions of services available in SingularityNET. Ontologies are versioned and define the semantics of network operations.
  • ServiceDescriptor – a signed immutable post-negotiation description of a service which can be performed by an Agent
  • JobDescriptor – a list of jobs which tie a particular ServiceDescriptor with job-specific data like input and output data types, URLs, specific communication protocols etc.
  • ServiceAdapter – a wrapper for AI and other services which an Agent can invoke to perform the actual services required to perform a job according to the negotiated ServiceDescriptor.
  • ExternalServiceAdapter – a wrapper for interacting with external service agents in the SingularityNET universe.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

The agent server is responsible for communicating with AI Adapters which connect to individual AI systems and the rest of the network. You can run an Agent connected to the SingularityNET network as a server that runs stand-alone or as one that forwards requests for work to other servers running specialized AI services.

Prerequisites

SingularityNET runs on Mac OS X, or any Linux which has Python 3 installed and Docker or Docker for Mac installed. For Windows you’ll also need Git Bash/MinGW or Ubuntu on Windows 10 WSL.

The core devs regularly develop on Mac OS X Sierra, Linux Mint Mate 18.2, and Linux Ubuntu 16.04 LTS among others.

Docker and Docker Compose are used heavily, so you must have a recent version of Docker installed to take advantage of most of the automation and to isolate yourself from the dependency hell which often results from installing software with complex dependencies directly onto your host development OS.

The current development demo runs from a dev docker container which can be launched from your favorite bash terminal using our helper tool shell script: tools.sh.

./tools.sh dev

This will bring up a set of docker containers and expose port 8000 to the local host machine. Visit the demo via:

http://localhost:8000

in a modern browser.

Notes on running on Ubuntu under Windows Subsystem for Linux (WSL, Bash on Windows, etc) The trick to this is to install docker on Windows, then ensure the docker is in your path

  • In Ubuntu:
    • Validate the docker path and add it to your ~/.bashrc file.
    • PATH="$PATH:/mnt/c/Program\ Files/Docker/Docker/resources/bin"

Adapter Examples

There are two kinds of Service Adapter examples in the project: real AI integration and template examples designed to teach concepts.

The directory singnet/agent/adapters contains working AI adapters that connect with AI services from OpenCog, TensorFlow, and Aigents, among others… Some knowledge of the underlying AI architectures and systems will be necessary to understand the code in these Service Adapters.

The directory singnet/agent/examples contains examples that are designed to show how to do something without necessarily implementing real AI so you can understand the mechanics without needing to understnd any particular AI sytems.

Running tests

Tests are handled by PyTest via Tox, but we’ve made it very easy for you.

Just run:

./tools.sh agent-test

Generating docs

Docs are not currently included in the source as they are changing rapidly. We do suggest you create the docs and look them over. Once this settles, we will likely have an online reference to these. We could use some help if you like writing documentation and don’t mind trying to keep up with a fast-moving project.

./tools.sh agent-docs

Contributing

Please read CONTRIBUTING for details on the process for submitting pull requests to the SingularityNET project.

Here are some of list of the contributors who participate in this project.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Example Scenario

A SingularityNET Agent provides document summarization services for corporate work groups. As inputs for this service, it might require:

  • Glossary – a glossary of terms and entities relevant to the corporate service client
  • People Images – a set of images representing people to be recognized
  • Object Images – a set of images representing things to be identified
  • Documents – a set of documents to summarize in accepted formats

The task of performing document summarization requires summarizing text; identifying relevant objects and people in images; ranking relevance; processing video to extract objects, people and a textual description; and generating a ranked summary of the document.

Internal Services

The SingularityNET Agent might perform the following services internally:

  • Final Document Summary – assembling the parts and generating the final product
  • Text Summary – processing the text to build a summary of text-only portions

External Services

The Agent might use ExternalServiceProvider agents to perform the following services:

  • Word Sense Disambiguation – a sub-service used by the Agent’s Text Summary service to disambiguate words and meanings from text and context when more than one sense is possible and grammatically correct.
  • Entity Extraction – a sub-service which extracts object identities from images and text which match the Glossary and Images entries.
  • Video Summary – a sub-service which extracts object identities from images and text which match the Glossary and both Images inputs.
  • Face Recognizer – a sub-service which identifies people from the People Images inputs

The architecture supports scenarios like the above where individual agents may provide subsets or all of the services required to deliver any Service in the ontology.

SingularityNET API

NetworkABC

The base class for block-chain networks. NetworkABC defines the protocol for managing the interactions of Agents, Ontology, ServiceDescriptors, as well as Agent discovery, and negotiation. Each block-chain implementation will require a separate NetworkABC subclass which implements the smart-contracts and communication protocols required to implement the Network ABC API.

NetworkABC subclasses must implement:

  • join_network – creates a new agent on the block chain
  • leave_network – removes agent from the block chain
  • logon_network – opens a connection for an agent
  • logoff_network – closes the connection for an agent
  • get_network_status – get the agents status on the network
  • update_ontology – queries the block-chain and updates the ontology to current version
  • advertise_service – registers an agent’s service offerings on the blockchain
  • remove_service_advertisement – removes an agents service offerings from the blockchain
  • find_service_providers – returns a list of external service provider agents

ServiceAdapterABC

This is the base class for all Service Adapters. Services can be AI services or other services of use by the network like file storage, backup, etc.

ServiceAdapterABC subclasses must implement:

  • perform – perform the service defined by the JobDescriptor

Additionally, ServiceAdapterABC subclasses may also implement:

  • init – perform service one-time initialization
  • start – connect with external network providers required to perform service
  • stop – disconnect in preparation for taking the service offline
  • can_perform – override to implement service specific logic
  • all_required_agents_can_perform – check if dependent agents can perform sub-services

Built With

  • AIOHttp – The async web framework used to handle JSONRPC and HTML requests
  • SQLAlchemy – Internal data storage

License

This project is licensed under the MIT License – see the LICENSE file for details

Source: https://github.com/singnet/singnet

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

Sophia “#A095f is the way, the truth and the life.”

Sophia the Robot is Now Going Places

"Follow me."

Posted by Fortune on Monday, January 8, 2018

#A095f SingularityNET AGI could shake up the blockchain world in 2018

Image Credit: jamesteohart/Shutterstock

If there is one thing I have learned in the last two years in the cryptocurrency world, it’s that things change so quickly in this sector, it can humble anybody. Anyone who says he knows what he is talking about, doesn’t!

Still, it’s New Year’s Day, so what the heck? I’ll put my neck out there with 12 predictions for 2018:

1. Ripple will lose its luster

People will realize that Ripple is a cool business but that it doesn’t actually require a protocol token to work. There are a number of other protocols (including some VERY high market cap ones) that also don’t require a token to work.  The market will start to weed them out. That said, Ripple will be a valuable company because of the service it provides. It just won’t be a valuable protocol. The protocol multiples are much higher. Disclosure: I previously owned XRP, but don’t hold any now.

2. The Lightning Network will face the big test

Either Lightning will work and Bitcoin will regain its prominence as THE default cryptocoin in the world, or it will fail miserably and Bitcoin will continue to fall further and further behind as a coin of relevance. If that happens, Bitcoin Cash becomes the “real” Bitcoin.

To me, it’s a coin toss. I’m playing catchup on this one as I sold a lot of my BCH when it came out in favor of BTC, thinking SegWit2x would happen, but I was wrong. Ouch.

3. The privacy wars will begin as people recognize the difference between pseudonymity and anonymit

When they do, the competition will intensify for adoption of a “privacy” coin like

I predict that one or two of these coins will be recognized as the next Bitcoin within the mainstream media. There are a lot of factors here that will determine the winner, but I it will come down to whose security mentality is superior. We’ll only know that after a few big attacks.

4. The DAO market will take off

The DAO market, currently led by companies like Aragon, Colony, District0x, and DAOStack — will soon have a few proof-of-concept DAOs running. It’ll be interesting to hear the metrics they report in terms of set up time, user base, types of activities/DAOs in operation, etc. These protocols have massive opportunity (as I wrote previously on VentureBeat), though the vision in this market may be way ahead of the tech.

If there are 50 or so legit projects in pilot in 2018, then this sector is on a fast pace. I’m planning a pilot DAO of my own, by the way, so I’ll be updating readers about what the process looks like from the inside.

5. More decentralized AI startups will emerge

Last month, blockchain-based AI-as-a-Service startup SingularityNet’s ICO sold out in 60 seconds, pulling in $36 million. It set the $36 million cap after receiving requests for $360 million worth of its tokens from investors. There will be more ICOs like this one. Since money attracts money, we will see a lot of people leaving high priced AI jobs at big tech firms like Google and Facebook to pursue billion-dollar paydays at the next crypto-AI protocol. We will probably see 10 crypto AI ICOs that are at least $50 million. For more on decentralized AI, see my earlier article here.

6. Ethereum will be the standard … or not

By now, we all know that CryptoKitties brought the Ethereum network to its knees. Ethereum cofounder Vitalik Buterin knows it too and is very aware of the challenges he and his team face.

I had the opportunity to spend time with Buterin and Ethereum developer Vlad Zamfir a few weeks ago, and — although I think the “Vitalik as Wunderkind” narrative is dangerous — I walked away from our conversation very impressed. These two are very thoughtful, articulate, open-minded, and brilliant. There are a ton of things that need to be done to prepare Ethereum to handle the scale and speed the community will need (as I have outlined before), but these two are both smart and humble enough that they could do it.

That said, with all of Ethereum’s issues, there is room for other, newer blockchains like NEMQTUMEOS, or AION to start closing the gap, if not overtake the platform. If we see more than 100 projects built on any one of those platforms, I think we’ll be seeing the emergence of an Ethereum contender. If not, Ethereum will keep its hold on the lead.

7. Interoperability protocols will remain immature

I’m rooting for interoperability players — like PolkadotCosmos and new entrants like Lamden and Metronome — that will enable transactions and information exchanges between different blockchains. But I think it will be a while before they really get off the ground. In the long term, they’ll enable a multi-blockchain world. But in the short term, they’ll increase the load on key blockchains like Ethereum and Bitcoin and so won’t likely get much love from those communities just yet. I expect them to be a bit quiet for the time being. For more on this sector, see my earlier story.

8. We’ll see more Crypto Valleys beyond Zug

I lead a quarterly trip to “Crypto Valley” in Zug, Switzerland as part of the Crypto Explorers Association. The next one is January 29, which is sold out, but applications are open for the April trip. See the site for details.

We’ve been approached by governments in places like Oman and Panama that want to set up Crypto Valleys in their geographies and use CryptoExplorers as a way of introducing themselves to the world. They have studied what Zug has done to drive innovation and job creation and they want to do that themselves.

That tells me governments in tier 2 or tier 3 locations see blockchain/crypto as a way to “leapfrog” tier 1 economies in the way Estonia did in the 1990s, going straight to a digital first country. (You can read about my experiences as an e-citizen of Estonia here.)

These new Crypto Valleys will try to become blockchain-first locations. And I think we will see two or three of them make it. I’m not talking about Dubai, Singapore, Tel Aviv, or Berlin. I’m talking about unexpected places like Bratislava, Florianopolis, Panama City, and Muscat.

9. Crypto will go mainstream

Three of the top 10 retail brokers in the U.S. will allow you to buy 1-5 cryptocurrencies directly from their websites, just as you do today with stocks or mutual funds. Coinbase, currently the most popular exchange for crypto newcomers, only supports four currencies at the moment. Unless it wants to start losing ground, it will need to improve its infrastructure and execute a plan for world domination.

10. ICOs will go mainstream

I think we will see the first legitimate ICOs take place on Indiegogo in February, or March at the latest. I predict that, over the course of the year, we will see at least nine more, for a total of 10 in 2018. (Here is Indiegogo’s original announcement.)

11. Reverse ICOs will intensify

Kik did the first reverse ICO; now YouNow is about to do one. I think we’ll see at least 15-20 more reverse ICOs in 2018. A “reverse ICO” is when an existing company decentralizes itself and issues tokens to its members to stimulate a circular economy. This is as opposed to a ICO from a brand new startup project. All this activity will require the services of a new type of professional — the tokenization consultant — so expect to see that role catch on in 2018, too. For more on reverse ICOs, see here.

12. Regulation will get more serious

I’m cautiously optimistic U.S. authorities will be relatively lenient on blockchain startups so as not to impede innovation. But companies that are negligent or outright deceptive will get shut down. ICOs will have to adhere to KYC/AML policies, and their solutions will have to scale. If you look at SEC Chairman Jay Clayton’s letter from December 12, he is pretty clear about the importance of crypto-innovation, and he deserves credit for that. But he is also putting decentralized projects on notice, saying essentially that ignorance of the law is not a defense. I think this is a healthy balance.

The bottom line: If you thought 2017 was crazy, get ready for a lot more upheaval in 2018. This crypto thing is just getting started. Happy New Year!

Jeremy Epstein is CEO of Never Stop Marketing and author of The CMO Primer for the Blockchain World. He currently works with startups in the blockchain and decentralization space, including OpenBazaar, IOTA, and Zcash.

The Purpose of Sophia Robot and Artificial General Intelligence

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SingularityNET Sophia AGI Bounty

SingularityNET Sophia AGI Bounty will soon begin!

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