AIRIS represents the first proto-AGI (Artificial General Intelligence) to harness a comprehensive tech stack across the alliance.

SingularityNET, founded by renowned AI researcher Dr Ben Goertzel, uses agent technology from Fetch.ai, incorporates Ocean Data for long-term memory capabilities, and is soon expected to integrate CUDOS Compute infrastructure for scalable processing power.

“AIRIS is a significant step in the direction of practical, scalable neural-symbolic learning, and – alongside its already powerful and valuable functionality – it illustrates several general points about neural-symbolic systems, such as their ability to learn precise generalisable conclusions from small amounts of data,” explains Goertzel.

According to the company, this alliance-driven procedure propels AIRIS towards AGI—crafting one of the first intelligent systems with autonomous and adaptive learning that holds practical applications for real-world scenarios.

AIRIS’ learning mechanisms

AIRIS is crafted to enhance its understanding by interacting directly with its environment, venturing beyond the traditional AI limitations that depend on predefined rules or vast datasets. Instead, AIRIS evolves through observation, experimentation, and continual refinement of its unique “rule set.”

This system facilitates a profound level of problem-solving and contextual comprehension, with its implementation in Minecraft setting a new benchmark for AI interaction with both digital and tangible landscapes.

Shifting from a controlled 2D grid to the sophisticated 3D world of Minecraft, AIRIS faced numerous challenges—including terrain navigation and adaptive problem-solving in a dynamic environment. This transition underscores AIRIS’ autonomy in navigation, exploration, and learning.

The AIRIS Minecraft Agent distinguishes itself from other AI entities through several key features:

• Dynamic navigation: AIRIS initially evaluates its milieu to formulate movement strategies, adapting to new environments in real-time. Its capabilities include manoeuvring around obstacles, jumping over barriers, and anticipating reactions to varied terrains.

• Obstacle adaptation: It learns to navigate around impediments like cliffs and forested areas, refining its rule set with every new challenge to avoid redundant errors and minimise needless trial-and-error efforts.

• Efficient pathfinding: Via continuous optimisation, AIRIS advances from initially complex navigation paths to streamlined, direct routes as it “comprehends” Minecraft dynamics.

• Real-time environmental adaptation: Contrasting with conventional reinforcement learning systems that demand extensive retraining for new environments, AIRIS adapts immediately to unfamiliar regions, crafting new rules based on partial observations dynamically.

AIRIS’ adeptness in dealing with fluctuating terrains, including water bodies and cave systems, introduces sophisticated rule refinement founded on hands-on experience. Additionally, AIRIS boasts optimised computational efficiency—enabling real-time management of complex rules without performance compromises.

Future applications

Minecraft serves as an excellent launchpad for AIRIS’ prospective applications, establishing a solid foundation for expansive implementations:

• Enhanced object interaction: Forthcoming stages will empower AIRIS to engage more profoundly with its surroundings, improving capabilities in object manipulation, construction, and even crafting. This development will necessitate AIRIS to develop a more refined decision-making framework for contextual tasks.

• Social AI collaboration: Plans are underway to incorporate AIRIS in multi-agent scenarios, where agents learn, interact, and fulfil shared objectives, simulating real-world social dynamics and problem-solving collaboratively.

• Abstract and strategic reasoning: Expanded developments will enhance AIRIS’s reasoning, enabling it to tackle complex goals such as resource management and prioritisation, moving beyond basic navigation towards strategic gameplay.

The transition of AIRIS to 3D environments signifies a pivotal advancement in the ASI Alliance’s mission to cultivate AGI. Through AIRIS’s achievements in navigating and learning within Minecraft, the ASI Alliance aspires to expedite its deployment in the real world, pioneering applications for autonomous robots, intelligent home assistants, and other systems requiring adaptive learning and problem-solving capacities.

Berick Cook, AI Developer at SingularityNET and creator of AIRIS, said: “AIRIS is a whole new way of approaching the problem of machine learning. We are only just beginning to explore its capabilities. We are excited to see how we can apply it to problems that have posed a significant challenge for traditional reinforcement learning.

“The most important aspect of AIRIS to me is its transparency and explainability. Moving away from ‘Black Box’ AI represents a significant leap forward in the pursuit of safe, ethical, and beneficial AI.”

The innovative approach to AI evident in AIRIS – emphasising self-directed learning and continuous rule refinement – lays the foundation for AI systems capable of independent functioning in unpredictable real-world environments. Minecraft’s intricate ecosystem enables the system to hone its skills within a controlled yet expansive virtual setting, effectively bridging the divide between simulation and reality.

The AIRIS Minecraft Agent represents the inaugural tangible step towards an AI that learns from, adapts to and makes autonomous decisions about its environment. This accomplishment illustrates the potential of such technology to re-envision AI’s role across various industries.

(Image by SkyeWeste)

See also: SingularityNET bets on supercomputer network to deliver AGI

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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While today’s AI excels in specific areas – think GPT-4 composing poetry or DeepMind’s AlphaFold predicting protein structures – it’s still miles away from genuine human-like intelligence. 

“While the novel neural-symbolic AI approaches developed by the SingularityNET AI team decrease the need for data, processing and energy somewhat relative to standard deep neural nets, we still need significant supercomputing facilities,” SingularityNET CEO Ben Goertzel explained to LiveScience in a recent written statement.

Enter SingularityNET’s ambitious plan: a “multi-level cognitive computing network” designed to host and train the incredibly complex AI architectures required for AGI. Imagine deep neural networks that mimic the human brain, vast language models (LLMs) trained on colossal datasets, and systems that seamlessly weave together human behaviours like speech and movement with multimedia outputs.

But this level of sophistication doesn’t come cheap. The first supercomputer, slated for completion by early 2025, will be a Frankensteinian beast of cutting-edge hardware: Nvidia GPUs, AMD processors, Tenstorrent server racks – you name it, it’s in there.

This, Goertzel believes, is more than just a technological leap, it’s a philosophical one: “Before our eyes, a paradigmatic shift is taking place towards continuous learning, seamless generalisation, and reflexive AI self-modification.”

To manage this distributed network and its precious data, SingularityNET has developed OpenCog Hyperon, an open-source software framework specifically designed for AI systems. Think of it as the conductor trying to make sense of a symphony played across multiple concert halls. 

But SingularityNET isn’t keeping all this brainpower to itself. Reminiscent of arcade tokens, users will purchase access to the supercomputer network with the AGIX token on blockchains like Ethereum and Cardano and contribute data to the collective pool—fuelling further AGI development.  

With experts like DeepMind’s Shane Legg predicting human-level AI by 2028, the race is on. Only time will tell if this global network of silicon brains will birth the next great leap in artificial intelligence.

(Photo by Anshita Nair)

See also: The merging of AI and blockchain was inevitable – but what will it mean?

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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While making some recovery in the past couple of weeks, the crypto market has suffered a horrid couple of months. Bitcoin crashed around 50 percent between November 2021 and the end of January 2022. As of writing, the largest cryptocurrency remains around 37 percent down while many “altcoins” have still lost over 50 percent of their value.

DynaSets combine AI algorithms with professional hedge fund traders in a bid to maximise profits and minimise losses in a notoriously volatile market (although the same could be said for the “stonk” market in recent weeks…)

Marcello Mari, CEO of SingularityDAO, said:

“I’m impressed by the preliminary results from the beta version of our DynaSets.

Over the next month, we’ll be further empowering our traders with more tools including the ability to short the market and execute trades with leverage.

We’ll also be launching real machine learning tools that have never been used in the crypto market before.”

Since the beta launch of DynaSets on 20 December 2021:

• Bitcoin DynaSet shows 10.3% better performance over just “hodling” Bitcoin
• Ethereum DynaSet shows 12.59% better performance over hodling Ethereum

“As we move closer to our 1.0 product offering, we will further improve on the performance we demonstrated with our beta. That is, deliver further and further automation with a constant focus on crypto asset protection and AI safety,” commented Chris Poulin, CTO.

The combination of SingularityDAO’s AI algorithms and professional traders were reportedly able to identify potential triggers for the crypto decline including the Fed’s hawkish policy shift, electricity price rise, and political instability of the world’s second-largest producer of bitcoin, Kazakhstan.

As of writing, two DynaSets have been launched for the two largest cryptocurrencies: Bitcoin and Ethereum.

In 2020, full-stack AI solution SingularityNET announced that it was collaborating with Cardano due to Ethereum’s issues.

Earlier this month, Goertzel announced HyperCycle—a lightweight layer 2 architecture designed to enable inexpensive, high-speed, large-scale on-chain execution of microservices and specifically designed to optimise AI-related processes.

HyperCycle leverages TODA/IP ledgerless protocol, SingularityNET’s Proof of Reputation, and Cardano’s EUTxO model and Hydra sidechain framework.

Cardano seems a prime candidate for one of the next DynaSets that SingularityDAO launches.

(Photo by Jared Schwitzke on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo. The next events in the series will be held in Santa Clara on 11-12 May 2022, Amsterdam on 20-21 September 2022, and London on 1-2 December 2022.

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SingularityNET is a decentralised AI marketplace which has the ultimate goal of forming the basis for the emergence of the world’s first true Artificial General Intelligence (AGI).

One of the brightest and most respected minds in AI leads the SingularityNET project, Dr Ben Goertzel.

“Current speed and cost issues with the Ethereum blockchain have increased the urgency of exploring alternatives for SingluarityNET’s blockchain underpinning,” says Goertzel.

“The ambitious Ethereum 2.0 design holds promise but the timing of rollout of different aspects of this next-generation Ethereum remains unclear, along with many of the practical particulars.“

SingularityNET claims that Cardano has now reached a level of maturity which makes it possible to port such a complex project to the new blockchain.

Back in August, Goertzel gave a talk at the Cardano Summit on why functional programming – enabled by Cardano’s Haskell and new Plutus languages – is invaluable for blockchain-based AI:

Current AIs in the SingularityNET marketplace are designed for specific, relatively straightforward tasks like image/language processing, time series analysis, and genomics data analysis. The project’s Android SDK has been used for tasks like separating vocals from music in the SongSplitter app.

While useful, these AIs show the current limitations of the technology today. SingularityNET, true to its name, has far more ambitious plans.

The broader vision of SingularityNET is to decentralise AI away from “big tech” and prevent AIs from being siloed so that one AI can outsource work to others and use their specific expertise to solve problems. This will ultimately bring us a step closer to AGI which acts more like a human by seeking help where needed.

In a blog post, SingularityNET provides further technical details about its decision to switch to Cardano:

“There may also be synergies between SingularityNET-Cardano integration and the OpenCog Hyperon initiative, which is focused on creating a more scalable, flexible and usable successor to the current OpenCog AGI R&D platform (which underlies a handful of specialized AI agents currently running on the SingularityNET network).

The OpenCog AGI design involves a metagraph knowledge store called the Atomspace, concurrently and cooperatively acted on by a number of different cognitive processes representing different learning and reasoning methods such as probabilistic logic, evolutionary learning, pattern mining and neural pattern recognition. Currently, to integrate OpenCog into SingularityNET, one creates a SingularityNET agent wrapping a whole OpenCog system with its own internal Atomspace and AI-process population.

However, in a SingularityNET-on-Cardano approach, it may eventually be possible to take a more decentralized approach in which the Hyperon Atomspace is provided as a service to any SingularityNET agent who needs it, and many of the cognitive processes involved in the Hyperon design are represented as SingularityNET agents that interact with Atomspace via channels set up via SingularityNET protocols. Such an approach would exploit the deep commonalities between the new version of OpenCog’s Atomese language being created for Hyperon and the dependent type based API of APIs under current exploration. The result would be a more fundamentally decentralized approach to AGI design.”

A fascinating interview between Cardano founder Charles Hoskinson and Dr Goertzel can be viewed here:

Cardano vs Ethereum

Ethereum is currently the world’s largest decentralised platform but suffers from slow speeds and increasing transaction costs. A switch to a more efficient and environmentally-friendly Proof-of-Stake consensus is underway which – along with new scaling innovations – should address Ethereum’s issues. However, it’s expected to be several years before Ethereum 2.0 is fully rolled out.

Cardano has observed Ethereum’s problems and is taking its time to address them with a scientific and peer-reviewed approach; which brings legitimacy to the project that will be needed for enterprise adoption.

While it could appear from the outside like Cardano has been lazy and is far behind other projects – after all, it’s yet to even support smart contracts – this is far from the case. Cardano is often ranked top of all blockchain projects for development activity and has continued signing large partnerships.

“Cardano has gone from strength to strength this year, and having the backing of such a prominent organisation only reaffirms this,” comments Hoskinson. 

“SingularityNET is a project we’ve followed for a long time, and we’re excited to see how the Cardano blockchain can help SingularityNET realise its ambitious goals.”   

Smart contracts are due to launch on Cardano in the coming months as part of what it calls its ‘Goguen’ phase. Unlike Ethereum, Cardano is using Proof-of-Stake from the start and won’t have the speed, cost, and scalability problems of the current decentralised platform leader.

Cardano will even become the most decentralised network in the space following the recent successful launch of its ‘Shelley’ upgrade.

On its website, Cardano explains:

“We expect Cardano to be 50-100 times more decentralized than other large blockchain networks, with the incentives scheme designed to reach equilibrium around 1,000 stake pools.

Current prominent blockchain networks are often controlled by less than 10 mining pools, exposing them to serious risk of compromise by malicious behavior – something which Cardano avoids with a system inherently designed to encourage greater decentralization.”

We’re already seeing groundbreaking projects like SingularityNET beginning to shift over to Cardano. While it may appear that Cardano has a long way to catch up with Ethereum, it’s worth remembering that – of Ethereum’s close to 3,000 apps – only a minority carry significant value or have many active users.

There is currently around $11 billion “locked up” in Ethereum’s much-vaunted DeFi projects. That’s nothing to be sniffed at, but it only takes some big projects to move to Cardano to put a big dent in Ethereum’s primary use case. It’s also worth remembering the whole space is very young with plenty of growth potential—the global legacy financial system is worth hundreds of trillions of dollars.

While multiple blockchain projects will likely co-exist, Cardano’s ability to “flip” Ethereum is looking more possible than ever.

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

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The partners are specifically looking at artificial general intelligence (AGI) technologies which aim to replicate the complex tasks of which humans are capable.

AGI is considered a step above standard AI because it aims to add human-like reasoning capabilities in uncertain scenarios. Such processing will enable AGIs to do things like solve puzzles and make plans which are beyond that of today’s AIs.

Dr Ben Goertzel, CEO of SingularityNET, said:

“The scale of the AGI deployments needed by a partner like Cisco is going to be tremendous, and we are working hard to make sure our AGI tools and our blockchain-based platform is up to the task.”

Such a large tech conglomerate as Cisco joining up with SingularityNET adds a lot of credibility to the project’s goals.

SingularityNET describes itself as the first decentralised AI network that lets anyone create, share, and monetise AI services at scale. The idea behind the decentralisation is that it prevents any single player from hoarding AI capabilities and instead for it to be distributed globally.

“To really build a global decentralized thinking machine we are going to need to put a lot of complicated ingredients together, and the collaboration between Cisco and SingularityNET has the potential to accelerate things tremendously,” Goertzel said.

In May, the Singapore and Malaysia division of Domino’s Pizza announced that it was partnering with SingularityNET to apply blockchain-powered AI to its supply chain processes.

“In 10 years, you’re going to see AGIs with IQs higher than humans,” Goertzel believes.

A beta of SingularityNET’s AI Marketplace can be found here which features 40 (as of writing) artificial intelligence-powered services.

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

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