As the first major corporate partner of the Fetch.ai Foundation, Deutsche Telekom joins forces with Bosch and Fetch.ai in supporting an open AI and blockchain platform aimed at widespread adoption. Its subsidiary, Deutsche Telekom MMS, will also serve as a validator on the decentralised Fetch.ai network, helping secure transactions on the blockchain.

The core of Fetch.ai’s technology relies on autonomous software agents that can manage resources, conduct transactions, and analyse data flows independently thanks to AI algorithms. These agents unlock a myriad of real-world applications across sectors like automotive, supply chain, healthcare, and digital identity. 

For example, AI agents could optimise production schedules based on supply chain data or match patients to clinical trials using health records. The tamper-proof nature of blockchain also enables secure transmission and access to sensitive data.

“The convergence of blockchain, AI and IoT is trailblazing the digital transformation of entire industries,” said Dirk Röder, Head of Deutsche Telekom’s Web3 Infrastructure & Solutions team. “Autonomous agents will automate industrial services, simplifying processes securely thanks to blockchain.”

As a validator, Deutsche Telekom MMS will ensure network security as more devices, users, and services integrate with the Fetch.ai blockchain. Built on the Cosmos protocol, Fetch.ai operates as a permissionless decentralised network with open-source code that is accessible globally.  

The collaboration demonstrates how blockchain can unlock AI’s potential by providing reliable, transparent data while AI can help securely analyse blockchain transactions. Together, these technologies lay the foundations for a decentralised Web3 internet that empowers user privacy and control.

“This partnership signals real progress in integrating AI and Web3 innovations into the machine economy,” said Fetch.ai CEO Humayun Sheikh.

Deutsche Telekom and Fetch.ai will be working together at one of Europe’s largest AI and IoT hackathons, Bosch Connected Experience, on 28-29 February 2024.

See also: Telcos to spend $20B on AI network orchestration by 2028

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Exfluency is a tech company providing hybrid intelligence solutions for multilingual communication. By harnessing AI and blockchain technology we provide tech-savvy companies with access to modern language tools. Our goal is to make linguistic assets as precious as any other corporate asset.

What tech trends have you noticed developing in the multilingual communication space?

As in every other walk of life, AI in general and ChatGPT specifically is dominating the agenda. Companies operating in the language space are either panicking or scrambling to play catch-up. The main challenge is the size of the tech deficit in this vertical. Innovation and, more especially AI-innovation is not a plug-in.

What are some of the benefits of using LLMs?

Off the shelf LLMs (ChatGPT, Bard, etc.) have a quick-fix attraction. Magically, it seems, well formulated answers appear on your screen. One cannot fail to be impressed.

The true benefits of LLMs will be realised by the players who can provide immutable data with which feed the models. They are what we feed them.

What do LLMs rely on when learning language?

Overall, LLMs learn language by analysing vast amounts of text data, understanding patterns and relationships, and using statistical methods to generate contextually appropriate responses. Their ability to generalise from data and generate coherent text makes them versatile tools for various language-related tasks.

Large Language Models (LLMs) like GPT-4 rely on a combination of data, pattern recognition, and statistical relationships to learn language. Here are the key components they rely on:

1. Data: LLMs are trained on vast amounts of text data from the internet. This data includes a wide range of sources, such as books, articles, websites, and more. The diverse nature of the data helps the model learn a wide variety of language patterns, styles, and topics.
2. Patterns and Relationships: LLMs learn language by identifying patterns and relationships within the data. They analyze the co-occurrence of words, phrases, and sentences to understand how they fit together grammatically and semantically.
3. Statistical Learning: LLMs use statistical techniques to learn the probabilities of word sequences. They estimate the likelihood of a word appearing given the previous words in a sentence. This enables them to generate coherent and contextually relevant text.
4. Contextual Information: LLMs focus on contextual understanding. They consider not only the preceding words but also the entire context of a sentence or passage. This contextual information helps them disambiguate words with multiple meanings and produce more accurate and contextually appropriate responses.
5. Attention Mechanisms: Many LLMs, including GPT-4, employ attention mechanisms. These mechanisms allow the model to weigh the importance of different words in a sentence based on the context. This helps the model focus on relevant information while generating responses.
6. Transfer Learning: LLMs use a technique called transfer learning. They are pretrained on a large dataset and then fine-tuned on specific tasks. This allows the model to leverage its broad language knowledge from pretraining while adapting to perform specialised tasks like translation, summarisation, or conversation.
7. Encoder-Decoder Architecture: In certain tasks like translation or summarisation, LLMs use an encoder-decoder architecture. The encoder processes the input text and converts it into a context-rich representation, which the decoder then uses to generate the output text in the desired language or format.
8. Feedback Loop: LLMs can learn from user interactions. When a user provides corrections or feedback on generated text, the model can adjust its responses based on that feedback over time, improving its performance.

What are some of the challenges of using LLMs?

A fundamental issue, which has been there ever since we started giving away data to Google, Facebook and the like, is that “we” are the product. The big players are earning untold billions on our rush to feed their apps with our data. ChatGPT, for example, is enjoying the fastest growing onboarding in history. Just think how Microsoft has benefitted from the millions of prompts people have already thrown at it.

The open LLMs hallucinate and, because answers to prompts are so well formulated, one can be easily duped into believing what they tell you.
And to make matters worse, there are no references/links to tell you from where they sourced their answers.

How can these challenges be overcome?

LLMs are what we feed them. Blockchain technology allows us to create an immutable audit trail and with it immutable, clean data. No need to trawl the internet. In this manner we are in complete control of what data is going in, can keep it confidential, and support it with a wealth of useful meta data. It can also be multilingual!

Secondly, as this data is stored in our databases, we can also provide the necessary source links. If you can’t quite believe the answer to your prompt, open the source data directly to see who wrote it, when, in which language and which context.

What advice would you give to companies that want to utilise private, anonymised LLMs for multilingual communication?

Make sure your data is immutable, multilingual, of a high quality – and stored for your eyes only. LLMs then become a true game changer.

What do you think the future holds for multilingual communication?

As in many other walks of life, language will embrace forms of hybrid intelligence. For example, in the Exfluency ecosystem, the AI-driven workflow takes care of 90% of the translation – our fantastic bilingual subject matter experts then only need to focus on the final 10%. This balance will change over time – AI will take an ever-increasing proportion of the workload. But the human input will remain crucial. The concept is encapsulated in our strapline: Powered by technology, perfected by people.

What plans does Exfluency have for the coming year?

Lots! We aim to roll out the tech to new verticals and build communities of SMEs to serve them. There is also great interest in our Knowledge Mining app, designed to leverage the information hidden away in the millions of linguistic assets. 2024 is going to be exciting!

• Jaromir Dzialo is the co-founder and CTO of Exfluency, which offers affordable AI-powered language and security solutions with global talent networks for organisations of all sizes.

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 Digital Transformation Week.

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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)

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70 percent of the 2,341 respondents across 30 business sectors picked AR as disrupting their industry most out of a selection of seven emerging technologies: AI, cybersecurity, cloud computing, IoT, blockchain, and 5G.

Filipe Oliveira, Senior Analyst at GlobalData, commented: “This change in how people see AR will likely be long term, and not just a temporary blip. It is clear that people are warming towards the technology, even if they don’t believe that it will make a big difference tomorrow.” 

AI wins some ground back when it comes to confidence in the technology. 57 percent of the respondents believe that AI will live up to all of its promises compared to just 26 percent for AR.

Along those same lines, 31 percent believe “The technology is hyped, but I can see a use for it” for AI, while a huge 50 percent report the same for AR.

Apple’s decision to add a LiDAR sensor to its latest mobile devices was seen as an important step towards the mass adoption of AR. Excitement is also growing around so-called “metaverses” that converge virtually-enhanced physical reality with physically-persistent shared virtual spaces.

SenseTime, one of China’s leading AI companies, announced earlier this week that it had partnered with BilibiliWorld to create a metaverse. The experience leverages SenseTime’s AI and mixed reality technologies to enable players to enjoy role-playing games that seamlessly blend reality with virtuality.

Facebook CEO Mark Zuckerberg recently said the company “will effectively transition from people seeing us as primarily being a social media company to being a metaverse company”. As the owner of Oculus, Zuckerberg’s plans for the future of Facebook will likely make people think of a large virtual space similar to that depicted in Ernest Cline’s Ready Player One novel and the 2018 film adaptation.

Some people have expressed concern about a large centralised company such as Facebook having control over such a potentially ubiquitous world and the content they consume. Many believe that an open-source decentralised version is vital:

Zuckerberg, for his part, claims that no one company will run the metaverse and it will be an “embodied internet” that is operated by many different players.

Decentraland is an early example of what a truly decentralised virtual space could look like. The platform makes use of a DAO (Decentralised Autonomous Organisation) to make policy decisions such as what content is allowed in addition to taking advantage of the NFT (Non-Fungible Token) trend to offer exclusive in-world items.

AR and AI are both important emerging technologies that can often go hand-in-hand, but it’s clear that the latter is losing its perspective among professionals as having the biggest impact on their industries over the coming years.

(Photo by My name is Yanick on Unsplash)

Want to find out more from executives and thought leaders in this space? Find out more about the Digital Twin World event, taking place on 8-9 September 2021, which will explore augmenting business outcomes in more depth and the industries that will benefit.

The post AR overtakes AI as the ‘most disruptive’ emerging technology appeared first on AI News.

Fetch.ai made our innovative companies to watch in 2021 list for its grand vision to build a decentralised network of autonomous “agents” that perform real-world tasks. For most companies, that plan could sound almost impossibly ambitious—but Fetch.ai has the talent and resources to pull it off and continues to gain votes of confidence by signing partnerships with the likes of Bosch, Festo, and IOTA.

The company’s mainnet went live in March 2021 and has been ramping up its announcements since.

The new DeFi Agents toolkit app is the latest in a barrage of announcements and allows users to customise stop-loss parameters on decentralised exchanges. Stop-Loss agents can automatically withdraw funds from liquidity pools if the exchange rate between the two tokens falls to a predetermined level to combat the risk of impermanent loss that liquidity providers face.

Humayun Sheikh, CEO of Fetch.ai, said:

“Intelligent automation has the potential to transform the end-to-end experience of the DeFi applications we use today.

Rather than constantly monitoring price action and having to manually withdraw liquidity, Fetch.ai DeFi Agents simplify and streamline that whole process for LPs.

By improving upon the current experience for LPs on popular DEXes like Uniswap and PancakeSwap, we have created the catalyst for the adoption and usage of DeFi applications.” 

Users will initially be able to create up to five agents with stop-loss triggers for all liquidity pools on Uniswap and PancakeSwap. Agents can be tracked and updated through a dedicated dashboard.

Customisations of the DeFi agents can include:

• Swap support: allows a swap to be performed at a given threshold for Uniswap v2 and PancakeSwap pools.
• APY Monitoring: will withdraw liquidity if APY is less than a specified amount. 
• ETH fund management I: Deposits funds in a contract and uses it to automatically top-up one-or-more pools.
• ETH fund management II: Allows agents to swap ERC-20s or BEP-20s for ETH if funds drop below a predetermined level.
• Strategy Creator: Creates IFTTT (If This Then That) strategies for pool deposits/withdrawals. 
• Portfolio management (Uniswap v3): Defines a weighting for a sector (e.g. oracles, AI, NFTs) and implements an ETF-like strategy (similar to market-weighted Balancer pool).
• Private Uniswap v3 strategy: Hides strategies behind the agent.

Over time, Fetch.ai plans to extend the functionality of its DeFi Agent tool to support further automatic deposit and withdrawal of liquidity based on conditions including token sentiment, move liquidity of ERC-20s or BEP-20s to a defined range if the price is breached (in Uniswap V3), and remove liquidity if ETH fees are becoming too high in a pre-set period of time.

You can get started with the DeFi agents app from Fetch.ai here.

(Image Credit: Fetch.ai)

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Fetch.ai has caught the attention of investors for its potentially groundbreaking machine learning network of autonomous “agents” that can perform real-world tasks. It’s also caught our attention, making our list of innovative companies to watch in 2021.

IOTA was among the most hyped projects during the 2017 cryptocurrency/blockchain frenzy (or bubble, dependent on your perspective.) While most projects have since collapsed, IOTA continues to go from strength-to-strength and has announced a series of partnerships with giants like Dell and Jaguar Land Rover.

One partnership that both companies have in common is Bosch.

IOTA was the first to establish a partnership with Bosch when it announced that it was integrating with IOTA’s Data Marketplace. Last February, Fetch.ai announced its own partnership with Bosch as part of a joint project called the Economy of Things (EoT).

No specific project involving Fetch.ai, IOTA, and Bosch has been announced but it wouldn’t be surprising to see the first real-world adoption coming from the three companies.

While we can speculate on the exciting future possibilities, what’s actually been announced today is an agreement between Fetch.ai and IOTA to deliver a controlled data sharing environment for IoT devices and infrastructures. The ultimate goal is to enable the automated fee-less retrieval and private sharing of data.

Humayun Sheikh, CEO of Fetch.ai, said:

“The fundamental goal of this collaboration is to enable granular control over data and to reduce the reliance on centralised systems that take advantage of data.

While there are numerous partnerships focusing on data privacy, this one adds the layer of economic benefit for stakeholders via autonomous economic agents without compromising data privacy.

Enabling these agents to perform “useful economic work” on behalf of individuals, businesses, companies, and other entities or organizations will speed up the adoption of Fetch.ai autonomous economic agents and IOTA Streams thereby allowing them to communicate with sophistication across industries like mobility, supply chain, IoT and more.”

Holger Koether, Director of Partner Management at IOTA Foundation, added:

“The main feature of this partnership is offering a serious AI application for the devices that make up the machine economy on the IOTA and Fetch networks.

We are enabling data producers to take control over who can access the data they produce whether from a mobile device, environment IoT sensor, connected vehicle, Industrial IoT solution, and a host of IoT-focused use cases.

With this partnership, we hope both the Fetch and IOTA communities expand the functionally of what devices can do autonomously on distributed networks.”

IOTA has faced various criticisms over the years but the project now seems to have overcome most of its problems. The one major lingering criticism is of centralisation due to its ‘Coordinator’ node. However, that is set for removal in IOTA 2.0.

The IOTA 2.0 ‘Nectar’ devnet went live last week. For the first time, assets on the network will be persistent even after upgrades.

“IOTA 2.0 DevNet ‘Nectar’ marks a major milestone on IOTA’s trajectory towards full decentralisation,” commented Dominik Schiener, Co-Founder and Chairman of the IOTA Foundation. “I cannot understate the importance of this release: Nectar is the living proof that you can have feeless, scalable, secure, resource-efficient, and fully decentralised DLT. It’s a game-changer.”

With IOTA 2.0 heading towards its first release candidate later this year, we can expect many more announcements in the months to come.

Want to learn more from executives at the heart of this space? The Blockchain IoT Solutions Congress on March 8 2022 will explore the convergence of these two technologies and the use cases and industries that will benefit.

The post Fetch.ai announces partnership with IoT-focused distributed ledger IOTA appeared first on AI News.

The global engineering giant will test key features of Fetch.ai’s testnet until the end of this month and will deploy a node on the network. The strategic engineering project between Fetch.ai and Bosch is called the Economy of Things (EoT).

Dr Alexander Poddey, the leading researcher for digital socio-economy, cryptology, and artificial intelligence in the EoT project, said:

“Our collaboration with Fetch.ai spans from the aspects of governance and orchestration of DLT-based ecosystems, multi-agent technologies to collective learning.

They share our belief that these elements are crucial to realising the economic, social, and environmental benefits of IoT technologies.”

Fetch.ai’s testnet launched in October 2020 and the firm is now gearing up for its mainnet launch in March. The company has been ramping up announcements in advance of the mainnet launch and just last week announced a partnership with FESTO to launch a decentralised marketplace for manufacturing.

After the mainnet launch, Bosch intends to run nodes and applications on Fetch.ai’s blockchain network.

Jonathan Ward, CTO of Fetch.ai, commented:

“We have been working with Bosch for some time towards our shared vision of building open, fair, and transparent digital ecosystems. I’m delighted to be able to announce the first public step in bringing these technologies into the real world.

We’re looking forward to working further with Bosch to bring about the wide adoption of these ground-breaking innovations, which will hugely benefit consumers and businesses in many industries including automotive, manufacturing, and healthcare.” 

Fetch.ai is working on decentralised autonomous “agents” which perform real-world tasks. 

Bosch is attracted to Fetch.ai’s vision of collective learning technologies and believes it can be a key enabler in their plans for AI-enabled devices—allowing AI agents to be trained which operate within smart devices while preserving users’ privacy and control of their data.

Fetch.ai’s vision is bold but it has the team and partnerships to pull it off. The company’s roster features talent with experience from DeepMind, Siemens, Sony, and a number of esteemed academic institutions.

Bosch has long expressed a keen interest in distributed ledger technologies and established multiple industry partnerships.

The venture capital arm of Bosch, Robert Bosch Venture-Capital, invested in the IOTA Foundation. Bosch later patented an IOTA-based digital payments system and recently financially supported a hackathon for the DLT platform which uses a scalable DAG (Directed Acyclic Graph) data structure called the ‘Tangle’ in a bid to overcome some of the historic problems with early blockchains.

Fetch.ai and IOTA are in the same space but have different goals, it’s not a choice of one or the other. Companies like Bosch can take advantage of the exciting potential offered by both DLTs to gain a competitive edge.

(Photo by Adi Goldstein on Unsplash)

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Fetch.ai is based in Cambridge, UK and has built an impressive team of talent with experience from DeepMind, Siemens, Sony, and a number of esteemed academic institutions. The company is working on decentralised autonomous “agents” which perform real-world tasks.

FESTO was founded in 1925 and currently produces and sells pneumatic and electrical control and drive technology. The company has continued to thrive over the years through consistent reinvention and likes to show off around once a year by developing bionic robots like its ‘flying fox’ which uses machine learning to optimise its flight behaviour with every manoeuvre:

The partnership with Fetch.ai is FESTO’s first foray into blockchain and shows how the company aims to remain at the cutting-edge of technological developments.

Fetch.ai will develop a decentralised manufacturing marketplace for FESTO to help transform the company’s existing control systems and make them more efficient.

Maria Minaricova, Director of Business Development at Fetch.ai, said:

“We are delighted to be able to announce a collaboration with such an advanced technology company like FESTO.

With FESTO’s contribution, we will be able to demonstrate in real life the benefits of autonomous AI agents in manufacturing and supply chain.

We look forward to working further with FESTO to bring about the wide adoption of these ground-breaking manufacturing innovations.”

The marketplace will make use of Fetch.ai’s technology stack and its ‘Multi-Agent’ architecture. FESTO hopes the marketplace will help to avoid some of the challenges with existing centralised manufacturing process likes demand fluctuations and uneven utilisation of capacity.

Fetch.ai explained the advantages of switching to a decentralised solution:

“The advantages of an agent-based-approach within a decentralised manufacturing framework have the potential to lead to supply-chain optimisation based on real-time information, increasing the responsiveness of the enterprise to the market requirements, a higher degree of autonomy in manufacturing, and delivering personalised, tailored orders to customers.”

A report from TrendMicro last year found that 65 percent of manufacturing environments are using outdated systems even when more secure and efficient options are available.

“Industry 4.0 offers unparalleled opportunities to increase productivity, enhance process efficiencies, and realise on-demand manufacturing,” said Steve Quane, Executive Vice President, Network Defense and Hybrid Cloud Security for Trend Micro.

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.

The post Fetch.ai partners with FESTO on decentralised manufacturing marketplace appeared first on AI News.

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.

The post Full-stack AI solution SingularityNET switches Ethereum for Cardano appeared first on AI News.

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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