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)

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.

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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.

In this feature, AI News takes a look at some of the most innovative companies leading the way in maximising the opportunities while minimising the challenges of artificial intelligence deployments. In alphabetical order:

Affectiva

Affectiva is an MIT Media Lab spin-off which specialises in building AI which can understand human emotions, cognitive states, activities, and the objects people use. 

The company’s Emotion AI technology achieves this incredible feat through analysing facial and vocal expressions and was trained using more than 10 million face videos from 90 countries, representing one of the largest datasets of its kind. Furthermore, the data is purposefully diverse to help prevent the kind of algorithmic bias which has plagued some other solutions.

“Affectiva is humanising technology, building a world where technology understands people the way we understand one another, and forever changing how humans interact with technology and with one another in a digital world,” Affectiva CMO Gabi Zijderveld tells AI News.

One of the industries which most excites the company is automotive, an industry that is seeing rapid innovation mostly driven – no pun intended – by AI.

“Back in 2018, we launched Affectiva Automotive AI, the first multi-modal in-cabin sensing solution to understand what is happening with people in a vehicle. It uses cameras in the car to measure, in real-time, the state of the driver, the state of the occupants, and the state of the vehicle interior (i.e. cabin).

“This insight helps car manufacturers, fleet management companies and rideshare providers improve road safety, by understanding dangerous driver behaviour such as drowsiness, distraction and anger. It can also be used to create more comfortable and enjoyable transportation experiences, by understanding how passengers react to the environment, including content they can consume in the back of the car.”

Since the launch of Automotive AI, Affectiva has worked with an impressive array of transportation industry pioneers including Aptiv, Cerence, Hyundai Kia, Faurecia, Porsche, BMW, GreenRoad Technologies, Veoneer, and more.

This year, Affectiva is expanding its work in the automotive sector and will also be increasing its efforts in media analytics to understand audience engagement with a wide range of content.

Algorithmia

Algorithmia aims to provide a single solution for all stages of the ML operations (MLOps) and management lifecycle. The company’s platform has been used by over 120,000 engineers and data scientists, including from the United Nations, government intelligence agencies, and various Fortune 500 companies.

“Across industries what we’re seeing is the industrialisation of ML and the rising need for enterprise-grade MLOps to move models out of the lab and into production,” Diego Oppenheimer, CEO of Algorithmia, tells AI News.

Algorithmia points to five ways it differentiates from competitors; that it’s platform-agnostic, has an integration-first approach, a model service repository, follows MLOps security best practices, and this week launched much-desired governance capabilities.

Happy Money, a California-based fintech that operates a marketplace to connect borrowers with credit union lenders, recently used Algorithmia to integrate real-time and batch data from financial services firms to run through their models to generate savings recommendations, do risk analysis, and conduct fraud detection. Algorithmia’s platform reduced Happy Money’s model iteration speed from eight months to two hours.

Algorithmia’s recent state of enterprise machine learning report highlighted the huge investments companies are planning to make in AI and ML this year in addition to the appetite for ways to manage it. This year, Algorithmia will be increasing its focus on helping enterprises to manage AI governance.

Amelia

Amelia, an IPsoft company, aims to be “the most human AI for the enterprise” by delivering a conversational AI solution with all the best human elements of emotion, expression, and understanding.

The first iteration of the digital assistant was released back in 2014 and continues to advance. Amelia was called a virtual assistant leader by Forrester and Everest Group in 2019 and 2020, respectively.

“Unlike chatbots and more limited virtual assistants that react to keyword-driven instructions and follow static decision trees, her cognitive brain supports natural, human-like conversations to execute tasks or resolve queries,” says Faisal Abbasi, Managing Director of UK and Europe at Amelia, an IPsoft company. 

“Using advanced natural language processing and state-of-the-art affective computing, Amelia handles complex conversations and digressions, recognises, and adapts to the mood of the user, and independently execute complex tasks.”

Amelia has been refined by Kenneth S. Nugent, P.C. Attorneys at Law to act as a digital legal assistant. She is now the first point-of-contact for all inbound calls and serves the firm’s 40,000 monthly visitors. She signed 111 cases last September and earned approximately $500,000 in new business.

“Amelia is massively alleviating the demands on our case workers by removing mundane and time-consuming tasks,” commented Ken Nugent, founder and attorney at Kenneth S. Nugent, P.C. Attorneys at Law.

“It’s like giving a personal assistant to each of our case managers, so they can spend more time connecting with our clients and building winning cases.”

Last year, Amelia launched the Digital Employee Builder to lower technical barriers to adoption. This year, the company is developing new roles for Amelia to drive greater business outcomes.

Darktrace

AI is advancing the offensive capabilities of cybercriminals and Darktrace is countering increasing threats with its Autonomous Response technology, a self-learning AI which is modelled on the human immune system and used by over 4,500 organisations to protect against threats to their clouds, emails, IoT devices, networks, and industrial systems.

“When it comes to the cyber threat landscape – we have entered a new area. Security teams are overwhelmed not only by the volume of attacks but their sophistication. The reality is we are up against silent but deadly attacks – where the perpetrators enter a company unknown and then move at machine speed to cause damage,” explains Max Heinemeyer, Director of Threat Hunting at Darktrace.

“Legacy security tools, based on creating rules and signatures for known attacks, are simply no good against these novel threats we see today.”

The company was founded in 2013 in a collaboration between British intelligence agencies and Cambridge University mathematicians and has a stellar advisory board featuring the likes of Alan Wade, former CIO of the CIA and Lord Evans of Weardale KCB, former Director-General of the British security service MI5.

“Some other solutions claim to be using AI – but it is important to remember that not all AI is equal. These tools are really analytics tools that create reports after an event has occurred.

“Darktrace AI sits in the heart of an organisation and is self-learning – it understands the unique pattern of life for that organisation. From that understanding, it is then able to detect when activity deviates from that normal pattern, indicative of malicious activity and, crucially, it is able to take intelligent action to stop the behaviour in its tracks.”

Recently, the company announced its work with the Vatican Library—a gargantuan effort to digitalise over 80,000 documents to preserve them against time. Darktrace is catching more than100 threats to the library every month.

Darktrace will be continuing its efforts this year to stay ahead of attackers using ever more creative and capable means.

“We’re seeing an increase in automated attacks and we expect attackers will leverage AI themselves to launch even more sophisticated, targeted, and stealthy attacks. We need to keep up with these attacks, and fight fire with fire, using AI.”

Fetch.ai

Fetch.ai combines two emerging technologies: artificial intelligence, and blockchain. Their aim is to build trusted autonomous “agents” that perform real-world tasks.

“Fetch.ai’s network is based around open source technology and we want to enable users, businesses, and organisations to access the power of AI so they can carry out complex coordination tasks in the modern economy,” Fetch.ai CEO Humayun Sheikh tells AI News.

The company’s roster features talent with experience from DeepMind, Siemens, Sony, and a number of esteemed academic institutions.

Fetch.ai’s testnet launched in October 2020 and its mainnet is due to launch this month. Ahead of the launch, Fetch.ai has been ramping up partnership announcements with the likes of Bosch and Festo.

Commenting on Fetch.ai’s partnership with Festo, Sheikh said: “The reason why this is so interesting is that – by implementing a decentralised manufacturing system – Festo aims to reduce the challenges associated with conventional, centralised manufacturing processes such as demand fluctuations and the uneven utilisation of manufacturing capacity.

“They see the value of implementing a decentralised manufacturing framework using Fetch.ai’s agent-based-approach. The tangible benefits include 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.”

Following the launch of their mainnet this month, Fetch.ai will be focused on launching toolkits to help businesses build solutions with multi-agent systems

Skymind

Skymind is a dedicated, open-source AI ecosystem builder which helps enterprises to launch deep-learning applications.

“With open source enterprise deep learning software, developers can freely innovate until they’ve created something to go to market. Only then do they pay for the software,” explains Shawn Tan, CEO of Skymind.

“With other tools, you have to start spending money on the cloud—which is quite a significant cost upfront for startups or independent developers and can be a financial barrier to creating the AI applications you want.”

The company created Deeplearning4j, the deep-learning framework for the Java Virtual Machine.

“By providing clients with supported free access to Eclipse Deeplearning4j and other open-source tools, Skymind is enabling innovation capabilities for everyone and democratising the accessibility to AI development.”

Coming off a year when the healthcare industry has never received so much attention, Skymind is excited for the potential of AI to make groundbreaking advancements.

“The first solution we’ve deployed in this area is Axial AI, a breakthrough that emerged during the pandemic last year. This is AI software that provides solutions for multiple disease analysis for hospitals and research facilities.  

“It was initially used as a CT scan diagnosis platform to help medical teams analyse the progression of COVID-19 in patients faster and with an accuracy rate of more than 90 percent. Through AI innovation, the tool automates the analysis of CT scan images within 10 seconds, thereby speeding up the recovery strategy for an infected patient.

“Without assistance from the innovation, doctors can take up to 30 minutes to examine results—and the potential margin for error is much higher.”

Skymind has bold visions for the future and is hoping to raise another fund this year to invest in more AI companies; with a focus on the UK and across Europe. The company is also involved in pioneering smart city projects around the world such as Iskandar in Malaysia which aims to use AI to make it work well for citizens.

SparkCognition

SparkCognition’s range of artificial intelligence products have already won several awards. AI News sees those awards as fully justified and the company is definitely one to watch this year – and beyond.

“SparkCognition’s core mission is to use AI to catalyze growth – for individuals, organisations, industries, and the scientific community as a whole. We are focused on real-world, meaningful applications of AI that make a nearly immediate difference to our customers,” explains Amir Husain, Founder and CEO of SparkCognition.

The company has four key products: DeepArmor, SparkPredict, Darwin, and DeepNLP.

“Our core platform hasn’t been retrofitted to adapt to AI, it’s been engineered with AI capabilities – such as neuroevolution, deep learning, and reinforcement learning – from the ground up. Our products can either stand independently or be deployed as an interoperative suite depending on the customer or industry’s unique needs.”

One recent exciting partnership SparkCognition has formed is with Boeing, to bring AI to aviation. AI News recently covered one of the fruits of the joint venture, SkyGrid, an AI-first OS for drones that also incorporates blockchain to mandate airspace rules and ensure compliance.

“We strongly believe that the skies of the future will be filled with millions of autonomous drones of all shapes and sizes, conducting all types of missions.

“How do you deal with the infrastructure needs of this new era? With SkyGrid we are building just that infrastructure; an AI-first operating system for future aviation that encompasses route management, regulatory integration with the FAA, predictive and prescriptive maintenance, collision avoidance, integration with conventional air traffic control (ATC), and even autonomous cybersecurity for manned and unmanned aircraft.”

Last month, SparkCognition acquired financial technology company AIM2. The company will be using that acquisition to grow its capabilities in financial services this year but will also be deepening its work in other verticals such as automotive, defense, renewable energy, and manufacturing.

Husain teases that SparkCognition is currently considering further acquisitions… so watch this space.

(Photo by Olya Kobruseva from Pexels)

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 Featured: AI News’ list of innovative companies to watch in 2021 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)

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 Bosch partners with Fetch.ai to ‘transform’ digital ecosystems using DLTs appeared first on AI News.

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.

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