• First-ever AI-based 360° drone cybersecurity system that can detect, prevent, and respond to multiple cyber threats in real-time without requiring an operator
• Designed specifically for industrial and commercial drones, robotics, and autonomous platforms, Mobilicom’s ICE Cybersecurity Suite is a 3600 and multi-layered system that protects the platform, safeguards communication channels, and encrypts data
• The system will be incorporated into Mobilicom’s range of end-to-end smart solutions for the drone and robotics market and caters to fast-growing cybersecurity demand
• The Cybersecurity Suite expands Mobilicom’s offering and aligns with its transition to a software-as-a-service business model

Mobilicom Limited (Mobilicom or the Company, ASX: MOB) has launched its AI-based Immunity Cybersecurity and Encryption (ICE) cybersecurity suite to provide industry-leading 360° protection for commercial and industrial drones, robotics, and autonomous platforms against a wide variety of malicious attacks, including jamming.
Mobilicom’s ICE cybersecurity suite is the first AI-based 360° system in the world to be able to detect, prevent and respond to multiple drone/robotics cyber-attacks in real-time without requiring intervention by an operator. The ICE multi-faceted and multi-layered suite protects the platform, safeguards communication channels and encrypts the data that is transmitted and collected.
Specifically designed for commercial and industrial drone, robotics and autonomous platforms, Mobilcom’s ICE cybersecurity solution protects against more than 10 different types of cyber breaches and malicious attacks including jamming.
Continue reading: https://www.suasnews.com/2021/08/mobilicom-launches-world-first-ai-based-360-cybersecurity-suite-for-drones-robotics/

Ready to launch a blockchain project? Not so fast. Before you get started, you’ll want to make sure you know how to take a blockchain project from start to finish. CompTIA’s Blockchain Advisory Council has developed an infographic to help technology and business professionals better understand the seven phases of blockchain implementation.
Phase 1: Learn
Ensure everyone in your organization understands blockchain.

• Review recent research, business use cases and case studies.

Phase 2: Strategize
Integrate blockchain strategies into your business strategy.

• Define the business transformation opportunity.
• Determine if blockchain is the right choice.
• Develop a blockchain strategy.
• Integrate the blockchain strategy into the current business strategy.

 
Continue reading: https://connect.comptia.org/content/infographic/7-phases-of-blockchain-implementation/

According to its potential, blockchain is being used in various sectors of our life
A blockchain is a digital database, often known as a ledger, that is used to collaboratively record information and transactions. Blockchain is currently widely discussed in the media throughout the world. They’ve already been used in a variety of applications as decentralized ways to fraud-resistant computing that don’t rely on a trusted authority. A distributed, append-only log of time-stamped entries that is secured by cryptography from manipulation and alteration is known as a blockchain. Because of its unique characteristics, blockchain has been proposed for usage in a variety of applications following its successful implementation in Bitcoin.
1. Finance: By establishing a distributed public ledger, the blockchain reduces the complexities involved with financial services by allowing miners to verify transactions using proof-of-work.
2. Cryptocurrency: Blockchain has enabled the creation of cryptocurrency, which now has a market capitalization in the billions of dollars. A new block is created by running a consensus method such as proof-of-work on the Bitcoin network, which is based on a blockchain – a distributed transaction public ledger.
Continue reading: https://www.analyticsinsight.net/blockchain-is-being-used-in-various-sectors-of-our-life/

The study of history and ancient people is immensely important to preserving the knowledge passed down through the generations. 
Unfortunately, the significance of the knowledge is particularly acute when it is lost. With tragedies such as the fire of the Library of Alexandria, or the pillaging of the House of Wisdom in ancient Baghdad, or the more recent losses of artifacts at the Iraq Museum, perspectives were lost, advancements in philosophy and literature were forgotten, and languages and translations vanished from the earth. 
As we look to preserve our history, how can we safeguard the artifacts of our heritage from disaster?
Using blockchain technology to keep a record of the data stored on a decentralized cloud service could be exactly what the historical and archive industries need to protect our collective human history from destruction, pillage and faulty record-keeping.
Blockchain as a data keeper
The archive industry in many sub-sections is underfunded and lacks the means to properly care for the data being held. As told in this 2014 declaration petitioning for more funding for the United States Archive, it is clear that there is a lack of funding on many fronts, which could result in the loss of physical and digital records. 
An alternative solution is to store data directly on the blockchain. As David Vorick, CEO of Skynet and co-founder of Sia, said to Cointelegraph, “a major advantage of using a blockchain is that you can build on an open marketplace, which ensures fair pricing for everyone.” This prevents third parties from taking part of the funding, while also making sure that community members who are passionate about protecting their heritage can fund a storage system directly. 
Continue reading: https://cointelegraph.com/news/how-blockchain-could-have-saved-the-library-of-alexandria

The blockchain industry market size was estimated by some to reach more than $21 billion by 2025. The market capitalization of the cryptocurrency market as a whole already reaches over $1.9 trillion. An ecosystem that was once defined by its tight-knit community and exclusivity now reaches governments, businesses, institutional investors and individuals who are all becoming more positive about the evolving space.
With this new popularity, a crossroads has emerged. We have reached the stage of adoption where the amount of users utilizing decentralized technology has exceeded the functionality of the technology itself. This has resulted in regularly congested networks and a demand for solutions.
Many of the roadblocks we are experiencing could easily be solved with scaling solutions such as bridges, parachains and other features that create seamless transitions for Web 3.0 users and depend solely on a shared vision of a multichain approach to the next wave of blockchain adoption.
Scalability: The Ethereum challenge
Today, nearly all DeFi projects are being built on the Ethereum blockchain, making it the standard default blockchain for many decentralized applications (DApps) and protocols. However, scalability on Ethereum has presented many challenges. The pain points that have delayed adoption include costly gas fees, a complicated onboarding process and unnecessary repetition and obstacles for developers aiming to create new DApps and accompanying products.
Continue reading: https://cointelegraph.com/news/a-multichain-approach-is-the-future-of-the-blockchain-industry

Could your next lawyer be a robot? It sounds far fetched, but artificial intelligence (AI) software systems - computer programs that can update and "think" by themselves - are increasingly being used by the legal community.
Joshua Browder describes his app DoNotPay as "the world's first robot lawyer".
It helps users draft legal letters. You tell its chatbot what your problem is, such as appealing against a parking fine, and it will suggest what it thinks is the best legal language to use.
"People can type in their side of an argument using their own words, and software with a machine learning model matches that with a legally correct way of saying it," he says.
The 24-year-old and his company are based in Silicon Valley in California, but the firm's origins go back to London in 2015, when Mr. Browder was 18.
"As a late teenager in Hendon, north London, I was a horrible driver," he says. "I got a lot of expensive parking tickets - which, since I was still in secondary school, I couldn't afford."
Continue reading: https://www.bbc.com/news/business-58158820

From maximizing advertisement relevance to customizing user experience, the benefits of applied sciences and advanced data analytics have become more apparent as industries adopt data-driven approaches to create new competitive advantages. In this article, we focus on companies in the insurance industry that are implementing applications of data science to deliver efficient, risk-adjusted solutions by detecting fraudulent activity and providing a personalized customer experience. The best place to start is by looking at some of the technological trends being used by insurance companies today.
Growing Trends in the Insurance Industry
Customer Experience & Coverage Personalization
With access to a customer’s behavioral, geographic, social, and account data, AI-enabled chatbots can provide seamless, automated, and personalized buying experiences. These bots are quickly becoming the industry standard. According to a 2020 MIT Technology Review survey of 1,004 business leaders, customer service (via chatbots) is the leading application of AI being deployed today. The study shows that 73% of respondents indicated that by 2022, it will still be the leading use of AI in companies.
Behavioral-Based Policy Pricing
In the auto insurance industry, we are seeing ubiquitous IoT sensors provide personalized data to pricing platforms, allowing safer drivers to be rewarded by paying less for auto insurance (known as usage-based insurance). These techniques have expanded beyond auto insurance, and we are now seeing health & dental insurance companies also use IoT sensors that provide people who maintain a healthier lifestyle with a lower rate for insurance. A recent article highlighted dental insurance company Beam Digital for their use of IoT technologies. This company provides a smart toothbrush to every customer and monitors their oral health, while using this information to support a dental insurance plan. Beam sends the customer notices and encouragement if their brushing habits are falling short of the required standard. The company hopes this will result in improved dental hygiene and reduced premiums.
Continue reading: https://venturebeat.com/2021/08/14/science-applied-3-ways-ai-and-ml-are-advancing-the-insurance-industry/

Pepperdata, a provider of tools that optimize IT infrastructure for computation, has seen a lot of trends come and go over the years. Now organizations are using the company’s tools to optimize infrastructure to process AI models.
VentureBeat caught up with Pepperdata CEO Ash Munshi to gain a deeper appreciation for IT issues, such as data management, that are holding back the rate at which enterprise IT departments can meaningfully implement AI. But he also pointed out that a lot of companies struggling with AI might be fighting the wrong battle for their business needs.
VentureBeat: What’s the trouble with data management in the enterprise today?
Ash Munshi: When we had just classic databases, data warehouses, and stuff like data was managed sort of centrally, people had a very well-defined view of what was going on. It was very narrow in scope. That definition has been blown to smithereens. It’s like everything is enterprise data. It’s just ballooned.
People have recognized data is important. That’s a good thing. More data is better, but what do you do with it? People don’t really know this.
Continue reading: https://venturebeat.com/2021/08/15/pepperdata-ceo-says-ai-ambitions-outpace-data-management-reality/

Teachers are one of the professions least at risk of being automated. A job that requires emotional intelligence and flexibility — in adapting lesson plans on-the-fly to a particular group of children, for example — is not one particularly well-suited to robots. Artificial intelligence, however, still deserves a role in the classroom. This is not as a replacement for teachers, but as a tool or an assistant that can aid them both in trying to close the gap in achievement between the rich and the poor and in making up for lost teaching time during the pandemic.
In the UK, school closures to stop the spread of coronavirus have helped to accelerate the adoption of AI-based learning platforms as teachers sought new online methods to keep students engaged and to track their progress. These new approaches, where they have been seen to work during the pandemic, will continue when pupils return to something that looks more like a normal education.
The right approach to such technologies is to see them not as substitutes for human labor, but as a way of improving its quality and productivity. Machine learning may be more sophisticated than a shovel but the principle is the same: tools enhance humans’ existing capabilities. The best AI applications promise to improve and accelerate teachers’ knowledge of what their students need, how best to deliver that teaching, and which students require the most help — from a human teacher — to keep up with their learning. 
Continue reading: https://www.ft.com/content/ef231955-e97d-4552-8dcc-f1afe01ad613

The Internet of Things (IoT) is already transforming supply chains, from asset tracking to inventory management to warehouse and fleet operations. There are more than 10 billion IoT devices operating today, and in the next decade, experts project an additional 15 billion devices will come online. IoT devices have the potential to tell supply chain managers where assets are, keep employees safer onsite and yield valuable data that can be used to eliminate logistics bottlenecks and ensure product quality.
But to date, the limitations of wired and conventional/ disposable battery-powered solutions have made the deployment of IoT challenging. It has been dramatically slow in adoption of intermodal tracking. When products leave the manufacturing site, there’s often no visibility into location until products are received inside a distribution center. Technologies such as wireless power will transform the supply chain by closing that gap, and giving supply chain managers more insight into the conditions the product encounters along the way that may affect quality or safety.
Wired power and conventional batteries won’t allow IoT to reach full potential
Currently, most IoT devices in the supply chain are powered by electricity delivered via wire or batteries that have to be changed or charged up using traditional cords, disposable batteries or charging pads. Delivering electricity to sensors through conventional wiring tethers devices, which limits where and how they can be deployed, making their use impractical for supply chain applications that involve moving products.
Disposable batteries don’t tether devices, but they are expensive to deploy at scale, and their manufacture has many negative environmental impacts, plus they can leak toxins and corrosive materials if not properly recycled. It’s also expensive and inefficient for workers to replace batteries at points along the supply chain. Labor costs are an issue with rechargeable batteries too; employees have to place them on wired charging pads, which is impractical when products are in transit.
Even with these power-related limitations, IoT has changed how supply chain managers keep track of goods. Supply chain managers currently use sensors to monitor products in the cold chain and keep track of assets in warehouses. But, real wireless power is poised to have an even more transformative effect, making intermodal asset tracking a reality.  
Innovations in truck trailer tracking point to wirelessly powered future
There’s one recent innovation that illustrates how real wireless power can be a gamechanger. Tracking truck trailers at giant distribution centers has long been a significant challenge. Distribution centers that serve huge retailers or logistics companies can occupy several square miles and receive hundreds of trucks per day, making it hard to precisely track dropped trailers in rows of nearly identical containers.
Continue reading: https://www.sdcexec.com/software-technology/supply-chain-visibility/article/21603100/ossia-how-real-wireless-power-will-transform-the-supply-chain

The final specification of Matter, the smart home interoperability protocol founded by Apple, Google, and Amazon, has been delayed by a few more months. While it was originally expected to be ready this fall, according to Tobin Richardson, the CEO of the Connectivity Standards Alliance (CSA), that timeline has been pushed out until the first half of 2022, with members getting a sneak peak before voting on the spec at the end of this year.
That means we’ll have to wait until the first half of next year for the software development kit, the start of a formal certification program, and the first certified devices it turns out. When I asked Richardson if he could narrow that time frame down a bit, he declined. For consumers, it means the wait for new smart home devices that support the Matter protocol will be delayed until the latter half of 2022 (I can’t wait for our 2022 Gift Guide!) and for those developing products, it means they will need to hold off on their plans for a few more months.
Richardson gave several reasons why the Matter Working Group (formerly known as the Project Connected Home over IP Working Group) decided to delay the specification. They included the resurgence of the COVID-19 pandemic, the addition of another 29 companies to the Matter membership, and the challenge of delivering a high-quality software development kit as part of the spec.
The delay is disappointing, but it isn’t a huge shock. What the folks behind Matter are trying to do is audacious. The goal is to deliver an interoperable smart home protocol that lets devices talk to each other and share their capabilities. It will help cut through the challenges of building a smart home, where consumers have to worry if their light bulb will work with Alexa or Google, or if their door locks can talk to their security sensors. All Matter-certified devices will be able to work together; consumers will be able to choose from among multiple digital assistants, hubs, and apps as suits their needs.
The idea for Matter was launched in December 2019; participants expected the standard would be ready in about a year’s time. But then COVID happened, so the spec was delayed until the first half of 2021. Then in May, we learned that spec was delayed further, until the fall. But we did get several updates on its progress, including details about some of the planned features and supported devices. For those wondering, here’s what we know about Matter so far, and what we still don’t know.
Continue reading: https://staceyoniot.com/does-it-matter-smart-home-standard-is-delayed-until-2022/

Advances in commercial drone technology are opening up new growth opportunities for the space industry, which has an often underappreciated synergistic relationship with uncrewed aerial vehicles.
The fast-evolving market for drones attracted $1.4 billion in venture capital investment in 2020, according to data from early-stage space technology investor Seraphim Capital.
That’s roughly double the amount of capital it recorded in 2019, a sign startups looking to provide services ranging from drone deliveries to building inspections are gaining traction.
Clearing regulatory hurdles so drones can fly autonomously beyond visual line of sight (VLOS), where they can then carry out tasks without human intervention, marks the next step in the market’s evolution — and satellite communications are crucial for making this a reality.
“This has to come from space because you need something that has coverage everywhere, no matter what,” says Joakim Espeland, CEO of Danish drone startup QuadSAT.
While satellites might not be the primary connectivity source for all these next-generation drones, they can provide a layer of resiliency in case 5G wireless or other terrestrial networks fail midflight.
“A drone does all the processing for flying onboard,” Espeland says.
“So the only thing you need is a little bit of data going through, and that can be enough for you to sit on another side of the world and know where the drone is, what speed it’s going at and what orientation it has [and for sending a command] to safely get it back to where it needs to be.
“[A]s drones get full autonomy, we will see that in combination with space technology.”
QuadSAT is returning the favor to the space industry with a business that uses quadcopter drones that act as stand-ins for satellites, enabling operators to test and calibrate their antennas more efficiently than in a laboratory.
Espeland said this capability is becoming increasingly valuable as the rise of megaconstellations places new demands on user terminal development.
U.S.-based startup Rammaxx is also developing a drone-based business that aims to serve the space industry directly.
It recently launched a simplified “electric firework” drone for retail customers, based on those used for large-scale light show displays.
After seeing how its drones could replicate fireworks that shoot quickly and vertically into the sky, Rammaxx CEO Dan Lubrich said it began in December exploring ways to also launch satellites with them.
“As we realized how incredibly quickly drones can go up we realized that it could be useful for vertical lift, especially for space,” Lubrich said.
Rammaxx recently tested a proof of concept where a small group of drones successfully lifted a small-scale rocket to a certain height before detaching from it, enabling the launch vehicle to continue its journey.
Continue reading: https://spacenews.com/connecting-the-dots-drones-in-space-satellites-seen-as-key-to-giving-full-autonomy-to-uncrewed-aerial-vehicles/

The cryptocurrency market has left everyone astonished with the kind of returns it has given to its investors. Though this market is known to be highly volatile, the reason why it continues to grab attention from everywhere across the globe is because of the return it promises. The last year or so has been no less than a roller coaster ride for a majority of cryptocurrencies. Despite this, one cannot deny how swiftly this market corrects itself. The fact that almost all the prominent cryptocurrencies have set record gains over the course of time turns out to be a reason why investors get inclined to the cryptocurrency market.
Talking about how one can maximize their returns by virtue of the cryptocurrency investment, it makes every possible sense to mention the technology that it is built on, Blockchain. This technology has tremendous potential, thus accounting for the fact that Cryptocurrencies are gaining immense popularity with the passage of each day.
Blockchain is a distributed technology that allows extremely secure transactions to take place by means of a point-to-point network. Ever since it was introduced, Blockchain has always been in the limelight because of the popularity that it enjoyed. Apart from its wide application in the field of Cryptocurrencies, it has proven to be useful in areas such as governance, cybersecurity, industrial processes, financial sector, entertainment, etc.
Having understood why Blockchain is important, have a look at some of the reasons that’d throw light on – How learning Blockchain can benefit you in the future?
Continue reading: https://www.analyticsinsight.net/how-learning-blockchain-can-benefit-you-in-the-future/

The key to getting more value from industrial internet of things (IIoT) and IoT platforms is getting AI and machine learning (ML) workloads right. Despite the massive amount of IoT data captured, organizations are falling short of their enterprise performance management goals because AI and ML aren’t scaling for the real-time challenges organizations face. If you solve the challenge of AI and ML workload scaling right from the start, IIoT and IoT platforms can deliver on the promise of improving operational performance.
Overcoming IoT’s growth challenges
More organizations are pursuing edge AI-based initiatives to turn IoT’s real-time production and process monitoring data into results faster. Enterprises adopting IIoT and IoT are dealing with the challenges of moving the massive amount of integrated data to a datacenter or centralized cloud platform for analysis and derive recommendations using AI and ML models. The combination of higher costs for expanded datacenter or cloud storage, bandwidth limitations, and increased privacy requirements are making edge AI-based implementations one of the most common strategies for overcoming IoT’s growth challenges.
In order to use IIoT and IoT to improve operational performance, enterprises must face the following challenges:

• IIoT and IoT endpoint devices need to progress beyond real-time monitoring to provide contextual intelligence as part of a network. The bottom line is that edge AI-based IIoT / IoT networks will be the de facto standard in industries that rely on supply chain visibility, velocity, and inventory turns within three years or less. Based on discussions VentureBeat has had with CIOs and IT leaders across financial services, logistics, and manufacturing, edge AI is the cornerstone of their IoT and IIoT deployment plans. Enterprise IT and operations teams want more contextually intelligent endpoints to improve end-to-end visibility across real-time IoT sensor-based networks. Build-out plans include having edge AI-based systems provide performance improvement recommendations in real time based on ML model outcomes.
• AI and ML modeling must be core to an IIoT/IoT architecture, not an add-on. Attempting to bolt-on AI and ML modeling to any IIoT or IoT network delivers marginal results compared to when it’s designed into the core of the architecture. The goal is to support model processing in multiple stages of an IIoT/IoT architecture while reducing networking throughput and latency. Organizations that have accomplished this in their IIoT/IoT architectures say their endpoints are most secure. They can take a least-privileged access approach that’s part of their Zero Trust Security framework.

Continue reading: https://venturebeat.com/2021/08/14/realizing-iots-potential-with-ai-and-machine-learning/

From deep learning-enabled software to autonomous cars, smart robots to IoT applications, AI is deepening its claws everywhere and leaving unforgettable remarks on the world. AI-enabled technologies have specific ranks in the Gartner Hype Cycle For Emerging Technologies, which indicates that AI is unbeatable in the technology world.
However, AI business intelligence and analytics capabilities are a major attraction among businesses, as the concept improves the revenue streams and gives valuable insights. Actually, the increasing volume and complexity of data within organizations are supporting the adoption of AI to enhance enterprises.
AI and machine learning are enabling businesses to pull out valuable insights that enable businesses to forecast industry trends and user behavior. That’s the reason enterprises are eager to hire AI developers to upgrade solutions. More or less, AI usage in business intelligence can bestow enterprises with billions of dollars worth of information.
Wondering how AI in business intelligence can be leveraged? Let’s understand the undeniable potential of AI in business intelligence.
 
How Can AI Empower Business Intelligence Applications? 
Business intelligence is all about processes designed to collect, process, and analyze big data. For this, enterprises leverage a variety of business intelligence tools such as Tableau, Datapine, Zoho Analytics, and more.
In this process, some issues can hamper the value the system contributes to businesses. For example, a huge volume of data can raise a capacity limit that needs to be pushed away.
Let’s see how AI can solve shortcomings.
• AI Boosts BI functionality
Business intelligence’s real potential can be gauged in breaking down a large volume of data into granular insights. It enables enterprises to comprehend smaller aspects of the big picture. AI boosts the capacity and functionality of BI applications too. However, the real issue can arise in real-time insight.
Actually, BI’s mainstream process is to process and visualize data. But! BI can not generate this data result and predict trends in real-time. AI with the combination of latest technologies like ML infuses the capacity of generating real-time insights and trends.
Boosting BI functionality improves the value to the organization.
Continue reading: https://www.analyticsinsight.net/how-can-ai-transform-business-intelligence-top-use-cases/