Just as a physical wallet allows you to store your money, a blockchain wallet allows you to manage and use your cryptocurrencies and other blockchain-based digital assets. With the rising adoption of cryptocurrencies as an investment asset class, digital payments option, and digital economy facilitator, people who own cryptos should be familiar with blockchain wallets and their uses.
Here's what you need to know and some points to consider when choosing the type of blockchain or crypto wallet to use.
What is a blockchain wallet?
A blockchain or crypto wallet is a way to manage, secure, and use cryptocurrencies such as Bitcoin (CRYPTO:BTC) and Ethereum (CRYPTO:ETH) and other digital assets based on a blockchain (for example, an NFT). There are two basic types of blockchain wallets: software wallets and hardware wallets.
Types of software wallets include web (or crypto exchange) wallets, mobile wallets, and desktop wallets. A hardware wallet is a physical device that secures access to your cryptos offline. Here are some details on each.
Web-based wallets
These are easy-to-use wallets like those hosted by an exchange where you can buy and sell cryptocurrencies. Security keys are stored and managed by the wallet provider themselves. For example, if you buy crypto using Coinbase Global (NASDAQ:COIN), security keys that manage access to the assets are held in a web-based wallet that is always connected to the internet (known as hot storage). There are security issues with this (for example, if the exchange gets hacked), but this type of storage provides some of the easiest options for managing crypto transactions and purchasing cryptos.
Continue reading: https://www.fool.com/investing/stock-market/market-sectors/financials/blockchain-stocks/blockchain-wallet/

A new method forces a machine learning model to focus on more data when learning a task, which leads to more reliable predictions.
If your Uber driver takes a shortcut, you might get to your destination faster. But if a machine learning model takes a shortcut, it might fail in unexpected ways.
In machine learning, a shortcut solution occurs when the model relies on a simple characteristic of a dataset to make a decision, rather than learning the true essence of the data, which can lead to inaccurate predictions. For example, a model might learn to identify images of cows by focusing on the green grass that appears in the photos, rather than the more complex shapes and patterns of the cows.  
A new study by researchers at MIT explores the problem of shortcuts in a popular machine-learning method and proposes a solution that can prevent shortcuts by forcing the model to use more data in its decision-making.
By removing the simpler characteristics the model is focusing on, the researchers force it to focus on more complex features of the data that it hadn’t been considering. Then, by asking the model to solve the same task two ways — once using those simpler features, and then also using the complex features it has now learned to identify — they reduce the tendency for shortcut solutions and boost the performance of the model.
Continue reading: https://news.mit.edu/2021/shortcut-artificial-intelligence-1102

Specifically designed for installation on mobile platforms, EGV improves upon Easy Aerial’s MIL-STD-810G system, which currently sees use in a wide variety of applications across the world. Owing to its compact size and lightweight, EGV’s UAVs can quickly mobilize, deploy and land from any vehicle type traveling up to 25 miles per hour, on or off-road. Available in three sizes, each system can be integrated with manned, unmanned and optionally manned systems and are all remotely deployable from any location.
Like previous Easy Guard models, EGV can be configured with a tethered, free flight or optionally tethered (untether and go) UAV, enabling optimization for a variety of payload options. EGV models implement topside doors that deploy a separate landing pad when opened, unfolding to extend beyond the box’s footprint. This allows the system to operate a larger UAV with improved safety margins on uneven terrain and on the move. Encrypted data links and non-GPS dependent landing capabilities guarantee the systems can operate in hostile environments. Each of the three systems feature either a 110/220v AC or 18-36v DC (MLD-STD-1275 compatible) power supply option for operating and charging the UAV.
EGV grants operators highly flexible inspection, monitoring and surveillance capabilities – even in remote areas lacking in infrastructure. EGV provides defense organizations with reconnaissance, real-time situational awareness for increased force protection, and communication relays for tactical maneuvering forces, special operations, and dismounted warfighters on the battlefield.
Continue reading: https://dronelife.com/2021/11/01/easy-aerial-new-drone-in-a-box-solution-ultra-portable-easy-guard-vehicle/
 

The first time I interviewed Eric Schmidt, a dozen years ago when he was the CEO of Google, I had a simple question about the technology that has grown capable of spying on and monetizing all our movements, opinions, relationships and tastes.
“Friend or foe?” I asked.
“We claim we’re friends,” Schmidt replied coolly.
Now that the former Google executive has a book out Tuesday on “The Age of AI,” written with Henry Kissinger and Daniel Huttenlocher, I wanted to ask him the same question about AI: “Friend or foe?”
“AI is imprecise, which means that it can be unreliable as a partner,” he said when we met at his Manhattan office. “It’s dynamic in the sense that it’s changing all the time. It’s emergent and does things that you don’t expect. And, most importantly, it’s capable of learning.
“It will be everywhere. What does an AI-enabled best friend look like, especially to a child? What does AI-enabled war look like? Does AI perceive aspects of reality that we don’t? Is it possible that AI will see things that humans cannot comprehend?”
I agree with Elon Musk that when we build AI without a kill switch, we are “summoning the demon” and that humans could end up, as Steve Wozniak said, as the family pets. (If we’re lucky.)
Talking about the alarms raised by the likes of Musk and Stephen Hawking, Schmidt said that “they think that by unleashing AI, eventually, you’ll end up with a robot overlord that’s 10 or 100 or 1,000 times smarter than the humans. My answer is different. I think all the evidence is that these AI systems are going to think, not like humans, but they’re going to be very smart. We’re going to have to coexist.”
You don’t think Siri and Alexa are going to kill us one night?
“No,” he said. “But they might become your child’s best friend.”
Continue reading: https://www.sltrib.com/opinion/commentary/2021/11/01/maureen-dowd-what-will/

Artificial intelligence, or AI, has been a buzzword for a while now. Although it has its own set of rewards and accolades mustered through disciplines like machine learning (ML), deep learning (DL) and natural language processing (NLP), there have been reservations about AI acquiring a greater meaning and purpose that may lead the technology astray. Think of all the dystopian sci-fi scenarios you may have read about.
But that’s not necessarily the case. It all starts with the fine line between AI and artificial general intelligence (AGI). Despite the fears and trepidations, why should we strive to build AGI? Let’s take a look.
First things first — what is artificial general intelligence?
AGI refers to a machine’s ability to leverage human-level intelligence to comprehend, learn and perform actions. In simpler words, AGI is the ability of a machine to understand and navigate the world as any human would.
What transforms AI into AGI?
Although AI has made exponential progress in the past few years, human intelligence continues to remain far more complex. For AI to achieve the status of AGI, it would have to incorporate:
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2021/11/01/why-should-humankind-strive-to-build-artificial-general-intelligence/?sh=2220b4263323

Companies in the financial sector may leverage artificial intelligence to analyze and manage data from multiple sources to provide valuable insights. These innovative results help banks overcome the difficulties they face on an everyday basis while providing day-to-day services such as loan management or payment processing. Now, let’s examine some use cases of FinTech innovation driven by AI, and the main benefits FinTech companies can gain from this technology. 
Increased Security
AI in the realm of finance powers many solutions aimed at enhancing security precautions. For instance, banks offer apps that can be accessed only with facial or fingerprint recognition. This is made possible due in large part to Artificial Intelligence.  
Some experts claim that passwords and usernames will be replaced by AI-backed security solutions in the near future. Speech recognition, face recognition, and other biometric data can add a supplementary security layer and are more difficult to bypass than traditional passwords.
Continue reading: https://www.iotforall.com/4-ways-artificial-intelligence-will-change-fintech

This article features how IoT will impact the world of Wi-Fi and the internet
IoT is short for the Internet of Things, which refers to a collection of devices connected to a network. These devices share a connection through Wi-Fi or Bluetooth networks. Examples of them are smart home appliances such as thermostats, refrigerators, home security systems, cameras, wearable devices, routers, smart speakers, and so on.
IoT can have a huge positive impact on Wi-Fi and the internet (network) because of the integration of Smart Home technology, advancements in home and property security, and even in the social setting such as prevention of traffic jams and accidents.
How Does The Internet of Things Function?
All smart devices connected by the Internet of Things function using the Internet protocol address (IP), the same protocol that identifies computers, allowing them to communicate with each other. The primary purpose of the Internet of Things is to improve home efficiency and help devices share essential information much more quickly.
Continue reading: https://www.analyticsinsight.net/how-will-iot-impact-the-world-of-wi-fi-internet/

Cointelegraph is following the development of an entirely new blockchain from inception to mainnet and beyond through its series, Inside the Blockchain Developer’s Mind. In previous parts, Andrew Levine of Koinos Group discussed some of the challenges the team has faced since identifying the key issues they intend to solve and outlined three of the “crises” that are holding back blockchain adoption: upgradeability, scalability, and governance.
Blockchain testnets are an interesting subject because they come in all shapes and sizes. So, in this post, my goal is to leverage my inside experience as the CEO of Koinos Group (developers of Koinos) to demystify testnets and perhaps give some insight into why they seem to have such an impact on price.
The most obvious place to start is with the name: testnet. The purpose of a testnet is to test a network. At a very high level, there are two “flavors” of testnet. The first is a testnet that is released prior to a mainnet (main network), and the second is a testnet that is released after a mainnet is already in operation. The functions these serve are similar, but the context in which they are released dramatically impacts the perception, and impact, of the release.
Continue reading: https://cointelegraph.com/news/inside-the-blockchain-developer-s-mind-what-is-a-testnet

Since the release of the Bitcoin white paper exactly 13 years ago, blockchain technology has revolutionized several industries with multiple use cases, including facilitating money transfers, automated legal contracts, and providing traceability to the supply chain. And a blockchain project advised by the co-inventor of blockchain technology, Dr. Scott Stornetta, has decided to launch their mainnet on this very day. Jax.Network positions itself as an extension of the Bitcoin (BTC) network, fixing the scalability problem of the latter.
Through many years of research, the Jax.Network team believes they have found a solution to the Blockchain Scalability Trilemma. Jax.Network brings this to life as the first full-state sharded proof-of-work (PoW) network, introducing an approach for solving the scalability problem in blockchain networks like Bitcoin. The team believes they are well-positioned to achieve this goal due to the onboarding of Dr. Stornetta, one of the co-inventors of blockchain technology, as an advisor.
The project is an open-source protocol anchored to the Bitcoin network to build a universal standard for quantifying economic value. It also has a native digital currency known as JAX, the backbone of the Jax.Network’s blockchain value proposition.
Continue reading: https://cointelegraph.com/news/crypto-payments-platform-introduces-a-solution-to-scalability-concerns-with-the-help-from-co-inventor-of-blockchain

SINGAPORE - Cross-border payments, which typically take three to five days to clear, can now be processed within a few minutes using a new service being tried in a pilot program.
Partior, a blockchain technology provider for payments clearing and settlement, was formed by Temasek and DBS and JP Morgan banks to test the initiative.
It managed to achieve end-to-end settlements in Singdollar and US dollar in under two minutes, all thanks to blockchain technology, which allows a network to move and validate information simultaneously.
Partior was conceived during Project Ubin, a collaborative project between the Monetary Authority of Singapore (MAS) and the financial industry to explore the use of blockchain and distributed ledger technology for clearing and settlement services.
Partior chief executive Jason Thompson told The Straits Times that the instantaneous exchange of information is akin to "a data handshake", which is very different from what is happening elsewhere.
Continue reading: https://www.straitstimes.com/business/banking/no-more-waiting-days-for-global-transactions-to-clear-thanks-to-blockchain

I recently came across Marc Andreessen’s article from 2014 on Bitcoin (BTC). In many ways, it is visionary (no surprise). I have been in the industry for four years now, with most of my focus being on the social impact of blockchain. It is astonishing to me that in 2014, before there was any institutional presence in Bitcoin — or, indeed, a popular understanding of this new technology — Andreessen was able to outline its potential economic and social impact for the future.
Nearly eight years after he inked his words, I would like to address one of the topics from his article: micropayments. I will explore how blockchain could help transform micropayments and thus enable not only the monetization of certain aspects of businesses that are in need of a solution but also could assist society’s most vulnerable.
Micropayments
Micropayments are not a new concept. Since the mid-1990s, micropayments have experienced various degrees of popularity. By definition, micropayments are transactions with a value smaller than a certain threshold. Importantly, below that threshold, the transaction fee incurred becomes a significant portion of the total transaction value and, consequently, not economical. Another important aspect is that due to the minuscule monetary amounts, micropayments refer only to digital transactions of non-tangible goods. Any additional cost of handling and shipping might mean a hundredfold increase of the original transaction value, making it utterly irrelevant.
Continue reading: https://cointelegraph.com/news/blockchain-technology-can-make-micropayments-finally-functional

Lately, cloud storage has arisen as the favored alternative for an ever-increasing number of organizations attributable to its adaptability, limits, and easy access to data. Also, many reputed cloud storage suppliers offer solid information encryption and other dependable arrangements to ensure security. Many organizations have moved their server centers onto the cloud because of load adjusting, information trustworthiness, and reinforcement choices.
What do you understand by Blockchain-based Cloud Storage?
In Blockchain-based cloud storage, information is separated into numerous scrambled fragments, which are interlinked through a hashing capacity. These safe sections are conveyed across the network, and each fragment lives in a decentralized area. There are solid security arrangements like transaction records, encryption through private and public keys, and hashed blocks. It guarantees powerful protection from hackers. Thanks to the sophisticated 256-bit encryption, not even an advanced hacker can decrypt that data.
In an impossible instance, suppose a hacker decodes the information. Even in such a situation, every decoding attempt will lead to a small section of information getting unscrambled and not the whole record. The outrageous security arrangements effectively fail all attempts of hackers, and hacking becomes a useless pursuit according to a business perspective. Another significant thing to consider is that the proprietors’ information is not stored on the hub. It assists proprietors to regain their privacy, and there are solid arrangements for load adjusting too.
Continue reading: https://www.analyticsinsight.net/five-ways-blockchain-technology-is-enhancing-cloud-storage/

We have some great news coming out of the United States on the cryptocurrency industry this month with potentially more good news coming later this fall. On Oct. 6, Gary Gensler, head of the U. S. Securities and Exchange Commission (SEC), confirmed during a House Committee on Financial Services hearing that the regulator will not ban cryptocurrency, potentially blazing the path for the world’s largest economy to become the global leader in the development of decentralized finance (DeFi) and blockchain technologies.
Gensler, who taught a class on cryptocurrency at MIT, also said that prohibiting cryptocurrency doesn’t fall under the SEC’s mandate and the only way to legally ban digital assets would be through Congress. “It’s a matter of how we get this field within the investor consumer protection that we have and also working with bank regulators and others — how do we ensure that the Treasury Department has it within Anti-Money Laundering, tax compliance,” Gensler said. He also added:

“Many of these tokens do meet the test of being an investment contract, or a note, or a security.”

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U.S. regulators will not ban cryptocurrencies
The SEC’s announcement comes after U.S. Federal Reserve Chair Jerome Powell said on Sept. 30 that the regulator has no plans to ban Bitcoin (BTC) and other cryptocurrencies during testimony in Congress. When asked by Rep. Ted Budd, a longtime advocate for the cryptocurrency sector and a member of the Congressional Blockchain Caucus, whether he intended to “ban or limit the use of cryptocurrencies,” Powell responded with a resounding “No. [I have] no intention to ban them.”
Continue reading: https://cointelegraph.com/news/the-united-states-will-become-the-global-crypto-and-blockchain-leader

As the Founder and CEO of Peerro, a career pathway management system that  connects employers, schools, training organizations, governments and non-profits via one platform, Dr. Rachel Angel doesn’t work to make a living, she lives to work.
However growing up in an entrepreneurial household and witnessing her parents struggle to make ends meet, being self-employed left little to be desired. She quickly discovered that becoming a profitable entrepreneur extended far beyond the strength of having a solid idea.
Angel says, “We exist to provide access as well as actionable  instruction and education to individuals seeking a seat at the proverbial table. I’m  genuinely inspired by all the ways sharing just a small bit of information can help  change the course of a person’s life journey. The way I see it, when one of us wins, we  all win.”
Making the world a better place is a fundamental part of everyday business at Peerro.
Through passion and purpose, Dr. Angel was able to raise $1.3 million in capital from investors that believed in her vision. Her value proposition for providing a more efficient  system for employment candidates and related services was further validated when Franklin County, the largest district in the state of Ohio, began using Peerro’s software.
Continue reading: https://www.blackenterprise.com/meet-the-woman-who-raised-1-3-million-to-develop-a-career-pathway-app-for-students-of-color/

Sometimes it’s the obvious things that are overlooked. Why aren’t there pictures of women building robots on the internet? Or if they are there, why can’t we find them when we search? I have spent years decades doing outreach activities, providing STEM opportunities, and doing women in robotics speaker or networking events. So I’ve done a lot of image searches looking for a representative picture. I have scrolled through page after page of search results ranging from useless to downright insulting every single time.
Finally, I counted.
My impressions were correct. The majority of the images you find when you look for ‘woman building robot’ are of female robots. This is not what happens if you search for ‘building robot’, or ‘man building robot’. That’s the insulting part, that this misrepresentation and misclassification hasn’t been challenged or fixed. Sophia the robot, or the ScarJo bot, or a sexbot has a much greater impact on the internet than women doing real robotics. What if male roboticists were confronted with pictures of robotic dildos whenever they searched for images of their work?
The number of women in the robotics industry is hard to gauge. Best estimates are 5% in most locations, perhaps 10% in some areas. It is slowly increasing, but then the robotics industry is also in a period of rapid growth and everyone is struggling to hire. To my mind, the biggest wasted opportunity for a young robotics company growing like Topsy is to depend on the friends of founders network when it leads to homogenous hiring practices. The sooner you incorporate diversity, the easier it will be for you to scale and attract talent.
Continue reading: https://venturebeat.com/2021/10/31/a-call-for-increased-visual-representation-and-diversity-in-robotics/

Supercomputing has come a long way since its beginnings in the 1960s
Initially, many supercomputers were based on mainframes, however, their cost and complexity were significant barriers to entry for many institutions. The idea of utilising multiple low-cost PCs over a network to provide a cost-effective form of parallel computing led research institutions along the path of high performance computing (HPC) clusters starting with “Beowulf” clusters in the 90’s.
More recently, we have witnessed the advancement of HPC from the original, CPU-based clusters to systems that do the bulk of their processing on Graphic Processing Units (GPUs), resulting in the growth of GPU accelerated computing.
Data and Compute – GPU’s role
 
While HPC was scaling up with more compute resource, the data was growing at a far faster pace. This has presented big data challenges for storage, processing, and transfer.
HPC’s GPU parallel computing has been a real game changer for AI as parallel computing can process all this data, in a short amount of time using GPUs. As workloads have grown, so too have GPU parallel computing and AI machine learning. Image analysis is a good example of how the power of GPU computing can support an AI project. With one GPU it would take 72 hours to process an imaging deep learning model, but it only takes 20 minutes to run the same AI model on an HPC cluster with 64 GPUs.
How is HPC supporting AI growth?
Storage, networking, and processing are important to make AI projects work at scale, this is when AI can make use of the large scale, parallel environments that HPC infrastructure (with GPUs) provides to help process workloads quickly. Training an AI model takes more far more time than testing one. The importance of coupling AI with HPC is that it significantly speeds up the ‘training stage’ and boosts the accuracy and reliability of AI models, whilst keeping the training time to a minimum.
Continue reading: https://technative.io/hpc-ai-working-together-data-overload/

ORACLE, GOOGLE, MICROSOFT, and Amazon are archenemies in the competitive cloud computing market. But in late 2018, top executives from the four companies, including future Amazon CEO Andy Jassy, teamed up on an unpaid side gig: advising the president and US Congress on how artificial intelligence can bolster national security.
The executives were named to the National Security Commission on AI, created by Congress. Its chair was Eric Schmidt, previously CEO of Google, who later said it would help the US “harness this transformative technology to benefit both our economic and national security interests.”
Schmidt, Jassy, and the other commission members from Big Tech also had an economic interest in the topic. Their companies compete for Pentagon contracts, like the $10 billion JEDI project that is now being reworked after a lawsuit from Amazon. Schmidt sat on the board of Google parent Alphabet until 2019 and has since invested in Pentagon contractor Rebellion Defense.
The NSCAI completed its three-year mission and shut down on October 1. But fans of the body say—and critics fear—its legacy will live on. Both point to how the group’s recommendations, some of which steer the Pentagon to work more closely with the tech industry, have already been written into law. The US has few laws specifically concerned with AI, and the commission shaped a significant chunk of those on the books.
NSCAI says 19 of its recommendations to Congress were included in the defense budget approved in December 2020. One directs the Pentagon to use an existing industry exchange program to bring in more AI talent from tech companies. Another promoted the director of the Pentagon’s Joint AI Center, which aims to expand military use of AI by tapping commercial AI providers, including Google, to report directly to the deputy secretary of defense.
Other recommendations from the group include having the Pentagon create an internal platform for current and future AI projects that draws on “computing and storage services from a pool of vetted cloud companies." Another calls for a department-wide push to use “commercial AI solutions” to automate its many administrative processes.
Continue reading: https://www.wired.com/story/group-pushed-ai-us-security-boosted-tech/

Companies in the financial sector may leverage artificial intelligence to analyze and manage data from multiple sources to provide valuable insights. These innovative results help banks overcome the difficulties they face on an everyday basis while providing day-to-day services such as loan management or payment processing. Now, let’s examine some use cases of FinTech innovation driven by AI, and the main benefits FinTech companies can gain from this technology. 
Increased Security
AI in the realm of finance powers many solutions aimed at enhancing security precautions. For instance, banks offer apps that can be accessed only with facial or fingerprint recognition. This is made possible due in large part to Artificial Intelligence.  
Some experts claim that passwords and usernames will be replaced by AI-backed security solutions in the near future. Speech recognition, face recognition, and other biometric data can add a supplementary security layer and are more difficult to bypass than traditional passwords.
Artificial Intelligence in FinTech embraces behavioral solutions and can lead to a revolution in finance. The AI can monitor how a customer interacts with their transactions and determine their typical behavior. Let’s say a customer tries to withdraw $7,000 from their account in a place outside their typical location several times in a row. AI-powered machine learning will detect this activity as possible fraud and block it.
Continue reading: https://www.iotforall.com/4-ways-artificial-intelligence-will-change-fintech

Artificial Intelligence (AI) – the capability of a machine or piece of software to display human-like intelligence – permeates our daily lives, often in ways we do not notice. It touches us in myriad ways. Advanced technology operates behind the scenes, powering and optimizing smartphone apps, transportation, healthcare, retail, and more.
In the words of my colleague at EastBanc Technologies, Levon Paradzhanyan, “AI-capable agents have cognitive functions that allow them to observe, learn, take action, and solve a problem or task autonomously. … [AI-powered]] computers can make use of human brain structure to perform natural language processing, image recognition, and much more, in some cases surpassing human expert benchmarks!”
How is this possible? It’s all about math and computing power. The key is to be able to process more complex mathematics faster and with more accuracy. That requires more computer power: vaster processors and more memory to be able to hold more data. And because Moore’s Law, which in 1975 predicted a doubling of transistors on a chip every two years, has largely held up, we continue to have the computational power needed to carry out increasingly complex and ambitious Deep Learning (DL) models and AI algorithms.
Even though machines can solve certain tasks much quicker than humans, today’s AI remains firmly at its first level, which we sometimes refer to as “narrow AI” because it is limited to handling certain tasks in a very clearly defined – narrow – way. Beyond narrow AI are two more levels, “general AI” and “super AI,” which together offer a theoretical view of what AI may eventually become.
AI has long been a favored subject in popular culture where it has obtained an almost mythical status at times. It’s often dystopian. “Blade Runner” – and the short story on which it was based, Philip K. Dick’s “Do Androids Dream of Electric Sheep” – introduced us to android antagonists called “replicants,” which are generally superior to humans, but some of which – or whom? – do not actually know that they are machines. In “The Terminator,” innovative but reckless humans build intelligent machines, which become self-aware – i.e., autonomous and untethered from human control. Naturally, the machines decide to wage war against humankind in a near-successful attempt at wiping us out. In another genuine sci-fi classic, “2001: A Space Odyssey,” HAL, the onboard computer/spaceship operating system, goes rogue and tries to kill the crew in an act of very humanlike self-preservation. Fascination becomes fear as AI is used to exemplify humankind’s hubris.
Real-life AI is more benign. Driverless commuter trains. Semi-autonomous cars built by Tesla and a rapidly growing number of other innovative automakers. Smart home appliances that “talk” to each other (and us). Financial technology solutions that facilitate payments and incorporate advanced algorithms. Computer-driven coordination of public transportation. All examples of supercomputers running algorithms and making calculations far beyond what any human can do – making our lives just a little bit easier.
One of the most famous examples of just how smart a machine can be was IBM’s “Deep Blue” computer defeating world chess champion Garry Kasparov. How did a computer get the better of the world’s best chess player? Very simply put, IBM’s machine had the ability to crunch through every possible action and outcome on the chess board faster and with more accuracy than any human could. And that – carrying out a clearly defined intellectual task – is where current AI excels. The machines cannot think independently, but when it comes to crunching such numbers, they are far ahead of us.
Continue reading: https://customerthink.com/the-three-levels-of-artificial-intelligence-weve-only-just-begun/

During the mid-twentieth century, managing the household was transformed by the mainstreaming of technological innovations such as washing machines, dishwashers and vacuum cleaners.
Perhaps in three decades from now, technology will have evolved to a level to allow humanoid robots, such as Andrew played by the late Robin Williams in the 1999 movie Bicentennial Man, to take over the household chores entirely.
Whether or not this represents a flight of fancy, what we know is that technological advancement rarely happens in great leaps but rather, through incremental steps.
Sydney and San Francisco-based AI and robotics startup a•kin, who have developed robotics alongside the likes of NASA, are currently working towards one such important staging post.
Smart speakers like Amazon Alexa and Google Home are already transforming the home for many and voice activation provides a particular boon for users with physical disabilities.
A•kin is focusing on taking things one stage further by creating a more empathetic, goal-orientated home AI system that will be initially targeted towards caregivers living with disabled family members.
Taking on, in its first iteration, the form of a voice-activated kitchen hub with tablet-based personalized breakout avatars for every family member — a•kin’s system is designed to help with everything from meal planning to setting goals and the efficient allocation of household chores.
Read more: https://www.forbes.com/sites/gusalexiou/2021/10/30/lg-and-akin-to-develop-ai-home-helpers-for-families-living-with-disability/?sh=5ff7d0823736

In the first blog in the AI transportation and logistics series, I featured AI transformation innovations at Purolator; the second blog focused on the acceleration of smarter AI telematics in fleet management. The third blog explored AI emotion sensors and the impact that the affective computing market is having on the transportation and logistics industry. The fourth blog discussed AI revenue growth and operational optimization use cases relevant to the T&L industry and touched on drones and their economic impact.
This fifth blog discusses the impact of smarter intelligence integrated into the supply chain management (SCM) value chains, from picking, sorting, delivering, and all sales and customer service operations. A complete technology end-to-end connected - IoT a smarter AI sensor value chain, where humans are the strategic architects, controlling the dynamics of their SCM ecosystems, determining and adjusting in real-time operational requirements.
We will see in our life time, more robots, cobots, driverless vehicles and smarter IoT sensor highways integrated creating this realtime pulse that will reshape millions of jobs around the world.
Sound far-fetched. Likely in my life time, I won’t see all of this come together. However, my children likely will.
Just look how at some history of the origin of the aerospace industry which dates to 1903 when the Wright brothers demonstrated an airplane capable of powered, sustained flight. The world’s first scheduled passenger airline service took off in 1914, operating between St. Petersburg and Tampa, Florida. This historical event helped advance daily transcontinental flights.
In just 100 years, we went from literally no airplanes in the sky, to having over 250 international airlines, and over 5,000 airlines having official ICAO codes.
Let’s compare this speed to the speed of the drone and IoT smart logistics industry transformation. What are the drivers of the change. Perhaps four key drivers are noteworthy 1) the disappearance of space and time barriers 2.) the ability to stay connected while on the move 3.) The Internet of Things and 4.) The universality of the internet and rise of cloud computing enablements. The outcome - smarter connections in everything.
Continue reading: https://www.forbes.com/sites/cindygordon/2021/10/31/advancing-ai-smarter-intelligence-everything-in-the-transportation-and-logistics-industryindustry-series-blog-5/?sh=31ff2f347837

Traditional drones and satellites for military surveillance could be joined by the PHASA-35: a new uncrewed aircraft developed in the UK that flies in the stratosphere— a part of the atmosphere unencumbered by other aircraft or satellites.
“It stays up for a long while and it can look a long way—those are two of the real key attributes for a surveillance platform,” notes Drew Steel, an aviation adviser for BAE Systems, the company that is developing the system after acquiring it from its initial designers at the British company, Prismatic.
PHASA-35 stands for “Persistent High Altitude Solar Aircraft.” The number 35 is its wingspan in meters: that’s 115 feet, as wide as those of a Boeing 737. But the carbon fiber aircraft weighs a mere 330 pounds, which is one three-thousandth the weight of the 737. 
The drone is a high-altitude long-endurance (HALE) unmanned air vehicle that runs on solar-powered electric engines during the day, and lithium-ion batteries at night. It’s designed to fly at an altitude of about 65,000 feet in the stratosphere, the layer between Earth’s atmosphere and space. For comparison, a passenger aircraft flies no higher than 42,000 feet. Because the air there is about a thousand times thinner than it is closer to the Earth, the aircraft’s wings have to be extremely long to keep it airborne. 
Steel says that “the solar power enables [the PHASA-35] to stay airborne for up to a year and at 65,000 feet, it’s above all the traffic and most of the weather, so it can look a long way.”
Continue reading: https://www.popsci.com/technology/solar-powered-drone-will-fly-stratosphere/

In the first blog in the AI transportation and logistics (T&L) series, I featured AI transformation innovations at Purolator; the second blog focused on the acceleration of smarter AI telematics in fleet management. The third blog explored AI emotion sensors and the impact that the affective computing market is having on the transportation and logistics industry. The fourth blog discussed AI revenue growth and operational optimization use cases to ensure that your T&L company is positioned for accelerated growth. This fifth blog and is looking at the impact of robotic drones.
AI : Robotic Drones - Why is this important?
First the drone logistics and transportation market is estimated by Precedence Research to surpass US$ 41.4B by 2030 and is growing at a CAGR of 21.2% from 2021 to 2030. According to Precedence Research, the drone logistics and transportation market size was valued at US$ 8.7 billion in 2020. Drones are defined as unmanned aerial vehicles that can be operated from a remote area. These unmanned aerial vehicles are used for various purposes such as in delivery services, border surveillance, combat operations and many others. The delivery services provided by the commercial drones are more cost effective and time efficient in nature. It has an accurate locating program that enables the accurate location of the consumer and this helps in delivering the packages faster. With the advancement of technologies, innovative features can be added to the drones that improves their efficiency. All these attributes of the drones is expected to drive the growth of the drone logistics and transportation market.
Unmanned aerial vehicles are expected to generate $82 billion in economic growth by 2025 along with 100,000 jobs. Despite recent regulations, the USA Federal Aviation Administration (FAA) has issued hundreds of waivers to companies interested in commercial drone use. While drones will impact a number of industries, they will have the greatest impact on supply chain and logistics. Some of the rulings require special notice and awareness on some of the go to market complexities in building drones.
For companies interested in commercial drone usage like drone delivery, several rules stand in their way. Most notably, the “line of sight” rule which requires drone owners to keep their drones within eye shot at all times. For other limitations, businesses can apply for waivers to circumvent the regulations, including:
·     Flying a drone from a moving aircraft or a vehicle in a populated area,
·     Flying at night,
·     Flying multiple drones with only one remote pilot,
·     Flying over people,
·     Flying over 400 feet above ground level,
·     Flying over 100 miles per hour groundspeed, and
·     Flying with less than 3 statute miles of visibility.
 
Continue reading: https://www.forbes.com/sites/cindygordon/2021/10/31/advancing-ai-revenue-growth-insights-in-the-transportation-and-logistics-industry-series-blog-5/?sh=747073091049

From dressing up in terrifying costumes to getting candy from roving neighbors, drones and robots had some serious fun this Halloween 2021. Here’s a compilation of some of the best drone Halloween videos and photos from this year, including an epic drone light show in Dallas.
Haunted drones spook hapless ice cream lovers
Halloween means it’s time for Ellen DeGeneres to scare her staff. This year, she lured them to the parking lot with an ice cream truck – but it turned into an “I scream” truck with haunted drones. An old trick that never fails to impress!
Watch more: https://dronedj.com/2021/10/31/drones-halloween-2021/

The drone market size is expected to grow by $21.01 billion at over 14% compound annual growth rate (CAGR) from 2020 to 2025, according to the latest research report from Technavio.
The drone market report covers insights on major trends, key growth drivers, and challenges impacting the overall growth of the market.
Attractive Opportunities in Drone Market by Application and Geography – Forecast and Analysis 2021-2025
The drone market size report covers the following areas:
Drone Market Sizing
Drone Market Forecast
Drone Market Analysis
The report identifies the rise in applications of drones as one of the major factors driving the growth of the market. The increase in legal acceptance of drone operations for commercial applications will be crucial in fueling the growth of the market over the forecast period. The drone market analysis includes the application segment and geographic landscape.  
Continue reading: https://azbigmedia.com/business/drone-market-size-expected-to-grow-by-21b-by-2025/