Managing data gravity through proper planning prevents poor performance.
Top-notch real estate agents know how to ask the right questions before a home search begins. What are you looking for? How many people need their own room? Do you have a budding percussionist in the family that needs a spot to bang the drums without driving everybody else nuts? How much guest space do you need? These questions help ensure the home will meet your needs and allow for growth when, for example, Uncle Lou unexpectantly shows up and asks to stay for a few weeks.
What does this have to do with data gravity? In the words of Alexander Graham Bell, “Before anything else, preparation is the key to success.” And so it goes with data gravity.
Proper planning’s potential
In two previous and related blogs, we described the very real challenge of reducing the data gravity pull. While keeping data for future use isn’t inherently bad, if not managed properly, data builds over time to create latency and rising costs, especially when trying to extract value from that data while at the same time processing new data. In this blog, we will look at ways to properly plan to avoid data gravity – before it grows to unmanageable levels. In turn, this helps prevent poor performance and unnecessary expenses.
Data gravity planning must also ask the right questions. What different kinds of data are we going to keep at this new location? What are we expecting from it? Who needs answers, and how fast are those answers needed? How much data can and should be housed at this location? What is the cost/penalty for slower answers or the cost of managing, protecting, copying, and storing that growing amount of data?
Preventing poor performance
Let’s look at an example. A healthcare organization wants to open up a new remote clinic. That new clinic will need the data from images and tests they run to be analyzed on location and get patient results fast. In this highly oversimplified scenario alone, two categorically different types of data need to be collected and managed:
+ Transactional information, such as name, insurance details, health history and co-pay
+ Testing information, such as X-rays, MRIs, and Lab tests
From a data management perspective, the remote clinic will not save all of the data on location. And the different types of data have different levels of value. While all the data is governed by HIPAA regulations, the transactional information can often be readily reproduced, but the testing information is not as easily. While organizational data management practices differ, it is likely the remote clinic’s data is going to be protected in some fashion and then securely copied to another location.
In this scenario, decisions need to be made on how data will flow before the remote clinic is up and operational. For example:

• Which types of data (e.g., transactional, testing, raw data, analyzed data) should be saved and in which ways?
• How long (e.g., days, months, years) should the data be stored?
• Where (e.g., onsite, offsite) should the data be stored?
• How (e.g., (tape library, disk, cloud) should the data be stored?

Powering forward
Making these decisions in the planning phase will help mitigate data gravity and avoid costly performance drops and financial penalties later. Concepts such as capacity planning and long-term lifecycle management are vital to proper, proactive planning in the effective collection, use, and storage of data. These strategies must be articulated before data collection. Just like in our house metaphor…
When we start to hit the limit of practical effectiveness inside of our house, we must make some tough decisions. Can we expand what we have by building out? Do we need to rent a storage locker and move things out to another location? Maybe we need to call in a hoarding specialist to help figure out a plan for reducing the clutter. Similarly, in data planning, regardless of the options chosen, resolving issues after implementation are costly, may take significant time to fix, and can negatively affect the bottom line and customer experience.
Continue reading: https://www.rtinsights.com/five-ps-of-managing-data-gravity-at-the-edge/

Companies are waking up to data architecture being a companywide matter, not just an issue for the chief data officer. But like anything in IT, it has led to an explosion of hype, IT concepts, acronyms, loose definitions, and confusion. 
Data leaders wading through this growing alphabet soup of new IT vocabulary terms, two have emerged to have a polarizing effect: data mesh and data fabric. Each has its merits and reasons why companies are taking a hard look.
While they offer options for companies trying to tame the unruly mess left by data fragmentation and unlock more value from their data sets, they also put data governance at the front and center of their data strategies.
Reframing the data headache
Data fabric is essentially a design concept and technology architecture. Forrester analyst Noel Yuhanna was among the first to define the term in the mid-2000s. 
“Data fabric is a design concept and technology architecture geared toward addressing the complexity of data management to operate in any hybrid or fragmented data ecosystem. It emphasizes data automation, a robust metadata foundation, and a flexible technology backbone,” says Jon Teo, data governance domain expert at Informatica.
The primary value of a data fabric for a disparate data ecosystem is that it unifies its representation, management, and data access without having to consolidate the data assets physically. According to Teo, the “beauty” of having a flexible, unified platform is that new or changed data can be easily added or onboarded using a low or no code approach. Essentially, it allows data stewards, engineers, analysts, and scientists to create better data pipelines and oversee them. 
While the benefits are clear, practicing it has been a problem. In the past, assembling a data fabric with the full suite of data management capabilities for both on-premises and cloud ecosystems would require multiple vendors' tools. Then, you are saddled with the additional cost and associated risks of stitching these together. 
Now, companies like Informatica offer all the pillars needed to establish a data fabric architecture built on AI-powered metadata across end-to-end data management capabilities. They range from data integration to data governance and from data mastering to self-service analytics. 
Data mesh takes a different tact to address data fragmentation within the enterprise. Instead of an overarching technology management layer, it makes it a human question by creating distributed teams to manage their data domains as they see fit. 
“Data mesh focuses on organizational change – enabling domain teams to own the delivery of data products with the understanding that the domain teams are closer to their data and thus understand their data better,” says Teo. 
The idea is that these localized data “product teams”  (composed of various roles such as business data stewards, analysts, and engineers) will know their domain data better. Combining or “meshing” their management capabilities will help companies quickly gain insights into complex questions and scale analytic capabilities across the organization. 
Continue reading: https://www.cdotrends.com/story/16560/how-modernizing-data-governance-speeds-data-mesh-and-data-fabric-adoption

Whether an organization is large or small, private or public, many chief data officers (CDOs) are dealing with the exponential growth of their data. Based on my experience working with leading enterprises in Latin America, the investment in advanced analytics increased by 22% in less than a year. The amount of stored customer data in Microsoft Azure and the variety of the data has also doubled in the last three years.
IT leaders are handling this complexity while working to meet existing regulatory requirements, facilitating access to data and delivering value from that data. To address an organization's needs related to operational databases, big data, advanced analytics and artificial intelligence (AI), a seamless data platform can empower organizations to invest more time in creating value through business agility and innovation.
However, to deliver on the promise of data value to the business, CDOs must collaborate with chief information security officers (CISOs) to ensure the organization also manages the risk of data breaches and regulatory compliance. Together, they need to achieve a higher state of security, privacy and compliance across their entire data estate and throughout the data life cycle.
Five Governance Capabilities To Consider
For CDOs and CISOs beginning or continuing their data governance journey, it is worth considering the following five capabilities.
1. Data Visibility
An organization should have the ability to manage the creation and storage of data in any solution and the need to maintain a basic level of metadata. Therefore, it is important to have processes and tools to scan and collect the metadata required to create and maintain a physical inventory of specific data assets.
2. Data Discoverability
A vital part of any data governance strategy is empowering people of the data ecosystem to find and maintain metadata. This includes business glossaries, data dictionaries and data catalogs.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/30/data-governance-protect-while-generating-business-value/?sh=22f670f74990

Self-driven cars, traffic sign detection, facial recognition, and self-checkouts. What unites all of these progressive solutions is computer vision. Computer vision allows computers to extract information from raw images and open a lot of opportunities for more effective digitalization of business. Let’s take a look at how computer vision is disrupting various industries and what unique benefits it brings to help owners solve key business challenges.
#1: Object Detection
Traditional computer vision implementations used in-depth analysis of inputs and outputs. The typical flow in the case of old-school CV depended on image processing techniques like edge detection to identify and label objects in an image.
The advent of deep learning architecture in computer science caused a monumental shift from classical CV techniques like definition-based feature structures to AI-driven neural network analysis of imagery, which allows near-complete automation of extraction and classification of data in images. In simpler terms, artificial intelligence takes the programming out of the picture in favor of a less supervised approach in which the computer interprets the input data and trains itself to recognize the content of images.
Use Cases
When AI steps into fields like medical imaging, the computer leverages superior pattern recognition to identify subtle elements in raw images, such as whether or not cancer cells are present in minute amounts in an X-ray or MRI. Despite the fact that human interpretation and expertise are still needed to check the deductions of the machine, an additional layer of lightning-quick analysis helps supplement human intelligence and save lives.
As self-driving cars hit the road across the United States and many other countries, the CV field will see explosive growth. Autonomous vehicles can’t exist without computer vision. Since the vehicle’s onboard computer needs to make quick decisions about potential obstacles on the road, it depends on a highly optimized set of CV-based technologies. 
It’s important to note that in areas such as medicine, security, manufacturing, etc., the transparency of how an AI-powered system makes a decision is crucial. This is where explainable AI comes into play. This technique allows for interpretation of the findings of the system in a way humans can understand and shows the reliability of a particular decision made by an AI algorithm.
Use computer vision to address the following business challenges:

• Public security (vehicle identification, weapon type recognition, locating suspicious objects, etc.)
• Sales automation and inventory management (identifying low-stock or misplaced items on the shelves, detecting empty shelves, performing quality control, product recognition for self-checkouts, etc.)
• Eliminating human error and preventing double-counting in the workflow

Continue reading: https://www.iotforall.com/computer-vision-business-challenges

Australian universities are not only using the Internet of Things (IoT) in their research – some have also been using the technology to provide safer environments for thousands of students and staff members.
This includes at the University of Melbourne, which saw a need to help students and staff return to Covid-safe campuses. This would be no small task, considering the university has hundreds of teaching spaces.
Enter LoRaWAN, a radio-based IoT network infrastructure used to help solve this safety and compliance conundrum.
What is LoRaWAN?
LoRaWAN is a wide-area network protocol that enables low-power, battery-operated devices from any manufacturer to connect using LoRa long range radio modulation. It is commonly used in IoT applications where small data transmissions are required.
LoRaWAN is a global, open standard that suits both indoor and outdoor bidirectional communications across thousands of devices with a key benefit being that no SIM card is required. It is a complementary technology to other low-power, Internet of Things-compatible, LPWAN (low-powered WAN) connectivity standards such as NB-IoT (narrowband) and CAT M1 (cellular).
How did LoRaWAN and IoT solve a university’s safety and compliance problem?
The University of Melbourne has previously partnered with Australian LoRaWAN specialist Meshed in 2019 to deploy a campus-wide LoRaWAN network across all of its Victorian campuses including Carlton, Parkville, Creswick, Dookie and Burnley.
The networks offer public and private access via The Things Network community portal and the MeshedX Private Network Server (which is based upon The Things Stack). This enabled students, nearby businesses and industries to connect to the IoT data network at no cost, with no compromise to the performance or reliability of the university’s critical use case purposes – one of which would become safety and compliance.
Initially, the university’s Smart Campus initiative trialled a number of Proof of Concepts, but it wasn’t until Covid hit that the LoRaWAN network really came into its own. The university’s ‘COVIDSafe’ return-to-campus strategy saw the installation of ventilation and filtration controls as part of a virtual building management system, to protect the university community from airborne transmission indoors and improve general safety and compliance. 
To achieve this, the Smart Campus team rolled out more than 1,100 LoRaWAN-connected Elsys CO2 sensors to monitor carbon dioxide, temperature and humidity across 900 teaching spaces and lecture theatres. These sensors provide a constant, near-real-time status of indoor air quality and thermal comfort information.
Continue reading: https://www.iothub.com.au/news/how-the-university-of-melbourne-used-lorawan-and-iot-in-covidsafe-strategy-582055

Technology use in agriculture today is at relatively unimaginable levels. Various new agricultural technologies are on the horizon, and they look pretty promising. But now, IoT has entered the mainstream as a cutting-edge agrotechnology due to its increased use. Let’s learn what IoT is in its simplest terms. 
Do you know you use the Internet of Things (IoT) technology every time you look at your smartwatch to check your calorie intake or ask Alexa or Siri to figure out how much a pie is worth? IoT refers to the concept of the Internet controlling things. Intelligent (IoT) devices can send and receive data over the Internet. A Coke vending machine at Carnegie Mellon University from 1982 was one of the very first network-connected devices, and it could report whether or not any beverages were available.
IoT smart farming devices are made for the agriculture industry to help monitor agricultural fields using sensors and automating irrigation systems. Consequently, farmers and related brands may readily and conveniently check on the state of the areas from any location.
The horticulture sector must expand to fulfill demand despite an expanding population, which is expected to reach 9.6 billion by 2050. This is true despite environmental problems, including bad weather and climate change. The agriculture industry will need to adopt new technology to acquire a much-needed advantage to fulfill the demands of that expanding population. IoT-based smart farming and precision farming technologies will help the sector become more operationally efficient, cut costs, decrease waste, and produce higher-quality harvests.
So What Exactly Is “Smart Farming”?
IoT in Agriculture
A high-tech, capital-intensive method of growing food sustainably and cleanly for people is known as intelligent farming. It is a component of contemporary ICT (Information and Communication Technologies) applied to agriculture.
A system is created in IoT-based smart farming to automate the irrigation system and monitor the agricultural field using sensors (light, humidity, temperature, soil moisture, etc.). Farmers may monitor the condition of their lots from any location. Smart farming that is IoT-based is significantly more efficient than traditional farming.
The advantages of implementing modern technology, such as the Internet of Things in agriculture, include the following:
1. Weather Forecast:
Farming is mainly dependent on the climate. Also, poor climatic information seriously impairs the amount and quality of agricultural output. However, IoT technologies let you know the current weather conditions. The agricultural fields have sensors installed both inside and outside of them. They gather environmental information to choose the best crops for the specific climatic conditions.
The entire IoT network comprises sensors that can correctly identify real-time weather variables, including humidity, rainfall, temperature, and more. An alarm will be sent whenever any unfavourable weather is discovered. The requirement for human presence during adverse weather conditions is minimized, ultimately boosting output and enabling farmers to gain more significant agricultural advantages.
2. Precision Agriculture (PA):
One of the most well-known Internet of Things applications in agriculture is precision agriculture or “precision farming.” Precision agriculture (PA) is a method of farm management that leverages information technology (IT) to guarantee that crops and soil receive the exact nutrients they require for maximum health and productivity. PA aims to ensure economic success, environmental preservation, and sustainability by assessing data produced by sensors and responding appropriately.
To increase efficiency and effectiveness, various precision farming techniques, including animal management, vehicle tracking, and irrigation management, are used. To improve operational efficiency, you can assess soil conditions and other relevant characteristics using precision farming. In addition, you may check the connected devices’ real-time functional status to check the level of nutrients and water.
Continue reading: https://webtimes.uk/5-iot-applications-for-smart-agriculture/

What's not to love about working from home? It allows you to savor piping hot morning cappuccinos at your own pace and snuggle with your cat while typing reports from under a fluffy blanket. Unfortunately, the comfort of a home office might come at the expense of a promotion. When individual contributions become harder to recognize due to a lack of on-site presence, getting a promotion becomes more challenging. For instance, between 2020 and 2021, promotions worldwide plummeted by 48%, an Ascend study from Harvard Business Review found.
Despite less connection with coworkers, promotions are certainly not out of reach for teleworkers who can prove their mettle. In fact, a fair number of workers find telecommuting a boon to their careers. According to a 2022 Pew Research Center survey querying U.S. teleworkers, 44% of participants said that working remotely made it easier for them to get their job done.
So, what are the things you can do to advance in your job from the comfort of your home?
Let your output speak for itself Promotions are bound to land in the laps of those who can showcase their productivity in visible results no matter where they work. According to a 2015 ConnectSolutions survey, 77% of respondents who worked remotely a few times every month saw higher productivity. Among them, 30% reported completing their assignments faster and 24% accomplishing more within the same time. If you're naturally introverted, busy taking care of your kids, or having mobility difficulties, remote working might be the perfect opportunity to up your game.
Read More: https://www.glam.com/911496/get-promotion-work-from-home/?utm_campaign=clip

Despite the drone global market having an expected worth of 15 billion US dollars by 2022, the manufacturing industry was reported to account for less than two percent of drone deployments. This is surprising, given that Unmanned Aerial Vehicles (UAVs) find a wide variety of industrial applications, from surveillance to infrastructure inspection. Here Neil Bellinger, Head of EMEA at EU Automation, discusses the benefits of drone use in manufacturing. 
Drones are far from being just fancy flying cameras. Their sophisticated technology allows them to obtain and record information where humans cannot, such as in dangerous environments and difficult to access areas.
Although challenges have slowed the introduction of drones to manufacturers, such as a lack of consistent and clear regulation, this regulatory gap was bridged in 2021, when new EU guidelines on leisure and commercial drone operation were established to regulate the manufacturing and operation of drones by taking a risk-based approach. The risk is categorized into low, medium and high, each having regulations and restrictions.
The prohibition on beyond visual line of sight operations has also been lifted for drones that weigh more than five kilograms. This allows bigger drones, ideal for commercial and industrial applications, to be used more consistently in manufacturing, although their use beyond visual line still requires approval.
Continue reading: https://www.themanufacturer.com/articles/the-benefits-of-drones-in-manufacturing/

The tech world is ablaze with Web3 debate. Is it the people’s internet, free of tech-giant control? Or is it an idealistic illusion that ignores the reality of what users want and how the tech behind it works?
Either way, money is pouring in. According to Crunchbase News, 2021 saw a huge jump in investment in blockchain-related startups, from $2.1 billion in 2020 to around $17.9 billion. Early signs suggest another bumper year in 2022—deals so far include $200 million in funding for Web3 developer Alchemy and $450 million for blockchain business Polygon.
Business leaders are taking notice. CEOs and C-suite leaders I work with frequently ask five key questions about Web3—let’s dive into each.
1. WHAT IS WEB3?
To explain Web3 as we understand it today, we need to go back to Web 1.0 and Web 2.0. The differences lie in how we interact with the internet. In Web 1.0, we consume content on static websites. In Web 2.0, we interact with social platforms as active contributors and content creators. In the current shift from Web 2.0 to Web3, our interaction with the internet is becoming increasingly connected. The boundaries between the physical and digital worlds are blurring, and we are benefiting from smarter predictions of our behavior as our devices talk to each other. The Web3 features primarily enabling these changes are decentralization and increased ownership.
To bring this concept to life, imagine a group of talented experts come together to release a product to market. Today, they might form a company, taking set roles with varying degrees of influence on running the company.  With Web3, whatever your role, you have a say in the group’s purpose, how funds are allocated, and what policy looks like—including users. It’s a level of engagement that is practically unheard of, and it’s an idea that is really taking hold.
Continue reading: https://www.fastcompany.com/90761899/five-questions-business-leaders-should-be-asking-about-web3

Seventeen years ago, Paul Graham, then a relatively obscure web developer, gave a talk at Harvard titled “How to Start a Startup.” The lecture, which Graham adapted into a widely read essay, argued for a vision of entrepreneurship that was more limited than what had been attempted during the dot-com bubble. He suggested that entrepreneurs should be skeptical of venture capitalists, that they should be obsessively cheap, and that they should focus on small, unsexy markets. Above all, Graham urged founders to seek out customers from the very beginning and to respond to their needs. “Make something customers actually want,” he said.
Over the next two decades, this advice became canonical in Silicon Valley. Graham co-founded an incubator and venture capital firm, Y Combinator, that would go on to seed dozens of big companies while adopting his advice as something of a mantra. Walk around tech campuses, and you’ll see T-shirts with the Y Combinator logo, proclaiming: “Make something people want.” The advice was applied to an entire generation of so-called Web 2.0 companies—a category that came to include Facebook, YouTube, Airbnb, and dozens of other wildly successful companies.
As a startup philosophy, “Make something people want” comes with obvious limitations. Critics have long pointed out that Graham’s advice, which you could boil down to “Take a couple of MIT dormmates and build a little app,” led to companies that, at their worst, were less companies than impossibly trivial projects, led by founders who tended to be white, male, and dweeby. It also led to companies with shaky economics. There were the Web 2.0 startups that offered addictive products without making money—Vine, for instance—and those, like Uber, where customer desires (sure, dirt-cheap taxis sound great) have yet to translate into profitability.
Continue reading: https://www.bloomberg.com/news/articles/2022-06-28/web3-is-the-big-idea-customers-didn-t-ask-for

Blockchain businesses don’t operate the same way normal startups do. Blockchain communities are breaking the norm because their founders don’t all come from business schools, accelerators or traditional startup channels. Rather, they are emerging from the world of chat rooms, Twitter spaces and collaborative video calls.
Regardless of what you think about the industry’s volatility or underlying value, the amount of growth that blockchain projects have seen in the last five years is nothing short of amazing.
Interviews with more than three dozen founders, CEOs and early adopters for the KryptoNurd YouTube video series this last year (in which I participated) made it apparent that the successful projects have three key commonalities. These three tips from the current crypto craze can be applied to reinvigorate any mature business or help a startup get off the ground.
1. Focus on building communities.
It’s all about the community. Crypto projects do an amazing job at creating communities that aren’t just investors but advocates. Social media chat rooms in Telegram and Discord offer direct communication between the community and the project team.
Blockchain companies build in public, and in doing so, everyone gets to share in the success of incremental progress. People love success, and sharing progress openly allows the community to gain a sense of accomplishment and belonging. Blockchain projects will often ask their community for input, assistance and introductions, further solidifying the relationship.
Continue reading: 
https://www.forbes.com/sites/forbesbusinessdevelopmentcouncil/2022/06/29/3-strategies-from-the-crypto-craze-to-grow-your-business/?sh=172e1cf814fd

Blockchains are the Doritos Locos Taco of computer science. Complex as software can become, there are a limited number of tools available to software developers. Software developers combine arrays, databases, objects, pointers and other logical constructs in unique ways to create efficient solutions to problems, but most of these combinations have been known for decades. (This is the classic book describing some of these common combinations.) Software developers are like chefs at a Mexican restaurant mixing hard shells, salsa and beans to make a taco, but later using a flour tortilla, salsa and beans to make a burrito.
Because there are only so many ingredients available, innovative combinations are rare. In the fast-food space, the Doritos Locos Taco was one of these innovative combinations: It is just like a regular taco, but its shell is instead a giant, folded Dorito. It was unveiled at Taco Bell in 2012 and quickly became the restaurant's most popular menu item. It was a brilliant combination of existing ingredients, it took everyone by surprise, and it was delicious.
Like the Doritos Locos Taco, blockchains combine well-known software ingredients to make something completely new, brilliant and surprising. Hashing and peer-to-peer file sharing have been standard software constructs since the early days of computing, but no one thought to piece them together to build a blockchain until recently. And blockchains have had a big effect on software, the economy and internet culture in the form of cryptocurrency, non-fungible tokens (NFTs) and public ledgers of ownership.
And like a taco, the elements of a blockchain are not complicated. This post walks through building a blockchain from scratch to explain how it all comes together to create something unique in computer science.
The Ingredients
While there can be more involved as they become more complex, the basic ingredients of a blockchain are hashing and peer-to-peer file sharing. IP/Decode has discussed hashing in two posts:
Continue reading: https://www.hklaw.com/en/insights/publications/2022/06/building-a-blockchain-from-scratch

By raising standards for efficiency, trust, and integrity of data, blockchain looks set to upend traditional enterprise finance in coming years. Below, we explore the potential of blockchain for finance and look at some of the enterprise market’s early movers, including a fully end-to-end digital letter of credit.
Financial transactions across the world today are becoming more efficient thanks to decentralization and peer-to-peer interchanges, made possible by blockchain and distributed ledger technologies. By design, these technologies have proved very effective in simplifying traditional transaction processes and enabling instant payment solutions globally.
What is cryptocurrency?
A cryptocurrency, such as Bitcoin, is a decentralized digital currency that is based on blockchain technology. Unlike fiat money which is a currency declared legal by a central government and is backed by said issuer, cryptocurrency is not backed by any central authority. Through distributed ledger technology that can record and synchronize electronic ledgers across multiple computers (known as nodes) globally, rather than a central database, cryptocurrencies also eliminate the need for intermediaries and their related costs.
Although blockchain evolved with smart contracts several years ago, opening the door for blockchain to be deployed across a wider variety of industries, banks and financial sectors still represent by far the highest share of blockchain deployments today, mainly for clearing settlements, cross-border payments, and digital identity management. According to a report by Jupiter Research, blockchain deployments will enable banks to realize savings on cross-border settlement transactions of up to USD 27 billion by the end of 2030 - reducing costs by more than 11 percent.
What is decentralized finance?
Decentralized finance, also known as DeFi, is the umbrella term used for peer-to-peer financial services by using blockchain technology. This makes it an alternative financial system that can compete with centralized services in terms of accessibility, resilience, and transparency in a peer-to-peer fashion.
Continue reading: https://www.ericsson.com/en/blog/2022/6/enterprise-blockchain-finance

If you’ve recently eaten at a fast-food restaurant, driven on a toll road or checked out groceries at the supermarket, you may have noticed one thing they all have in common: Many people who used to help you have been replaced by machines.
Most people regard this as simply the price of progress. As new technology is introduced, it displaces an older technology, along with the jobs it created. What is often overlooked is that the new technology, whatever it happens to be, typically brings with it new jobs for those with the smarts and the skills to take advantage of the new opportunities at hand.
The same holds true for artificial intelligence. In its recent Future of Jobs Report, the World Economic Forum estimated that AI will replace some 85 million jobs by 2025. The same report, however, concluded that some 97 million new jobs would be created in the same timeframe due to AI. While the healthcare industry is expected to benefit most from this change, with AI-assisted healthcare technicians seeing a tremendous upward surge, all industries will likely be affected. And while many of those new positions—notably machine learning engineers, robotics engineers and data scientists—will require advanced degrees, the demand for less-skilled jobs, such as AI maintenance, will also skyrocket.
The interesting thing about this AI-inspired change is that while virtually no one denies it is already underway, some mistakenly view today’s AI as all that it will ever be. In reality, today’s AI, while impressive, actually represents little more than “a powerful method of statistical analysis ... which gives the illusion that it ‘knows’ what is happening when it attempts to perform a given task,” as I described in my previous article.
But as the old adage popularized by Mark Twain goes, “There are lies, damned lies and statistics.” People have been making poor decisions and lying with statistics throughout history. AI just adds to the problem because the people currently running AI and doing the analyses often have no understanding of what’s happening on the inside.'
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/28/as-ai-advances-will-human-workers-disappear/?sh=186922465e68

Most of us are aware that artificial intelligence is playing an ever-growing role in how modern society operates. But many of us may not know how wide-ranging and eclectic its applications are. For example, BBC News recently featured a story about actors who are concerned about AI-generated “deep fakes” that can replicate an actor’s face and voice.
Some new and upcoming uses of AI have the potential to make a big positive difference in areas such as fraud control and public safety. However, others may influence human behavior in ways that are unpredictable or even disquieting. Here, 14 members of Forbes Technology Council share new and emerging applications of AI that may be new to you.
1. Guiding And Monitoring Financial Transactions
AI in the financial industry is little understood outside of the internal technical space. AI is already present in all of the plastic transactions that take place each day in the form of fraud detection and prevention. Increasingly, AI helps make lending decisions, suggest new products or services and even offer first-line support. The percentage of AI present in the day-to-day functions of the financial industry will only grow. - Denver Hunter, PenServ Plan Services, Inc.
2. Tracking Mouse/Trackpad Activity
Recently published research has shown that AI can identify individuals by their mouse/trackpad activity on a website. In an era where privacy is threatened, this use of AI strips consumers’ agency in opting out from tracking and targeted advertising. Transparency in the use of consumer data—including click activity—should be codified across the digital ecosystem. - Nicolas Dupont, Cyborg Inc.
3. Creating Unique Images
I recently tested a beta version of a technology that allowed me to describe an image using only words. The output was a set of unique images created by a computer using AI. It was truly an incredible experience. I can’t wait for this to go mainstream! - Adam Ayers, Number 5
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/28/14-ways-ai-is-or-will-soon-be-leveraged-that-you-may-not-know-about/?sh=24b8bb221349

Artificial intelligence has completely upended the business world. Whether you’re a fledgling startup or a billion-dollar global conglomerate, the way you do business today is radically different than it was just five years ago.
In the modern paradigm, one of your company’s greatest assets is the data generated by your employees, clients, and customers. And, sadly, most businesses are leaving money on the table by simply storing that data away somewhere to collect digital dust.
The problem: How do you audit your company’s entire data ecosystem, deploy models to identify and infer actionable items, and turn those insights into positive business outcomes?
The solution: vertical intelligence.
Unfortunately, “vertical intelligence” is a buzzword. If you try to Google it, you’ll just get pages and pages of companies that specialize in it explaining why it’s important. Nobody really tells you what it is in the context of modern AI solutions.
I spoke to the team over at NowVertical Group, a big data company that specializes in vertical intelligence, to find out exactly what it means.
And it turns out that it’s quite simple. Vertical intelligence is the combination of human expertise and big data analytics applied with surgical precision and timing.
Continue reading: https://thenextweb.com/news/business-ai-solutions-beginners-what-is-vertical-intelligence

Since its conception, Artificial intelligence has come a long way. The significance of Artificial Intelligence has grown so much that, per a report from Statista, the revenue from the artificial intelligence (AI) software market worldwide is expected to reach 126 billion dollars by 2025.
To understand the various ways that AI is being adopted into business, one can take a look at the uses of AI listed below:
Market prediction
With highly volatile stock markets, the risk vs returns is exceptionally high. According to research by Forbes, it is evaluated that the total world market for algorithmic trading will expand by 10.3% by 2020. Technologies like Support Vector Machines and Artificial Neural Networks can learn the patterns that occur and predict the future of financial markets and High-Frequency Trades with high accuracy.
Customer Analysis
The analysis of the reception of the customer base towards their engagement and products can be done quickly by Artificial Intelligence. In addition, AI helps with various surveys that the companies undertake, which allows minimizing inaccuracy, emotional aspects, and any errors that could have occurred in understanding the feedback overall. This allows the business to create better strategies and make more customer-centric engagements.
Targeted Marketing
Using algorithms and NLPs, a business can create targeted ads that can be customized and shown to specific market groups. This can also be achieved through SEO and keyword matching. Overall, targeted marketing positively impacts the growth of a business.
Continue reading: https://www.businessinsider.in/tech/enterprise/news/artificial-intelligence-benefits-in-business/articleshow/92538071.cms

Despite all of the progress that has been made to make the tech industry more inclusive, it is still true that only around 19 percent of the tech sector workforce is made up of women, which means we all have a long way to go until true equality is reached in this important industry.
If you are currently working in tech and you want to do everything you can to support more women coming into, and being accepted within, the tech industry, here are a few things you can do:
1. Be an amazing role model
If you currently work in the tech industry, one of the best things you can do is to support other women who wish to enter the workforce is to be the best role model you can be.
The tech sector has a lot of male role models from Bill Gates to Steve Jobs, but far fewer well-known female role models. Women like Ada Lovelace who was an early example of a strong woman in tech, are well-known, but modern examples are surprisingly hard to come by.
By grabbing every opportunity you can to raise your profile and show the world what women in tech are able to achieve, you will be able to inspire the next generation of women in tech by showing them that it is more than possible to forge a path in what is still a male-dominated industry.
2. Become a mentor
If you already work in the tech industry, then you are in an excellent position to become a mentor. Taking another woman under your wing and teaching her everything you know about the tech industry, how to break into it and make a good impression, and how to forge a strong and lasting career, is a great way to bring more women into the fold n d support them in achieving their full potential in tech, A mentor can do everything from explaining the benefits of mechanical keyboard switches for better productivity to introducing their mentees to the right people in the right places at the right times. It is one of the best ways to support women in tech right now.
Continue reading: https://swaay.com/6-ways-to-support-women-in-the-tech-industry

Technology has undoubtedly contributed to global biodiversity loss and ecosystem degradation.
Where forests once stood, artificial lights now illuminate vast urban jungles. Where animals once roamed, huge factories now churn out microchips, computers, and cars. But now, we can also leverage technology to help repair our precious ecosystems.
Here, we discuss our two new research papers published today. They show how drones and genomics (the same technology used to identify COVID strains) can help protect and restore nature.
One paper demonstrates that drones can help safeguard biodiversity and monitor ecosystem restoration activities. They can also help us understand how impacts in one ecosystem may affect another.
Genomics can help identify populations that may be vulnerable to future climate change, and monitor elusive animals such as platypuses, lynx, and newts. Yet, our other paper found ecologists without genomics expertise thought the technology still needed to be tried and tested.
Remote sensing with drones
Drones are an increasingly common sight in, for instance, urban parks and weddings. Farmers also use them to assess crop health, and engineers use them to detect damage to bridges and wind turbines.
Drone technology has rapidly advanced over the last decade. Advancements include obstacle avoidance, enhanced flight times, high-definition cameras, and the ability to carry heavier payloads.
But can drones help repair damaged ecosystems? We reviewed the scientific literature from various environmental sectors to explore the existing and emerging uses of drones in restoring degraded ecosystems. The answer, we found, is a resounding “yes”.
We found drones can help map vegetation and collect water, soil, and grassland samples. They can also monitor plant health and wildlife population dynamics. This is essential for understanding whether a restoration intervention is working.
Continue reading: https://theconversation.com/drones-and-dna-tracking-we-show-how-these-high-tech-tools-are-helping-nature-heal-185140

It’s been a nightmare couple months for cryptocurrency investors. They’ve watched their BitcoinBTC +0.3% holdings hemorrhage 70 percent of their value since the record high of $69,000 back in November. Overall, they’ve suffered crypto losses totaling more than half (55%) of capitalization, or an estimated market loss of $2 trillion.
The days when crypto enthusiasts could talk about crypto as if Bitcoin were the new reserve currency, or the digital equivalent of the gold standard, or even a transformation of what it means to invest, are over. Crypto looks more like a classic boom and bust investment, like Dutch tulips, rather than the next best hope for humanity.
As I warned in an earlier Forbes column, the crypto boom was driven by systematic policy failures by major central banks. As long as they made bad decisions about monetary supply or failed to take on inflation, cryptocurrencies were going to look like solid investments. As soon as central banks shook off their inertia, crypto values started heading south. Meanwhile, the threat of regulation of the crypto market—regulations that might strangle the Bitcoin goose—has raised additional uncertainties about where the market is headed, and whether it pays to buy low now—or run for the hills.
Nonetheless, as Bloomberg reports, venture capitalists still want in the crypto game. They’re being smart. They sense that despite the burst bubble since January, cryptocurrencies will be here to stay. They may not save humanity from itself, as some thought, but they remain a valuable speculative instrument but also a store of value when other investments look uncertain or too volatile to handle.
At the same time, Bitcoin and crypto do offer a deeper secret that is important to the rest of humanity. That secret isn’t what they do, but how they do it. i.e. with Distributed Ledger Technology or blockchain.
Continue reading: https://www.forbes.com/sites/arthurherman/2022/06/27/can-crypto-still-save-the-world/?sh=73ae1763581a

Blockchain Creative Labs, a Los Angeles-based company owned by Fox entertainment, is looking to dive deeper into the future of Web3. The platform has already been experimenting with non-fungible tokens (NFTs) and Web3 experiences, and it is now looking to find ways to create content and distribute it on Fox’s platform, all while taking baby steps, according to the company’s CEO.
“We believe we can leverage the Fox platform to teach people what it means [for] them to value a digital good [and] the value of an NFT,” Blockchain Creative Labs CEO Scott Greenberg said during an interview with CoinDesk at NFT.NYC.
The Web3 native platform launched with a tie-in with the Fox prime-time series “The Masked Singer,” releasing NFT packs via the MaskVerse, which lets users purchase collectibles using a credit card or crypto.
Those efforts were followed by IRL experiences at music festivals like South by Southwest.
In June of last year, Fox tapped Greenberg, who was then the CEO of animation studios Bento Box Entertainment, to lead the network's efforts to develop “Krapopolis,” an animated series that would live entirely on the blockchain.
The partnership also marked Fox’s commitment to NFTs, placing $100 million behind the project. “Krapopolis,” derived from “Rick and Morty,” will air next fall on Hulu, Greenberg said.
Continue reading: https://uk.sports.yahoo.com/news/web3-adoption-inevitable-blockchain-creative-165244035.html

Jack Dorsey has announced plans for Web5, a successor to Web3. How do these blockchain standards work?
Many popular websites are rushing to embrace cryptocurrency, blockchain, NFTs, and related technology. However, the trend is part of a long journey that began in the earliest days of the web. Here’s how standards have progressed.
Web1 and Web2 Came Before Blockchain
When the internet came into common use in the 1990s, it was primarily made up of static web pages. Users could retrieve information, but even basic interactions such as on-site comments were rare. Often, user content was published manually.
Later, around 2005, Web2 emerged as a de-facto standard. Websites began to allow users to interact and post their own content in a variety of ways—through social networks, blogging, comment sections, video sharing, and more. Web2 began when websites introduced ways to automatically handle user data.
Many major websites, including Google, YouTube, Facebook, and Twitter, are Web2 sites because they dynamically display user-generated content.
The fact that Web2 introduced the possibility of online user interaction also set the stage for Web3 and the addition of blockchain transactions.
Web3 Introduced Blockchain Tokens
The term Web3 came into usage when Ethereum co-founder Gavin Wood coined the term in 2014, several years after Bitcoin went live as the first blockchain.
Though Web3 is still a loosely defined concept, it generally refers to websites that use blockchain technology to handle data and transactions.
Continue reading: https://www.bitrates.com/news/p/web3-and-web5-what-are-blockchain-based-web-standards

Blockchain is one of the most disruptive technologies of the last 2 decades. Unfortunately, its entry barriers are known for being one of the biggest in the tech industry, making adoption a difficult task for developers and users alike. When regulation is added into the mix, it is easy to understand why mass adoption has not taken place yet.
As anyone who has dealt with decentralized apps or cryptocurrency knows, joining the blockchain space can be overwhelming. Crypto wallets, tokens, cryptocurrency, blockchain networks, gas, addresses, protocols, and exchanges, are only some of the terms a beginner will find. There is no going around it and denying it, blockchain is not the most user-friendly technology out there.
If understanding these terms and navigating them is hard as a user, understanding how they work on the backend and the complex infrastructure that supports it can be even harder. In fact, ease of development is considered by many as one of the biggest issues preventing corporations from actively using blockchain. Not only are blockchain developers in limited supply but the work required to transform existing infrastructure into its decentralized version can also result in high costs.
Continue reading: https://gritdaily.com/struggling-to-adopt-blockchain-meet-the-token-that-could-change-that/

WASHINGTON - Singapore and the United States on Monday (June 27) launched a programme to help women in the tech industries of both countries learn from each other, build international contacts and expand their businesses overseas.
The programme will include networking and mentoring sessions, as well as workshops, the US Commerce Department and Singapore's Ministry of Communications and Information said in a statement.
It was launched by Minister for Communications and Information Josephine Teo, who is on a working visit to the US this week, and US Commerce Secretary Gina Raimondo, during an investment conference near Washington.
The two ministers also helmed a panel discussion with Singaporean women business leaders, on how their governments could support women tech entrepreneurs and attract and develop more women professionals in the tech industry.
Citing her experience of being a woman in the tech industry, Ms Raimondo, a former venture capitalist, said during the discussion: "Sometimes you just need to know what questions to ask. You need to know who to call. You need to know the right way to pitch your company.
"Often, women are left out of those informal discussions in networks. So that is exactly why we started this mentorship network," she added.
Continue reading: https://www.straitstimes.com/world/singapore-us-launch-networking-programme-for-women-in-tech

Recently, a friend and leader sent me an SOS about her new IT job, “I don’t know how you did this, please send help. How do I succeed here as a woman?” We set up a series of mentorship calls, but my overarching advice for her echoed throughout: “You deserve a seat at the table. Don’t act like you’re new or stay quiet. Take up space–you’re in that room for a reason. Speak with confidence. Don’t undermine yourself.” 
I no longer hide myself at work. But it wasn’t always this way. When I started my career in tech, I was already living inauthentically. I was married to a man, and my colleagues were mostly straight, white men, whose clothing styles I emulated to try to fit in. Yes, that meant I showed up to work most days in khakis and a polo shirt. I wasn’t dressing for my personality, I was dressing to play a role. A manager at the time pulled me aside and told me I needed to dress more professionally, which really meant fitting into the conformed standard of femininity: blouses, skirts, lipstick, and heels.  
I quickly realized I had lost my voice. The once-confident intern with a degree in computer science and a passion for tech hid under the cloak of the heteronormative IT world. I didn’t have role models or mentors who looked like me or who could give me cues of how I should dress or act. There was a lack of representation in my space. I was often the only woman in the room and one of the few queer people. I was playing a part and hiding my identity both publicly and privately. 
TAKING UP SPACE
This changed once I decided to finally start living authentically. I met a woman who would eventually become my wife and the love of my life, moved across the country, even spent a year pursuing my own Eat, Pray, Love narrative. I left corporate America and started a position at a woman-led tech PR firm. I stopped  showing up only for others and started showing up for myself.
Continue reading: https://www.fastcompany.com/90764727/this-is-how-i-lead-with-compassion-as-a-queer-black-woman-in-tech