According to the FWHA, there is a need for early-stage research to support emerging advances in artificial intelligence to help solve complex issues in highway transportation.
A new Federal Highway Administration (FHWA) program aims to transform highways with artificial intelligence. Some of the areas where the technology is expected to play a future role include improved safety, environmental mapping, bridge capacity insights, and smart parking.
The Exploratory Advanced Research (EAR) Program is currently soliciting proposals up until December 5. It will then award contracts or engage in cooperative agreements. It is looking for research projects that “could lead to transformational changes and truly revolutionary advances in highway engineering and intermodal surface transportation in the United States.”
Additionally, the call for proposals indicated that “this program will support scientific investigations and studies that advance the current knowledge and state-of-the-art in the sciences and technologies employed in the planning, design, construction, operation, maintenance, and management of the nation’s highways. Strategically, this research will enable and expedite the development of revolutionary approaches, methodologies, and breakthroughs required to drive innovation and greatly improve the efficiency of highway transportation.”
Continue reading: https://www.rtinsights.com/artificial-intelligence-to-drive-safer-highways-program/

Today’s design engineers are always looking for ways to innovate and compete in today’s global design environment. The 21st century has opened up a plethora of connected workflows that allow for seemingly real-time data interaction, no matter where you are in the world. The days of the central data center and being tied to the office or factory are over. Powerful mobile devices are in our pockets, with us at our bedside tables and more cost effective than ever.  We are at an inflection point; forward thinking engineers will have the advantage if they implement technology from the edge, AI and the IIoT worlds.
3D Design Platforms Reduce Design Time
Have you ever wanted to design a custom component for a product you don’t have the 3D CAD data for? If so, you are most likely familiar with the almost never-ending process of acquiring an expensive 3D scanner, getting a point cloud and manipulating it in high-priced specialty software. Next steps include converting that point cloud into a mesh, taking that into a mechanical CAD system to use finally. 
With LiDAR capabilities now built into many of these devices on the edge, 3D design platforms like Onshape, a PTC technology, can drastically reduce the amount of time and effort it takes to get useful dimensional information about an object without even sitting in front of a traditional CAD workstation. Simply point your iPhone for example at your target, walk around it and hit go, and you will then immediately have a 3D Mesh object instantly available to share with your fellow colleagues, customers, and suppliers. These consumers of the information can use whatever plane of glass you bring to the party; any modern device that connects to the internet, like a Chromebook, Mac, Windows PC, Android, or iOS device are options now for product designers who want to get their work done wherever they are.
Continue reading: https://www.designnews.com/design-software/artificial-intelligence-pushing-boundaries-design-engineering

Businesses with contact centers increasingly are striving to find ways to improve customer experience while reducing costs and the burden on employees. Enter artificial intelligence, which can help contact center agents respond to customers faster and be more productive while improving customer experience.
AI also holds the key to helping businesses reduce the cost of running contact centers. Research firm Gartner recently predicted that AI will reduce contact center labor costs by $80 billion by 2026.
Despite its promise, the technology remains highly misunderstood. Let’s explore some common assumptions surrounding the impact of AI in the contact center.
Fact: AI Is vital to Customer Success
Customer experience is now the top brand differentiator in many industries, outweighing price, product quality and all other factors. For example, 54 percent of consumers (and 57 percent of millennials) told OnePoll researchers that they would consider dropping a brand after a single bad experience. With contact center agents overwhelmed, customers are experiencing long hold times.
Conversational AI can offload many of the high-frequency, low-complexity inquiries though the use of smart bots that enable fast and accurate self-service. A recent survey from cloud contact center provider Five9 makes this point. Its 2022 Customer Service Index found that 94 percent of respondents said AI can enhance customer service.
Continue reading: https://biztechmagazine.com/article/2022/11/why-artificial-intelligence-taking-over-contact-centers

How would you describe your current testing processes? Are they manual, automated, or a combination of both? Over the last few years, more organizations have been adding test automation into the mix, and it’s easy to see why. Adil Mohammed, founder and CEO of Virtuoso, shares seven key benefits of AI-driven test automation.
Manual testing can take hours and make continuous development difficult unless you have access to unlimited resources. Accuracy is also an issue – testers are only human and can easily miss small changes. Software testing is subject to error in organizations that rely solely on manual testing and often presents a bottleneck. 
The Limits to Test Automation 
Many businesses are now combining automation with manual testing in order to speed up the process. Teams can carry out test cycles faster by automating repeated test cases, leaving the manual limited to defining the case, reviewing outputs, and carrying out a final quality assurance (QA) overview. However, test automation is never a case of ‘set and forget.’ Each test environment must be set up manually, requiring significant resources from the outset. Then, if the tests meet dynamic or unusual data, problems can occur that need humans to fix. The speed benefits of automation can therefore be canceled out by the time taken to investigate and resolve issues that arise. 
Testing User Interfaces (UIs) using a coded automation approach comes with further challenges. For example, the test may not pick up on a button that’s changed color or on overlapping UI elements. Although automation has improved the process considerably, coded tests still rely on a complex setup, consistent maintenance, and a team of human testers to verify and fix. There is also a limit to how many tests can run, with this number reducing even further when tests need to operate cross-browser.
Continue reading: https://www.spiceworks.com/tech/artificial-intelligence/guest-article/benefits-of-ai-driven-test-automation/

This is going to be a soapbox article. “Working with AI,” Thomas H. Davenport and Steven M. Miller, is an MIT Press book that has some good points but overall loses out. As the headline states, this book has a nice spread of case studies, but the higher point they try to make is not correct.
Let’s start with the good. As mentioned, the first two-thirds of this book is a series of fairly short case studies that show the breadth of artificial intelligence (AI) adoption across the business world. AI is a very valuable tool and it is increasingly being used in many ways that impact business and citizens day-to-day. For those who want to understand the rapid spread of the technology, this book will help them see how adaptable AI is and how it is transforming knowledge and processes.
It's that last part, however, where the authors miss, and they most likely do it intentionally. The repeated trope that AI won’t destroy jobs is used in a way that academics are providing to management to use in their own corporate messaging. Messaging, not reality. The AI revolution is not an industrial revolution, and economies aren’t where they were in the Eighteenth Century.
The best way to talk about what will happen to jobs is to use one of the case studies and then a part of the polemic later in the book. One case study is about how underwriting has changed. AI is being used for the simplest of underwriting cases, the argument being that will help lower boredom of the experts and let them focus on the complex cases. An expert employee, however, does wonder how they will train the next generation of underwriters, since humans no longer will see the easiest ones, the policies on which people learn in order to prepare for the complex cases. It’s a valid point, but it’s short term.
Continue reading: https://www.forbes.com/sites/davidteich/2022/11/15/working-with-ai-read-it-for-the-case-studies/?sh=57c238a43367

With the advent of Artificial Intelligence, human-machine interaction has not been interwoven into many of our everyday jobs. Over the past few years, technology has made considerable advances in approximating human interaction, especially regarding speech recognition, detecting emotions, visual cues, and voice intonation. From Apple’s Siri to Google Home, these technologies are fast becoming omnipresent and are likely to significantly impact how we perform our jobs in the future. We are rapidly moving towards a workplace where people interact with machines on a routine basis.
What is AI?
Before examining how AI technologies impact business transformation, defining the term is essential. “Artificial intelligence” is a broad term that refers to any computer software that engages in humanlike activities – including learning, planning, and problem-solving. 
Calling specific applications “artificial intelligence” is like calling a car a “vehicle” – technically correct, but it doesn’t cover any specifics. 
To understand what type of AI is predominant in business, we need to understand the contexts in which AI is used for business transformation. The two flavors predominantly used as synonymous with AI are Machine Learning and Deep Learning.
Machine learning
Machine learning is one of the most common types of AI in development for business purposes today. Machine learning helps put vast troves of data – increasingly captured by connected devices and the Internet of Things – into a representable context for humans. Machine learning can rapidly analyze the data as it comes in, identifying patterns and anomalies. This will facilitate decision-making based on the inference made by the Machine Learning Model.
Continue reading: https://timesofindia.indiatimes.com/blogs/voices/artificial-intelligence-paving-the-way-for-new-age-business-transformation/

The key focus of the company is on blockchain technology and offering custom blockchain development services and a line of blockchain-based products.
Accubits Technologies is a venture studio for blockchain and Web 3.0 companies and offers product development and digital transformation services to tech startups, Fortune 1000 companies, governments, and SMEs. The key focus of the company is on blockchain technology and offering custom blockchain development services and a line of blockchain-based products. Accubits is helping businesses embrace blockchain by getting access to quality blockchain development with minimal go-to-market time. The company is cutting down on the time for companies to build a quality blockchain product solving with the help of its product CoinFactory. The product is a suite of white-label blockchain products and platforms that help organizations take crypto or blockchain projects to the market in days. It offers a full spectrum of blockchain components as white-label solutions while offering white-label solutions for custom blockchain, block explorers, wallets, crypto exchanges, NFT marketplaces, Defi lending platforms, Defi staking platforms, IDO launchpads, DAO platforms, and ICO/STO launch platforms. The product has completed 500-plus projects. Some key clients of Accubits include the Dubai Land Department, the Government of Cameroon, International Deal Gateway, JP Morgan Chase, etc.
"We innovate to invent technological solutions to support this cause. We enable businesses and organizations to embrace emerging technologies to help them perform better and stay relevant in this accelerated technology era. We enable the change-makers with technology and innovations to bring the change they want to see in this world to build a better future," said Rahul A.R., head of blockchain, Accubits Technologies.
Rahul believes the traditional methods are not enough to enable businesses to stay competitive today. He adds that the company is reinventing the software development through automation. The company has embraced behavioral economics and psychology innovations to develop solutions that provide a competitive advantage to our customers. The expertise of the company across domains such as AI, Blockchain, Robotics, BioTech, and Behavioral economics, coupled with our vertical knowledge in retail, manufacturing, healthcare, and BFSI, empowers our clients and partners to pioneer or disrupt their marketplace.
Continue reading: https://www.entrepreneur.com/en-in/entrepreneurs/inventing-blockchain-solutions/439177

Blockchain has revolutionized the whole world. Be it healthcare, banks or any other sector has not remained untouched by its effect. From the latest survey, it’s found that there are over 83 million bitcoin block explorer blockchain.com wallets users worldwide as of July 2022. Where around 10% of the global population owns cryptocurrencies.
Now, around 16% of Americans have started investing in cryptocurrency. The decentralized ledger system of Blockchain helps the financial institution save up to $12 billion every year.
Indeed Blockchain has created great hype all around. But do you know there is a popular term called Nonce? It’s a popular term that was hidden under the shadows for years.
A nonce is a number or value you can use only once. In Blockchain’s context, it refers to a pseudo-random number utilized as a counter during mining. It is often used on authentication protocols and cryptographic hash functions.
For further understanding, continue reading this blog. We’ll uncover all the basics and its major significance in Blockchain. So, let’s get started.
What is Nonce?
A nonce is an abbreviation for ‘number used only once.’ In finance and cryptography, it is a randomly generated number used to verify transactions or perform security checks. It may seem simple, but it has a diverse range of use cases, including small transactions and space stations.
For instance, we often find captchas on websites that we must type to proceed. Even OTPs we receive via mail or phone to verify transactions are all nonces, having one-time use to verify something in a limited duration.
Continue reading: https://securityboulevard.com/2022/11/nonce-the-core-of-blockchain-security/

As time passes, it’s becoming harder to imagine a world without cryptocurrencies and Blockchain technology. The reason is that cryptocurrencies are now a part of major industries in the world. Financial solutions, gaming solutions, supply, and logistics solutions, you name it. Blockchain technology and cryptocurrencies have helped to greatly advance these parts of society and they have become highly valuable for it.
Users are making money just by being a part of these projects and buying into them. Here are three crypto projects that can potentially make you a lot of money in the future. Out of the three projects, Big Eyes Coin (BIG) has shown immense promise.
Big Eyes Coin: Big Opportunities With Big Eyes
Meme Tokens have been considered the escape token of the Crypto Space because users don’t need to concern themselves with the complicated aspects of Blockchain technology. Big Eyes Coin (BIG) is the latest token that users have their eyes on. The project is a new one that’s about to be launched on the Ethereum blockchain and made available for trading on major exchanges.
The project intends to uncomplicate Decentralized Finance (DeFi) and provides a means of wealth generation for its community of users.
Being community-owned, the users will be the first to receive news about developments and exciting rewards. Also, the ecosystem will be a decentralized one where the users have a say in the operational decisions and developments of the platform. Big Eyes Coin will not be left behind in the NFT race and is already making plans to build special NFTs the market has never seen. Being a Cat-themed project, there is no doubt that Big Eyes Coin will win the race.
Users will have access to a trading and exchange platform called Big Eyes Swap as well as exclusive events organized by the network.
The BIG token will be the utility token of the network and users who are holders are automatically granted voting rights.
Continue reading: https://www.coinspeaker.com/these-3-crypto-assets-are-reimagining-the-blockchain-technology-big-eyes-coin-apecoin-and-litecoin/

The Great Resignation has contributed to the labor shortage that has had an impact on every business – especially those with a large hourly workforce. And as companies look for solutions, including new ways to attract and retain talent, employees continue to re-evaluate their priorities for what they value in their jobs, says Kshitij Dayal, SVP of engineering and operations at Legion.
Large organizations like Walmart and Target are hiking salaries to attract hourly workers. However, with so many companies now offering sign-on bonuses and record pay packages, employers looking to compete in a tight labor market need to find a new way to win over employees. AI-powered workforce management and demand forecasting may be the solution. 
Demand Forecasting with AI-derived Insights
Every brick-and-mortar business experiences periods of peak and low workforce demand. From holidays to weather events, throughout the day, week, and month, many factors influence the ebbs and flows of a business. However, without the right tools to properly predict demand, managers are unable to create optimal labor plans and employee schedules, unsure of how many employees should work on a certain day or at a certain time. Scheduling too many people will lead to overspending on labor, and scheduling too few will ensure missed revenue-generating opportunities, as employees’ productivity may be hindered while trying to meet customer demand. 
Continue reading: https://www.spiceworks.com/tech/artificial-intelligence/guest-article/how-ai-can-help-battle-the-ongoing-labor-shortage/

The sunsetting of third-party cookies is just around the corner, and marketers are struggling to keep up with constantly evolving regulations and privacy concerns. As marketers strategize to combat the loss of third-party data to inform marketing decisions, first- and second-party data collection strategies will be paramount for driving successful data-driven marketing campaigns.
Artificial intelligence is another effective approach to capturing important customer information and unlocking insights that might otherwise go unnoticed. As a partner at fifty-five, I spearheaded the development and launch of our organization’s first customized AI-based attribution models. The potential of AI technology continues to span several topics including privacy and measurement.
By leveraging AI to replace data loss brought about by the sunsetting of third-party cookies, marketers can automate time-consuming manual processes, ensure marketing budgets are effectively allocated and ultimately make more effective business decisions.
Some common ways you may already be using AI in your marketing strategies include using AI to find propensity audiences and creating look-alike strategies. Look-alike models allow businesses to create simulated audience pools that share similar characteristics and behaviors with a business’s ideal customer group. AI-driven look-alike models analyze a broad range of first-party data to create constantly evolving profiles that can help businesses better target customers who are most likely to be attracted to the selected product or service.
Continue reading: https://www.forbes.com/sites/forbesagencycouncil/2022/11/14/3-ways-brands-can-leverage-ai-to-unlock-value-in-a-cookieless-world/?sh=211a8d4e7d86

Large language and image AI models, sometimes called generative AI or foundation models, have created a new set of opportunities for businesses and professionals that perform content creation. Some of these opportunities include:

1. Automated content generation: Large language and image AI models can be used to automatically generate content, such as articles, blog posts, or social media posts. This can be a valuable time-saving tool for businesses and professionals who create content on a regular basis.
2. Improved content quality: AI-generated content can be of higher quality than content created by humans, due to the fact that AI models are able to learn from a large amount of data and identify patterns that humans may not be able to see. This can result in more accurate and informative content.
3. Increased content variety: AI models can generate a variety of content types, including text, images, and video. This can help businesses and professionals to create more diverse and interesting content that appeals to a wider range of people.
4. Personalized content: AI models can generate personalized content based on the preferences of individual users. This can help businesses and professionals to create content that is more likely to be of interest to their target audience, and therefore more likely to be read or shared.
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   Continue reading: https://hbr.org/2022/11/how-generative-ai-is-changing-creative-work

For all their benefits, artificial intelligence tools can also introduce risk. Here are three common issues and how to protect against them.
Artificial intelligence systems and projects are becoming more commonplace as enterprises harness the power of this emerging technology to automate decision-making and improve efficiency.
While its benefits are clear, AI can also introduce risk. How should you prepare if you are leading a large-scale AI project? Here are three of the most significant risks associated with AI and how to mitigate them.
1. From privacy to safety
Worries about privacy go far beyond our clicking habits. Facial recognition AI is rapidly progressing in some ways that raise ethical concerns about privacy and surveillance. For example, this technology could allow companies to track users' movements, or even emotions, without their consent. The White House recently proposed an “Artificial Intelligence Bill of Rights” to curb the technologies from causing real harms that contradict our core democratic values, including the fundamental right to privacy.
Continue reading: https://enterprisersproject.com/article/2022/11/ai-3-top-risks-avoid-them

Nearly 75% of the world’s largest companies have already integrated AI and machine learning (ML) into their business strategies. As more and more companies — and their customers — gain increasing value from ML applications, organizations should be considering new security best practices to keep pace with the evolving technology landscape. 
Companies that utilize dynamic or high-speed transactional data to build, train, or serve ML models today have an important opportunity to ensure their ML applications operate securely and as intended. A well-managed approach that takes into account a range of ML security considerations can detect, prevent, and mitigate potential threats while ensuring ML continues to deliver on its transformational potential.
Machine learning security is business critical 
ML security has the same goal as all cybersecurity measures: reducing the risk of sensitive data being exposed. If a bad actor interferes with your ML model or the data it uses, that model may output incorrect results that, at best, undermine the benefits of ML and, at worst, negatively impact your business or customers.
“Executives should care about this because there’s nothing worse than doing the wrong thing very quickly and confidently,” says Zach Hanif, vice president of machine learning platforms at Capital One. And while Hanif works in a regulated industry—financial services—requiring additional levels of governance and security, he says that every business adopting ML should take the opportunity to examine its security practices.
Devon Rollins, vice president of cyber engineering and machine learning at Capital One, adds, “Securing business-critical applications requires a level of differentiated protection. It’s safe to assume many deployments of ML tools at scale are critical given the role they play for the business and how they directly impact outcomes for users.”
Continue reading: https://www.technologyreview.com/2022/11/14/1062881/best-practices-for-bolstering-machine-learning-security/

The origin of cryptocurrency traces back to 2009, when Satoshi Nakamoto introduced the world’s first crypto coin – Bitcoin – to the world. It was the first time a decentralized digital currency was introduced, and since then, the lure of crypto has been on a constant rise. Not just that, but there are chances of further improvement in the future.
The world is becoming more modern, digital and advanced, and as of now, not just individuals but businesses are also adapting to the changing standards. If you think that your business isn’t able to reach its potential in the local market, taking it to the international market and taking advantage of crypto might prove to be beneficial for you.
That said, before we tell you how crypto can benefit your business, let’s have a brief overview of cryptocurrency and its working algorithm.
What is Crypto and How Does It Work?
Cryptocurrency is the term given to a digital currency that doesn’t have an intermediary party to control its flow of transactions. With the help of a transparent digital process, consumers can connect with each other directly.
Whenever a transaction is to be carried out in cryptocurrency, it is submitted to a public ledger, and it won’t be completed until confirmation of proof of ownership via an encrypted e-signature. Miners are individuals who know how to solve computation puzzles, and they confirm the authenticity of a transaction before adding it to the blockchain.
Additionally, it should be clear by now that unlike traditional banking systems, you don’t have to trust third parties to facilitate the transactions.
Continue reading: https://thebossmagazine.com/3-ways-cryptocurrency-can-benefit-your-business/

Blockchain technology provides a decentralized, secure way to store and manage data, enabling new levels of transparency and collaboration that transform strategies and operations. With blockchain technology, organizations can create a shared, tamper-proof database to track transactions, assets, and interactions among parties. This provides a single source of truth that everyone can trust, eliminating the need for costly intermediaries and manual reconciliation. But leaders must take a strategic approach to ensure that their organizations can reap the full benefits of this transformational technology.
How we think about leadership is changing, and blockchain technology plays a significant role. In the past, leaders have been in charge of centralized organizations with top-down decision-making. But as we move into the digital age, decentralized systems are becoming more popular.
President Recep Tayyip Erdoğan recently stated at his government’s blockchain summit, “It is clear that we cannot ignore this potential while we are preparing for the Century of Turkey. We want to be the country that uses this tool.” Erdoğan’s remarks underscore that leadership is changing, and countries must evolve with the times or risk being left behind. As such, leaders must adapt because there are four ways in which blockchains will impact their roles in the years to come:
1. Increased transparency will lead to more accountable leaders
According to a recent IBM study, senior executives believe blockchain technology will significantly increase managerial transparency, making it easier for leaders to be held accountable for their actions. “Blockchain enables all transactions will be stored on a public ledger that anyone can view,” agreed Serge Baloyan, CEO and founder of x10 agency—a Web3 firm—in an email. He believes the aforementioned transparency will level the playing field between employers and employees. “In the past, information asymmetry has typically favored the employer,” said Baloyan. “But with a blockchain, employees can track their progress and performance, therefore garnering a better understanding of opportunities for advancement within their company.”
Continue reading: https://www.forbes.com/sites/benjaminlaker/2022/11/09/4-ways-blockchain-technology-will-change-leadership/?sh=4aebf7a64bd3

Could a blockchain-based ecosystem strengthen the security of digital ID and future-proof the next generation of online interactions?
Perhaps the most valuable asset we have online is our identity. It allows us to buy and sell goods, even open a bank account. 
It’s understandable then, that users might have qualms about trusting their identifying personal data to blockchain (the technology behind crypto), which has experienced more than $1bn (£0.87bn) in fraud since the start of 2021. 
Trust, though – along with greater security – is the object of the exercise. Blockchain-based digital ID is based on the principle of self-sovereign identity (SSI), whereby users can share selected information with vendors or service providers instead of their entire identity. The analogy is of a person walking into a bar and presenting a trusted credential that only showed they were of legal age to buy an alcoholic drink – instead of presenting an ID card that might also reveal their name and address details.
SSI means that the interacting parties know they can trust each other because they can see the key information in question. And blockchain-based digital ID could make this a reality. 
“This is significant because currently there isn’t a way for businesses online to interact with contractual trust in a peer-to-peer way that isn’t intermediated by a third-party login service,” says John Jordan, executive director of the Government of British Columbia’s Digital Trust Service, which is starting to implement blockchain-based ID systems for citizens and local businesses. “Blockchain presents the opportunity to have confidential friendships and business partners on a foundation of trust.”
Continue reading: https://www.raconteur.net/digital/how-blockchain-can-make-digital-id-more-secure/

The emerging longevity sector is attracting many crypto natives, who can both benefit from it and contribute to it with blockchain tools.
The nascent longevity industry focuses on the research and implementation of solutions and technologies to extend the lifespan of human beings — making people live healthier, longer lives.
Longevity is not yet considered an official medical term, and aging is not officially considered a disease but a natural occurrence in every living thing.
However, some biologists, researchers and practicing doctors believe this approach should change, and they are striving to discover the mechanisms of aging in humans. In doing so, they are creating age clocks by defining biomarkers for measuring biological age, exploring the best lifestyle habits and natural supplements, and inventing new drugs that could stop us from getting older.
Longevity has been on the radar of crypto leaders for some time already, which is not a surprise given that the industry promises to improve humankind through innovation. Indeed, one prominent event in the longevity industry, the Longevity Investors Conference, is organized by Marc P. Bernegger and Tobias Reichmuth, who were previously involved with the Crypto Finance Group.
Crypto meets longevity
At the most recent iteration of the Longevity Investors Conference in September 2022, speakers taking part in the “Crypto meets longevity” panel noted that both industries — crypto and longevity — are disruptive fields that challenge established norms.
“Everybody here in this room is, to a certain extent, a pioneer because we really come together in a phase where it’s similar to the internet, Bitcoin and other exciting industries,” said Bernegger, who is the founding partner at Maximon — an accelerator for longevity companies.
Continue reading: https://cointelegraph.com/news/what-can-blockchain-do-for-increasing-human-longevity

As gender equality in the workplace becomes the standard instead of the exception, a number of careers that were once open only to men are now seeing more diverse demographics among their workers. Improved access to education and professional opportunities means that more and more women are now doctors, lawyers, politicians, and a whole slew of other professionals.
Despite these improvements, certain fields remain dominated by only one gender. For example, the United States Department of Labor found that of the 74,000 crane and tower operators working in America in 2014, only 0.2% were women. Another field that’s experiencing a major discrepancy is human resources. In 2016, the U.S. Bureau of Labor Statistics (BLS) found that 72% of HR managers were women; in 2017, Payscale.com reported that a whopping 86% of HR generalists were women.
So great is women’s presence in the field that John Sumser, a principal analyst for the blog HRExaminer, famously proclaimed that ‘HR is a 47-year-old white woman.
Continue reading: https://www.analyticsinsight.net/why-women-are-the-best-to-dominate-the-hrtech-world/

Underrepresentation of women in STEM (Science, Technology, Engineering, and Mathematics) continues to be a major issue even with government initiatives in recent years to boost women studying and being employed in these disciplines. Yet, women continue to be underrepresented in these areas, and discrimination and systemic barriers still exist today.
Research shows women are still underrepresented in STEM
In 2018, women earned the majority of all college degrees in the U.S., accounting for 58% of all college degrees. Furthermore, women earned 53% of all STEM college degrees, yet the majority of those (85%) were in health-related fields with just 22% in engineering and 19% in computer-related studies. 
However, even with women earning the majority of STEM degrees, only approximately 14% of those take employment in these areas leading to a considerable gender disparity in workplaces. Additionally, research has shown that women still tend to earn less than their male counterparts in STEM roles with Asian men earning the highest and black and Hispanic women earning the least
Women struggle to get their voices heard in academia
Differences in pay form just one-factor affecting women in STEM, though, contributing to a larger issue of discrimination. A recent study looked at 1.07 million physics papers published from 1990 until 2020 across 35 physics journals. Its findings were that male-sounding names were frequently over-cited compared to female-sounding names that were consistently under-cited. 
Even though it was previously thought that women applied less often and for less money compared to men, recent research has shown that this is not the case. Women win fewer grants and are awarded proportionally less of the requested sum of money compared to men when applying for grant funding. This can have a negative effect on innovation and productivity since their findings are often overlooked. 
Continue reading: https://womenlovetech.com/more-focus-on-women-in-stem-is-needed-to-tackle-underrepresentation/

We’re living at a time when uncertainty is the only thing we can be certain about. A global recession is looming, and countries around the world are facing unprecedented challenges. It’s time we reevaluate what works and what doesn’t—and which voices are part of that conversation.
One voice that we should include is that of women of color. Recovery requires resilience, and women of color share the intimate lived experience of overcoming insurmountable challenges. Within a difficult time, there has never been a better moment to imagine a more functional, fortified future.
WHY WE NEED TO INVEST IN WOMEN OF COLOR 
Creating a better future requires investment. Unfortunately, women and other entrepreneurs that aren’t cisgender men only command a tiny stream of venture capital funding. In 2020, women-led startups comprised only 2.3% of VC funding, a number that’s worsened over time—down from 2.8% in 2019. And out of those statistics, only a sliver of a sliver goes to women of color, despite businesses touting the virtue of diversity. 
For women of color who are successful in raising capital to realize their dreams, that investment falls off a cliff between the seed and Series A stages. And those seed rounds are far smaller than rounds raised by white and male-led companies. In 2020, Black women raised $125,000 in a median seed round, while Latina founders raised a median of $200,000. Yet the average investment for businesses not helmed by women was $2.5 million. 
Continue reading: https://www.fastcompany.com/90808896/nows-a-great-time-to-start-investing-in-women-of-color

Move over Great Resignation because the “Great Breakup” looks set to shake up gender balance—and not in a good way—into 2023 and beyond. 
Move over Great Resignation because the “Great Breakup” looks set to shake up gender balance—and not in a good way—into 2023 and beyond. 
That’s according to the latest Women in the Workplace report from McKinsey, in partnership with LeanIn.Org, which found that women leaders are switching roles at higher rates than men, and companies are struggling to retain the few women leaders they do have. 
Along with sustainability, diversity and inclusion (D&I) are two of the biggest buzzwords in workplace relations. Large organizations in particular have a heightened sense of awareness that their workforce needs to be representative and supportive of all women, including women of color and LGBTQ+ women. If you look at many leading companies’ values, D&I features heavily, so why are so many women, particularly those in leadership roles, jumping ship?
What Is Happening?
The McKinsey report highlights that women in corporate America are leaving their roles for a number of reasons: microaggressions such as being mistaken for a more junior member of staff, not being rewarded for striving to create a more inclusive workplace, and not being afforded flexibility to help foster a more manageable work-life balance topped the poll. 
On a global scale, only 25% of women feel fully included in the workplace, and women who feel excluded at work are three times more likely to quit than those who feel included. These findings from Bain & Company’s global study, The Fabric of Belonging: How to Weave an Inclusive Culture also highlight another worrying trend.
Continue reading: https://tech.eu/2022/11/11/why-women-are-leaving-the-workplace/

As the applications for surveillance devices expand beyond traditional security capabilities and into business intelligence and operations, interest in the technology has expanded among both developers and consumers.
Artificial intelligence (AI) has come a long way very quickly – so quickly, in fact, that the public perception of AI remains heavily influenced by its portrayal on television or in movies, even as its real-life capabilities have begun to match and even exceed many of those depictions.
Never fear, a rogue AI is not going to form Skynet or create an army of Austrian-accented Terminators, nor does it mean you are likely to be having a conversation with an AI companion anytime soon.
That said, it does mean that working with artificial intelligence technology is no longer the exclusive practice it once was. Today, different forms of AI are being used in a wide range of devices and for a variety of different business and consumer applications.
For the security industry, this is wonderful news. Today’s security devices, like internet protocol (IP) camera and audio solutions, are increasingly capable of leveraging AI technology natively, at the network edge. This means that more powerful analytics can be run on the devices themselves, keeping bandwidth and data storage needs in check.
This means that not only are more developers capable of creating AI-based solutions, but those solutions are becoming available – and valuable – for an increasing number of consumers as well. This growing democratization of AI technology is enabling valuable new applications, both within the security industry and beyond.
Where AI Stands, and How It Got Here
Artificial intelligence is a scientific term with a scientific definition: it applies to digital systems capable of performing tasks that normally require human intelligence. If that sounds like a broad definition, that’s because it is – AI is essentially an umbrella term that encompasses everything from chatbots to self-driving vehicles. But under that umbrella, there are other, more specific terms: machine learning and deep learning.
Machine learning (ML) is more complex, and it applies to technology that shows signs of basic cognition, or the ability to learn. Deep learning (DL) adds even more complexity, helping machines perform tasks like pattern recognition and information classification. Based on that definition, it should come as little surprise that the advent of deep learning – and the deep learning processing units (DLPUs) that power today’s advanced cameras – has been a boon for the security industry.
Continue reading: https://www.securityinfowatch.com/video-surveillance/video-analytics/article/21284767/the-democratization-of-ai

AI is everywhere. The advances in AI have benefited virtually every commercial industry - but there is as much (or more!) hype about AI as there is real AI. In the midst of this are the terms - AI, Data Science, Machine Learning, Deep Learning, etc. - that are adding to the confusion. In this post, I offer perspective on two of these terms - AI and Data Science, and what they (commonly) mean relative to each other.
What is AI?
Artificial Intelligence (AI) is an umbrella term for any technology where a computer program is attempting tasks that come naturally to the human brain. Skills such as understanding written language, detecting speech, recognizing objects from images, and making plans to optimize time, are all examples of intelligence that humans display every day. Most are learned by our brains naturally as we grow and interact with the world around us, and are then refined and advanced by formal learning.
These tasks come naturally to humans but are quite challenging for computers. Computer algorithms (ways to structure programs) that can learn and perform these tasks are usually classified as AI.
What is Data Science?
In the same way that AI is an umbrella term for intelligence, Data Science is an umbrella term for insights from data. Data Science is a set of methods and practices for gathering insights (information, learnings, etc.) from data. The data can be anything (stock prices, voice recordings, sensor data from rainfall meters, satellite images, etc.). Data Science can include processing the data, performing statistical analysis of the data, presenting the data in ways that others can understand (called data storytelling), and so on. Sometimes these analyses are simple (like average rainfall). Sometimes they are far more complex. But it is all data science.
Does AI need Data Science?
Often, yes. Before a computer program tries to learn from the data, it is often helpful for a human (or data analysis program) to study the data. Data Scientists often clean the data, extract out important elements, and feed these to an AI to learn further from. This intervention often helps AIs learn better because the AI can focus on selected subsets of the data, thereby improving the learning process.
Continue reading: https://www.forbes.com/sites/nishatalagala/2022/11/10/ai-and-data-sciencewhat-is-the-difference/?sh=500e0df44b44

Artificial intelligence (AI) makes for a splashy headline, but how often does it get implemented effectively? The results of one study note that only one in 10 companies report significant ROI from using AI in their processes. The report goes on to expand on why that might be: Apparently, companies are taking on and applying AI tools for the novelty and excitement of it without taking time to apply them strategically.
This is an easy mistake to make, given the monumental claims made around AI. To let the headlines tell it, AI is the one-size-fits-all solution for businesses of every size, stripe and strategy. But AI, as impressive and fascinating as it is, must be applied intentionally—like any other tool. Personally, I’m inclined to see the value in it for network security. With the help of AI tools, businesses can do more than ever to protect their data and their team.
Security, after all, needs to be proactive. It’s not just about putting up a good “fence”—it’s about appropriately analyzing traffic and observing patterns to identify issues in advance. AI can help organizations do that. AI can, better than any human, gather information and observe patterns—and use those observations to make predictions. It can help organizations understand where their weak spots are. It can even predict the type of data breach that might befall any given company.
It’s really all about prevention. If you can gather enough information and elevate analysis to a much more abstract level, you can potentially prevent serious problems.
Consider phishing. A company facing extensive phishing attacks often doesn’t quite know how to deal with it. You can only educate your team so much on how to avoid phishing scams, but truly skilled scam artists can continue to make their way through. AI could look at the patterns of your phishing attacks and make some estimations as to where they’re coming from and who to block. Or, if you’re experiencing DDoS attacks, AI can take a high-level look at the behavior of those attackers and analyze it.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/11/08/why-you-should-consider-using-ai-in-your-network-security-strategy/?sh=298d3226734c