Artificial Intelligence (AI) is a trending topic for many industries now. A variety of organizations currently employ AI mechanisms to support their operational functions. Automated tasks, natural language processing, deep learning, and problem-solving; such AI characteristics have made business tasks much easier. The factor of security in AI is largely overlooked, and with the increasing number of cyber threats and attacks, AI security serves as a crucial element that should be paid attention to. Security in AI falls into two different areas:

• Using AI for cybersecurity.
• Using cybersecurity for AI.

Using AI for cybersecurity
Distinct capabilities of AI, for instance, deep learning and unsupervised learning, serve huge benefits for cybersecurity since it holds the ability to analyze and mitigate large sets of potentially malicious data without any human interaction, while providing recommendations for future threats.
The application of AI for Digital Safety has several benefits and usages:

• The ability to detect and identify anomalous patterns and vulnerabilities within extensive networks. It is time-consuming or rather complicated for humans to monitor and analyze large-scale networks. With AI, analyzing data from multiple endpoints becomes more efficient and faster which leads to quick detection of vulnerabilities and threats before any attack is executed. AI-powered Intrusion Detection Systems (IDS) detect any unusual or malicious traffic over normal traffic that enters a network. A real-life application of Artificial Intelligence for IT operations (AIOps) platforms uses big data analytics and Machine Learning (ML) to detect problems by analyzing large amounts of data and predicting to prevent future issues.

Continue reading: https://www.tripwire.com/state-of-security/artificial-intelligence-new-chapter-cybersecurity

• By Dr. Christopher Richard, MD & Chief Cloud Architect, G7 CR Technologies India 5G technology is picking pace and finding its way to sweep businesses by offering ultrafast transmission rates. According to a report by Grand View Research, the global 5G services market is expected to reach USD 664.75 billion. This is a compound annual growth rate of 46.2% from 2021 to 2028. In fact, the research firm also predicted the adoption of 5G and its use to grow in numerous industries, including agriculture, retail, and utilities. Many enterprises have already started to integrate 5G technology into their systems. As companies are nowadays dependent on a large amount of data, there is a need for cloud computing to make the data actionable. This is where the concept of 5G technology comes into place for offering faster connectivity rates that are expected to be at least a hundred times faster than the existing 4G. Many sectors like healthcare, BFSI, automotive, education, transportation, and eCommerce will be able to completely change the landscape of the businesses, which was earlier not possible with 4G. In fact, it is estimated that there will be over 1 billion connections of 5G by 2022 and 2 billion by 2025. Also, every two in five people would live within reach of a 5G network, reported by GSMA. No matter which industry it is, every tech and non-tech industry would look forward to shifting to cloud services along with 5G technology to compete with the industry leaders. The benefits of leveraging cloud computing and 5G technology are never-ending. With the upcoming release of 5G services, businesses will be able to take advantage of services like Multi-access Edge Computing (MEC), Mobile Cloud Computing (MCC), and different networking architectures. How is 5G technology transforming cloud computing? 5G technology accelerates businesses to achieve streamlined work processes with incredible speed and efficiency. Here are some of the transformation areas which companies are currently exploring:
• As 5G has faster data rates, it speeds up the analytics software and enables remote login.
• 5G technology lets you analyze big data at a lower price to streamline your business operations with extensive speed and high reliability.
• It enables edge computing to eliminate any latency associated with the data centers. Also, edge computing reduces data usage by 50%. Businesses can use 5G technology to enhance the significant capabilities of cloud computing technologies like AI (Artificial Intelligence) and NLP (Natural Language Processing).
• As 5G allows high-speed data transfer, much attention is paid to detecting and preventing cyber-attacks.

Continue reading: https://www.crn.in/columns/how-innovations-in-5g-technology-will-lead-to-new-possibilities-for-cloud-computing/

Considered to be roadblocks to digital transformation, legacy systems and infrastructure have to soon be replaced if organizations have to stay ahead of the curve. These systems operate in silos harming productivity and are not compatible with other data systems. Being unreliable and inefficient they increase the downtime and maintaining them is expensive too. Delivering poor customer experience, these obsolete systems pose many risks and challenges and are unsustainable.

Ravindra Katti
On the other hand, it makes good business sense for organizations to modernize their infrastructure to benefit from the several advantages it offers. Reliability, cost-effectiveness, faster go-to-market, scalability, and flexibility are only a few rewards the modern IT environment extends. Furthermore, this advanced infrastructure is highly secure and supports innovation which drives the creation of differentiators for the organization. Businesses have this sound option of modernizing the infrastructure and applications thereby empowering teams to deliver better performance.
There are several factors to be taken into consideration when it comes to modernizing the IT Infrastructure. With organizations modernizing their IT infrastructure, the existing application stacks are transformed.
Multi-cloud strategy Cloud services help in optimizing those applications that are unique to the respective services provider. The portfolio of cloud services, the tools to enable DevOps and other advantages differ from one cloud service provider to another. To manage the various cloud providers and run different workloads on specific clouds as the business demands, is by establishing a multi-cloud infrastructure. This enhances efficiency across all environments. IT leaders are choosing hybrid cloud to accelerate the organization’s IT infrastructure modernization efforts. This approach delivers more flexibility and intensifies security measures.
Hybrid approach Hybrid cloud integrates across on-premises infrastructure, and private and public cloud environments. Being a seamlessly connected system, it enables orchestration and portability across the environments. The traditional hybrid cloud infrastructure only focused on transforming select aspects of the on-prem to private cloud to be later connected to the public cloud. In contrast, the modern hybrid cloud architecture improves app portability across all cloud environments. Automating the deployments of the workloads to the most suitable environment is another significant aspect of the hybrid approach.
Organizations are now aware of the long-term advantages of hybrid cloud adoption including cost efficiency. During the expansion of IT capabilities, investments in buying, installing, and maintaining additional servers are eliminated. It also delivers edge computing capabilities increasing the speed of operations and ensuring critical services are close to end-users.
Machine learning (ML) and Artificial Intelligence (AI) Intelligence is not present in the IT infrastructure for learning and observing the correlation between various IT elements. Data trends and insights for making the right decisions are not possible without the introduction of AI-based IT infrastructure which leverages Machine Learning, Big Data, and Analytics. Advanced Machine Learning (ML) algorithms help in effectively identifying the outliers and prevent potential disruptions of the IT infrastructure. Read more: https://www.expresscomputer.in/news/modernizing-it-infrastructure-enables-businesses-to-become-future-proof/91725/

Lyndsey McGonnell from Salesforce shares some tips for women keen to progress their career in tech leadership.
Succeeding in technology consulting obviously takes a lot of hard work, but I would like to offer a few top tips from my two decades in the sector as a woman with an atypical personality type. In summary, these are:

• Tackle imposter syndrome by surrounding yourself with the right team
• Lead authentically
• Ensure you're comfortable with the core competencies of your role
• Adapt your personal style when necessary

I have occasionally succumbed to imposter syndrome. This isn't entirely bad as it tends to drive you to do your best and demonstrate your value. However, as the scope of your role expands, it will inevitably encompass too many topics for any single person to claim to be a subject matter expert in all of them. No one is expecting you to be amazing at everything. Great leadership involves being honest with yourself about your strengths and weaknesses and building a team around you that compensates for your weak points whilst amplifying your strengths. It took me years to grow comfortable with letting go and fully delegating some aspects of my roles but, once I did so, this epiphany led to a step-change in my performance. 
Continue reading: https://www.computing.co.uk/sponsored/4059832/tips-women-harnessing-differences-excel

To eliminate the biases from the sector, talent managers work extremely hard alongside running awareness campaigns or educating the people of the company. However, a few more steps are yet to be taken on the ground level to completely abolish it from the spectrum.
The Indian technology sector is long known for gender biases as it has always been dominated by males. However, with the advent of new-age technologies, there is a radical shift in women's behavior in exploring IT as one of the most sought-after career options. The number of women enrolling in BTech and other IT courses has significantly increased from eight percent to 19.72 percent between 2016 and 2021, as per the Ministry of Education's recent data. Yet still, there is a stark gender divide in the Indian tech industry that needs a vital solution to promote diversity, inclusivity and enhance profitability.
Usually, women reaching their mid-thirties give up on their careers to handle societal and cultural responsibility. Though the number of women entering the IT sector is almost equal to that of men, their ratio in the industry certainly decreases while working at managerial levels.
As per the facts, women in entry-level recruits are close to 51 percent while women in management positions account for 25 percent and less than 1 percent, at the C-suite level. As a result, the industry remains male-dominated, creating a wide gender diversity gap.
To eliminate the biases from the sector, talent managers work extremely hard alongside running awareness campaigns or educating the people of the company. However, a few more steps are yet to be taken on the ground level to completely abolish it from the spectrum.
Continue reading: https://www.indiatoday.in/education-today/featurephilia/story/women-tech-strategies-hr-break-down-barriers-2295544-2022-11-10

Despite career benefits from remote work, nearly half of women in tech have seen an increase in workplace sexual harassment in the last five years.
In the U.S., diversity and inclusion are at the forefront of the corporate arena. Companies have realized that to get the best tech talent, they must do more than talk a good game. 
“I think that there’s been substantial movement just over the last five years,” said Meredith Graham, chief people officer at Ensono. “Is there a lot of work that still needs to be done? Yes.”
Ensono recently surveyed 1,500 women working in technology across the U.S., India and U.K. for its Speak Up 2022 report to understand day-to-day challenges, gaps in support and training and the impact of remote work. More than half of women in tech surveyed felt the number of male allies had increased in the workplace over the past five years, according to data from Ensono released Thursday. And nearly all the women surveyed said they consider their company to be an inclusive workplace.
Implementing anonymous employee hotlines, ongoing education and training and eliminating the fear of retaliation for employees that speak up are just a few starting points for leadership at companies wanting to support folks, Graham said.
The industry’s inclination toward remote work has positively impacted women in the field, as well. More than 70% of women in tech said remote work made it easier to be promoted, improved work/life balance, increased happiness and expanded opportunities.
But, even though most companies claim to be inclusive, toxicity remains for women technologists.
Continue reading: https://www.ciodive.com/news/women-tech-toxic-workplace/636080/

Artificial intelligence (AI) at the edge of the network is a cornerstone that will influence the future direction of the technology industry. If AI is an engine of change, then semiconductors are the oil driving the new age that is being defined by machine learning (ML), neural networks, 5G connectivity and the advent of blockchain, digital twins and the metaverse.
Despite recent disruptions to the chip industry due to supply chain and more recently, macroeconomic factors, the confluence of AI – and the Internet of Things (IoT) known as AIoT– is poised to shift the world from cloud-centric intelligence to a more distributed intelligence architecture.
It is expected that a staggering 73.1 zettabytes of data is expected to be generated by IoT devices, in 2025 according to IDC Research. As a result, endpoint data will increase at a CAGR of 85% from 2017 to 2025, driving intelligence from the cloud to the endpoint to run AI/ML workloads within tiny machines (TinyML). Some of the applications that are seeing the most disruption include the development of “voice as a user interface” to improve human-to-machine communication, as well as environmental sensing and predictive analytics and maintenance. Major growth segments include wearables, smart homes, smart cities and intelligent industrial automation.
What are the benefits of embedding intelligence at the endpoint? Many industrial IoT applications operate within environments constrained by memory capacity, limited computing and battery power and sub-optimal connectivity. Moreover, these applications often require real-time responses that may be mission and system critical. Expecting such devices and applications to operate in a cloud-centric intelligence architecture just does not work.
This is where the power of embedding intelligence at the endpoint is evolving from standard industrial IoT implementations to what we are calling AIoT for industrial applications.
Transforming data at the source of collection minimizes latency and enables optimized processing for time-critical applications. Because data is not processed and transported over the network, the security concerns related to transfer and flow of data, are greatly minimized. Another advantage is that data handling, can be linked with root-of-trust at the endpoint, making the implementation impervious to attacks. Since data processing is handled at or very near to the source, we can fully leverage data gravity and reduce the power consumption associated with turning on radios or moving data through the network.
Our commitment to our customers is to lead the industry in endpoint compute technology with the broadest range of MCUs and MPUs. Already this has enabled designers to leverage our rich ecosystem of IoT and AI/ML building blocks by tapping into a technology ecosystem that features more than 300 building blocks of commercial grade software provided by Renesas’s trusted partners.
Continue reading: https://www.renesas.com/us/en/blogs/executive-blog-ai-iot-edge-disrupting-industrial-market

IoT applications are growing in complexity and generating high volumes of data. This creates the need for improved data ingestion and processing capabilities – where new data can be translated into valuable insights. With the help of IoT partners, communication service providers (CSPs) can support their customers to make data-driven business decisions and generate value from the data collected from the IoT ecosystem.
But exactly what role should the CSP play in the IoT ecosystem? What are the data platforms of choice for efficient management of data-driven services?
IoT is an immediate opportunity for CSPs to seize
The adoption of IoT continues to grow in many industries. Based on an Analysys Mason survey of 108 CSPs and IoT service providers worldwide, it’s projected that the total number of IoT connections worldwide will increase from 1.8 billion at the end of 2020 to 6.2 billion in 2030.
When it comes to cellular IoT, based on the Ericsson Mobility Report, the number of IoT devices with cellular connections is expected to reach 5.5 billion in 2027 compared to around 1.9 billion at the end of 2021 (See figure 1).

 
The questions that always arise in the IoT business revolve around answering how this will bring value to CSPs, and what their role is in managing this data. We’ll endeavor to answer these questions.  
In terms of value, in the same survey, the total revenue from the value chain for traditional cellular and low-power wide area (LPWA) networks worldwide is expected to be around USD 247.5 billion by 2030. While this promises a substantial revenue increase in coming years, it indicates that the application layer accounts for two thirds of the total revenue (see figure 2).
Continue reading: https://www.ericsson.com/en/blog/2022/11/the-future-iot-ecosystem-will-fuel-monetization-of-data-driven-use

Although factories and processing plants around the world are progressively adopting more automation to improve production, quality and efficiency, these efforts remain largely old-school, using hard-coded automation logic that endures statically once it is commissioned. Continuous marginal improvement is possible through the efforts of hands-on operations personnel, but once a system is in production, it is often difficult to initiate major changes.
But what if an automation platform could provide the intelligence and visualization needed to empower operations personnel to make certain adjustments in real time? These improvements could include minor changes, often suggested by data visualization and analytics, or significant changes driven by machine learning-enabled automated decision-making. This would allow organizations to move beyond basic automation and toward a much more advanced state of automation, keeping them competitive.
Modern industrial Internet of Things (IIoT) technologies, edge and cloud software, machine learning (ML), artificial intelligence (AI) and low-code platforms are enabling this type of advanced automation and putting companies on the path to benefitting from artificial intelligence of things (AIoT) implementations.
Taking An AloT Approach Led By Operational Know-How
Applying digital automation techniques to industrial operation challenges has been effective for decades, but this work is often gated behind capital projects requiring specialized engineering and programming skills. Once facilities are in production, human operators usually remain involved as partial or essential decision-makers, so why not explore ways to make greater use of these boots-on-the-ground experts?
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/11/09/advancing-to-the-future-of-industrial-automation/?sh=2413834d3db8

Businesses understand artificial intelligence and machine learning will transform the way they work with data. But boardrooms find the details confusing
“Don’t believe the hype.” While it may take many by surprise, that’s the fresh call to action among analysts paying close attention to how companies are – or aren’t – factoring artificial intelligence (AI) and machine learning (ML) into their data management plans and playbooks. 
After years of reading sensational stories about the limitless potential of intelligent machines, stakeholders and C-suite, executives in particular appear to be confused about the best course of action to take. Commercial missteps and the total failure of some products have resulted. Experts say it doesn’t have to be this way.
“AI and ML has become crucial and necessary for nearly all businesses in every sector,” says Elliott Young, CTO, Dell Technologies UK. “In the same way that businesses have had to transform digitally and become digital-first, companies are going to need AI and ML to remain competitive. Those on the path towards this are already reaping the benefits of being able to make decisions driven by predictive analytics.”
But most boardrooms and bosses don’t fully understand the potential use cases for AI and ML. “Stakeholders often don’t know what to ask for in order to get the right benefits out of the technology,” says Young.“ This means they don’t really know what their business could be missing out on.  
Continue reading: https://technologymagazine.com/articles/artificial-intelligence-strategists-are-drowning-in-data

Everyone should consider learning more about Artificial Intelligence Maturity and the factors that impact this development. Although AI has been around since the 1950s, it seems to be going through an accelerated growth spurt on its way to full maturity, and this transition phase appears to be making some people a little nervous.
Those nerves will undoubtedly calm as specific AI technology gets closer to maturity and as additional industries become more comfortable with AI. To get there, it’s important to acknowledge AI’s strengths and weaknesses. For instance, there are real and valid concerns around AI’s transparency and trustworthiness, but there are also undeniable benefits in the form of measurable and significant efficiency gains and valuable insights for better decision-making.
Take the legal industry, for example. It tends to fly under the radar when it comes to discussions about AI use, but corporate legal departments and law firms are awash in data from invoices, contracts, and law firm “scorecards” – all of which can benefit from AI’s valuable insights. Legal is also a field that deals with sensitive information and millions of dollars derived from fees and contractual agreements, so maintaining transparency and integrity in AI is essential.
In short, the likely monetary, time and strategic benefits to be derived from the use of AI in the legal industry are substantial. That makes it a great use case for AI maturity through what I call the “four Vs:” Variety, Volume, Veracity, and Velocity.
Continue reading: https://aithority.com/machine-learning/follow-the-four-vs-to-achieve-artificial-intelligence-maturity/

This past spring, I had the opportunity to develop a virtual cybersecurity camp for young women and girls called CompuGirls. CompuGirls was founded in 2006 by Dr. Kim Scott and introduces adolescent girls to the fields of science, technology, engineering, and mathematics (STEM) through culturally responsive practices and social justice.
During one of our Saturday classes, I sat in one of the virtual sessions and listened to the group conversation about the dangers of cyber vulnerabilities. The instructor likened the protection from cyber hacking to the strategies that one might take when approaching their vehicle at night in an isolated area:
“Think about when you place your key sticking outward between your fingers, just in case someone tries to attack you,” explained the instructor.
Eyes widened across the Zoom boxes, their innocence captured on screen. “Wait, what?!” exclaimed a student.
“Yeah, you need to know how to protect yourself,” replied the instructor. This conversation was one of many that reminded our learners about the dangers that exist in physical and online spaces. Women worldwide are targeted at higher rates than men for online and offline violence. Yet, I wonder, are other affinity groups having the same conversations about safety online, and in the real world, in the same way that we are? Better yet, how are we promoting physical and online spaces that consider the complex and marginalized social identities our students hold?
This generation of youth, or “Zoomers” as they’ve been called, need clear guidance and instruction on safely navigating physical and online spaces. As a millennial, I emerged from adolescence with a relatively small digital footprint. Now, as a parent and teacher, I have never seen a generation with their physical, digital, and social identities so tightly woven.
Continue reading: https://www.edsurge.com/news/2022-11-08-what-my-girls-camp-reveals-about-the-promise-of-women-in-stem-and-the-dangers-of-online-hate

Alan Turing, widely considered to be the father of theoretical computer science and artificial intelligence, reportedly said that “once the machine thinking method had started, it would not take long to outstrip our feeble powers”, and that we should “expect the machines to take control”.
The world has changed dramatically in the decades since Turing left us, and the voices portending a dystopian future proliferated by artificial intelligence technologies have grown louder.
We live in an era where AI isn’t confined to the world of science fiction or even a tour of Silicon Valley; it permeates much of our daily lives. Whether in the form of predictive internet search engines, chatbots that help us book everything from restaurants to Covid-19 vaccines, smart devices in our homes, or virtual assistants telling us how long the drive to the office will be – AI is everywhere.
Market research forecasts that the global AI industry will grow at an annual rate of 33.6 per cent from 2021 to 2028. We are standing on the brink of the AI-driven Fourth Industrial Revolution.
As AI technologies evolve, there will be a significant shift in the composition of our workforce. According to a 2020 report unveiled at the World Economic Forum, automation and workplace digitisation will disrupt 85 million jobs globally. Another forecast by the World Intelligence Congress also points to AI potentially replacing nearly 70 per cent of an average human manager’s workload by 2024.
The alarm bells of human workers being displaced by technology are sounding once again.
Continue reading: https://www.scmp.com/comment/opinion/article/3198719/age-artificial-intelligence-human-skills-are-needed-more-ever

Despite climate mitigation efforts to keep global warming below 1.5°C, many experts expect the world to warm by 3.5°C by the turn of the next century. This ever-warming world has brought floods and wildfires and the loss of life with more disruption expected in the decades to come.
So, it is crucial to focus on climate adaptation at scale, as well as climate mitigation. We must strengthen our ability to adapt to current and expected climate events, using actionable climate insights to inform decisions. The use of artificial intelligence (AI) for its climate modelling capabilities is fundamental to this, yet we see significantly more AI innovation focused on climate mitigation, such as leveraging AI to measure and reduce emissions. This innovation gap needs to be addressed and the development of responsible AI must be accelerated to acquire actionable climate insights.
This means that governments and businesses must radically rethink their approach to climate adaptation. AI is key to this, with a recent survey by BCG posed to over 1,000 public and private sector executives, finding that 87% see AI as an important tool to fight climate change. Here's how AI can be key to climate adaptation:
Using AI to build climate resilience
Between 3.3 and 3.6 billion people live in areas at high risk of climate change, areas where we already see or will see a significant increase in natural disasters and this is likely to increase as the climate crisis is exacerbated. This year’s extreme weather events, such as droughts, hurricanes, wildfires and floods, have shown us that adapting our societies to the perils of climate change is a daunting task.
Continue reading: https://www.weforum.org/agenda/2022/11/how-artificial-intelligence-can-prepare-us-for-climate-adaptation/

While the field of artificial intelligence (AI) has made steady progress over the past few decades, only recently did progress rapidly accelerate, allowing scientific achievements to be translated into real-world use cases. In the last few years, AI has been developing at a consistently rapid pace and has achieved an inflection point. We’re currently in the midst of an AI revolution, utilizing AI’s capabilities like never before.
But before we can examine just how AI is revolutionizing our way of life, we must first look at how it got to where it is today. AI had already entered the minds of prominent scientists by the 1950s, as evidenced by Alan Turing’s 1950 paper, “Computing Machinery and Intelligence.” Between 1957 and 1974, computing capacity advanced to the point where people were able to improve machine learning algorithms and put AI to use.
Still, it took years, and recent innovations such as deep learning, for AI to achieve escape velocity. As the memory and computational horsepower of computers has improved, the capacity for AI has grown exponentially. Today, in the digital information age, AI has become an instrumental tool in such diverse fields as banking, medicine and marketing. It has ushered in unprecedented levels of commercial success for the companies willing to wield it, and, as I wrote in a recent article, its ability to solve complex problems continues to grow each day.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/11/08/ai-the-apex-technology-of-the-information-age/?sh=52c98ae63f6a

Artificial Intelligence as a tech category has become so broad that it’s nearly lost all meaning. It encompasses everything from chatbots to autonomous vehicles to scenes from Terminator 2.
This ambiguity impacts AI’s adoption across many businesses and increases the desire for data privacy protections and greater accountability in AI. Recently, President Biden unveiled an AI Bill of Rights designed to set an AI framework and new standards for AI in government.
So how can agency leaders move AI forward responsibly and with confidence?
Demystifying and defining what AI can do, or can’t do, is the first step in the process. By clearly defining what AI is and is not, misconceptions can be dispelled and AI models that support complex missions at the speed of relevance employed with confidence.
AI as a Force Multiplier
AI is a means to an end, an enabler and force multiplier for government agencies and businesses who can and should use it to their advantage. Most of the AI solutions being utilized today keep humans involved in each task to ensure creativity, common sense and, in some cases, emotional intelligence remain central to decision-making.
Although today’s AI is unable to flex every human-like muscle, it does bring five important “sights” to the table: hindsight, foresight, insight, oversight and rightsight. Fully understanding these five sights and their value is the key to operationalizing AI capabilities to accelerate mission outcomes in matters as complex as national security and disease control or as routine as help desk calls.
Continue reading: https://www.c4isrnet.com/artificial-intelligence/2022/11/08/demystifying-the-five-sights-of-artificial-intelligence/

Almost three in four (72%) women between the ages of 16 and 27 in Britain consider working in tech to be prestigious but are far less likely than men to pursue a career in the sector, according to new research by HelloFresh, the world’s leading meal kit company and integrated food solutions group. The survey of 1,000 young people by HelloFresh and Kantar highlights a need for more representation from women, better training and information, with the prevailing perception that it is a male-dominated industry.
Women between the ages of 16 and 27 report seeing a role in technology as desirable, citing good job prospects (63%), great benefits and perks (50%) and the potential to have a positive impact on society (29%). Despite recognizing the strengths of the sector, only 19% of those surveyed said they were likely to pursue a career in the sector with only 6% of those saying they were ‘very likely’. That compares with 28% of male respondents who said they were likely to pursue a career in the sector with 14% of those saying it was ‘very likely’.
Surprisingly, despite being no older than 27, one in five of those surveyed believe they are too old to switch into a career in tech (19.3%). When asked about their perception of the sector, 77% of women still consider it to be male-dominated (compared to 59% of men). Almost half (49%) of women aged 16-27 believe more women in leadership roles would encourage them to enter the sector, and 45% want to see more role models.
Women are also more likely than men to believe they don’t have the right skill set (55% vs 31%). This uncertainty around starting a tech career is also reflected in the finding that 32% of women who are discounting a career in technology mention that they don’t have enough information about the sector.
Continue reading: https://techround.co.uk/tech/women-under-30-consider-working-in-tech-prestigious/

Women have had a major impact on the tech industry, and their presence in a variety of tech-focused roles and leadership positions is growing. As more and more females launch new tech companies, step into the C-suite and create new tech products and services, being part of supportive and educational communities can be a tremendous source of strength and inspiration.
There’s a wide variety of resources women in tech can and do turn to as they navigate their careers—some of them might surprise you. Here, 15 members of Forbes Technology Council share the resources they’ve found to be especially helpful and impactful, both for themselves and for female tech professionals in general.
1. Female Mentors And Investors
As a female founder who’s raised €17 million but who’s also the mother of two young children, having female mentors was really decisive. I think all the resources that give women confidence make a huge difference, such as women’s networks (including Women in AI and The Galion Project), venture capitalists investing in female founders (including SISTA, which has dedicated $100 million to women), and podcasts featuring bold women (such as Legend Ladies). - Delphine Groll, NABLA
2. How I Built This
I believe in the power of storytelling, and my best ideas come from hearing examples of what has worked for others. The How I Built This podcast provides authentic human stories that I pull from when faced with obstacles to growth in my own company. I especially appreciate the large number of female leaders who have been featured, giving me inspiring and relatable role models to reference. - Kate Eberle Walker, Presence
3. Authority Magazine
For me, the single most valuable resource truly has been listening to other women who are in a similar position or have been on my journey as a female founder and CEO. I very much hope I am able to do the same now for the women CEOs coming through. Listening to other women CEOs has been very insightful. For example, Authority Magazine has been running a “Top 5” series featuring women founders. - Maria Scott, TAINA Technology
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/11/07/15-industry-leaders-share-helpful-supportive-resources-for-female-tech-professionals/?sh=6bea755f5dd9

Women enter technology-related fields from different angles. Many look for positions where they can contribute to and grow with an existing company, and some, like me, jump head first into the startup fray. Whichever road a woman in tech chooses, the data points to the inevitability that she is going to encounter some type of gender bias.
UNDERSTANDING THE OBSTACLES
Half of women in STEM jobs report experiencing discrimination at work. That climbs to 74% if narrowed to just women who work in computer jobs. Much of this can be attributed to a lack of representation, especially in male-dominated computer science disciplines.
Females entering computer science make up just 25% of professionals in the field, with women computer programmers earning, on average, 96 cents for every dollar a male programmer makes. Half of women who enter a tech field leave it by the age of 35, with two-thirds reporting the lack of a clear path for advancement.  
Women who go the startup route can also expect to encounter pushback, particularly from VC funders who may see women-owned companies through a lens of higher risk and lower return. That’s probably at least one of the reasons behind the dismal fact that in 2021,female founders secured only 2% of venture capital in the U.S., the smallest share since 2016. Women who paired with a man did somewhat better, capturing 15.6% of the VC money doled out last year.
Something has to give if women pursuing tech have any chance of beating these odds.
Continue reading: https://www.fastcompany.com/90802904/women-in-tech-gender-bias-and-tips-to-beat-the-odds

CIOs seeking big wins in high business-impacting areas where there’s significant room to improve performance should review their data science, machine learning (ML), and AI projects.
A recent IDC report on AI projects in India[1] reported that 30-49% of AI projects failed for about one-third of organizations, and another study from Deloitte casts 50% of respondents’ organizational performance in AI as starters or underachievers.
That same study found 94% of respondents say AI is critical to success over the next five years. Executives see the AI opportunity for competitive differentiation and are looking for leaders to deliver successful outcomes.
ML and AI are still relatively new practice areas, and leaders should expect ongoing learning and an improving maturity curve. But CIOs, CDOs, and chief scientists can take an active role in improving how many AI projects go from pilot to production.
Are data science teams set up for success?
A developing playbook of best practices for data science teams covers the development process and technologies for building and testing machine learning models. Developing models isn’t trivial, and data scientists certainly have challenges cleansing and tagging data, selecting algorithms, configuring models, setting up infrastructure, and validating results.
Leaders who want to improve AI delivery performance should address this first question: are data scientists set up for success? Are they working on problems that can yield meaningful business outcomes? Do they have the machine learning platforms (such as NVIDIA AI Enterprise),infrastructure access, and ongoing training time to improve their data science practices?
Continue reading: https://www.cio.com/article/411198/how-to-launch-your-ai-projects-from-pilot-to-production-and-ensure-success.html

Machine learning has been inducted into various domains for automation and insights. It has helped businesses grow by aiding decision-making based on data. Organizations create and deploy machine learning applications as Software-as-a-Service or use them for streamlining internal processes such as data entry operations, sales and marketing. This article will discuss how machine learning has evolved the marketing industry and how companies leverage it for profits and growth.
What Is Machine Learning?
Machine learning is a branch of artificial intelligence that deals with predictive modeling and analysis based on historical data. In simple terms, it uses complex mathematical algorithms to extract useful, encoded information from structured data to make predictions regarding trends and behaviors.
Machine Learning Applications In Marketing
Market leaders have been using data and machine learning to improve their sales for years. This is done by understanding the customer base and making data-driven decisions. Machine learning has several uses in marketing—let’s discuss some of them below.
• Customer Segmentation: Create divisions among customers based on their usage patterns, purchase histories, demographics or all of these. These divisions can be used to create personalized marketing campaigns for increased customer satisfaction and marketing success rate.
• Recommendation Systems: Machine learning-based recommendation systems are designed to keep your customers hooked on new products. These systems use models that contain information about the purchase history of each customer and know what would appeal to them. Such systems help boost sales and increase customer interaction.
Continue reading: https://www.forbes.com/sites/theyec/2022/11/08/introduction-to-machine-learning-for-marketing/?sh=36bbc3a917b0

In part, because hybrid and remote workplaces are the new normal for most companies, the sophistication of cyberattacks and the risks they pose have grown rapidly over the last few years. In fact, these new work styles have opened up a whole new set of phishing methods for threat actors.
According to Cybersecurity Ventures, global cybercrime is expected to grow by 15% per year over the next five years, costing about $10.5 billion by 2025.
Cyberspace is massive. Even though hundreds of IT experts analyze threats daily, it is a daunting task. The need for new, faster and more efficient technology arises since the human capacity to respond to emerging threats is limited. One potential solution lies in the world of artificial intelligence (AI). In this article, I’ll review a few common attack methods and how AI solutions can work against cyberattacks.
Lookalike Detection
Cybercriminals register thousands of lookalike domain names, disguising themselves as reputable brands or trusted personnel and tricking victims into submitting sensitive credentials or performing financial transactions. In this instance, cyber actors register a domain similar to that of the targeted company. They alter the URL name and create fake websites and email addresses by adding characters or replacing a single letter. (For instance, “1” for “l” and “0” for “o.”) They may also use a series of letters like “vv” for “w” and “rn” for “m.”
Typosquatting is another common tactic designed to trick the eye. Think of it as if someone registered “gooogle.com” instead of “google.com” or “yahooo.com” instead of “yahoo.com.”
Defending your organization from lookalike domain attacks can be difficult. Automation, machine learning and AI, brand protection solutions have evolved to offer:
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/11/07/how-ai-solutions-can-defend-against-cyberattacks/?sh=2d9c3d3d6693

Cybersecurity risks are steadily growing in number and complexity. We expect that effective attacks on industrial control systems and critical infrastructure will accelerate sharply in 2023. For business leaders, few things are more urgent than the need to hire enough qualified cybersecurity professionals to manage technology portfolios and protect operations.
Recent surveys (registration required) have shown that hiring and retention rank as the biggest problems facing cybersecurity managers. Candidates whose talents are rooted in the IT world often lack the specialized knowledge needed to deal with industrial operations and the Internet of Things (IoT). At the same time, cyber professionals report increasing levels of burnout. Teams are swamped with cybersecurity data from a myriad of tools and sources but lack accurate risk assessment to guide their actions. They also struggle to seamlessly manage events across the six theaters of cyber (IT, OT, IoT, hyperscale/cloud, “work from home” and supply chains). What explains the disconnect?
A major factor is the recent explosion of new cybersecurity solutions. The market has been flooded with new products to assist CISOs, who are desperate to stay ahead of the bad guys in a rapidly growing and changing cyber landscape.
But these new options rarely incorporate significant advances in technology. Each requires expert personnel—and a lot of them—to properly implement and manage. Worst of all, these solutions tend to produce a massive amount of raw information, which must be constantly analyzed by (even more) trained experts.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/11/07/how-artificial-intelligence-allows-businesses-to-focus-on-critical-cyber-risks/?sh=1c8b4b4225f9

The blockchain is an important innovation in the world of cryptocurrency. It provides a secure, transparent, and tamper-proof way of recording transactions.
Today, we'll cover the basics of blockchain technology, what blockchain investing is, how to determine if a blockchain project is a good investment, and whether investing in blockchain projects is worth your time.
How Blockchain Technology Works
Blockchain technology is a decentralized database managed by computers connected to its network. These computers, called nodes, validate and timestamp transactions by solving complex mathematical problems, then add them to the ever-growing chain in chronological order.
This makes it virtually impossible to tamper with transaction data or records because doing so would require changing not just one record but every subsequent record in the chain—an incredibly intensive undertaking.
Additionally, each node in the network possesses its own copy of the blockchain that gets updated automatically whenever a new block is added, so the network doesn't rely on a central server that could be compromised or taken offline.
However, despite its advantages, blockchain technology also has some drawbacks. That's why it's important to know its pros and cons before you consider investing in it.
What Is Blockchain Investing?
Blockchain investing is an investment strategy involving investing in companies developing or using blockchain technology. Since blockchain is a distributed database that allows for secure, transparent, and tamper-proof transactions, it's an attractive technology for various industries, such as finance, healthcare, and supply chain management.
Continue reading: https://www.makeuseof.com/what-is-blockchain-investing/

1. What is Humanode?
Humanode is the first human-powered crypto-biometric network, where 1 human = 1 node = 1 vote.
Humanode is a new-age decentralized crypto-biometric network that integrates pioneering cryptography with private biometrics and blockchain technology. The project aims to create a strong and sustainable decentralized system that is grounded on the existence of unique human beings.
The Humanode project was conceived by the co-founders of Paradigm research institute in 2017. They were one of the many who were optimistic about the Web 3 potential but, at the same time, were stumped by the fact that mining cartels and validator oligopolies seemed to dominate the crypto market. By using human biometrics as the stake, the founders of Humanode saw the possibility of creating a truly decentralized network of equals.
Humanode enables a range of new use cases while solving problems with existing ones. 
With Humanode enabling the pseudonymous biometric DIDs tied to various online services, many spheres stand to benefit from such as insurance, financial services that involve credit score, trading, marketplaces, yield farming and many others including airdrops, healthcare, metaverse authentication and nonfungible token (NFT) ownership.
2. What problems does Humanode solve?
Humanode brings decentralization, Sybil resistance and innovative governance models to the blockchain industry using biometric technology.
In its very foundations, the Humanode project aims to bring accessibility, inclusivity and innovation in the tech and crypto spaces and economics as a whole. The project is an alternative to the majority of blockchain networks that are based on consensus algorithms such as proof-of-work (PoW) and proof-of-stake (PoS) that currently dominate the field. 
It is known that PoW and PoS are decentralized technologically but not power-wise, granting voting rights and rewards in proportion to users’ economic investments in an activity or resource, stake or computational power, leading to capital-based oligopolies and mining pools. 
In contrast to PoW and PoS, Humanode utilizes facial recognition biometrics with the combination of proof-of-uniqueness and proof-of-existence — efficient tools capable of creating a decentralized protocol to counter malicious attacks on online platforms. The most spread attacks on peer-to-peer networks are Sybil attacks with the utilization of multiple fake virtual identities or, in the case of cryptocurrencies, nodes. 
The Humanode system is designed to check and ensure that every person in the network is unique and has a singular identity. Human nodes are created through crypto-biometric authentication which is a combination of cryptographically secure matching and liveness detection mechanisms verifying the uniqueness and existence of real human beings.
Bringing equality and Sybil resistance to the system, Humanode design guarantees every individual the same amount of voting power and rewards, creating a democratic and fair peer-to-peer structure.
Continue reading: https://cointelegraph.com/explained/what-is-humanode-human-powered-blockchain