In 2009, Satoshi Nakamoto released Bitcoin unto the world, and with it, a technology with the potential to define the next century: blockchain.
As a default, blockchains secure transactions with a level of privacy exceeding that which is achievable through centralized payment networks. Consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS) provide methods for decentralized consensus, allowing cryptocurrency networks to settle transactions without a centralized authority.
However, experts amongst the cryptocurrency community are expressing concern over whether this level of privacy is enough given developments in modern anti-privacy technologies.
Blockchain: Private or Not?
Banks and centralized payment networks like Visa have no choice but to record personal transaction data – sender and receiver names, amounts, times, locations, and often the types of goods or services purchased – in order to facilitate the movement of money and protect users from fraud.
While blockchains are advantaged in this regard, the privacy they provide is not perfect. Sender and receiver wallet addresses, as well as transaction amounts, are stored permanently on blockchains for all to see. Bitcoin.org describes how this applies to the Bitcoin network:
“All Bitcoin transactions are public, traceable, and permanently stored in the Bitcoin network. Bitcoin addresses are the only information used to define where bitcoins are allocated and where they are sent. These addresses are created privately by each user’s wallets. However, once addresses are used, they become tainted by the history of all transactions they are involved with. Anyone can see the balance and all transactions of any address.”
Continue reading: https://www.newsbtc.com/news/company/the-blockchain-that-brings-privacy-to-the-masses/

For some time now, artificial intelligence (AI) has been a hot topic in the world of technology. Depending on who you ask, it can do everything from achieving omnipotence to predicting the future with laser-like accuracy. So how much is reality and how much is hype? As you’ve probably surmised, the truth lies somewhere in the middle.
While many companies have invested in AI, to-date most have not yet put it to work. This means there’s an enormous advantage for those who do so sooner rather than later, particularly when it comes to business continuity. Why? It delivers actionable intelligence based on analytical and predictive capabilities that significantly outpace human-only intelligence gathering.
Almost half of businesses report requiring hours or even days to analyze, understand and act on critical event data. Sixty-one percent of large enterprises have experienced an incident where they didn’t receive critical information until it was too late to respond. And 24 percent of businesses report feeling challenged by a limited ability to respond quickly.
Continue reading: https://www.securitymagazine.com/articles/96753-why-the-hype-around-ai-its-actionable-intelligence

How machine intelligence complements humans in the workplace.
Since the dawn of the Industrial Revolution, the relationship between humans and machines has been, well, complicated. 
Right around the time John Henry was losing his fictional battle with a steam-powered rock-drilling machine, a British author named Samuel Butler penned an article for a New Zealand newspaper entitled Darwin Among the Machines. In the article, Butler speculates that machines might also undergo evolution—eventually knocking humans off our dominant perch.
Happily, these tales of human demise at the hands of robots have been greatly exaggerated. In fact, the more we embrace artificial intelligence, the more obvious it becomes that people are a critical part of the equation. 
AI today—and tomorrow
Enterprise AI has come a long way since it first made the scene back in 1974, when an expert system called Mycin used a series of if/then rules to diagnose blood infections more accurately than human medical students.
In a recent IEEE global study of 350 global CIOs, CTOs and technology leaders, more than one in five respondents (21%)  predicted that AI/machine learning and cloud computing will be among the most important technologies of 2022. And 95% agreed that AI will drive the majority of innovation across nearly every industry sector in the next one to five years.
Continue reading: https://www.forbes.com/sites/servicenow/2021/12/17/are-you-in-the-ai-loop/?sh=6001c3322773

Artificial intelligence (AI) has revolutionized many industries, and marketing is one of the most compelling examples. AI has breathed new life into marketing by providing deeper insights into customer behavior, allowing marketers to build loyalty through improved user experience and tailored communications. 
Better Results, Less Time
Data drives marketing. But the typical marketing technology stack makes it challenging for brands to leverage data properly. Years of add-on technology investments have left customer data in silos, scattered across the organization. Marketers spend hours sifting through data from various sources and then figuring out how to act on it quickly.
AI breaks down data silos, creating a more holistic view of the target customer. As a result, it can increase campaign results significantly. AI can analyze factors like peak engagement times, customer channel preferences and past behaviors. Once marketers launch a personalized campaign, real-time A/B or multivariate testing powered by AI can pinpoint the top-performing content and update it automatically to boost engagement instantly.
It sounds too good to be true, but it’s already happening today. In addition to better campaign performance and increased sales, AI saves the marketing team countless hours of analysis, testing, reporting and implementation. Many people begin careers in marketing hoping to exercise their creativity and develop exciting, successful campaigns for clients. Yet a recent study by media and marketing company PHD found that 88% of marketers spend most of their time on reporting tasks and just 18% of their time thinking creatively. With AI, we ask, what if the opposite were true? What could you achieve then?
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2021/12/17/five-ways-ai-improves-brand-marketing-roi/?sh=6a6196794132

While we’re still debating whether and how long it will take to reach singularity and superintelligence, artificial intelligence is playing an increasingly important role in our everyday lives. Artificial intelligence – most commonly machine learning (ML) – is the process of training algorithms using data, instead of explicitly programming them. Such algorithms are already being used in applications ranging from HR to finance and transport to medicine, and in use cases almost too numerous to mention.
The benefits of machine learning are obvious: they enable faster analysis of vastly more data than any human or even groups of humans are capable of. Many ML applications that can surpass human capabilities already exist, such as those designed to play Go and Chess, or detect fraudulent insurance claims. Unlike past AI boom-and-bust cycles, we’re unlikely to see the return of an AI winter. Current ML algorithms are generating enough value to justify continued research and funding. AI is here to stay – and set to be more pervasive in both industry and our personal lives.
However, one hurdle still exists on the path to true AI success – trust. How can we trust AI when we’ve seen it make so many poor decisions?
Obstacles to reaching AI’s full potential
At the risk of oversimplifying the situation, I believe that there are just two fundamental aspects that must be addressed before AI can reach its full potential. Those are a proper understanding of what AI is capable of and how it should be used, and improvements to the security of AI.
Continue reading: https://www.helpnetsecurity.com/2021/12/20/secure-ai/

What is artificial intelligence (AI)?
Artificial intelligence is a rising technology in today's world and is already being used in many ways. From self-driving cars to language translation software, AI has proven to be so much more than we thought it was in the past.
AI is an idea that is often made before it is understood
When people think of AI, they often think of some distant future where humans are no longer needed. The truth of the matter is that AI is already here — it's even on your phone. The difference between old AI and new AI is that old AI was applied to a very narrow field, while new AI is based on deep learning and neural networks. The future of AI will depend heavily on the ability of AI to understand and complete tasks as well as to have a good understanding of the world.
What is an AI writer assistant?
An AI writer assistant is software that can be programmed to generate content for a specific topic or niche. The idea behind an AI writer assistant is to get rid of writer’s block and generate content ideas at scale.
Continue reading: https://www.mysanantonio.com/business/article/How-to-Leverage-AI-for-Maximum-Benefits-for-Your-16712793.php

The retail industry looks set to end this year, having poured more investment into Artificial Intelligence than the previous top AI-spending sector, banking, according to a recent report from International Data Corp.
Retail giants including Wayfair, Ikea, Walmart and Ocado are turning to the technology for a wider range of operations, from inventory management to delivery and more personalized online search and shopping.
Meanwhile, PwC forecasts that AI has the potential to add a 10% boost to the UK economy of £232bn before the end of the decade.
Serious investment in AI has moved it rapidly from proof of concepts with lots of potential to a major business focus, helped in part by the acceleration of e-commerce during the pandemic.
Retail will now be a major beneficiary of 10 years of technology innovation, which took place over the course of just 90 days in 2020 and AI will play a leading role.  
But from a marketing perspective, how can AI’s rapid evolution help to capture consumer attention near the top of the purchasing funnel?
Continue reading: https://mediatel.co.uk/news/2021/12/20/where-ai-is-heading-and-how-it-can-help-retail-media-plans/

The United States has added drone maker DJI and seven other Chinese companies to an investment blacklist, raising even more pressure on businesses in the world's second largest economy.
The US Treasury Department announced Thursday that it has placed investment restrictions on the firms due to their roles in facilitating human rights abuses against China's Uyghur Muslims in Xinjiang and other ethnic and religious minorities.
As a result, American investors will be barred from buying or selling shares of the companies.
"Today's action highlights how private firms in China's defense and surveillance technology sectors are actively cooperating with the government's efforts to repress members of ethnic and religious minority groups," said Brian Nelson, undersecretary for terrorism and financial intelligence. "Treasury remains committed to ensuring that the U.S. financial system and American investors are not supporting these activities."
The news was widely expected after being first reported by the Financial Times earlier this week.
DJI and the seven other companies are already on the US entity list, which means they are barred from buying US products or importing American technology without a special license.
Continue reading: https://www.cnn.com/2021/12/16/tech/dji-us-investment-blacklist-intl-hnk/index.html

The world is being transformed by the Internet of Things (the IoT) as ever more devices and activities are linked through the internet and endowed with computing power. This transformation brings an exponential rise in the security challenges inherent in digital connections, especially connections with the networks with politically untrusted countries. Yet, even as Australia’s political relations with China worsen, we see neighbors around East and Southeast Asia continuing to build denser economic links with China through the IoT’s international ecosystems and underlying supply chains.
The complexity and transnational nature of these supply chains and markets are frustrating attempts to shift them away from China, even as distrust of the Chinese state and its digital technology champions grows in the Western world. US efforts to promote technological “decoupling” from China are now well known. But the measures being advanced are simply not on the scale needed to untangle the global Gordian knot of economic interdependence with China.
Southeast Asia’s digital economy is projected to be worth US$1 trillion by 2030.
This knot might be cut through coercive measures, such as the export controls that led non-US firms to break ties with Chinese technology giant Huawei. But the Biden administration has proved reluctant to take this path, even as it follows its predecessor in encouraging a global divorce from China in digital technologies. Meanwhile, the US private sector continues to pour money into China’s digital technology industries. Absent a clear priority for closer economic integration with East and Southeast Asia, the United States is unlikely to turn the regional tide towards closer integration with China.
Continue reading: https://www.lowyinstitute.org/the-interpreter/china-australia-and-internet-things

Internet of Things devices developed over time with unique and sometimes proprietary implementations. This causes difficulties when trying to network different devices. It also can lead to vendor lock-in, where users are tied to a certain company’s products due to incompatibility with other products on the market. The Web of Things was proposed to address the standardization of the Internet of Things and resolve some of these issues.
What is the Web of Things?
The concept of the Web of Things was first introduced by researchers around 2007. It has since been adopted and promoted by organizations like Mozilla, Siemens, and the World Wide Web Consortium (W3C). These organizations have established interest groups to define the standards that should govern the Web of Things. This includes the Web Thing Model, which represents a standardized way to provide information on a virtual or physical device, known as a Thing.
Along with the Web Thing Model, the groups involved in developing the Web of Things have also introduced several other standards. These include the WoT Architecture, WoT Thing Description, WoT Scripting API, and WoT Binding Templates. Each of these makes up the core components of the Web of Things design.
Continue reading: https://www.iotforall.com/introduction-to-the-web-of-things

Six of the 10 best companies for women to work at in the U.S. right now are in the technology sector, a new survey shows.
IBM Corp. was listed as the top large company for women to work at this year, according to Comparably, a platform where workers review employers. Comparably compiled its list from ratings made by female users between November 2020 and November 2021. The next highest-ranking tech company was Adobe Inc. in third place; HubSpot, Inc. in fourth; Medallia Inc. in fifth; Microsoft Corp. in ninth; and The Knot Worldwide Inc. in 10th.
RingCentral Inc. topped a separate list by Comparably that ranked companies with diversity in mind. Adobe and IBM rounded out the top three.
Workers of all backgrounds and identities have faced numerous hurdles while working during the pandemic, and a brunt of those complications are falling on women. School closures and difficulty finding child care have contributed to the strain on working mothers, and women of all races and ethnicities have not reentered the workforce at the same rates as other groups.
Continue reading: https://www.bloomberg.com/news/articles/2021-12-16/ibm-adobe-top-list-of-best-companies-for-women-to-work-6-of-10-in-tech

This has been a historic year for Israeli hi-tech, with the sector reaching unprecedented highs in 2021 in terms of funding. While the industry has progressed in one way, however, there may still be work to do incorporating women and granting them equal opportunities in hi-tech.
“We meet hundreds of companies, and I don’t see many female entrepreneurs or executives in the meetings we hold,” said NTT Innovation Laboratory Israel CEO Noa Asher. “The current state of gender equality in the industry isn’t a very positive one. This is really disappointing.”
She explained how she feels that women are perhaps less encouraged to apply to executive roles in hi-tech, and that women are afraid to apply for jobs for which they feel they are not 100% qualified. According to the World Economic Forum’s Global Gender Gap Report, the percentage of female legislators, senior officials, and managers in Israel is a meager 34.6%. While this places it above some of its neighbors (Egypt: 7.4%, Lebanon: 21.2%), there is clearly much room for growth, and a global ranking of 60th means finding a female CEO in the Israeli tech sector is something of a rarity.
Continue reading: https://www.jpost.com/business-and-innovation/tech/women-in-high-tech-challenges-they-face-and-hope-for-the-future-688924

For more than a decade, women have earned more doctoral degrees than men in the United States. Despite that, women still lag behind men in getting tenure, getting published and reaching leadership positions in academia.
Much of the research into why that might be focuses on structural barriers and explicit prejudice. But a new study by a team of researchers at Stanford Graduate School of Education (GSE) finds a widespread implicit bias against academic work that simply seems feminine—even if it's not about women or gender specifically.
Analyzing nearly 1 million doctoral dissertations from U.S. universities over a recent 40-year period, the researchers found that scholars who wrote about topics associated with women, or used methodologies associated with women, were less likely to go on to get senior faculty positions than those who did not.
The issue wasn't so much a prejudice against feminist studies or gender studies, which have expanded considerably since the 1970s. In fact, people who wrote their dissertations explicitly about women had slightly better career prospects than those who wrote explicitly about men.
Continue reading: https://phys.org/news/2021-12-reveals-hidden-obstacle-women-academia.html

Edge computing, the concept of the metaverse and the enterprise usage of non-fungible tokens (NFT) are among the top technology trends unlikely to emerge as fully-fledged booms in the new year, according to at least one tech market advisory firm.
Chief research officer at ABI Research, Stuart Carlaw, reckons these trends are not likely to have a “meaningful impact” within the technology industry during 2022.
The metaverse, which was thrown into the spotlight by Meta CEO Mark Zuckerberg this year with grand claims of it being the future of Facebook, focuses on the concept of a singular virtual universe, but has been chided by the firm as merely being a buzzword at this stage.
“Despite all the headlines and investments, the metaverse will not arrive in 2022 or, for that matter, within the typical five-year forecast window,” ABI Research claimed in its 70 Technology Trends That Will—And Will Not—Shape 2022 report.
“What we have today is a number of tech companies building their version of a 'metaverse', but this multiverse is not fully interconnected, does not yet widely employ open standards and certainly has not fully embraced extended reality (XR) — all tenets of the metaverse vision,” it added.
Likewise, the firm was also critical of the enterprise relevance of NFTs — essentially virtual receipts stored on the blockchain — which has generated both accord and controversy within online entertainment circles, particularly in art.
“The vast sums being exchanged over NFTs have understandably raised hopes for the application, breathing new life into blockchain interest, as NFTs could potentially also be leveraged to serve more enterprise-focused applications in real estate and manufacturing,” ABI Research said.
“The reality, however, is that enterprise blockchain is a slow-burner. The passion that drives individuals (from artists to fans) has driven the success of NFTs in that space; a mirror of the incentives that drive the market for cryptocurrency and altcoins.”
Continue reading: https://www.arnnet.com.au/article/694000/metaverse-edge-computing-miss-boom-status-2022/

There are many reasons to be excited about edge computing, a paradigm that places workloads closer to end users in order to boost performance, reliability and more.
But edge computing also poses some very steep challenges. Among them – and arguably the most difficult – is physical security. In an edge environment, guaranteeing physical device security is not just hard, it’s a nightmare.
Here’s why, and what IT architects and security teams can do to guarantee the physical security of edge infrastructure.
Edge Computing and Physical Security
The reason why physical security is so vexing in the context of edge computing is simple enough: Edge networks typically involve a large number of devices that are distributed across a wide geographic area. Preventing unauthorized physical access to each one of those devices is much harder than it is to secure a conventional server or PC that lives in a data center or an office building.
To contextualize this challenge, imagine a network of edge devices that a brick-and-mortar retailer deploys in each of its stores to process transactions locally. Each of those devices may store and manage sensitive data such as customer information and sales records. As a result, anyone who gains physical access to the devices inside retail stores may be able to access this data.
Likewise, consider an edge infrastructure composed of smart home devices that consumers use to do things like control their homes’ temperature or lock and unlock doors. If those devices are linked together by an edge network that connects them to a vendor’s data center, an attacker who gains access to one of those devices could potentially use that access as a beachhead to compromise other devices – including those owned by consumers other than the one whose device was first compromised.
These are physical security risks that don’t exist in the context of conventional computing (or, for that matter, cloud computing). But they’re risks that must be solved if edge computing is truly going to go mainstream.
Securing Edge Devices: What Works and Doesn’t Work
What’s the best way to secure edge devices against physical security threats?
The obvious answer may seem to be to prevent unauthorized physical access by locking edge devices behind closed doors. That’s the strategy that businesses typically use to enforce physical security for conventional IT infrastructure.
The problem with using this approach for edge computing, however, is that it’s just not practical or highly effective in many cases. You can’t lock smart home devices inside closed boxes without disrupting their usability. You could try to protect edge infrastructure in a retail store by placing it in a secure room, but that only provides so much protection. It’s also expensive to implement if you have hundreds or thousands of stores.
Continue reading: https://www.itprotoday.com/cloud-computing-and-edge-computing/how-prevent-physical-security-nightmares-edge-computing

The cloud’s primary notion of providing a centralized data source that can be accessed from anywhere in the globe appears to be the polar opposite of edge computing’s local data handling concept. In many respects, though, edge computing was created by the cloud. The big data movement would never have grown to such proportions without centralized data storage. Many internet payment providers, for example, would not exist and companies like Microsoft and Amazon would be very different from what they are now. We’ve spent some time attempting to sift out the benefits of edge and cloud computing. Which is the most effective? The solution isn’t as simple as one would believe.
Cloud computing
Cloud computing refers to the storage, processing, computing, and analysis of large amounts of data on remote servers or data centers. It also refers to “the supply of many Internet-based services, such as data storage, servers, databases, networking, and software.” Because data centers are frequently located in faraway locations, there is a time lag between data gathering and processing, which is usually undetectable in most use cases. In time-sensitive programs, however, this time latency, despite being measured in milliseconds, becomes critical. Consider real-time data collecting for a self-driving automobile, when delays might have disastrous implications.
Advantage of cloud computing
Infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service are the three basic categories of cloud computing (SaaS). High infrastructure availability, self-service provisioning, elasticity, mobility, workload resilience, migration flexibility, broad network access, disaster recovery, and pay-per-use are just a few of the advantages of cloud computing in the form of IaaS.
The back-and-forth movement of data from the point where it is created to the central server for processing and subsequently to the end-user requires a lot of bandwidth, which slows down data processing and transfer. Because emerging technologies and IoT devices require sub-second reaction times, the tendency is to locate data processing and analytics as near to the data source as feasible.
Edge computing
Edge computing, as opposed to cloud computing, brings computation, storage, and networking closer to the data source, lowering travel time and latency dramatically. The procedures take place near the device or at the network’s edge, allowing for speedier reaction times. Edge applications limit the amount of data that has to be moved, as well as the traffic generated by those transfers and the distance that data has to travel.
Continue reading: https://www.analyticsinsight.net/cloud-computing-vs-edge-computing-who-wins-the-race/

Much of the federal government’s IT modernization efforts over the last decade have focused on centralizing computing power in the cloud. But as those capabilities increase, agencies must also be thinking about how to improve computing at the edge, on devices people can touch.
For federal agencies, edge computing ranges from lower-powered devices like desktops, laptops and smartphones to high-performance supercomputers like those used at the Energy Department’s national labs and NASA, among others. The U.S. Postal Service is another such example, with its own Edge Computing Infrastructure Program, or ECIP, testing advanced tools at processing facilities.
Continue reading: https://www.nextgov.com/cio-briefing/2021/12/special-report-computing-edge/359872/

Crypto mania is in full swing. Some people just can’t get their heads around it, and others can’t get enough of it. 
Watching the testimony last week of six innovative leaders of crypto-asset firms before the House Financial Services Committee was an educational experience. They explained the crypto phenomena like astrophysicists talking about the dark matter in the universe that we don’t yet understand. But I found myself wondering about the questions that went unasked, particularly what long-term risks crypto assets may pose to national and global economies.
There is already about $3 trillion of cryptocurrency trading throughout the world. Those crypto products are being used and sliced and diced into another $2.7 trillion of derivative crypto-securities traded on traditional markets and crypto exchanges. 
Assuming that some of these financial instruments are purchased on margin or otherwise leveraged, we are talking about a potential crypto global footprint approaching $10 trillion. Except for stablecoins, those are financial instruments supported by little if any intrinsic value beyond the decentralized networks that create and transmit them. 
Continue reading: https://thehill.com/opinion/cybersecurity/585895-crypto-and-the-insecure-internet

Each year, Gartner ranks emerging technologies and places them along a Hype Cycle curve. The curve starts with an innovation trigger, followed by a peak of Inflated Expectations brought about by success and failure stories from early adopters. Naturally, this leads to a steep decline into the Trough of Disillusionment, the make-or-break point for producers of the technology — when iterations either catch on successfully or fail to deliver. Fret not, there is a gradual upswing through the Slope of Enlightenment, where the innovation becomes more understood and accepted in terms of realistic functionality, finally landing at the Plateau of Productivity. This is the sweet spot where paradigm-shifting technologies become socially adopted and broadly recognized.
This year, non-fungible tokens (NFTs) sit proudly at the Peak of Inflated Expectations; we know what’s coming next. But with the resilience of stable coins, the rebranding of Facebook to Meta and regulators finally paying attention to DeFi, we can safely assume that blockchain, in general, is heading up the Slope of Enlightenment.
Blockchain’s most obvious financial applications appear across lending, insurance, money transfers and audits, but there are emerging, powerful and often overlooked applications within the traditional investing space. Below, I outline three areas where blockchain is starting to make quiet waves in noisy capital markets.
Continue reading: https://www.forbes.com/sites/forbesfinancecouncil/2021/12/17/3-ways-blockchain-is-going-to-shake-up-traditional-investing/?sh=6e4835d76dee

Common sense isn’t common, especially when it comes to artificial intelligence. Computers struggle to make fine distinctions that people take for granted. This is why websites require you authenticate your humanity before logging in or making a purchase: Most bots can’t tell the difference between a crosswalk and a zebra.
At the USC AI Futures Symposium on AI with Common Sense earlier this month, more than 20 USC researchers reported on the technical reasons why that’s the case, and different avenues of research to address this. Advances in common sense AI will improve human-facing services, from enhanced social services to better serve society to personal assistants that better predict our context and needs.
“AI systems today can converse with us to order a book, find a song, or vacuum our floors,” said Yannis Yortsos, dean of the USC Viterbi School of Engineering. “But they do not have the common sense to know that we read books for learning and for pleasure, that music relaxes us, and that tidy homes are more enjoyable. Mindsets taking into account human interaction must be applied in tackling the commonsense challenge for AI as we are laying the foundations for AI to be responsible and ethical, and to impact society in meaningful ways.”
Continue reading: https://news.usc.edu/195978/commonsense-artificial-intelligence-ai/

• Artificial Intelligence has the capacity to significantly enhance the power of marketing and marketers across the world are opening up to the possibilities AI presents to them in engaging better with consumers, while also improving customer experience.
• Sarin Menoky, Lead - Thought Leadership Marketing, Infosys BPM writes about the opportunities that AI presents for marketers and what the future looks like.

Marketing is a sector that has among the most to gain from artificial intelligence (AI). At its core, the purpose of marketing is to understand customer requirements, map them to relevant products and services, and persuade people to buy. AI has the capacity to significantly enhance the power of marketing. A 2018 McKinsey study of over 400 use cases involving advanced AI techniques, found that marketing was the function where AI had the most significant potential. And as per a Salesforce report, from 2018 to 2020, adoption of AI by marketers saw a whopping 186% increase.
What can AI do for marketing? AI-driven marketing uses technology to improve customer experience. AI collects large and diverse amounts of data on customer sentiment, transactions, journeys, and everything in between, and uses that to build machine learning and predictive algorithms on customer behavior. The goal is to develop customer acquisition and retention strategies, and to generate personalized content, recommendations, and communications. AI promises accurate, rapid, adaptive, and human-like decisions that will help save costs, increase revenue, and improve customer satisfaction and experience.
Continue reading: https://www.businessinsider.in/advertising/brands/article/triggering-marketing-impact-through-artificial-intelligence/articleshow/88334160.cms

Albert King, the Chief Data Officer of the Scottish Government, discussed the key aspects involved in Scotland's artificial intelligence (AI) strategy in a session of Cognilytica's AI in Government speaker series. The country prioritizes data as a means to improve decision-making and enable national goals.
The Scottish government first committed to the development of an AI adoption strategy in 2019, which led to the ongoing delivery of the technologies starting in 2021. Although the COVID-19 pandemic delayed the process, King notes the positive side of the lockdown, which led to more collaboration across the entire country as Scottish officials worked virtually.
"Our approach enabled us to understand public views as well as those of experts to engage the public in a debate, and to understand, fundamentally and importantly, where leadership is required in order to shape the way we adopt AI and data driven technologies in our society," he says.
Continue reading: https://www.securitymagazine.com/articles/96746-the-4-tenets-of-scottish-ai-adoption

As 2021 draws to a close and the world eagerly awaits the shift to the endemic era, exponential technologies will persevere as vanguards of business transformation. Across sectors, companies will persist with the adoption and advancement of their deployment journey of cloud computing and artificial intelligence (AI). Agility, scalability, time-to-market coupled with security and compliance at the core would remain key primary drivers for cloud adoption.
So, in 2022, here are the top trends and shifts we anticipate in these technology domains.
Hybrid cloud as dominant architecture: An IBM Institute for Business Value (IBV) study revealed that 99 percent respondents in India are leveraging varied combinations of hybrid cloud, indicating hybrid is the dominant architecture for enterprise cloud estates. This is driven by the need for secure open cloud environments to avoid vendor lock-in while giving them the flexibility to test capabilities and benefits offered by different cloud providers. In this multi-cloud environment, consistent monitoring, security posture, regulatory compliance, billing and license management, and workload optimization will become critical, resulting in the explosion of new tools and platforms.
Continue reading: https://www.forbesindia.com/blog/technology/what-can-ai-and-hybrid-cloud-do-for-businesses-in-2022/

2021 was a year marked by the implementation of the rapid digital transformations that first sprouted when the coronavirus pandemic hit the world in 2020. Fintech firms and other businesses around the world invested heavily in transforming to meet the needs of the new normal — remote working, social distancing and a business world changed perhaps forever.
Now, as we move into 2022, it’s clear that those developments are here to stay. Trends are poised to become industry standards and there is a reinvigorated focus on consumer-friendly tech. Naturally, AI (artificial intelligence) and ML (machine learning) are at the heart of this, and it comes as no surprise that the industry is predicted to be worth over $17,440 million with a CAGR of 17.9% by 2027. The only question is, how will companies use these tools to implement digital transformation and more importantly make it count?
As the world moves forward into 2022, let’s take a look at some of the top ways AI and ML are transforming fintech today and in the future.
Data analytics becomes more than just statistics. 
Over the last few years, the value of data has been growing. Armed with the right knowledge, companies can seek to “hack” the market and improve their offerings to suit consumer demand. It is estimated that by 2025, more than 180 zettabytes of data will be in existence. Two years later, by 2027, the data market is set to be valued at over $103 billion. But what does this actually mean for companies? 
Continue reading: https://www.forbes.com/sites/forbesfinancecouncil/2021/12/17/how-ai-and-ml-are-changing-finance-in-2022/?sh=5fa400b862f2

As we look forward to 2022, we are seeking your input to assist us with building content, research, and resources that you are most interested in. Your responses are completely confidential, and data will only be viewed in the aggregate.
Access the survey here: https://surveys.comptia.org/s3/ai-tig-interests