Marketing is one of the many industries that stands to be disrupted by artificial intelligence (AI.) In fact, a McKinsey study found that aside from sales, marketing is, “the single business function where AI will have the most financial impact.”

Marketing departments are already using AI to set and measure KPIs, to draft and edit copy for websites and social media, to generate visuals and more - tasks that were previously human-driven. The uncertainty of how to adjust to the rapid growth of AI is putting the industry on edge, with executives to entry level staff wondering if the future of their careers are at risk. But many are embracing the technology, recognizing its staying power and acknowledging that marketers would do well to adapt or risk becoming irrelevant.

Some predicted the mass adoption of AI technology years ago. “Edelman’s senior leadership was quick to recognize the enormous potential of AI and set-up an AI Centre of Excellence, seven years ago, not seven months ago,” says Justin Westcott, the agency’s global chair of technology.

Westcott says it’s important to have a unified AI strategy that focuses on effectiveness and ethics. “A pivotal part of our initiative was introducing a thorough code of conduct,” he says. “With clients increasingly curious about AI, our approach emphasizes cautious experimentation and continued education. While AI is evolving and these tools still emergent, its presence in the industry is undeniable.”

"Adding AI to our toolkit is a component of the business landscape today,” says Maggie Malek, Crispin Porter + Bogusky’s president of North America.

Continue reading: https://www.forbes.com/sites/amysho...g-leaders-are-approaching-ai/?sh=4deea7a161e4

Before last year, Jana Soldicic’s understanding of artificial intelligence was mostly limited to what she’d read on the pages of science fiction novels. But in the fall, after getting the chance to use the technology in real life as she played around with the generative AI tools ChatGPT and DALL-E, she got more curious.

“I really wanted to know what was behind it. I knew it couldn’t be magic,” Soldicic said.

She searched online and found Elements of AI, a self-paced, online course created by MinnaLearn and The University of Helsinki that provides an introduction to artificial intelligence designed for people without a background in technology, and was surprised by how much she enjoyed the course.

“I got a little bit addicted to it,” she says. “It gave me a basic understanding of what AI is now and what it could be.”

The experience gave her a deeper understanding of how artificial intelligence actually operated—far beyond what she might have learned from messing around with the publicly available programs. Now, she’s bringing that knowledge to her work as an event planner. “I now have more of an understanding what it could do for me, my work, [and] my colleagues, other than just creating texts or pictures.”

Soldicic, who is based in Hamburg, Germany, uses AI text-to-image generators like DALL-E to bring adverts and flyers to life with designs that it might have previously been impossible for her to create on her own. “We wanted little squirrels on a tandem bike for one event [flyer], and you could never find such a picture in real life. I put in ‘two squirrels on the tandem bike’ [on DALL-E] and there were so many different and cool results. I didn't have to find somebody to realize my idea, I could just do it at home.”

Continue reading: https://time.com/6302984/ai-jobs-career/

Blockchain technology has brought about a significant revolution in the way data is stored and transferred. It is considered one of the most groundbreaking innovations of the 21st century. However, due to the seeming complexity of its 5 technology layers, many users remain unaware of its fundamental structure.

At its core, the blockchain is a decentralized and distributed ledger that ensures secure, transparent, and immutable transactions. It functions through a network of computers that verify and record each transaction in a series of encrypted blocks, which are then linked together to form a chain. While cryptocurrencies like Bitcoin and Ethereum have popularized this technology in recent years, its applications extend far beyond digital currencies alone.

To fully comprehend the capabilities and potential of blockchain technology, it is essential to understand the multiple layers that enable its functionality and effectiveness. Businesses and investors who wish to leverage blockchain for their operations or investments must acquire a comprehensive understanding of these underlying components.

The key advantages of blockchain technology include transparency, enhanced security, increased efficiency, reduced operational costs, and the elimination of intermediaries. With the emergence of Web 3.0 and Decentralized Ledger Technology (DLT), understanding the different layers of blockchain becomes crucial. These layers play a vital role in the overall architecture of blockchain systems, enabling the seamless functioning and organization of decentralized networks. In the following sections, we will explore the importance of these layers and how they contribute to the workings of blockchain technology.

Components of blockchain technology​

Node Application: A node application allows any internet-connected computer to participate in the blockchain ecosystem. Examples of node applications include Bitcoin wallets and blockchain platforms. In certain cases, such as a bank chain, participation may be restricted to specific entities like banks.

Distributed/Shared Ledger (Database): The blockchain system employs a distributed ledger that enables participants to access shared databases and content. The ledger contains a set of regulations that must be followed. For instance, in a bitcoin node application, compliance with the program code’s regulations is necessary.

Consensus Algorithm: Consensus algorithms are vital for the functionality and security of a blockchain network. They ensure the integrity and consistency of the blockchain data. The consensus algorithm determines how network nodes agree on which transactions to accept. Additionally, the blockchain’s tamper resistance is achieved by the requirement to regenerate all subsequent blocks if any change is made to a block.

Virtual Machine: A virtual machine is a software representation of a machine, real or hypothetical, that can be controlled through instructions in a specific language. It abstracts physical objects or entities into virtual counterparts on a computer. For example, a graphical application’s button on the screen triggers a change in the program’s state inside the computer.

Peer-to-Peer (P2P) Network: A peer-to-peer network is a decentralized model where multiple peer nodes communicate without relying on a central server. In blockchain networks, each node acts as both a client and a server, collectively providing and managing data. This peer-to-peer architecture enhances data availability and reduces the risk of information loss.

Continue reading: https://www.cryptopolitan.com/blockchain-capabilities-5-technology-layers/

We often overlook the security of Internet of Things devices, but they contain lots of private info. That's why they need to be penetration tested.

Look around you, and you'll likely find Internet of Things (IoT) devices everywhere: from the smartphones in our pockets to wearable technology on our wrists and even household appliances and industrial equipment.

The IoT can be described as any tool featuring a network of interconnected physical devices that communicate and exchange data via the internet. But of course, anything connected to the internet poses a risk, and unfortunately, IoT devices raise security concerns as well. That makes pentesting an important way to keep personal data safe.

How Risky Are IoT Devices?​

The convenience and innovation of IoT devices come with a significant risk: security.

For instance, a report by IoT Security Foundation stated that the vulnerability disclosure practice remains at 27.1 percent, and many consumer IoT companies are still not taking basic steps to maintain their product security. Another eye-opening report conducted by Netgear and Bitdefender revealed that home networks see an average of eight attacks against devices every 24 hours. Most exploited IoT devices are victims of denial-of-service (DoS) attacks.

So how can we balance the benefits of IoT devices with the pressing need for robust security? Here's where IoT pentesting comes in.

What Is IoT Pentesting?​

First of all: what is penetration testing? Imagine your computer system or network as a fortress. Penetration testing, or "pentesting," is like conducting a practice attack on that fortress to find weak spots.

Pentesting is done by pretending to be a cyberattacker; an expert then discovers security holes and flaws. Once they find these weaknesses, they can fix or strengthen them, so real attackers can't take advantage.

Similarly, IoT penetration testing is like the practice attack on the fortress, specifically for smart devices and how they talk to each other and the internet. There are pros and cons to pentesting to consider, of course.

IoT penetration testers use some clever techniques to find flaws, including: reverse-engineering the firmware (i.e. taking apart the device to see how it works and if it can be picked); analyzing network traffic (watching all the traffic going in and out of the network and verifying if there's anything suspicious); and exploiting vulnerabilities in IoT web interfaces, in an attempt to find a weak spot in your IoT device security that might let an attacker sneak in.

Through these techniques, the testers identify security flaws like unencrypted data, unsecure firmware, weak passwords, improper authentication, or access control, and fix them to ensure that your smart devices' private information stays safe.

Continue reading: https://www.makeuseof.com/how-iot-pentesting-protects-private-data/

The Sustainable Development Goals (SDGs) comprise 17 global objectives established by the United Nations in 2015 to achieve a more sustainable future by 2030. Harnessing the power of the Internet of Things (IoT), companies can make significant strides towards these goals by leveraging data to optimize processes, enhance efficiency, and reduce waste. Several statistics highlight how IoT drives sustainable development:

According to the Global e-Sustainability Initiative (GeSI), IoT solutions have the potential to reduce global greenhouse gas emissions by 16.5 percent by 2030. By enabling smart energy management, waste reduction, and resource optimization, IoT plays a crucial role in combating climate change.

Studies by Intel indicate that the adoption of IoT solutions in the energy sector can result in energy consumption reductions of up to 30 percent. Real-time data monitoring and analysis enable companies to identify inefficiencies, optimize energy usage, and drive sustainable practices.

The World Economic Forum (WEF) estimates that IoT implementation in precision agriculture can increase crop yields by up to 70 percent and reduce water consumption by up to 90 percent. By leveraging IoT sensors, farmers can gather critical data on soil moisture, nutrient levels, and weather patterns, allowing for precise irrigation and resource management.

Continue reading: https://www.iotforall.com/iot-is-key-to-meeting-sustainable-development-goals-by-2030

Representation of women in tech jobs and university degrees has improved steadily over the past few decades, but we are far from reaching equality, particularly when it comes to technology. Women account for 21% of the degrees earned in Computer Science, and in the Big 5 tech companies, only 31% of the employees are women. These statistics worsen as we scrutinize more senior level positions with representation sharply falling off in C-suites and boardrooms.

To their credit, banks have done a better job than tech giants when it comes to gender diversity. But while company-wide representation may have increased, women are still underrepresented in tech-related jobs in the financial industry. The problem of underrepresentation in the tech field is a three-headed hydra and counteracting any one particular aspect without the others leads to less-than-perfect results.

Tech is from Mars: Rene Descartes' philosophy of the “mind-body divide” asserts that the mind deals with logic while the body deals with our baser (animalistic) instincts. The belief that men are rational while women are emotional is tied to this characterization of the mind and body. Since women are considered “emotional”, they are thought to be less-equipped to deal with hard sciences like engineering and computer science. This deeply misogynistic belief hinders women from pursuing careers in STEM. This results in classrooms that don’t have equal representation and cause women to feel like outsiders or imposters.

Lack of mentors: When fewer women pursue science, there are fewer women who can be role models, whether that is in the role of teachers or mentors. Since there are a limited number of senior role models who are women, young girls don't get access to mentors that can provide insights into the real world and act as affirmation of their goals.

A path to success: What use are technical skills if you can’t put them to use? Young girls need access to roadmaps and career guidance that can help them forge their own paths in tech.

Bottom line: When girls feel uncomfortable and foreign in tech classrooms, we get tech departments that are unrepresentative.

Perhaps we have to change the narrative around tech. If we don't have enough women data science students, how will we have enough women chief data science execs?

“You start to realize the problem permeates all the way into early education, and you can't show up in college and try to help someone -- you have to start early,” said Hari Gopalkrishnan, Head of Consumer, Business & Wealth Management Technology at Bank of America.

Continue reading: https://tearsheet.co/banking/women-...n-a-bank-of-america-and-girls-who-code-story/

While companies of all sizes across various industries adapt their processes to make room for innovative artificial intelligence (AI), the financial and investment industry is catching up and leveraging AI tools to enhance their operations and improve their performance. I'm seeing that the financial industry and investment firms can and are implementing various AI tools to help boost their productivity, error margins and overall efficiency.

Being the managing general partner of a global equity investment firm focused on life science companies, I have always been interested in the application of AI in the life science industry. I believe there is a significant opportunity to streamline and optimize drug discovery, development, data analysis, product launch, post-market analysis and patient experience. There are significant additional areas that AI and machine learning could be applied to as well, such as electronic patient records, intellectual property strategies and searches and more.

This is an industry that is data-rich, and as an investor with significant insights into science and operations, I can see value in using AI tools to streamline aspects of the research done at an investment firm. It could help with tracking news; researching the competition; comparing clinical trial results; and supporting predictive models to identify the probability of success for a specific catalyst, development milestone or product performance. AI can also help support portfolio construction, performance and real-time decision-making and adjustment, thus enabling portfolio managers to react quickly to internal and external information.

Use Cases For AI In The Investment Industry​

1. Elevating investment searches: Each investment brings a potential risk that must be vetted thoroughly. Investors might use AI to assist in the vetting process by providing background information. Access to the background of the business and its competitors in an efficient way can enable informed decisions with a faster turnaround period. AI tools can help streamline the analysis of a potential investment’s returns, sales and profitability as well.

2. Industry analysis and trend forecasting: Investors closely monitor trends across various industries, as macro and micro changes can impact the different companies in their portfolios. Traditionally, this means that teams or individuals must manually keep their proverbial “eye on the pulse” across many industries, a nearly impossible task in arenas that experience frequent change and innovation. Using AI to gather relevant data points, highlight new studies and analyze trends across various industries can provide a unique advantage to an investment firm.

Continue reading: https://www.forbes.com/sites/forbes...sing-ai-tools-as-an-investor/?sh=434b46f38ec2

Artificial intelligence has been used by big businesses for years, but the buzz over generative tools like ChatGPT that are available to everyone has drawn the attention of small businesses. And nearly all those utilizing the technology are seeing a boost, according to fresh data.

Survey results released Wednesday by Constant Contact found 91% of small business owners using AI say it has made their companies more successful, and more than a quarter (28%) of those respondents said they expect it to save them at least $5,000 over the next year.

Small business leaders using AI overwhelmingly agreed automating tasks using the tools has helped them cut costs and improve efficiency, Constant Contact reported. Sixty percent of small businesses that use AI say it has saved them time, with more than a third estimating it has saved them more than 40 minutes per week.

Constant Contact CEO Frank Vella told FOX Business the findings show small businesses "are focused on achieving their intended outcomes with tools that make it easy and intuitive for them to achieve their goals."

WHAT IS ARTIFICIAL INTELLIGENCE (AI)?

"We discovered that their level of excitement is growing, and those who are already leveraging these technologies are seeing impactful results at a business level," he said.

Twenty-six percent of small businesses surveyed said they are using AI. Another 44% said they were not using the tools for business but would like to start, and 16% were unsure. Only 14% of those not using the tools said they had no interest in giving them a try.

Of those not using the technology, 74% of decision-makers surveyed said they were interested in using AI or automation in their businesses, and 55% reported their interest grew in the last six months.

"Small businesses and nonprofit organizations are using tools that leverage AI for better outcomes — to enhance their creativity, get closer to their target audiences and drive more sales volume," Vella said. "As their marketing sophistication grows, we also see them look to incorporate AI and automations into more areas of their marketing."

Continue reading: https://www.foxbusiness.com/technology/small-businesses-using-ai-loving-it

SMS marketing has been a potent tool for marketers for many years. However, the introduction of generative AI has transformed SMS marketing, making it more personalized and conversational. Lubomir Kozak, CEO of BulkGate, shares tips with marketers on leveraging AI to boost their SMS marketing campaign.

In the fast-paced world of digital marketing, businesses are always looking for inventive methods to engage with their customers. SMS marketing has proven to be an effective channel for driving engagement and conversions, with impressive statistics such as a 98% open rate and a 45% click-through rateOpens a new window .

As we transition into a future dominated by AI, marketers must stay at the forefront of innovation and explore the potential advantages of incorporating AI into their SMS marketing initiatives. AI-driven SMS marketing leverages artificial intelligence to analyze customer data, optimize message timing, and create more personalized, engaging content, ultimately enhancing customer experiences and driving higher conversion rates.

1.Personalization Through Machine Learning​

Personalization is key to successful SMS marketing campaigns. According to a McKinsey studyOpens a new window , personalization in marketing can deliver five to eight times the ROI on marketing spend and can lift sales by 10% or more.

AI-driven platforms can analyze customer data to create highly targeted and personalized messages that resonate with individual recipients. Using machine learning algorithms, these platforms can continuously improve their targeting and personalization capabilities.

For example, an AI-driven SMS marketing campaign might analyze customers’ purchasing histories and tailor promotional messages to offer relevant products, discounts, or upsell opportunities. This could involve sending personalized discount codes for a customer’s favorite product category or offering complementary products based on previous purchases.

Continue reading: https://www.spiceworks.com/marketing/ai-in-marketing/guest-article/ai-revolutionizing-sms-marketing/

Marketing experts Ming-Hui Huang and Roland Rust wrote an influential article titled “Artificial Intelligence in Service” in which they theorized that there are four types of intelligences needed to perform service tasks: mechanical, analytical, intuitive, and empathetic. A key point made associated with the theory was that to perform some more advanced service tasks, artificial intelligence applications need to be able to move beyond just being mechanical and analytical to develop capacities that require intuition and empathy—and that type of intelligence needed should play a role in allocating tasks between machines/AI technology and human labor. As most of us who have dealt with chatbots for a customer service issue know, human intuition and empathy are more difficult to emulate via AI, leading this theory to make a great deal of sense.

It can be argued that Huang and Rust’s theory applies to marketing tasks beyond customer service. For example, in advertising, Amazon and Google have been masters of good targeting via effective mechanical and analytical intelligence, and AI has helped social media ad targeting immensely. Yet, applications that are more intuitive and empathetic can lead to new territory that may result in better customer response to ads by responding to emotions they are experiencing or intuitive patterns related to purchase behavior appear hold potential.

While time will tell the degree of AI advancement in the “feeling” realm and related functions, there is little question that more AI applications ere being effectively employed by many businesses, including small businesses. According to the U.S. Chamber of Commerce, the 33.5 million small businesses in the U.S., defined as those having 500 or less employees, represent 99.9% of all businesses and account for 4 % of employment and 43.5% of GDP. Thus, it is important to examine whether small businesses are making effective use of AI.

A survey of uses of AI by small business conducted by Constant Contact, a small business-focused digital marketing and automation firm, in conjunction with market research firm Ascend2, clearly documents that AI is not just for large businesses anymore. Results, reported in the company’s Small Business Now report show that 91% of small businesses who are using AI indicate that it has made their business more successful. Moreover, the study finds a strong correlation between a small company using AI and its overall success.

Continue reading: https://www.forbes.com/sites/charle...ping-todays-small-businesses/?sh=21922e676789

IT leaders must bring a pragmatic technology lens to gen AI’s potential — and its pitfalls — by optimizing their strategies for use cases first.

Hardly a day goes by without some new business-busting development on generative AI surfacing in the media. And, in fact, McKinsey research argues the future could indeed be dazzling, with gen AI improving productivity in customer support by up to 40%, in software engineering by 20% to 30%, and in marketing by 10%.

Still, it’s worth remembering that we’ve seen this movie before, with companies piling into exciting new technologies with a melee of premature experiments and pilots. CIOs and CTOs have a crucial role in avoiding those pitfalls when it comes to gen AI. They can bring a pragmatic technology lens to determine when and where gen AI can generate the greatest value — and where it is not the best option.

Doing so requires developing use cases based on a deep understanding of the unit economics of gen AI, the resources needed to capture those benefits, and the feasibility of executing the work given existing capabilities. With AI increasingly viewed as a business accelerator and disruptor, this complex equation is a challenge CIOs must get right.

Gen AI archetypes: Takers, shapers, and makers​

One key question CIOs face in determining the best strategic fit for gen AI in their enterprise is whether to rent, buy, or build gen AI capabilities for their various use cases. The basic rule is to invest in creating a unique gen AI capability only when there is a proprietary advantage. We’ve found it helpful to think in terms of three archetypes:

Takers use a chat interface or an API to quickly access a commodity service via a publicly available model. Examples include GitHub Copilot, an off-the-shelf solution to generate code, or Adobe Firefly, which assists designers with image generation and editing. This archetype is the simplest, both in terms of engineering and infrastructure needs, and is generally the fastest to get up and running. It does not allow for integration of proprietary data and offers the fewest privacy and IP protections. While the changes to the tech stack are minimal when simply accessing gen AI services, CIOs will need to be ready to manage substantial adjustments to the tech architecture and to upgrade data architecture.

Continue reading: https://www.cio.com/article/648648/generative-ai-is-a-make-or-break-moment-for-cios.html

Artificial intelligence is transforming cloud computing as we know it, as evidenced by Forbes’ latest Cloud 100 list of the sector’s best privately-held companies. This year, AI is everywhere: New No. 1 OpenAI and No. 2 Databricks are supplying tools to help companies build AI features. No. 3 Stripe, a fintech company, adopted the tech to combat fraud; No. 4 Canva embedded AI features into its design software; No. 7 Grammarly launched a writing assistant that uses AI to spit out paragraphs of text almost instantaneously.

“The feeling I get talking to customers is everyone feels like this is a technology of transformation targeted specifically at their industry,” Dario Amodei, CEO of list newcomer No. 73 Anthropic, told Forbes. “Except, it’s targeted specifically at every industry.”

San Francisco-based Anthropic, which makes a ChatGPT rival called Claude, is one of seven list newcomers growing rapidly thanks to the AI boom. Infrastructure providers like Databricks and No. 44 Dataiku are also benefiting. “AI is a bright spot” in the otherwise “subdued” tech sector, said Mary D’Onofrio, a partner at Bessemer Venture Partners, which works with Forbes to create the list (see here for a full breakdown of methodology).

Anthropic, which Amodei and six cofounders defected from OpenAI to start just two years ago, only began selling to business customers in February 2023. But the company told Forbes it already has “many hundreds of paying customers” on Claude for use cases spanning from legal document analysis to speech-based language translation. In May, the company said it had raised $450 million in funding led by venture capital firm Spark Capital, with contributions from Google and Salesforce. Per data provider PitchBook, its valuation hit $5 billion.

Anthropic and No. 85 Midjourney, the company behind the popular image generator, also represent the promise of a new wave of AI-native companies poised to remake the software landscape. Whereas the majority of this year’s Cloud 100 companies are at least 10 years old and employ 1,000-plus employees, these two startups were both founded in 2021 and have some 200 employees or less.

Continue reading: https://www.forbes.com/sites/kenric...-ai-companies-headline-tktjk/?sh=559b033c78e4

Farming is hard work. It’s physically demanding, it can be dangerous, and it’s often repetitive. But it’s also essential. We all need to eat, and farmers are the ones who grow our food.

In recent years, drones have emerged as a powerful new tool for farmers.

Drones can perform a lot of the tedious, manual, and repetitive work that farmers have traditionally done, such as surveying fields, applying pesticides, and monitoring crop growth. This saves farmers time and effort and can help them be more efficient and productive.

But drones can do more than automate tasks. They collect data used to improve agricultural practices. For instance, drones often create field maps to show the spread and distribution of pests and diseases.

Farmers then use this information to target and apply pesticides more precisely, helping reduce the amount of chemicals used.

Drones are also being used to develop AI programs to help farmers make better decisions. For instance, one AI program is being used to predict crop yields based on drone data. This information can help farmers make informed decisions about planting, irrigation, and harvesting.

Drones are still a relatively new technology but have the potential to revolutionize agriculture. From seed to harvest, join us as we explore the top 5 ways drones are paving the way for a greener, more efficient future in agriculture.

Continue reading: https://greenerideal.com/news/technology/drones-in-agriculture/

Exploring the Impact of Cryptocurrency and Blockchain on Internet Security and Privacy: A New Frontier​

Cryptocurrency and blockchain technology have emerged as a new frontier in the realm of internet security and privacy. These innovative technologies are not only revolutionizing the financial sector but are also significantly impacting the way we perceive and manage online security and privacy.

Cryptocurrency, a digital or virtual form of currency that uses cryptography for security, has been a game-changer in the financial world. It operates independently of a central bank and offers a decentralized system of monetary exchange. This decentralization is made possible by blockchain technology, a digital ledger that records transactions across many computers so that any involved record cannot be altered retroactively, without the alteration of all subsequent blocks.

The advent of these technologies has brought about a paradigm shift in internet security and privacy. Traditional online transactions often involve third-party intermediaries, such as banks or payment processors, which can be vulnerable to hacking and data breaches. Cryptocurrency transactions, on the other hand, are peer-to-peer, eliminating the need for these intermediaries and reducing the risk of security breaches.

Continue reading: https://fagenwasanni.com/news/crypt...tier-for-internet-security-and-privacy/53809/

The Internet of Things (IoT) is a network of connected physical devices that communicate and exchange data. This network has seen immense growth in recent years, spreading across many sectors, industries and applications.

The real estate industry is no exception. This article will discuss the impact of IoT devices on the real estate industry's residential, commercial and development sectors, shedding light on the future of this symbiotic relationship.

IoT Innovation In Homes​

Smart home technology has gained significant traction, with many households adopting intelligent solutions for daily tasks. From automating lighting and temperature settings to remotely controlling appliances, IoT devices are rendering the concept of a futuristic home an everyday reality.

As the world gravitates toward sustainable living, energy management has become crucial to modern homes. Some of the ways IoT devices are contributing to energy management include:

• Real-time energy monitoring: IoT devices track energy consumption in real time, providing detailed information on their usage patterns and enabling users to make informed decisions about conserving energy.

• Smart thermostats: IoT-enabled thermostats can learn user preferences, detect occupancy and adjust temperature settings accordingly, resulting in more efficient heating and cooling and reduced energy consumption.

• Demand response programs: IoT devices can communicate with utility companies to participate in demand response programs, reducing energy consumption during peak demand periods and helping to balance the grid.

Continue reading: https://www.forbes.com/sites/forbes...ing-the-real-estate-industry/?sh=27dcd0b24296

The Internet-of-Things (IoT) continues its expansion across the economy, reshaping whole industries. Current trends are expected to continue, and some new trends will emerge. The IoT is likely to enter the healthcare industry and continue to expand in the remote work sphere. More IoT applications are expected to provide benefits through higher productivity and efficiency. This article considers the top 10 trends in IoT technology and its impact on the world.

More active penetration of IoT into the retail sector​

E-commerce has been growing immensely, winning its market share in the retail industry. Due to globalization and technological developments, the retail industry has shifted dramatically from brick-and-mortar supermarkets and malls to online shopping or e-commerce. In the coming years, we are likely to see even more innovation in the sector sparked by the development of the IoT. Amazon is about to offer a model of fully integrated supermarkets. Automation of the spread of the IoT is expected to continue and even accelerate in the upcoming years.

More growth in remote working driven by the IoT​

One key trend related to technology is the rise of remote working. An increasing number of companies shifted to remote work. However, productivity suffered due to the shift to remote working, and communication issues resurfaced. This is where the IoT comes in. Many companies already apply the technology, and the trend is not limited to tech companies. The IoT allows businesses to increase efficiency and productivity through more cooperation and better operations control because of increased automation.

The IoT and healthcare sector​

Another trend associated with the IoT is its increasing influence on the healthcare sector. Last year the technological revolution expanded in the industry due to new and unprecedented challenges in the healthcare system. This is represented by increased automation in the sector. Next year we will likely see the continuation of the IoT spread into medicine. This may include more automated medical devices and innovative data management. Therefore, investment in the IoT in health care will likely substantially increase in the years ahead.

The rise of “smart building” technology in the construction industry​

The construction industry is also likely to be affected by the IoT. In addition to 3D models, the IoT is expected to transform industrial operations and change safety standards. Next year we are more likely to see a shift in the industry toward more worker health and safety. The IoT is expected to help construction companies create a more protected environment without hurting financial results. New technologies will comply with strict work safety standards and will be cost-efficient at the same time.

Continue reading: https://readwrite.com/key-developments-and-trends-in-the-internet-of-things-iot/

When it comes to bringing diversity into the cybersecurity industry, let’s start by acknowledging that while the term “minority” may have served to characterize racially or ethnically diverse populations among the majority, it has evolved and can serve as a cringe-worthy elicitation of marginalization for those branded by the label.

So in our journey towards social awakening, we replaced the term “minority” with “underrepresented,” as a way to more subtly highlight “otherness.” In the Harvard Business Review, N.Chole Nwangwu argued that the term “underrepresented” suggests that the “solution to inequity is for leaders to place marginalized social groups into very visible positions while simultaneously failing to give them the tools needed to overcome individual and systemic biases.” Instead, Nwangwu writes that the behavior contributing to underrepresentation is the lack of recognition, or a term she calls “underrecognized.” that must be addressed by majority groups being intentional with leveling the playing field.

For too long, the cybersecurity industry has failed to recognize that the next generation of geniuses may not be forged from the same fire as existing practitioners. If we are honest with ourselves, we realize that some of the best level-one tech support comes from our young people, not the 20-year IT practitioner. Our industry has a unique opportunity to recognize that diverse perspectives representative of our global community has become critical in our journey to a more digitally-forward and securely accessible society.

But, how do we attract and even retain the diverse pool of women and minorities needed to make this shift? Here are some ways we can make a difference:

Continue reading: https://www.scmagazine.com/perspective/how-we-can-bring-diversity-into-the-cybersecurity-industry

The excitement and fulfillment derived from working in cybersecurity and the SOC are often powerful motivators to draw more women into this fun and rewarding field. When people ask me what I do, I tell them that I help to keep the “bad guys'” out, but I realized that I work in an industry where we also keep the “good girls” out. Being an engineer in cybersecurity for over 20 years, I look around the room too often to find that I’m the only woman. How do we change that narrative and open the door to encourage more women to find a career in cybersecurity?

(ISC)² recently reported that women comprise only 24% of the cybersecurity workforce. Here are six steps we can take to build and retain women in cybersecurity:

• Learn to walk in heels: We’ve heard the call for girls in STEM starting as early as elementary school, encouraging early exposure in the field. Many organizations focus on getting young women into computer science through camps, classes, and competitions. Organizations like Rosie Riveters, Girls Who Code, and Boolean Girl make learning computer science exhilarating at a young age. Throughout college, there are opportunities to recruit women from many different majors: business, marketing, math, data science, engineering, and computer science. By weaving cybersecurity into all of these majors and intentionally recruiting women from organizations like WiCys or WomenTech Network, there’s a chance.

Continue reading: https://www.scmagazine.com/perspect...t-do-to-attract-more-women-into-cybersecurity

The generative A.I. product war has officially begun.

Business owners have been investigating ways to integrate generative A.I. into their operations since OpenAI publicly released an API for ChatGPT--which connects the large language model (LLM) to other software platforms--in March 2023.

But many have discovered drawbacks to ChatGPT, including a lack of transparency regarding the data it was trained on, how it makes decisions, and a propensity for presenting false information as fact--a phenomenon known as hallucinating. Plus, ChatGPT lacks customization options, and perhaps most important, API users have to pay OpenAI a fee for every query and response processed and generated by its models, with the more advanced models sporting significantly higher prices than the lower-powered offerings. From there, the price is determined by the length of the query and response. That pricing model is fine for casual users but becomes costly at scale.


But now a new model has entered the fray.

Last month, social media titan Meta released Llama 2, its most advanced language model, to the public. Instead of selling an API, Meta announced that it would release the model as "open source." Usually this would mean that Llama 2 is free of charge for commercial use by anyone, and for many it will be, but some have questioned Meta's claim after reading the fine print. The model's community license agreement contains a stipulation that any product or service powered by the tech that reaches 700 million or more monthly users will have to pay a fee to Meta.
Still, Llama 2 presents some clear advantages over OpenAI's suite of language models, including GPT-4, the most advanced OpenAI model currently on the market. Here's how to determine which LLM is right for your business.

Which model is right for me?​

According to Tyler Ashby, president of A.I.-powered contact center firm Agents Only, there are three key factors to take into account when deciding which A.I. model to go with: "timing, budget, and how adventurous you are as a company. If you need a solution quickly, OpenAI has the advantage because it's simple to use and easy to set up."

Continue reading: https://www.inc.com/ben-sherry/how-to-pick-right-ai-model-for-your-business.html

Businesses and consumers are leveraging AI-powered tools every day, yet debate remains around the actual value of AI. There is a massive opportunity for companies to benefit from AI, especially as many need to deliver more with less in the backdrop of today’s macroeconomic landscape.

Many businesses may already use AI and machine learning-based capabilities in their operations without even realizing it. AI can provide more opportunities for creativity, innovation, and the ability to stay nimble in the face of unforeseen challenges. The question is: how can businesses capitalize on AI’s capabilities to recognize the most value?

With its vast number of applications, AI can be overwhelming, especially for entrepreneurs who likely aren’t tech experts and are already stretched thin from wearing multiple hats every day to run their growing businesses. Thankfully, several established, reliable ways exist to take advantage of AI for both long- and short-term business benefits. Here are three key areas where business owners can use AI to improve decision-making and create stronger operational efficiencies for rapidly scaling businesses.

Simplifying Financial Operations ​

Everyone knows that poor cash flow is detrimental to business health and success, but it’s still one of the most common problems for most entrepreneurs. According to a recent Intuit QuickBooks report, more than two-thirds of small business owners (68 percent) surveyed say they struggle with cash flow problems. To address these challenges, business owners need to leverage tools that can provide the visibility and insights they need to understand their financial performance. AI-enabled tools can predict cash flow by tracking money-in, money-out patterns from expenses, payments, and more. These insights are incredibly valuable and give entrepreneurs the timely information they need to make better decisions and catapult growth.

Continue reading: https://solutionsreview.com/busines...ways-ai-can-help-scale-your-growing-business/

In 2021, a malicious actor remotely accessed a water treatment plant in the US to increase the amount of sodium hydroxide in the water to a dangerous level – which could have potentially harmed millions of people. This is one example of how poorly secured IoT devices can affect public utilities and endanger citizens.

Across Southeast Asia, smart city initiatives like Singapore’s Smart Nation goals and Thailand’s Thailand 4.0 mission promise to improve the quality of life for citizens on national scales. But as physical systems become more intertwined with technologies like Internet of Things (IoT), vulnerabilities in these devices could lead to disastrous incidents.

The number of IoT devices is only set to grow. According to Statista, we can expect to see close to 30 billion connected devices globally by 2030, and at least 20 to 30 per cent of these devices will reside in Southeast Asia, says Poh Chang Chew, Principal Cybersecurity Consultant OT/Critical Infrastructure & Global Partners APAC, Fortinet to GovInsider.

Chew shares with GovInsider three emerging risks that IoT security professionals need to watch out for in the coming years.

1. AI-enabled cyber warfare​

First, security professionals will have to guard IoT devices against the rise of AI-enabled cyber attacks, says Chew.

As AI grows more advanced and generative AI such as ChatGPT proliferates, malicious actors could use these technologies to quickly identify vulnerabilities and loopholes within the source code of various connected devices, he explains.

Right now, threat actors use reconnaissance websites like Shodan or botnets to identify vulnerable devices connected to the Internet, such as IP cameras, heat sensors, and other devices used in smart city systems. Then, they can hack into vulnerable devices residing at data centres to modify cooling settings and disrupt operations, he explains.

IoT devices tend to lack strong security, as IoT vendors prioritize speed to market rather than security during the development lifecycle, Chew says. AI can make the process of exploiting these vulnerabilities even easier.

Continue reading: https://govinsider.asia/intl-en/art...-internet-of-things-will-have-to-fend-against

To stay a step ahead of the bad guys, businesses are leveraging artificial intelligence (AI)-powered automation to identify patterns of suspicious activity and thwart issues that can cause organizational, financial, and reputational harm.
It’s an unfortunate reality that economic uncertainty ignites fraudulent activity. According to the Nations on Occupational Fraud and Abuse, organizations lose 5% of revenue to fraud each year, totaling more than $4.7 trillion lost to fraud globally. That number is expected to continue climbing as desperation fuels criminal activity in the face of a vulnerable economy challenged by a looming recession, interest rate hikes, and bank volatility.

To stay a step ahead of the bad guys, businesses are leveraging artificial intelligence (AI)-powered automation, including machine learning (ML) and automated decisioning, to identify patterns of suspicious activity and thwart issues that can cause organizational, financial, and reputational harm.

Why AI is Key in Helping Fight Fraud​

As economic volatility persists, it is crucial for any organization to bolster its fraud management and mitigation approach. AI can provide fast, accurate, and cost-effective defense that not only helps detect fraud in real time but can also prevent it from happening in the first place —all without compromising the customer experience.

Continue reading: https://www.rtinsights.com/how-ai-helps-businesses-fight-fraud/

As new technologies reshape the world of work, artificial intelligence (AI) and automation are accelerating the digital transformation. These innovations are profoundly impacting how business leaders think about and invest in their organizations in 2023. It has become clearer than ever that the businesses that are primed to thrive and capture new horizons of market share in the years ahead will be those that are underpinned by innovative new digital technologies.

The data backs this up. The global AI market is projected to reach $1,345.2 billion by 2030 according to MarketsandMarkets, with a CAGR of 36.8% from 2023 to 2030. In 2017, Gartner predicted that by the end of 2020, AI would create more than 2.3 million jobs.

Finally, research from the Infosys Knowledge Institute found that “firms that use AI well can increase enterprise profit by 38% and will help deliver $14 trillion of gross added value to corporations by 2035.” These are compelling statistics that clearly show our future trajectory.

I will share a few areas where I see generative AI as a key enabler to empowering employees, and thus powering new business opportunities ahead for organizations.

Generative AI Applied To Work​

Generative AI has the transformative ability to reshape business processes, boost productivity and streamline repetitive tasks—all areas I see that can enrich the employee experience and complement how we as workers get our jobs done to maximum effectiveness.


Imagine a work world where we can spend less time on lower-value tasks (e.g., administration, research, report creation, customer support, etc.) and are able to engage our minds more in strategic thinking, decision-making, creativity and collaboration, for example. This is an AI-powered future that can benefit and enrich both the enterprise and individual alike.

Continue reading: https://www.forbes.com/sites/forbes...m-it-and-shape-its-evolution/?sh=7d26002934b4

Should you use A.I. in your business?

And if so, how?

Maybe you've quickly become a generative A.I. expert. Or maybe you've been playing around with GPTs and know enough to be dangerous. Or maybe you have no idea what all the fuss is about but it seems dystopian.

Either way, we're all acutely aware that the A.I. bandwagon is running out of room.

It's time to hop on.

Right?

Look, no one can give you the exact right answer, but I'll give you a framework to answer it for yourself.

First, Let's Ask the Right Question​

The part of A.I. that makes all the money is not so much about getting the right answer as it is about asking the right question.

So let's make sure we do that here too.

This new flavor of A.I. (and it is indeed just a flavor, is not the kind that's going to kill us all, yet) isn't all that new.

In 2010 and 2011, I co-invented the first commercially available natural language generation (NLG) engine and platform at Automated Insights, which is a fancy way to say that we taught computers how to write articles based on data.

While we used both A.I. and machine learning (ML) to enhance the engine and the platform, our product was neither pure A.I. nor pure ML. Since those early days, NLG has been combined with natural language processing (NLP), a science that started going mainstream with Alexa and Siri, and has now evolved to become generative A.I. -- what we think of as OpenAI and ChatGPT and the like.

But back in 2010, the term NLG hadn't been coined yet, or at least it wasn't mainstream enough to get on into our consciousness, so we referred to what we were doing as automated content, because automation is like 90 percent of what makes A.I. seem like magic and money.

So the real question you should be asking is, "How much automation should I use in my business?"

And to get to that answer, we have to understand the difference.

Thinking Versus Acting​

Machine learning is "thinking" and automation is "acting." As technology continues to blur the lines between machine learning (thinking) and automation (acting), we roll it all into one smart technology called A.I.

Continue reading: https://www.inc.com/joe-procopio/should-you-use-ai-in-your-business.html

Think of a self-driving vehicle. The ML tells it where to go, the automation executes those decisions. Those technologies are unrelated and usually self-contained, but they have to work in complete harmony.

Adopting blockchain-enabled web3 technologies offers a massive opportunity for all industries to upgrade their security and productivity dramatically

Technologies associated with web3 have had a turbulent time of late. From major declines in cryptocurrency prices to what some see as a cooling in enthusiasm for the metaverse, talk about the decentralized future of the internet has diminished somewhat.
According to research by Bain & Company only 20% of organizations have a well-defined strategy in place for web3, with the report suggesting businesses “lack confidence” in their abilities to deploy the new technology.
This month Technology Magazine speaks with three experts in the field of web3 - Daniel Field (DF), Director of Innovation & Global Head of Blockchain at UST, Simon Bain (SB), CEO of OmniIndex and Alex Leventer (AL), Web3 Development Lead, DataStax - to gather their thoughts into how the technology will accelerate digital transformations in future and how web3 is shaping business models.

In what ways can web3 technologies accelerate digital transformations?​

DF: Users will eventually curate collections of digital objects reflecting their past achievements, evolving interests and tastes and most memorable experiences, much as they do with photos, souvenirs and memorabilia today. Only these digital objects can also provide utility, such as access rights or service privileges. This will give new incentive mechanisms to retailers, employers, educators and the entertainment sector, such as new approaches to loyalty and reward.

Continue reading: https://technologymagazine.com/articles/how-web3-will-drive-the-future-of-digital-transformations