Legacy processes have been adversely impacted by changing consumer sentiment, and it's becoming increasingly clear that digital transformation is essential in helping businesses at all ends of the chain overcome mounting pressures.

Pressure Amid Mounting Headwinds

Supply chain issues can be varied. The lockdowns driven by the pandemic saw a surge in economic activity throughout Western economies, and growing chain pressures were compounded by closures and staff shortages impacting shipping, ports, and haulers.

For major shipping routes like the Suez Canal and Panama Canal, geopolitical conflicts and drought have impacted the flow of trade through both areas respectively, and these issues are showing no signs of improving soon.

These drawbacks come at a time when the ‘Amazonification' of trade means that customers have evolved to expect to know where their orders are at all times, and they want delivery times to be rapid as a minimum requirement.

When it comes to international supply chains, offering such clarity and accuracy can be extremely difficult. Many silos exist between global warehouses, suppliers, and vendors. This can make the accurate fulfillment of orders more complex, and fall short of customer expectations.

However, we're already beginning to see the emergence of digital transformation as a tool for optimizing international supply chains for enterprises of all scales. With this in mind, let's explore five essential ways that technology is helping supply chains to overcome its challenging headwinds:

Embracing the AI Boom

Artificial intelligence is a technology that's emerging at an extremely fast pace for countless industries, and it's through the ongoing AI boom that businesses can gain more supply chain optimization capabilities.

The beauty of AI solutions is that they can interpret big data on behalf of firms to generate automated and actionable insights to enhance the performance of supply chains. They can be utilized throughout chains to improve performance in areas such as:

• Anticipating demand
• Production planning
• Optimizing delivery routes
• Improving packaging
• Reducing costs

We're already seeing the unity of big data and AI in Amazon's supply chain optimization processes. Given the sheer scale of the store, fulfilling orders at scale is a challenge perfectly suited to artificial intelligence.

To manage extreme customer demand, Amazon utilizes AI to optimize its supply chain by forecasting customer demand, optimizing inventory levels, using data to effectively route orders to the best fulfillment centers, and planning delivery routes to save fuel.

The addition of AI alongside machine learning helps to anticipate product popularity based on a series of metrics and emerging trends and to adjust inventory levels in advance. This process helps to limit waste and ensures that all customers can receive their orders in an efficient and time-efficient manner.

Blending Data and Analytics

The sheer volume of data businesses produce each day can pave the way for comprehensive operational insights, but the vast majority of it is too unstructured to be effectively utilized.

Without accessing these insights, businesses are prone to sticking to their existing processes without the ability to stamp out supply chain pain points effectively.

However, the emergence of cutting-edge tools like process mining has empowered business decision makers to democratize their data to solve lingering supply chain issues.

For instance, it's estimated that at least 60 million shipping containers are shipped yearly. However, silos mean that businesses run their inventory, production, order management, and shipping processes in an isolated manner, meaning that many containers could be left underutilized on a regular basis.

In this instance, analytics could help to monitor shipping capacity in real time to bundle orders and maximize the cost-saving potential of this particular aspect of the supply chain.

Building on Automation

Additionally, automation technology and robotics are improving the efficiency of logistics and facilitating more interconnected supply chains.

The blending of AI and machine learning means that more algorithms can be utilised to analyze significant volumes of data to identify patterns and make autonomous decisions regarding key supply chain processes.

One key example here is demand forecasting, whereby algorithms can identify emerging trends or alterations in customer demand and automatically order more inventory to ensure the ongoing spike in demand can still be facilitated by the company.

Because this is a pre-emptive measure, these automated ordering systems can help to improve customer satisfaction from order fulfillment and save on costs through data-driven forecasts for demand.

The Internet of Things (IoT) is another key technology here, and the use of logistical tools like RFID tags and GPS trackers can help to facilitate a more holistic overview of the location, quality, and supply of goods through international supply chains.

Enhancing Order Visibility

One major disruptive influence in the supply chain landscape is blockchain technology.

While much industry attention has been focused on the AI boom, blockchain is capable of revolutionizing supply chain transparency, particularly for cross-border chains.

Having the ability to keep an accurate and immutable record of where your products are and have their quality assured at every stage of the chain is an invaluable asset for upholding complete visibility of a chain.

Because blockchain is a distributed digital ledger that requires a consensus to be reached among its network of nodes, records can be fully accessible and tamper-proof for all parties involved in the supply chain.

Additionally, smart contracts, which are self-executing, algorithmically-backed tools that work alongside blockchains, can leverage instant payments to parties based on the perceived quality of delivered goods.

Forming Connections with Suppliers

The only way to overcome industry silos is for businesses to form a conducive connection with their respective suppliers. In doing so, they stand the best chance of overcoming supply chain headwinds and can facilitate greater resilience should setbacks occur.

Through a blend of automation and analytical software, it's possible for companies to manage its payouts across various vendors and actively build transparent relationships that put performance at the forefront of partnerships.

This simultaneously helps companies to manage vendors and leverage AP automation while avoiding falling into its own on-chain silos when it comes to keeping avenues for communication open at all times.

Building a Sustainable Supply Chain Infrastructure

As more globally firms face up to supply chain disruption and the frailties of legacy systems throughout international chains, the emergence of technology like AI, machine learning, automation, the Internet of Things, and blockchain help to overcome industry headwinds and point to a more collaborative and transparent future for the essential industry.

With geopolitical, environmental, and staffing factors remaining as uncertain as ever, the implementation of these technologies to overcome industry silos may be imperative for the future sustainability of international supply chains.

The post 5 Ways Emerging Technology Overcomes Headwinds for International Supply Chain Efficiency appeared first on Datafloq.

Although it's been relatively slow in the uptake of digital transformation, the impressive growth of Open Banking has shown that there's plenty of room for innovation throughout finance.

While Open Banking refers to the exchange of services and data across financial institutions, Open Finance represents the next step in digital transformation and empowers trusted third parties to utilize customer data to deliver more transformative access to services such as banking, credit, alternative payments, financial advisors, insurance, investment tools, spending insights, mortgages, pensions, and a wide array of other fintech tools.

This next generation of finance can be leveraged by artificial intelligence, and the ongoing AI boom is already providing us with insights into how it can drive the growth of Open Finance.

Uniting AI and Open Finance

At its core, AI helps to harness the power of data effectively throughout the financial landscape. This bodes well for Open Finance, which is dependent on rich, structured data that artificial intelligence algorithms can deliver for effective decision-making.

This can help to enhance and automate processes that customers have long grown accustomed to in traditional finance. From personalized experiences at local branches to bespoke financial advice, AI helps to maintain the local aspect of finance in a world that's attempting to replicate physical connections in a digital landscape.

The post-pandemic era has seen many traditional financial institutions abandon their brick-and-mortar stores in a bid to tap into the cost-effectiveness and efficiency of Open Banking. While this can be a jarring shift, the ability of AI to accelerate Open Banking into a more functional Open Finance model could be a timely upgrade.

But how exactly will the artificial intelligence revolution support the growth of Open Finance? Let's take a look at five ways the innovative technology will transform the industry:

Embracing Predictive Analytics

One vital reason why AI is an excellent driver for Open Finance is because of its ability to algorithmically analyze historical data to anticipate future outcomes and trends.

In terms of Open Finance, this means that artificial intelligence has the power to anticipate customer behavior, identify risks before they emerge, and tap into its wealth of insights to optimize business processes in ways that human staff may be unable to recognize on such a rapid basis.

For instance, an integrated AI algorithm can utilize available customer data to create a bespoke analysis of a customer's risk of defaulting on a loan based on a multitude of behavioral, historical, and external factors. This paves the way for a better understanding of risk and allows institutions to adapt offers to mitigate the risk involved.

The emergence of generative AI can also enhance predictive analytics further by allowing firms to utilize synthetic data in understanding customer behavior. In the age of GDPR, synthetic data can be an excellent solution for bridging analytical gaps due to the unavailability of data.

The Age of Rapid Decision-Making

The ability of AI to get to grips with big data and drive actionable insights for decision-makers means that more institutions will be capable of reacting faster to the bespoke needs of customers.

Here, the technology can aid the reaction times of just about every player in Open Finance, from underwriters to customer service agents, in automating routine tasks to help employees allocate far more attention to any cases that are too complex to be handled by the AI.

In practice, this means that artificial intelligence can actively enhance decision-making in a cost-effective and efficient manner while humans can tap into actionable insights for more responsiveness when it comes to outlying cases.

The use cases for AI-driven decision-making in Open Finance are already growing. According to Suzanne Homewood, Decisioning Managing Director at Moneyhub, one lender saw a 15% dropout rate in loan applicants that AI flagged as fraudulent, while in Open Banking, loans made with better-informed decisions have been found to perform 50% better than others.

Personalization for Life After Branches

One of the biggest issues that digital transformation in finance poses is the loss of those personal connections that customers are accustomed to with brick-and-mortar banking. For many individuals who have long expected to be able to visit their local branch to speak to advisors who they're familiar with, the post-pandemic closure of banks has been jarring.

Artificial intelligence can help to restore this highly sought-after personable feeling among customers and recapture trust that may have been tested during the financial sector's push towards digital transformation.

“An example is AI-powered personalized conversational interfaces and biometric profiles that have shown promise in helping vulnerable consumers avoid debt traps fueled by late fees and inflexible payment schedules,” notes Charlene Coleman, Senior Managing Partner at Launch Consulting Group.

Additionally, big data analytics can help Open Finance services to understand their customers on a far more comprehensive level. In practice, this would mean that entire interfaces and fintech platforms could adapt directly to the customer's perceived requirements. Is a customer using a platform to invest in tech stocks? Then their portfolio will be displayed on their home screen. Has a customer been saving for a mortgage? The portfolio can load their cash ISA on launch.

It's through this comprehensive behavioral understanding that AI can help Open Finance deliver personalization on a level that can be even more convenient than before.

Live Compliance Monitoring

At this stage, it's crucial to highlight that Open Finance certainly carries a greater level of risk for customers and institutions alike. At its core, Open Finance services would be built on the widespread sharing of highly personal financial data for a multitude of customers. This means that the risk of data breaches could cause damage on an unprecedented scale to users.

With this in mind, we're likely to see the regulatory landscape surrounding Open Finance become increasingly stringent as the ecosystem grows. When backed by a sufficient AI framework, the challenge of compliance among challenger banks and fintechs can be simplified.

Let's look at the European Union's regulatory outlook for open finance as an example. The EU recently updated its Payment Services Directive (PSD) to better accommodate the emerging technological landscape and ensure that data is shared safely throughout the bloc's financial institutions.

As these directives are continually updated to ensure the safe flow of information throughout the financial landscape, artificial intelligence and generative AI tools can help to actively monitor compliance throughout the flow of Open Finance services, and could even make adjustments on the fly should incidents or possible inefficiencies threaten the legality of certain services.

Open-All-Hours Support

Generative AI is already making a significant impact on the quality of support offered to customers. As finance becomes increasingly digitalized, it's been a challenge for many institutions to replicate the quality of service that customers have lost in the closure of many local branches.

However, large-language models (LLMs) and virtual assistants are actively revolutionizing support systems in Open Finance.

With 24/7 coverage, these chatbots can respond immediately to queries, answer FAQs, and guide users through complex processes in an adaptable way. With the ability of LLMs to generate bespoke responses for more difficult issues, this support can become a reliable way of maintaining customer satisfaction while actively supporting tasks like loan applications, account management, and transactions to ensure no business is lost along the way.

AI to Drive the Digital Transformation Revolution

Given the necessity of access to financial services for everybody at all times, the digital transformation revolution in finance is nothing short of essential.

While the post-pandemic landscape has been a challenging one for traditional finance, the arrival of Open Finance powered by artificial intelligence is set to recapture the essence of personalization and adaptability lost with the closure of local branches.

With powerful insights and the ability to offer more bespoke services instantaneously, AI has the potential to take the financial sector to unprecedented heights. While this will bring new regulatory challenges, it's shaping up to be a key stepping stone in the Open Finance revolution.

The post 5 Transformative Ways AI is Driving the Open Finance Revolution appeared first on Datafloq.

The smartphone industry has been struggling to rediscover its momentum in recent years, having a decline in global shipments spanning eight consecutive quarters in 2023 and showing a 9.5% decrease in shipments in Q2 last year in comparison to the year before.

Despite a sustained downturn, hope may have arrived in the form of generative AI. Although many analysts had looked to the emergence of 5G data as a watershed moment in the evolution of the smartphone industry, it appears that the meteoric rise of GenAI holds masses of potential in delivering next-generation tools and services for users.

We're already seeing generative AI take its first steps in the smartphone landscape thanks to Google's partnership with Qualcomm in leveraging new experiences for Android devices.

The two tech and telecommunications giants announced their partnership during the Snapdragon 8 Gen 3 launch, and Google's advanced foundation AI models are set to run on Qualcomm's Hexagon NPU to provide us with a glimpse into how smartphones will undergo an IQ boost over the coming years.

The partnership will utilize the same foundation AI models that have brought some generative AI features to the powerful Google Pixel 8 Pro such as on-device recorder summaries, Smart Reply functionality in Gboard, and the soon-to-be-released Video Boost feature.

“Over the past few months, researchers at Google have been working to take their massive next-generation large language models and distill them to fit on a mobile device. Soon, you'll be able to do more on-device with Google applications than ever before,” explained Alex Katouzian, senior vice president at Qualcomm.

Google Leads the Race for GenAI Smartphones

While other leading smartphone manufacturers have been cautious about harnessing the power of generative AI, Google has led the way in a series of intuitive enhancements for Android handsets.

As the GenAI boom was still gathering momentum, Google announced three features for its Search Generative Experience (SGE).

The first innovation comes as a means of viewing definitions of words in the search summary, helping users to better understand words or terms that may not be commonly known. This would empower users to hover over words in the summary to view definitions, related images, or wider contexts that are automatically generated for clarity.

Another feature is ‘SGE while browsing', this artificial intelligence list of key points for supported articles can help users discover the precise point within texts where their queries are answered. Additionally, an explore section will generate questions that the article answers with links to the relevant sections.

The arrival of SGE, which is available in the Google app for both iOS and Android, will only be the tip of the iceberg in terms of Google's expiration into generative AI.

At Google's annual software conference I/O 2023, the tech giants announced a series of generative AI features designed to add more levels of personalization and convenience to daily smartphone processes.

The announcement of Magic Compose was the showstopper, which comes in the form of a Messages by Google feature that offers suggested responses based on the context of your messages and conversations. This feature helps to craft messages that perfectly suit your style and context.

Additionally, Google unveiled a fresh approach to Android wallpaper which can automatically become dynamic through generative AI based on just a few initial prompts.

As one of the world's largest tech firms, Google has been capable of offering more generative AI features across the smartphone landscape earlier than its competitors. Even Apple, which has often stood at the forefront of innovation for tech hardware, is only beginning to catch up through the recent launch of its own AI framework, MLX.

Google's trailblazing innovations in generative AI have been facilitated by its own advanced large language model (LLM), Bard. Although the 2022 launch of ChatGPT had been the catalyst for the generative AI boom over the past year, the constant stream of updates and fresh features rolled out through Bard points to one of the most sophisticated generative AI models available today.

Generative AI is the Future of the Smartphone

Automated messaging and dynamic wallpapers are just the very beginning of the disruptive influence GenAI will have in making smartphones smarter, with the possibilities offering virtually limitless boundaries.

“AI is the future of the smartphone experience,” said Katouzian, “and when it comes to mobile technology, it's what we've been building toward for over a decade.”

Soon, personalized content and suggestions will significantly enhance the user experience. Generative AI will be capable of generating fully customized wallpapers, ringtones, emojis, stickers, image filters, and avatars while automatically auditing recommendations, notifications, and settings to ensure that you're handed a seamless experience when using your device.

By the way of an example, Cristiano Amon, chief executive of Qualcomm highlights how generative AI will transform texting among other daily tasks.

“When you write a text, you think about it as a message that you are sending to another person,” explains Amon. “But for the AI, that could be a query. As you type that text message, the AI is running and thinking, ‘Is there something for me to do here?'.”

“You just said that you want to get on a call with Clare next week and you suggested Tuesday, so the AI will bring up the calendar app and say, ‘Tim, you have these slots available. Do you want me to send a calendar invite to Clare?' The other kind of thing that is going to happen is: you tell me that you just had a wonderful holiday with family, and as you mention this, the AI is going to say, ‘These are the photos you took, do you want to share that with Cristiano?'.”

The examples above indicate that generative AI could become a highly intuitive personal assistant for us, which operates in a non-intrusive way until it recognizes an opportunity to deliver convenient solutions.

It's also worth highlighting the levels of privacy that generative AI can bring. Because of its ability to generate synthetic data for testing, training, and analytics purposes, artificial intelligence models can become more efficient without having to use real user data.

It's also possible for GenAI solutions to actively mask the face, voice, and identity of users as a means of protecting device owners from facial recognition, voice recognition, and biometric hacking.

Could Generative AI Retire the Smartphone?

In understanding the capabilities of generative AI, it's worth asking whether there's room in the future for smartphone devices as we know them today.

Generative AI has the potential to seamlessly communicate with our friends, family, and colleagues on our behalf with minimal prompts, and can complete essential tasks in an instant simply by learning our behavior and anticipating our actions.

The greater levels of intuition that GenAI brings may pave the way for seamless verbal communication. So what's the use of a display when we're talking to AI? Why would we need a keyboard if AI can predict our messages for us?

The role of the smartphone is about to change on a fundamental level and become more intelligent than we can imagine. The emergence of generative AI will herald the level of innovation that we were dreaming of for 5G and lift smartphone sales to boot.

Whether the smartphone will still exist as we know it today when GenAI fully takes hold remains to be seen, but we can be sure that it'll steer our favorite portable assistants into their smartest iteration yet.

The post Inside Google’s Plan to Use Generative AI to Ramp Up the IQ of Our Smartphones appeared first on Datafloq.

This streaming ‘flippening' event took place in 2022, according to a Nielsen report. “In July, streaming amounted to 34.8% of the share of total TV consumption, a growth of nearly 23% within the past year,” the annual report stated.

“Cable and broadcast viewership both dropped year-over-year, with the former amounting to 34.4% and the latter making up just 21.6%. Both fell around 10% compared to July 2021.”

This change in viewer habits represents the rapid rise of digital transformation in the television landscape. Just a decade ago, satellite and television were entertainment behemoths while streaming services like Netflix were still building momentum and Amazon Prime was yet to launch.

Today, we've become accustomed to streaming apps providing the majority of our favorite series, and new players like Disney+ and Paramount Plus providing access to vast libraries of shows old and new.

As the power of 5G connectivity becomes harnessed by the streaming world's leading apps, viewers can expect a revolution in how shows and movies can be watched-particularly on the go.

Harnessing the Power of 5G

By now, you're likely well aware of 5G, but what does it actually mean? 5G is the name given to the fifth generation of mobile connectivity, which offers far greater download speeds and lower latency rates, more comprehensive support for devices, stronger flexibility, and better reliability for a vast number of purposes.

How can we quantify the difference between 5G and its precursor? While 4G reached download speeds of 1Gbps (gigabyte per second), the goal is for 5G services to increase tenfold to offer 10Gbps speeds.

Such a rapid acceleration would pave the way for immersive rich media, significant levels of transformation in cloud computing, the rise of autonomous technology, and the potential for smart cities emerging in the future.

In terms of entertainment, 5G has the potential to drive our viewing habits far beyond the confines of the traditional satellite and cable services that ruled the roost just a decade ago.

The Next Generation of Streaming

Perhaps the clearest implementation of 5G in the immediate future will be the enhancement of streaming services.

With faster data speeds and lower latency, platforms like Netflix and Hulu will be capable of offering more high-quality content without the threat of buffering or other factors that could slow services down.

5G also brings greater network capacities that enable more ultra-high-definition (UHD) content for fully immersive streaming experiences.

This is likely to be just the beginning of what 5G can offer in terms of streaming entertainment. The introduction of buffer-free UHD content can pave the way for a more seamless integration in 3D streaming services, and even mixed-reality experiences.

The next generation of connectivity will also help to improve the accessibility of streaming services to everyone, even in rural or remote areas. For the millions of Americans and global citizens living outside of cities, this can offer unprecedented access to content that has never before been available.

In addition to streaming services, 5G will be a major innovation for internet protocol television (IPTV) content, where viewers will be capable of accessing high-bandwidth content for their favorite international TV shows, live sports coverage, geo-locked content, or multi-device access services to stream without disruption.

With much of this content only accessible with a VPN, 5G services mean that users can use a VPN for IPTV to enjoy a comfortable viewing experience without the problem of having their access slowed down due to the end-to-end encryption that takes place during the viewing experience. You can check out this handy guide on IPTV VPNs from Fire Stick Tricks.

The Return of Social Viewing

5G will also be capable of improving existing satellite, cable, and 4G streaming experiences for viewers.

In a world that's becoming more intrinsically connected to social media, 5G has the power to leverage more viewing experiences in a social setting.

Through the use of integrated technology, we may soon see streaming services offer real-time entertainment experiences such as live or on-demand concerts, movie premieres, sporting events, and multiplayer video games that friends or competitors can experience together on a remote basis.

We're already becoming accustomed to seeing international artists performing in metaverse environments like Fortnite, Roblox, and Meta, and 5G can empower more users to experience similar digital events as part of their streaming services.

Thanks to improvements in connectivity, Netflix has already created its own vibrant video game streaming service for users to play either at home or on the go. As the power of 5G becomes more commonplace, we'll likely see these efforts grow into a tangible opportunity for users to interact with one another and play together online.

Greater Personalization

Another key advantage that 5G supplies streaming services over traditional digital viewing comes in the form of personalization. For customers and businesses alike, personalized ads can help to bring relevance and build better viewing experiences.

Today, more streaming services are warming to the notion of incorporating ads into their packages, and we're likely to see advertising become commonplace in one form or another in the future of entertainment services.

However, 5G can help to make ads more intrinsic and personalized. If the age of the two-minute advertising breaks is far from over, at least we can be treated to a bespoke range of ads that offer relevance based on our viewing behaviors and online profiles.

How these personalized ads will appear on our screens may change with greater connectivity. If we're watching sports, rather than taking an extensive break, these personal ads can run throughout digital advertising hoardings near the playing field.

The Future of XR, VR, and AR in Streaming

As we've touched on, 5G connectivity can also help streaming services implement their extended reality (XR), virtual reality (VR), and augmented reality (AR) experiences in the future to compete with the rise in metaverse social viewing events that are largely centered around concerts and other large crowd experiences at present.

The high-bandwidth performance of 5G means that broadcasting can take on many new forms over the coming years, and we're likely to see renewed interest in reality technology as a more immersive content experience gathers momentum.

Owing to the ability of 5G to deliver high-resolution graphics and faster loading times, the sky could well be the limit for the incorporation of TV series and movies into the world of virtual reality.

Whether you would like to view your favorite sitcom as if you were in the audience or gain a pitch-side view at a football match, 5G could be a watershed moment for uniting reality technology and entertainment on a comprehensive scale.

The 5G Revolution Will be Televised

Faster data means that our television no longer needs to be wired in on cables or broadcast from an orbiting satellite. With 5G, streaming services can deliver a seamless viewing experience with little chance of disruption.

While a more comfortable experience is assured, this only represents the tip of the iceberg. 5G is the first technology that can bear the load of high-performance reality technology and the potential for more immersive viewing experiences among audiences.

With this in mind, it's worth watching the space that the entertainment industry is growing into. Faster connectivity opens the door to near-limitless possibilities for TV and film.

The post Why the 5G Era Will Revolutionize Television and Entertainment as we Know it appeared first on Datafloq.

Leading IoT devices like smart lighting, thermostats, security cameras, and doorbells have all helped improve our home lives. They provide unprecedented levels of control and empower homeowners to continuously monitor their environment. 

It doesn't stop there, IoT appliances from voice assistants to smart fridges can offer a more bespoke level of service that paves the way for more control over what happens in the house. This can help to look after expenses, automate processes such as the online food shop, and, crucially, monitor your premises for suspicious activity.  

Exploring the Smart Home Revolution

The growth of IoT and AI technology means that the potential use cases for smart home optimization are nearly limitless. The expanding capabilities over the coming years include: 

AI Integration: The continued blending of AI and IoT will empower homeowners to adapt and impose their preferences on systems. This can range from automated lighting adjustments to suit home schedules, background music, and responsive temperature adjustments.

Efficient Energy: The Internet of Things can also help homes optimize their energy usage through real-time data analytics. This helps to improve carbon footprints while saving money for homeowners. 

Limitless Interconnectivity: Homeowners can also expect a great number of devices to become interconnected, paving the way for a seamless smart home experience. From your toaster to your greenhouse and everything in between, it will be possible to become aware of any aspect of your home that needs attention immediately. 

Next Generation Home Security

There's little doubt that the Internet of Things holds great potential for improving home security. Tools like smart doorbells, WiFi CCTV, and intelligent alarm systems can all make the process of spotting unusual activity far more efficient and deliver a greater piece of mind. 

Leading smart security firms like Nest and Ring combined IoT technology with AI to deliver intelligent doorbells that can monitor front doors, send alerts when activity is identified, and even communicate with visitors via their smartphones. 

For instance, Nest's 2nd Generation video doorbell comes equipped with familiar IoT mod-cons such as the notifications users can receive when activity is recorded, but it also uses AI to distinguish what movement is taking place. This means that users won't receive false alarms when a cat, passing vehicle, or familiar face comes into view, which helps to bring the right level of relevance to new alerts. 

These smart security tools also leverage real-time data and intelligent algorithms to offer a comprehensively secure living environment for inhabitants. 

Learning Your Routines

While AI-powered doorbells can learn faces, more artificial intelligence security systems will be capable of remembering the routines of residents based on their behavior. 

If somebody comes home from the office at a similar time on Mondays, Tuesdays, and Thursdays, systems will learn and switch on outdoor lighting at an appropriate time to welcome them. It will also note any discrepancies or facial mismatches for arrivals within this time frame. 

By linking routines to faces, AI can help to alert users only when something unusual is taking place that doesn't synchronize with typical behavior. 

This routine-learning behavior can also offer privacy and security both inside and outside of the house. It can understand when you prefer to keep your time in the garden private, which can be a great asset in overlooked spaces. 

By learning your shade sail usage, your AI security can automatically roll out a shade sail or canopy based on factors like routines or even weather forecasts to keep your time in the garden private and comfortable throughout the day. 

Looking Beyond Facial Recognition

We readily associate AI with facial recognition because it has become such a powerful example of the technology in practice today. However, this is only the tip of the iceberg in terms of what artificial intelligence can achieve in the Internet of Things age. 

The smart home security technology of tomorrow will look to implementing hands-free access to properties based on near-field communication (NFC) keys connected to our phones, or smart locks.  

Powered by AI cameras and home surveillance systems, access to properties can be granted to NFC holders while all-purpose cameras actively verify the faces of key holders as they enter and exit the property. If something doesn't look right, access will be denied until the key holder's identity can be verified. 

The combination of IoT and AI is only just beginning to produce next-generation products for users to keep their homes safe from intruders. 

In the future, we're likely to see more convenience brought into the field through artificial intelligence, which is set to help provide more authenticity to smartphone security alerts while maintaining a comprehensive level of privacy and safety based on behavioral learning.

This will help to make the home our castle once again, equipped with its own AI-powered moat constantly on the lookout for threats. 

The post How AI and The Internet of Things are Creating a New Standard in Home Safety appeared first on Datafloq.

According to Accenture data, 91% of consumers are more likely to buy from brands that offer relevant recommendations and deals, and this element of personalization can be championed through strong customer journey analytics.

How can your brand take its customer journey analytics to the next level? And what will the future of CX look like? Let's delve into how to take extra care of your customer journey:

Care for Qualitative and Quantitative Data

The best customer journey analytics are driven by crisp, accurate, and expansive data. This raw data is the key to understanding your customers, but you must create a clear process for gathering and compiling your data from the appropriate marketing sources, channels, and localities.

For the most comprehensive overview of your customer journey, you need to find a synergy between qualitative and quantitative data. These datasets are defined as:

• Qualitative Data: This type of data is far more contextual, and helps brands to understand the ‘why' and ‘how' surrounding customer trends. Examples of qualitative data include feedback forms, customer surveys, and user testing.
• Quantitative Data: This refers to more voluminous metrics such as website visits, bounce rates, and sales figures. Platforms like Google Analytics typically excel when it comes to leveraging more quantitative data.

When it comes to aggregative qualitative and quantitative data, marketing data aggregation tools can be a great way of uniting various metrics and utilizing them to generate a more holistic overview of your customer journey.

Unify Customer Data Effectively

By unifying your qualitative and quantitative data in one place, a centralized digital system can automate the process of matching and merging data across multiple different platforms. This can help to save time and uphold higher levels of accuracy when it comes to database management.

Today, as multi-channel purchasing becomes increasingly commonplace, customer journey analytics have become more complex across industries. However, automation can empower each aspect of your service to deliver consistent brand experiences.

In the age of digital transformation, your insights must stem from more than just sales metrics. By unifying data effectively, you can add much needed context to your customer interactions and discover what's driving their behavior.

Behavioral Segments Can Deliver Retention

Your customer journey analytics can be optimized further by utilizing behavioral segments to yield more information about specific customers rather than aggregating large swathes of data alone.

Churn may be inevitable for many businesses, but early lifecycle churn, such as when a customer cancels a service within a 30-day window or returns a product the next day, can be harmful because it indicates that the brand hasn't been able to recoup its customer acquisition cost.

Behavioral segments can help you to better examine your sales and marketing funnel to analyze churn at the early, mid, and late-lifecycle stages for your customers. This will pave the way for more targeted marketing and reinforce the core value of your product on a more consistent basis.

This is likely to pave the way for increased customer investments in your brand with the help of journey analytics to shed more light on up-sell and cross-sell opportunities across your services.

Hunting For Your ‘Eureka' Moment

Every successful customer journey involves a ‘eureka' moment where they finally understand the value that your product will bring to them.

These moments are so important that failure to reach them will inevitably lead to them navigating away from your brand, possibly forever.

Unified customer journey analytics can help you to understand where your ‘eureka' moment is most likely to be through spotting where purchase intent takes over from the evaluation stage in a customer's journey across your various channels.

Identifying and amplifying your ‘eureka' moment across channels is likely to generate more conversions and leverage better retention rates.

Unlocking the Future of CX Analytics

We've already been offered a taste of what the future will look like in terms of recent developments in artificial intelligence and machine learning. These innovations will move into the world of customer journey analytics to deliver more focused insights for businesses in real time.

AI and machine learning have the potential to analyze big data focused on customers as they are generated to identify patterns and insights that more traditional segmentation may miss.

This can pave the way for new and more focused segments while refining existing ones and creating more accurate customer profiles.

For example, brands will be capable of segmenting customers based on their past purchase behavior, website engagement, social media usage, and a series of other metrics that can be accessed with the help of artificial intelligence.

Platforms like ZoomInfo, a B2B database and sales intelligence platform, utilizes machine learning to deliver more focused segmentation based on the respective industries in which clients are based, company size, and various other metadata that can shape more focused retention measures.

This level of focused segmentation can help marketing teams to more effectively target their prospects and leverage more personalized campaigns based on the individual needs of each segment.

As digital transformation continues to ramp up the difficulty in outmanoeuvring competitors online, the ability to fine-tune and supercharge brand customer journey analytics will be essential in retaining customers for longer.

The post How to Supercharge Your Customer Journey Analytics for Optimized Retention appeared first on Datafloq.

From data analysis to aggregation, the insights we can gather from information can help to guide businesses and shape decisions across a multitude of sectors. It's for this reason that advancements in AI can help to improve processes throughout the landscape.

Here, the potential for automated processes that increase efficiency could be one of the single most important innovations for our relationship with data in the 21st Century. But how exactly will AI improve data analysis and other key processes?

Let's take a deeper look at the sweeping changes that generative AI can bring to data, and its impact on businesses on a global scale:

The Next Generation of Data Management

Generative AI programs powered by resourceful Large Language Models (LLMs) are helping to make a transformative impact on the world of data. According to McKinsey data, 90% of commercial leaders expect to utilize GenAI solutions ‘often' in the near future.

Crucially, generative AI has the power to aid data professionals in overcoming the fallacies of human processes in configuring data systems. Emerging technology has the power to streamline the analysis process while optimizing various data programs to validate and rectify data sets in an effective way that's free of error.

These LLM algorithms can deliver high-quality analysis or data assessment in a way that can automatically identify anomalies within data sets and overcome complexities with confidence. Businesses can introduce their own house styles or privacy requirements within the analysis and aggregation of data for generative AI programs to follow in a technically efficient manner.

Using the insurance industry as an example of this in action, generative AI can effectively analyze the intricacies between policies and claims, and identify trends in the relationships across different datasets and policies. Integrated user interfaces can then validate and suggest possible new rule changes, while clients can impose their own house business rules in natural language for models to convert into executable code using Spark, Python, or Structured Query Language (SQL).

Delivering Impactful Synthetic Data

One key problem that many industries have to overcome, particularly in the age of GDPR, is overcoming the challenge of missing data.

However, generative AI models will be capable of generating synthetic data that closely align with real-world data. This will be a significant asset to businesses operating with limited data sets or sensitive information.

These additional data points mean that generative AI models will be capable of improving the accuracy and efficiency of data analytics without the risk of human error creeping into play.

Similarly, the technology will aid businesses in better interpreting complex data sets through the implementation of synthetic data. By generating fresh samples based on existing data sets, GenAI models can identify patterns, correlations, and outlying data that may be too difficult to spot for human analysts.

This is made possible by AI learning common patterns and distributions by coming into direct contact with data. Any suspected deviations from learned patterns can be efficiently identified with relevant parties notified of the anomaly. It's this keen attention to detail that may help generative AI to become a leading component in fraud detection and cybersecurity.

Emerging Data Aggregation Use Cases

The AI revolution in data aggregation is already underway, and we're seeing many emerging use cases where firms are helping to manage data in a more intelligent manner in fields like finance.

For instance, a lack of uniformity in data feeds received from banks can be an issue when it comes to data transformation. Various data feeds from different sources can make the transformation process an extremely complex task for human users and the absence of clarity of guides means that the challenge is made far more difficult.

This leads to significant inefficiencies and a considerably higher chance of human error resulting from manual changes in data structures. It can also cause severe delays in the data aggregation process for firms.

However, firms like PetakSys have utilized AI to transform the financial data integration process to bring more efficiency for financial organizations.

Through the use of an AI-powered solution, systems are capable of adapting data formats autonomously once received from custodian banks. With the help of machine learning platforms, the system can learn how to interpret and translate the data it receives into a suitable format for a portfolio management system.

Delivering Visualizations for Added Ease

Generative AI will not only help to make it easier to generate and interpret data, but it will also pave the way for a more seamless experience in presenting data.

The AI revolution will fundamentally change how we consume data, and autonomous visualization tools can help to convert complex information into charts, graphs, and focused insights into emerging trends that could otherwise be impossible to identify.

These GenAI visualization tools can help to shed light on business curiosities. For instance, if an eCommerce marketing manager notices that a certain type of book shelf is selling better than others, they can consult the AI to discover that the product was recently featured in a marketing campaign and communicate this information to their team.

Building a Future Built on AI

Over time, generative AI models will fundamentally change data analytics and aggregation throughout virtually every industry. The revolution will span marketing, sales, and customer-facing operations, as well as research and development processes.

Crucially, our strengthening relationships with AI will remove the risk of human error from data sets. Guesswork will be redundant, and synthetic data will be capable of identifying stronger trends and emerging patterns with relative ease. It's through these insights that AI can help to generate greater opportunities for prosperity for all.

The post Is Generative AI About to Change Our Relationship with Data Forever? appeared first on Datafloq.

The generative AI market is forecasted to reach a value of $191.8 billion by 2032, representing a CAGR of 34.1%. In such a rapidly expanding digital landscape it seems certain that the technology will impact how we secure our property and possessions, and given that instances of burglary in the UK appear to be increasing, generative AI may be a technological revolution that can't happen soon enough. 

Data from the Office for National Statistics claim that instances of burglary in England and Wales have risen by 4% for the year ending March 2023, with total burglaries reaching 275,919 over the same period. 

Could generative AI help residents win the battle against the growing threat of burglary? Use cases suggest that the generative AI fightback against intruders is already underway, but it's more important than ever to balance your offline security measures with online considerations. 

The Next Generation of Intelligent Home Surveillance

One of the most effective ways that AI is helping to improve home security is through smart motion detention. 

Through artificial intelligence tools, cameras will be capable of not only monitoring activity around your property, but also learning and recognising your surroundings, routines, and frequent visitors. 

By actively scanning the faces that enter your property and analyzing their behaviour, generative AI models can calculate the optimal response based on their interpretation of a security threat. This would then trigger real-time alerts when the AI has determined that something isn't quite right. 

The reason that AI excels in this area of home security is because of its ability to identify and classify objects appearing within a camera's field of view. Generative AI can lean on machine learning to understand whether a car, neighbour, pet, or unknown person has entered the frame and act on their interpreted level of danger. 

Crucially, this improved accuracy can eliminate false alarms, helping you to treat an alert accordingly. Generative AI could even learn to determine whether to directly notify the relevant authorities based on its interpretation of an unfolding event. 

Learning From Routines

Just as machine learning can learn objects appearing in view, it can also learn our common routines and make decisions based on its identified patterns. 

While this could be conjuring images of your house becoming your very own HAL 9000, it can be a highly effective way of keeping your routines up even when you're away from home on business or taking a holiday. 

In the future, generative AI could link your arrival at home to your most common use of house lighting and may even be able to set up your TV and living space to your preferred requirements. 

On the flip side, if somebody arrives at an unusual time and can't be identified, a generative AI system could ramp up security measures on the fly. 

Knowing When to Use Smart Locks

Smart locks can use artificial intelligence to detect when somebody may be forcing entry, or keep a record of who has gained access to a property. 

The great thing about smart locks is that they can be used alongside just about any form of lock hardware, from traditional locks to deadbolts, to padlocks for garden sheds. 

They can also use a range of advanced technology to ensure that no unauthorised individuals gain access to your home or workspace. This can be achieved through fingerprint scanning, entry logging, the use of programmable cards or fobs, or integrated smartphone apps. 

Some tools, such as the Eufy Video Smart Lock, combine a lock with a video doorbell for unprecedented control over who comes and goes.

You can even combine your smart lock with some ultra-secure hardware measures by getting reputable residential locksmiths to install a steel or brass deadbolt as an added layer of protection should your AI system alert you to a prospective intruder.

Generative AI Poses Security Opportunities and Risks

While generative AI is likely to have a bright future in providing residents with more comprehensive ways to keep their homes safe, it's important to acknowledge that the power of the technology could come with its own security risks should any vulnerabilities become exploited by criminals. 

In introducing its Secure AI Framework in mid-2023, Google has sought to build “a bold and responsible, […] conceptual framework to help collaboratively secure AI technology,” in the words of Royal Hansen, Google's VP of engineering for privacy, safety and security.

The framework intends to help AI programs stay secure in the face of system risks and emerging cybersecurity threats. This would make the use of generative AI home security systems more efficient without online risks compromising the security of vital information about respective homes. 

However, the risk of leaking personal information or confidential data about smart properties could actively help burglars if system vulnerabilities arise. It's for this reason that adopters should always look for the best privacy features and algorithmic accountability from developers. 

With this in mind, it's important to regularly audit any AI smart home devices and who's logged into them around once a month. 

The emergence of generative AI has presented us with brand new ways to look after our respective properties. However, this technological breakthrough has once again raised fresh concerns surrounding online privacy. 

In shoring up the security of your homes, it's vital that you don't accidentally open the door for burglars to exploit your vulnerabilities online. 

The post Why Generative AI Will Win The Battle Against Growing Instances of Burglary in the UK appeared first on Datafloq.

The evolutionary change that AR is capable of bringing the industry can impact every stage of a car's path from the production line to the driveway of a new owner.

In utilizing augmented reality, it's possible to not only design more efficient cars but to also assist prospective buyers and help maintain motors, helping to promote better safety in vehicles.

Let's take a deeper look at some of the leading examples of the transformative change that AR is capable of providing the automotive industry:

Optimizing Automotive Design

Augmented reality has the potential to revolutionize automotive design. Through the power of AR, it's possible for designers to craft richly detailed virtual models of vehicles and make essential adjustments in real time.

This process enables quick and seamless modifications that can help save time and money. Not only can these models provide a fully functional overview of a vehicle during the design process, but it can also pave the way for more immersive prototyping of cars to better uphold safety standards.

We're already seeing augmented reality prototyping enter the automotive landscape to improve the design of vehicles. For instance, in 2019, Ford became the first vehicle manufacturer to utilize Gravity Sketch, which is a 3D tool utilizing reality technology to help the company's designers to craft more human-centric vehicle designs.

Delivering Assembly Line Efficiency

Because AR has the ability to join forces with smart glasses to offer hands-free access to data in real-time, car manufacturing employees have the ability to gather masses of information without having to individually test component parts or take any extra steps.

This can help to improve workplace safety while also paving the way for intelligent 3D visualizations that can help not only improve diagnostics but can also be used to improve the quality of training delivered to warehouse employees.

According to a recent study at the University of Maryland, subjects saw a recall improvement by as much as 8.8% when using a virtual learning environment. This can help to bring vast improvements to assembly line efficiency in comparison to more traditional training approaches.

Augmented reality can even provide more step-by-step instructions during the manufacturing process for staff, while Key Performance Indicators (KPIs) can help firms to quickly identify skill gaps that can be quickly addressed among employees.

Changing the Game in Car Retail

We may also see augmented reality transform the car purchasing experience in a new car industry that's in need of a boost.

Although new car registrations soared 18% in 2023 in comparison to the year prior, it's believed that much of these sales were driven by fleets, as opposed to consumers who are becoming more wary of how they spend their money.

However, AR could help to make the car purchasing process altogether more seamless by helping prospective buyers get up to grips with the models they're most interested in.

Imagine being able to position a full-scale 3D rendering of a car on your driveway, and to physically explore the vehicle by walking around the digital structure and looking inside.

Virtual car tours are becoming more commonplace among car dealerships around the world, where AR experiences help buyers to get to grips with motors while shopping online.

Jaguar Land Rover has also utilized a similar technology to allow customers to test drive its Velar vehicle. These 360-degree experiences of the car's interior take place when a user clicks on a banner ad, and different areas of their screen can reveal more about certain in-car features.

The Next Generation of Car Maintenance

Augmented reality can also improve the longevity of a vehicle through better-assisted maintenance programs for drivers.

If you're unfamiliar with mechanics, it's possible to undertake maintenance tasks through a fully immersive and engaging AR tutorial. Whether you're uncertain of how to change your windscreen wiper fluid or need to top up your engine oil, augmented reality can help you to perform these tasks confidently and efficiently.

In the future, we may even see augmented reality become more adept at highlighting these problems before they become costly repair work. For instance, it may be able to use onboard data to pinpoint a windshield crack and its rate of growth, helping to alert the owner to find an auto glass shop service in time before it gets worse.

The beauty of augmented reality is that it's already busy improving the automotive industry for all players, from manufacturers to car owners. In offering more intuitive prototyping, manufacturing, and purchasing procedure, the benefits of AR can help to make the world of motoring more efficient, from the production line to the driveway.

With the technology still emerging it seems that AR in the automotive industry has plenty more miles in the tank.

The post From Production Line to the Driveway: How Augmented Reality is Reinventing the Car appeared first on Datafloq.

Today, big data stands as a key driver of digital transformation for car manufacturers, and many factories already actively adopting sensors and connected devices that pave the way for M2M (machine-to-machine) communication, we're likely to see greater efficiency encapsulated within our vehicles and vast improvements to the user experience they provide.

Statista data suggests that there will be over 400 million connected cars in operation by 2025, which can remain connected to other devices, manufacturers, and even roads in the future, to deliver greater levels of convenience, safety, and performance for motorists around the world.

But how exactly will the big data boom change the car as we know it today? Let's take a deeper look under the hood of an IoT revolution that's building pace:

Over-The-Air Updates

Big data can carry a far-reaching impact on different areas of the automotive industry. One particularly key aspect can be found in the detection and prevention of errors to continually update vehicles and uphold a higher standard of quality.

For connected cars, over-the-air (OTA) software and firmware upgrades can be a significant asset to improve the driving experience and deliver more functionality and security.

Big data can help to improve the performance of motors on an ongoing basis, with a connected feedback loop continually providing manufacturers insights into possible pain points for users and shining a spotlight on regularly used features.

When it comes to matters of security, big data can quickly identify vulnerabilities and provide manufacturers with insights into how to update their vehicles to prevent instances of theft or other vulnerabilities.

We've already seen this in action in recent months after videos went viral on TikTok displaying how thieves can break into KIA and Hyundai vehicles without the use of a key. The manufacturers quickly rolled out a software update to help offer more safety for owners, including an upgrade to theft alarm software and a modification in how long the car alarm sounds.

As IoT technology makes more vehicle components increasingly intelligent, we may see software updates aiding customers with issues involving key fobs, and other accessibility components.

Big data can also be shared with external garages and locksmiths to help improve the accuracy of essential maintenance and can improve diagnostics on matters like car door lock repair, and other malfunctions related directly to the vehicle. For instance, you get locked out of your car and don't have any documents on you to prove ownership of the vehicle, hence when you're searching for a locksmith, theoretically, big data can help your chosen locksmith to identify you (the owner) and your car, and more importantly, confirm the ownership.

Prioritizing Safety

Manufacturers are also utilizing big data analytics as a means of delving deeper into understanding the mechanics of vehicle safety.

With the ability to collect vast data points from both test crashes, simulated scenarios, and real-world diagnostics, manufacturers are capable of setting up countless improvements for future models in terms of hardware, and even on-the-fly updates to in-car electronics that have room for further optimization.

This can be a great way to ensure that connected cars are more durable in the face of wear and tear over time and have the capacity to cope well in emergency situations.

Developments in this area can be a great asset to both manufacturers and consumers, who can enjoy a safer vehicle with peace of mind, while greater satisfaction rates and lower insurance costs can help to drive more purchases of connected models.

Over the coming years, as the big data revolution begins to take hold, we're likely to see cars begin to communicate with one another when driving to ensure that potential emergency situations can be avoided by adopting systems that can step in if immediate action is required to prevent a collision.

The Path to Autonomy

It's difficult to cover the future of big data and motoring without acknowledging the role that it will play in the eventual introduction of autonomous vehicles.

Today, testing on fully connected, autonomous motors is already being taken out by leading manufacturers like Tesla, Ford, UK firm Arrival, and German firm Vay. While the sheer level of safety standards and complexity of driving with no human input means that fully autonomous vehicles may not be on our roads in great numbers for decades to come, the prevalence of big data will invariably form the foundation of this innovation.

Despite this, the technology can help to revolutionize lower levels of autonomous driving already, and data-driven features like lane assist, self-parking, and the autopilot feature utilized by Tesla are already active and effective thanks to IoT technology and big data.

This is likely to only be the beginning of what's to come for big data and the automotive industry. Although many of the more ambitious innovations set to arrive will hinge on regulatory clearance, we're set to see great strides made in terms of driver safety and convenience today. As the big data revolution continues to gather momentum, we can be assured that this is just the beginning.

The post Why Big Data Will Place Cars at the Center of the Internet of Things Revolution appeared first on Datafloq.