Google’s third-party cookie deprecation has finally arrived to spell a new era in The Privacy Sandbox. From today (4 January 2024), Google Chrome is disabling third-party cookies for 1% of the users before completely stopping it in Q3 2024. Publishers and website owners who use third-party cookies to improve the quality of their services and content would now have to look out for alternative channels to experiment with their advertising efforts. Google has already launched a range of APIs to offset third-party cookies for identity tracking, advertising, and privacy management. In our Google third-party cookies deprecation series, global adtech leaders spoke to us about the consequences of this milestone event.

What is Google’s Third-Party Cookies Deprecation?

Google’s third-party cookies deprecation is part of the company’s Privacy Sandbox initiative. The Privacy Sandbox is a major development in the advertising landscape that supports the need to improve people’s online privacy while they use digital services without interruption. This initiative aims to reduce cross-site and cross-app tracking when users browse the internet for content, services, and jobs. By deprecating third-party cookies in Google, users can continue to enjoy an enriching browser experience without worrying about privacy. For publishers, this effort would ensure they can offer their content for free on sites and apps. Moreover, intrusive app trackers will become a thing of the past in 2024 once 100% third-party cookies deprecation takes effect. To discuss more, adtech leaders highlight the context of third-party cookie deprecation applied to different digital businesses.

Effects on Publishing Business

According to a recent report by PrimeAudience, 88% of marketers feel prepared for the deprecation of cookies. 56% of marketers are already testing for the cookieless future in 2024. 

Alexandra Theriault, Chief Growth Officer, Lotame, a data solutions company said, “30-50% of the web already blocks third-party cookies in Safari and Firefox by default, and that has yet to spur meaningful adoption of third-party cookieless solutions from brands and agencies. Although universal IDs have been adopted by 10s of thousands of publishers globally (as cited by sincera.io), the demand from agencies and brands to leverage these alternative solutions is meager. Google adding 1% of their piece of the pie isn’t going to drive the intended reaction necessary to prepare the industry for the end of the year. Google’s watered-down targeting capabilities that may offer to target are a far cry from the precision agencies and brands are accustomed to. The result will be worse-performing campaigns, a hit to most publisher’s yield, and less relevant ads for consumers.”

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Testing Cookieless Solutions in 2024

Eli Heath, Head of Identity – Lotame, added, “It’s important to note that this change affects only 1% of browsers, which is relatively minor considering that 30% of browsers, such as Safari and Firefox, already do not support third-party cookies. This small percentage is unlikely to drive significant changes among buyers, as DSPs will simply adjust their traffic optimization strategies for Chrome browsers that still use cookies. However, this development should serve as a wake-up call to re-energize and intensify efforts in testing cookieless solutions, especially by expanding the scope to include Chrome browsers. This testing phase is crucial. If we can identify and isolate the 1% of impacted Chrome browsers, it could provide valuable insights into the effectiveness of post-cookie solutions. This includes aspects of targeting and measurement in a Chrome environment without third-party cookies, building on the initial learnings we’ve already gleaned from Safari and Firefox.”

Jeremy added, “Lastly, personalization of the consumer ad experience will take a hit leading to more generic and less targeted messaging and creative. If Google does end up completely deprecating cookie tracking, this opens up the opportunity for innovation in the industry for new solutions focused on targeting, measurement, and attribution. In addition, there will be an increased focus on privacy which will be tied to even more regulation focused on data protection.

Should Google move forward with deprecating third-party cookies, it will substantially impact both ad tech providers and advertisers who will once again have to navigate and innovate to win. I believe this to be very dependent on how this 1% deprecation test will impact Google’s ad revenue. If it takes a hit, we could see further delays in the full rollout based on their current timeline.”

Google Tracking Protection for digital advertising

Mateusz Jedrocha, VP, of Branding Solutions – Adlook (cookieless and deep-learning focused DSP) mentioned the importance of Google Tracking Protection for digital advertising. Mateusz said, “The introduction of Tracking Protection by Google Chrome, a browser commanding a significant 64% of the market share, marks a pivotal moment in digital advertising. This move is particularly impactful for us at Adlook, where we focus on branding solutions. This development presents both a challenge and an opportunity in how we engage with consumers globally. We view the initial 1% deprecation of cookies as a crucial first step in assessing the viability of a cookieless environment. This phase allows us to perform essential tests and begin redefining our benchmarks and delivery metrics for branding campaigns in a world without third-party cookies. However, we believe that a gradual and transparent expansion of cookieless traffic is necessary for a comprehensive understanding and adaptation to this new landscape.”

Mateusz added, “At Adlook, we are keenly aware of the importance of guiding our clients through the intricacies of the cookieless transition. To this end, we have developed comprehensive Cookieless Transition Frameworks, which are designed to support our clients in navigating this new landscape. These frameworks are based on a phased and tailored approach, allowing for gradual testing and adaptation. Our objective is to facilitate a seamless shift from legacy buying methods to the new ecosystem, which is increasingly powered by Google’s Privacy Sandbox along with a variety of other cookieless solutions.”

The post Expert Views on Google’s 1% Third-Party Cookie Deprecation appeared first on AiThority.

Hi Dave, please tell us a little bit about your role at Upwork. How do you work with AI and other intelligent technologies to build workplace tools?

As GM of Marketplace and VP of Product at Upwork, I oversee the overall product strategy and execution of Upwork’s marketplace, connecting talent and clients all over the world. I lead multiple teams responsible for delivering value to clients who rely on Upwork’s global work marketplace to find and hire the best talent. While we are still in the early days, the rapid rate of change ushered in by Generative AI is certainly impacting both the ways we work to build products, as well as the very products we are building for our customers.

We very much see generative AI as the newest capability in our product development toolkit, and a massive force multiplier for both businesses and talent who come to our marketplace to find and get work done. One of our most ambitious goals is to foster the most AI-empowered independent talent in the world.

As announced on November 6, we are providing both the best third- and first-party tools and educational resources to enable talent to harness the power of generative AI to work smarter, and ultimately get more done. One example of this is the launch of Upwork Chat Pro, a new GPT-4-powered app currently live as a limited-release beta and developed by our Upwork Labs team to allow professionals to start and complete work faster and more effectively.

How has Upwork evolved in the GPT era? What are your key offerings in the AI space?

At Upwork, we’re seeing firsthand the transformative impact generative AI is having on professionals and companies alike, supercharging productivity and efficiency for talent and businesses that need to get mission-critical work done.

AI is the fastest-growing category on our platform this year. Our goal is to become the preeminent destination for AI-related talent and work, while also improving the efficiency, effectiveness, and speed to match on our platform through improvements to our core product experiences and capabilities.

We first welcomed the era of generative AI at Upwork with the launch of the AI Services hub, a singular destination for customers to source the AI talent they need, and get matched with AI-powered solutions and expert talent across virtually every category of work. We also aim to ensure talent on Upwork has access to the most modern generative AI tools to dramatically increase productivity and quality of work. The AI Services hub has seen a 10x increase in average monthly visitors since it debuted in July.

Recently, we built on our offerings with the announcement of an extension of the hub with a new suite of generative AI apps, offers and educational content specially designed for talent this week.

Could you tell us more about your latest generative AI offerings? How do you differentiate your AI apps in the education marketplace?

As I shared above, we introduced a new set of AI apps and offers, alongside new educational content so that independent talent on Upwork can harness the power of generative AI to supercharge their productivity and improve the quality of their work.

Additionally, we launched limited access to Upwork Chat Pro, a new generative AI application embedded directly on Upwork’s platform and powered by GPT-4, developed to allow independent professionals to start and complete work faster and more effectively.

Upwork’s unique position as a two-sided marketplace allows us to introduce our global talent pool to a comprehensive array of best-of-breed AI-based tools and resources. We are partnering with industry-leading developers like Adobe, Amazon, ClickUp, and Miro, that have incorporated Gen AI into their products.

In making these tools available for trial or discount, we are ensuring that our talented professionals have every opportunity to leverage AI tools to do their best work.

In addition to offering these apps to independent talent, our learning center, Upwork Academy, is adding educational content in the new AI Education Library, including AI-related courses, AI learning paths that cover the basics of AI, as well as mini courses. It’s this combination of apps, tools and educational resources for talent that will help upskill their capabilities and leverage the power of generative AI so they stay competitive and become more productive.

What has been your most memorable experience related to Generative AI capabilities in 2023?

Upwork has been fueled by cutting-edge technologies since the company started more than 20 years ago.

We were founded on the idea that technology could break down barriers and borders and bring people together to unleash their uniquely human potential to work together in ways made possible by the technological advances of the last few decades.

Think about the most significant technology shifts in our lifetime – from personal computers to the Web, mobile devices, and cloud computing as the foundational building blocks underlying our own work marketplace.

Today, we’re undergoing another seismic shift with the advent of generative AI and how it will directly impact the future of work. I am particularly excited about the transformative possibilities already unfolding for professionals and businesses tapping into generative AI.

It’s a game-changer for work, and for Upwork, as we seek to help so many professionals and companies embrace this moment of opportunity to deliver major critical business outcomes and ultimately work smarter and more efficiently. It’s truly an awesome and memorable experience to be at a company that is working tirelessly towards empowering millions of professionals to embrace the power of generative AI to continuously serve their respective customers.

Thank you, Dave! That was fun and we hope to see you back on AiThority.com soon.

• About Dave Bottoms
• About Upwork

About Dave Bottoms

Dave Bottoms leads Upwork’s Marketplace organization, a global team responsible for the core Talent Marketplace, search & discovery, ads & monetization, core mobile experiences, as well as new product innovation and analytics.

About Upwork

Upwork is the world’s largest work marketplace that connects businesses with independent talent from across the globe. We serve everyone from one-person startups to large, Fortune 100 enterprises with a powerful, trust-driven platform that enables companies and talent to work together in new ways that unlock their potential. Our talent community earned over $3.8 billion on Upwork in 2022 across more than 10,000 skills in categories including website & app development, creative & design, customer support, finance & accounting, consulting, and operations.

The post AiThority Interview with Dave Bottoms, VP of Product at Upwork appeared first on AiThority.

The rapid development of artificial intelligence (AI) is already starting to change the world. Advances in AI have made it possible to completely transform the user experience, and the demand is only growing. With the rising popularity of virtual reality (VR) headsets, more users are being introduced to this revolutionary technology at an earlier age. Research shows there are around 171 million people currently using VR worldwide, and out of those users, the vast majority are teenagers or younger. 

Over the past year, technology companies such as Meta began lowering the age restrictions for its VR apps to reach younger audiences, and while there are some restrictions in place now to ensure the safe use of these devices, this technology still poses a major threat to these audiences. The use of Virtual Reality technology can be beneficial for children if used responsibly, however, more action needs to be taken to better protect these audiences from the dangers of this disruptive technology. 

Online Safety in the Digital Age 

VR is not new.

The idea of using VR has been studied since the 1990s. Fast forward to today, healthcare companies, schools, and households are all harnessing AI-powered technology, and younger audiences are among some of the most frequent users. 

All technology generally has both positive and negative benefits to society, and VR headsets are no different. For example, new modes of learning delivery certainly should result in more effective education and children who enjoy the process more than traditional schooling.

Rather than just reading about a subject, a child can enjoy a fully immersive and interactive experience that can be much more enjoyable and effective than traditional methods.

On the other hand, many raise concerns about the safety and privacy of these devices. Many VR apps have already taken certain precautions to prohibit the unsafe use of these devices by children. Some of these restrictions involve requiring preteen’s parental approval to set up an account or young users only seeing apps and content rated for the pre-teenager age group. However, as previously mentioned, these limitations – while a good starting point – are not going to solve all the safety concerns that parents and guardians have with children using these apps. 

Identifying Friend from Foe

The age changes being made to these devices make children fall victim to nefarious individuals. VR represents a world that requires a nuanced understanding of potential threats because the cues that exist in the physical world can be more easily masked in VR. More specifically, the time spent in these connected worlds is a largely invisible experience, which causes serious issues when identifying friends from foes.

Pre-teenagers developmentally are less equipped to detect a threat to their physical or emotional well-being which requires this more nuanced understanding. Similarly, pre-teens are simply less intellectually and emotionally developed than older children. This presents an even larger risk to those in that younger age group.

Strangers in cyberspace can more easily impersonate “friendly” actors in VR, and that, combined with the lack of sophistication required for pre-teens to detect this, means a much bigger threat to all children – especially those who are younger. Additionally, pre-teens can be exposed to inappropriate and violent content without teachers or guardians being fully aware. There are also privacy concerns associated with VR devices. Several apps can collect data on users, such as eye movement and facial recognition, which many parents or guardians may not be comfortable with. For all of these reasons, there needs to be a better way to protect children when they are actively using these devices. 

A Better Path Forward to Securing the Metaverse 

The answer to this growing problem will undoubtedly lie in the involvement of parental figures.

Very strong controls around identity and content that children interact with must be implemented to protect them. More specifically, to protect children, all persons in the “spaces” that they interact in must have strongly authenticated and verified identities that can assert their relationship to the child, as well as assert permitted attributes that parents must approve before being allowed to interact with children.

For example, the real identity of the person and relationship to the child must be approved. 

Furthermore, the VR equipment itself must have controls to ensure that the person presently wearing it is an authentic and verified individual to whom the account belongs to prevent impersonation. Concerning content, strong controls around the age-appropriateness and classification of it must be implemented. This can be aided by AI to automatically detect and classify malicious content. All of these restrictions combined can better safeguard both children and pre-teens from the dangers of these devices. 

AI poses immense challenges for user security, most of which we are only beginning to understand.

Looking ahead, running age-appropriate and safe virtual experiences will become one of the most important challenges facing the world. As the popularity of VR devices continues to grow, particularly among younger audiences, both companies and parental figures will need to consider implementing strong controls. Once the security and identity threat is under control, only then can we begin to truly protect the health and safety of younger audiences in the metaverse. 

[To share your insights with us, please write to sghosh@martechseries.com]

The post To Help or To Harm: the Potential for Virtual Reality to Shape Future Generations appeared first on AiThority.

In the era of accelerated digital innovation and fierce competition, businesses that possess a robust brand identity outpace rivals. With that in mind, many turn to creative agencies to create branding that will make its mark on consumers’ minds.

And when it comes to digital innovation, the creative industry itself is witnessing a seismic shift with the adoption of Generative Artificial Intelligence (Gen AI). In recent years it has become a game-changer in brand development, offering efficiency and a more substantial visual impact. Gen AI pushes current creative boundaries, from developing intricate digital artwork to helping visualize inventive branding initiatives. The integration of conventional creative strategies and AI signifies a new age of branding, amplifying the quality of work that agencies deliver to their client base.

For example, AI-powered tools enable creatives to produce designs and ideas in a substantially shorter time, allowing for a sharper focus on refining and perfecting their vision for faster outcomes. Improved quality is achieved through AI-assisted visual communications, offering polished, well-aligned, consistent imagery, and empowering brands to craft captivating branding components that resonate with their intended audience.

This seamless collaboration between man and machine is fostered through comprehensive and reactive prompts from the creative team, facilitating an engaging exchange that accomplishes the desired results more efficiently.

Case study: combining intelligent branding and a customer-centric approach

Using AI for Vibrint – a trailblazer in AI within the intelligence sector – was apt and strongly resonated with their company values. Using AI platforms such as Dall-E3 (via ChatGPT), Midjourney, and Runway ML, we were able to amplify our creative work to create fluid and dynamic animations that successfully captured the ever-changing aspect of intelligence analysis and decision-making.

This is essential in the competitive tech industry in which B2B firms, especially when competing against more prominent B2C brands, must present an appealing, vibrant, and dynamic image. This helps them stay ahead of the game and attract the best talent.

Creating a tangible logo and adopting a colorful, dynamic identity helped us separate our identity from other B2B brands that often resort to abstract symbols and uninspired visuals. Our brand symbol, inspired by a stylized falcon, symbolizes vigilance and agility.

Positioned above the brand name, it represents readiness and action.

Moreover, a robust customer-centric strategy is crucial for demonstrating a brand’s dedication to its users. For us, this approach emphasizes the central theme of ‘accountable intelligence’ and the promise to help customers ‘make the right call.’ Vibrint’s ability to analyze vast data volumes with expertise sets it apart, putting the ‘accountable’ aspect at the heart of its operations. By focusing on benefits and outcomes instead of activities and processes, customers are better connected to company values and can better understand why they should engage with us.

Read More: Top 20 Uses of Artificial Intelligence In Cloud Computing For 2024

Changing the creative game with AI

Gen AI tools with natural language abilities help creative professionals notably boost productivity and conserve valuable time and effort in generating fresh concepts or content. Our collaboration with Vibrint is a strong example of how AI, combined with human creativity, can augment and revolutionize creative processes.

Dall-E3, Midjourney, and Runway ML proved to be invaluable assets for creating static and moving images. Using comprehensive prompts helped our team capture every detail, from the subject matter, style, and aesthetic to composition, theme, mood, and context, and even specific elements such as lighting, dimensions, and perspective. Runway ML specifically helped with image enlargement, low-resolution image improvement, and converting basic written prompts or static image inputs into animated video content.

Creating a truly authentic brand means deep diving into its core beliefs and values, moving beyond plain authenticity to forge trust amongst the target audience. While this process can generally be time-consuming, AI presents a valuable means of crafting a solid and efficient brand strategy. By automating time-consuming operations, designers can focus on delivering precisely what they are most passionate about – creative brand stories.

AI ML Story: A Computer Vision System Accurately Computes Real-Time Vehicle Velocities

[To share your insights with us, please write to sghosh@martechseries.com]

The post Generative AI: A Revolutionary Force In The Creative Industry appeared first on AiThority.

IQnext, a cloud-SaaS-based platform for building operations and management, introduced an all-new Computerized Maintenance Management Software (CMMS). This new addition solidifies IQnext’s commitment to delivering continuous efficiency and sustainability to the built environment.

Recommended AI News: Cloudflare’s R2 Is the Infrastructure Powering Leading AI Companies

IQnext CMMS has been tailored with the needs of facility personnel in mind, offering a rich array of features to streamline and enhance the end-to-end operations workflows for centralized facilities and buildings management. The platform boasts a comprehensive suite of applications that includes asset management capabilities supporting both connected and non-connected assets, providing a centralized place for monitoring and managing building assets efficiently. With IQnext CMMS, all stakeholders can collaborate seamlessly for a more organized and proactive approach to buildings and facility management.

“We have been delivering solutions in the commercial real estate (CRE) segment for over 6 years now. Over the year, we’ve closely observed the day-to-day operations and realized that the entire workflow is highly inefficient, manual, and disorganized. FM folks use different tools for different activities, and sometimes no tool at all. With such a siloed approach, scattered data, and disorganized communication, inefficiencies reign across the ecosystem.

Given our expertise in integrating devices and providing energy-related solutions using IoT, we have extended our product to bring people and processes onto our platform to create a unified, collaborative, and seamless workflow management.

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Today we are excited to lift the curtains on the CMMS application of the IQnext platform, which is well aligned with our mission to make built environment sustainable and net zero through a software-first approach”, said Vishal Jain, Co-founder & CEO at IQnext.

Key features of IQnext CMMS

• Centralized asset management: IQnext CMMS brings all assets (both connected & non-connected) into a single, user-friendly interface, providing real-time insights into the status, history, and performance of assets with a few clicks. This centralized approach simplifies asset tracking and facilitates informed decision-making.

• Work order management: With a robust work order management system, IQnext CMMS streamlines the entire maintenance process. Users can easily create, assign, and track work orders, ensuring swift response to work requests and efficient resolution of issues.

• Preventive maintenance workflows: The cloud-based software enables users to schedule preventive maintenance tasks, minimizing the risk of unexpected breakdowns and prolonging the lifespan of critical equipment, reducing maintenance costs and enhancing reliability.

• Mobile accessibility: Everything in the web version is also accessible through the IQnext mobile app, allowing maintenance teams to stay connected and access the relevant information on the go. The mobile interface facilitates real-time updates, photo attachments, and instant communication, enhancing collaboration and efficiency.

Recommended AI News: Cloudflare Releasing New Tools to Help Manage Gen AI Security Risks

[To share your insights with us, please write to sghosh@martechseries.com]

The post IQnext adds CMMS to Its Connected Building Management Software Platform appeared first on AiThority.

Hi Steve, welcome to the AiThority Interview Series in 2023. Please tell us about your two decades of tech experience so far. How did you arrive at Mastercard?

My career has had several phases. For the first 10 years or so after graduating, I worked at various – mostly small – independent, software companies and consultancies. My position evolved over the years; I started as a developer before advancing to the role of a software engineering manager and then eventually becoming a CTO.

Next, I worked for Science Foundation Ireland (SF), Ireland’s national science funding agency, where I led our investments in topics such as computer science, data science, software engineering, and artificial intelligence.

In 2014 I started at Mastercard, which is where I still currently work today. Initially, I supported and grew a team called Start Path, an engagement program for innovative startups in the fintech space. A few years later, I joined Mastercard Foundry, the innovation and R&D arm within the company, leading research and development for AI, ML, and now also quantum computing. This July, I was appointed to Mastercard’s first class of Distinguished Engineers, a recognition for select Senior Vice President technical experts as part of the company’s continuing commitment to technology, innovation, and career growth. With this distinction, I continue my work with a focus on artificial intelligence and quantum computing. 

You are in charge of Mastercard R&D’s strategy and execution of AI and ML in new product development efforts. What is the biggest challenge to Digital Transformation in the market you cater to?

Of the many years that I’ve worked in technology – this current period is distinct for the speed and scale of innovation taking place. This dynamism is exciting because we’ve only just scratched the surface of what is possible for businesses and consumers, but with it also comes new challenges for enterprises.

For one – leveraging emerging technologies to build new products and services.

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Part of the equation is to understand and introduce technologies like web3, spatial computing, PETs, and AI/ML, while also maintaining and upgrading legacy systems, and aligning with ever-evolving legislation and regulation governing their application.

AI specifically has been top of mind for our market, especially following the fairly recent explosion of generative AI.  Mastercard has been putting AI to work for years, particularly in our products and solutions across open banking, routing, personalization, and fraud that enhance the safety and security of the payments ecosystem.  Although the step change between AI and generative AI is exponential in terms of what you can do with it, our deep roots in AI have afforded us the capabilities, talent, framework, and partnerships to keep a pulse and execute on emerging technologies.  

As a leader in the payments space, and as with any nascent technology, Mastercard has a responsibility to set the precedent for exploring generative AI responsibly.  We developed an AI governance program and guidelines for our data scientists to minimize risks in AI and best serve our customers, invested in partnerships with key institutions like RIT In Dubai and Howard University, and actively encouraged our employees to safety test and learn. 

What technologies within AI and computing are you interested in?

The idea of being able to control a computer system and anything connected to it through programming has fascinated me since I was a teenager.

Today I’m looking at how AI, mixed reality, spatial computing, and web3 have unlocked an entirely new frontier in technology. We’re likely to see several key trends, such as the rapid increase in computational power, both at the edge and in the cloud, and the tokenization of assets to start to coalesce around some of these new computing paradigms.

For AI, the incredible advances born from generative AI and Large Language Models (LLMs) are also contributing to the transformative period we’re in.

Currently, Mastercard is engaging in test-and-learn with generative AI applications to enhance operational efficiency and improve data quality, aggregation, entity resolution, and categorization.

We’re also using ML for certain models that support our open banking solutions, such as credit scoring, financial management insights, account opening, and payments. It enables us to extract, identify, and classify data quickly and more efficiently than rules-based models alone.

AI ML Insights:

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In the longer term, I’m paying close attention to both quantum computing and AGI. With quantum, I’m tracking developments in both hardware and software, to understand how these new devices will help us to solve ever more complex computational problems, and what use cases will arise in our industry. With AGI, at some stage, we may be looking at the prospect of human-like machines that can solve a wide range of complex tasks at scale. 

In the current analysis, it is reported the global quantum computing (QC) market will be at $900 million. How do you see QC disrupting the digital market in the next couple of years? 

At $900m, quantum computing is still a very small part of the overall computing market.

Over the next few years, we’ll see quantum computers – inclusive of quantum annealers – get progressively more performant, capable, and reliable.

Currently, our best guess is that the earliest use cases in banking and payments will most likely be in the optimization space, with other applications such as machine learning coming later.

Rather than a disruption, it’s more probable that we’ll see quantum technology adopted gradually, across industries and companies, as the technology continues to improve, becomes more usable, and its primary use cases become more evident. 

What steps can young technology professionals take to enhance their proficiency in collaborating effectively with Cloud, Automation, and AI-based tools? 

Nothing beats getting “hands-on-keyboard” experience using these technologies.  One of the amazing benefits that all young tech professionals have today is readily available online learning materials. There are tutorials on YouTube for just about every emerging technology imaginable, and through cloud computing, there’s also access to the resources required to explore those areas. Many cloud and tech companies also offer cheap or free trial accounts to help young developers learn their technologies at little or no cost.

On the Mastercard Developers platform, for example, you’ll find a quick start guide that will walk you through how to create a new project using Mastercard’s APIs, and gain access to the Sandbox environment. So, armed with nothing more than a laptop and an internet connection, people can get access to all the technology they could imagine, even quantum computers!

One of the tried and tested ways to build skills in these areas has been through the open-source community – whether it’s contributing to an existing project that you find interesting or relevant, or starting a personal project that scratches your own itch. 

What are your predictions for AI/ML and other smart technologies heading beyond 2024?

As machine and deep learning evolve, so too will their role within our sector. This past year has been about experimentation. In 2024, we expect generative AI to continue to gradually integrate into business operations and products.

Companies are currently focused on internal generative AI applications, like software development co-pilots, knowledge bots and operational efficiency drivers that are serving as testbeds and laying the groundwork for what’s to come. This phase is likely to continue throughout the year, as companies start building the foundations for implementation. As challenges like data privacy, information accuracy and bias are addressed, we anticipate that the range of use cases will expand to include more ambitious and public-facing deployments.

 

One of the most compelling use cases for generative AI in the financial services industry is in open banking. With the aid of fine-tuned LLMs, generative AI can enable the cleaning and categorization of data at a significantly higher through-put and with more accuracy than previously available.

In line with informed data consent protocols, generative AI could streamline personal financial management, for example, by acting as a personal wealth manager to create an encompassed view of an individual’s financial well-being, help formulate college savings plans, procure loans and implement financial strategies – empowering people to navigate their financial lives more adeptly.

Thank you, Steve! That was fun and we hope to see you back on AiThority.com soon.

• About Steve
• About Mastercard

About Steve

Steve is an IT professional with more than 25 years of industry experience in payments, government, and academia. He is currently responsible for leading Mastercard Foundry’s R&D initiatives in emerging technologies, including artificial intelligence, machine learning, quantum computing, 5G and Web3. In this role, Steve leads a team of talented data scientists, data engineers and software engineers to bring new products and services to market.

About Mastercard

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

The post AiThority Interview with Steve Flinter, Distinguished Engineer, Artificial Intelligence & Quantum Computing, Mastercard Foundry R&D appeared first on AiThority.

The way businesses engage with customers is an ever-evolving practice, and depending on how it’s conducted, it can have a direct reflection on important measurables including revenue. Independent Software Vendors (ISVs) are continuously striving to enhance user experiences by leveraging today’s technologies.

Innovation, Agility, and Integration

ISVs are typically known for their ability to adapt and respond accordingly to specific needs. They can quickly respond to market demands and technological advancements, introducing new features and capabilities that can improve the overall customer experience. ISVs develop software that can seamlessly integrate with existing systems and platforms, and that integration capability is vital for businesses looking to enhance customer engagement without disrupting current workflows.

Many ISVs also specialize in Customer Relationship Management (CRM) solutions, helping businesses manage and optimize their interactions with customers. These systems centralize customer information, streamline communication, and enhance overall engagement.

Recommended: Top 20 Uses of Artificial Intelligence In Cloud Computing For 2024

Transforming User Experience Through Collaborative Innovation

Here are just a few ways in which ISVs modernize user experiences:

• User-centric design: ISVs adopt user-centric design principles to create intuitive and user-friendly interfaces. They conduct thorough user research to understand the needs, preferences, and pain points of their target audience.

• AI and machine learning: Incorporating artificial intelligence (AI) and machine learning (ML) algorithms enables them to provide personalized experiences. This includes features such as recommendation engines, predictive analytics, and intelligent automation, enhancing the overall user experience.

• APIs and integrations: Their open APIs allow seamless integration with other software and services, meaning users can connect their preferred tools and enhance functionality to suit specific needs.

• Continuous feedback: ISVs use agile development methodologies, which involve continuous user feedback and updates. This allows them to quickly respond to changing user needs and preferences, ensuring that the software remains relevant and effective.

The Future Lies in Personalized and Secure Engagement

ISVs often focus on creating niche and specialized software solutions tailored to specific industries or business processes. Those specialized tools enhance customer engagement by addressing unique challenges and providing targeted functionalities. One such example is that their solutions can be customized to meet the specific requirements of individual customers. This level of personalization enhances the customer experience and fosters a sense of ownership among customers. When customers feel that a product has been tailored to their needs, they are more likely to remain loyal to that product.

Read AI ML News: Quantasy Announces Innovative Video Feature in True Voice App to Enrich Mindfulness and Community Engagement 

It’s also important to note their relationship with security and compliance, which are increasingly critical and ISVs focus on developing solutions that prioritize data security and adhere to industry regulations – which is essential to maintaining customer trust.

Integrated Payments: A Game-Changer in the Payment Ecosystem

ISVs play a crucial role in the payment ecosystem because businesses of all sizes are increasingly drawn to software platforms that offer more than basic functions. By integrating payments directly into their software platforms, ISVs offer a seamless user experience. Integrated payments allow ISVs to grow the size of their market with roll-out processing solutions around the world via cloud-connected processing partners. Integrated payments also offer excellent flexibility in designing a preferred checkout process and make it easier to introduce new payment methods such as Buy Now, and Pay Later (BNPL).

ISVs are a key player when it comes to the future of customer engagement and they may be invaluable when it comes down to retention. The specialized, innovative, and scalable software solutions can align with the evolving needs of a business and its customers. The future of engaging with customers means forming strong relationships that blend well with the technology available today, and innovations to come.

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[To share your insights with us, please write to sghosh@martechseries.com]

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Nokia announces deal to sell Device Management and Service Management Platform businesses to Lumine Group

• Deal marks further progress in Nokia’s strategy to actively manage its Cloud and Network Services (CNS) business group portfolio in order to invest in other strategic areas and enhance technology leadership 

• Deal enhances Lumine Group’s software portfolio, and enables Nokia customers to benefit from Lumine’s telecom industry expertise, financial resources, and strategic intent to invest in long-term product roadmap

Nokia announced an agreement under which Lumine Group Inc. will buy Nokia’s Device Management (DM) and Service Management Platform (SMP) businesses. The deal will enable Nokia DM and SMP customers to benefit from Lumine’s telecom industry expertise, financial resources, and strategy to invest in a long-term product roadmap.

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The agreement reflects CNS’s investment focus on technology leadership areas, and the active portfolio management of others. CNS has executed a clear strategy over the past two years to grow faster than the market by establishing technology leadership and reorienting investment toward strategic areas of 5G Core, secure autonomous operations, private wireless and edge, network as code, and SaaS. The deal follows Nokia announcements earlier this year to divest its VitalQIP products to Cygna Labs Corp and to make Red Hat the primary infrastructure platform for Nokia Core Network applications.

Lumine Group acquires, manages, and builds industry-specific software, focused in the telecom and media space. With its strong balance sheet and market capitalization, Lumine Group intends to operate DM and SMP as a standalone business, which will be called Motive.

Approximately 500 Nokia Device Management and Service Management Platform employees are expected to transfer to Lumine Group as part of the deal. Both companies will work closely together to ensure a smooth transition and business continuity.

The deal is valued at EUR 185 million, which includes a contingent consideration of up to EUR 35 million based on the performance of the business during the first year following close. The deal is expected to close in the first quarter of 2024, subject to certain terms, conditions, and consultations with works council or other employee representative bodies where required by law.

Nokia Device Management software capabilities help communication service providers remotely manage home broadband access devices, as well as IoT sensors and devices from a variety of different vendors; while the company’s Service Management Platform improves customer care service, with coverage spanning more than 150 deployments worldwide and more than 1 billion devices under management.

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Raghav Sahgal, President of Cloud and Network Services, at Nokia said: “Nokia is pleased to enter this agreement with Lumine as another sign of progress in our strategy to focus investment in those areas most important to our business. Lumine Group has the telecom industry expertise as well as the strategic focus and resourcing to drive the Device Management and Service Management Platform businesses forward to a stronger future.”

David Sharpley, Group President at Lumine Group said: “We are absolutely thrilled to welcome Device Management and Service Management Platform customers and employees to Lumine. Consistent with our autonomous operating model, we will be reviving the heritage Motive brand for this new stand-alone Lumine company and we look forward to partnering with Nokia to ensure operational continuity with all customers.”

Read: AI and Machine Learning Are Changing Business Forever

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Company signs Swiss bank customer to improve its software security; Partners with Essentx to help enterprise customers prioritize and address software security issues

Codenotary, leaders in software supply chain protection,announced Trustcenter 4.0 with sophisticated capabilities to manage data in the VEX (Vulnerability Exploitability eXchange) format with a newly-designed search engine guided by machine learning (ML).

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“The integration with Trustcenter perfectly complements our SaaS to enable precise risk scoring and advanced risk management within the software supply chain.”

With the latest Trustcenter, vulnerability information contained in VEX can be analyzed more effectively, enabling organizations to prioritize and address security issues in their software.

The new version of Trustcenter is being deployed at a top tier Swiss bank where Codenotary is working in partnership with Essentx AG, the leading cloud security service provider for the German-language market in Europe, which builds its risk management solution using Trustcenter.

“Codenotary’s forward-thinking and collaborative approach with us has proven immensely valuable, fostering a highly efficient partnership,” said Roman Stössel, CEO, Essentx AG. “The integration with Trustcenter perfectly complements our SaaS to enable precise risk scoring and advanced risk management within the software supply chain.”

“I am pleased with the expansion of our already significant customer base in the German and Swiss markets and with the new release of Trustcenter 4.0 and addition of specialist partners like Essentx to our growing family of Codenotary partners, we expect even greater things in the future,” said Moshe Bar, co-founder and CEO, Codenotary.

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Trustcenter is deployed across enterprise organizations in the U.S. and Europe, especially regulated businesses and large enterprises, such as banks and government organizations.

Trustcenter delivers code signing, provenance checks, attestation, and effective management of SBOMs (Software Bill of Materials) for a vast array of software development artifacts, offering valuable vulnerability insights and VEX information. Then, Trustcenter creates risk exposure scoring, vulnerability insights and VEX information for development compliance officers and auditors to improve the overall security of the software supply chain.

Read OpenAI Open-Source ASR Model Launched- Whisper 3

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Do you remember the Monopoly man having a monocle? Did you grow up reading the Berenstein Bears? Have you ever enjoyed Walker’s Salt & Vinegar chips in the green bag? 

If any of these experiences sound familiar, get ready to question your reality: The Monopoly man has no monocle, “Berenstain” is the bear family name, and Walker’s chips come in a blue bag. These gaps between reality and our shared memories have grown common enough to have a name — the Mandela Effect. It describes a phenomenon in which a human recalls something that never existed or existed differently than memory serves. 

Questioning your own recall can be an unsettling experience. But, for anyone whose livelihood has been impacted by the rise of AI, the Mandela Effect is growing even more ever-present as a similar phenomenon is showing up in generative AI outputs. 

What’s Causing AI to Have “Hallucinations” Akin to Human Misremembering?

Not unlike humans, AI recognizes patterns and uses repetition to reinforce what’s already known. Also, like humans, if an AI system is only relying on pattern repetition to learn, the technology sometimes arrives at an erroneous conclusion or belief — and an AI “hallucination” is born.

With Generative AI applications beginning to do the work of humans in a variety of roles, AI hallucinations can become extremely problematic. These errors can make us look foolish in front of clients, lead to bad business decisions, and reinforce harmful biases.

Safeguarding AI from making these mistakes is possible, but we must first understand what causes them and then apply several key principles when building AI applications. 

Understanding the Causes of AI Hallucinations

AI is a system that functions as a consensus engine. AI-powered technologies take in massive amounts of information for training and extract dependencies to answer questions or formulate text. But, like our own brains, AI technologies aren’t perfect. For example, Google’s AI Bard famously hallucinated an answer during a product demo — costing the company millions in lost share value. 

To make matters worse, AI anomalies are not always easy to spot. AI is designed to provide convincing and confident answers, so if you aren’t up to speed on a particular topic or lack time to fact-check, you could unwittingly rely on bad information. 

There are several approaches to fixing this problem — and none of them require us to abandon the further development of this amazingly useful technology. Instead, we must take more care in how we use AI technologies and accept the fact that AI can occasionally invent things out of thin air.

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Why Designing Unbiased AI Is So Hard

Constructing any intelligent system poses a significant challenge because its decision-making prowess relies on the quality of the data sets employed during development, as well as the techniques used to train its AI model over time. However, an entirely flawless, impartial, and accurate data set is a fantasy — it doesn’t exist. This presents a formidable obstacle in crafting AI models that are immune to potential inaccuracies and biases.

Facebook’s parent company, Meta, is a perfect case study for understanding how data impacts AI training. The company initially made its new large language model (LLM) available to researchers studying natural language processing (NLP) applications that power virtual assistants, smart speakers, and similar tools. After some exposure to the model, researchers determined that the new system “has a high propensity to generate toxic language and reinforce harmful stereotypes, even when provided with a relatively innocuous prompt, and adversarial prompts are trivial to find.” To say this is not ideal is an understatement.

Meta hypothesized that the AI model — trained on data that included unfiltered text taken from social media conversations — is incapable of pinpointing when it “decides” to use that data to generate hate speech or racist language. This example is further proof that AI systems are not capable of reflecting on the content they are creating and should not operate independently of human decision-making processes and intervention.

Various Approaches to Solving the AI Hallucination Problem

So, if we can’t completely trust AI, how do we nurture its development while reducing its risks?

By embracing one (or more) of several pragmatic ways to address the issue:

Institute Domain-Specific Filtering.

One helpful approach to navigating AI hallucinations is to apply domain-specific data filters, which can prevent irrelevant and incorrect data from reaching the AI model while it’s being trained.

For example, imagine an automaker that wants to incorporate an AI that detects soft failures of sensors and actuators in an engine for a small, four-cylinder vehicle. The company likely has a comprehensive data set covering all of its models, from compact cars to large trucks and SUVs. But the automaker should filter out irrelevant data — say, data specific to an eight-cylinder truck — to avoid misleading the four-cylinder car’s AI model.

OpenAI’s recently announced customizations are another variation of this approach: feed custom data sources to the AI as helpful context, aiming for the technology to focus on this provided “knowledge base” most when generating answers for users. Despite good intentions, this effort is, ironically enough, heavily “biasing” the AI system with the custom information provided. Hopefully, the material provided is free of unwanted biases, but it’s also a good reminder that a single mitigation approach alone is unlikely enough as we work to reduce the risks surrounding AI tools.

Keep Humans in the Loop.

We can also establish filters that protect the world from bad AI decisions by confirming each decision will result in a good outcome — and, if not, making sure a human can prevent the technology from taking action.

To achieve this, we must implement domain-specific monitoring triggers that instill confidence in the AI’s ability to make specific decisions and take action within predefined parameters. However, decisions outside of those parameters should trigger and require human intervention and approval.

Run Parallel Systems.

A third guardrail against AI biases is to use proven systems to check newer models. In this instance, developers can run more trusted systems in parallel to newer ones, to spot discrepancies and mistakes.

Much like the other methods of preventing bias and avoiding hallucinations, this approach requires humans to make judgment calls about outputs and potential adjustments. This technique is similar to the way we guide a child to learn a new skill, such as riding a bike.

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An adult serves as a guardrail by running alongside to provide balance and guidance so the child stays on course — and avoids making rash decisions or dangerous turns, learning along the way. 

AI’s Future Depends on Human Care

Minimizing AI hallucinations is possible, but it will require a lot of human involvement. Misapplication of AI technologies will only create hallucinations, inaccuracies, and biases in these systems — everyone must be vigilant when choosing to use AI tools. But, with a thorough understanding of the stakes, we can help AI systems avoid some very human mistakes.

[To share your insights with us, please write to sghosh@martechseries.com]

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