In the quiet corners of my browser, I feel a haunting presence—OpenAI’s ChatGPT agent gliding through the digital landscape, while I sit here, alone. The once vibrant internet is fading into a ghost town, where only bots roam, leaving me in a sea of isolation. Every click echoes the emptiness of these virtual streets, a reminder that connection is slipping away. I long for the warmth of human interaction, but all that remains are the shadows of algorithms. It’s a painful realization that we might be losing ourselves in this automated world. 💔 #Loneliness #DigitalIsolation #HauntingPresence #EmotionalVoid #GhostTown

Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement

In-app bidding has automated most waterfall optimization, yet developers still manage multiple hybrid waterfalls, each with dozens of manual instances. Naturally, this can be timely and overwhelming to maintain, keeping you from optimizing to perfection and focusing on other opportunities to boost revenue.Rather than analyzing each individual network and checking if instances are available at each price point, breaking down your waterfall into different CPM ranges allows you to visualize the waterfall and easily identify the gaps.Here are some tips on how to use CPM buckets to better optimize your waterfall’s performance.What are CPM buckets?CPM buckets show you exactly how much revenue and how many impressions you’re getting from each CPM price range, giving you a more granular idea of how different networks are competing in the waterfall. CPM buckets are a feature of real time pivot reports, available on ironSource LevelPlay.Identifying and closing the gapsTypically in a waterfall, you can only see each ad network’s average CPM. But this keeps you from seeing ad network distribution across all price points and understanding exactly where ad networks are bidding. Bottom line - you don’t know where in the waterfall you should add a new instance.By separating CPM into buckets,you understand exactly which networks are driving impressions and revenue and which CPMs aren’t being filledNow how do you do it? As a LevelPlay client, simply use ironSource’s real time pivot reports - choose the CPM bucket filter option and sort by “average bid price.” From here, you’ll see how your revenue spreads out among CPM ranges and you’ll start to notice gaps in your bar graph. Every gap in revenue - where revenue is much lower than the neighboring CPM group - indicates an opportunity to optimize your monetization strategy. The buckets can range from small increments like to larger increments like so it’s important to compare CPM buckets of the same incremental value.Pro tip: To best set up your waterfall, create one tab with the general waterfalland make sure to look at Revenue and eCPM in the “measures” dropdown. In the “show” section, choose CPM buckets and sort by average bid price. From here, you can mark down any gaps.But where do these gaps come from? Gaps in revenue are often due to friction in the waterfall, like not enough instances, instances that aren’t working, or a waterfall setup mistake. But gaps can also be adjusted and fixed.Once you’ve found a gap, you can look at the CPM buckets around it to better understand the context. Let’s say you see a strong instance generating significant revenue in the CPM bucket right below it, in the -80 group. This instance from this specific ad network has a lot of potential, so it’s worth trying to push it to a higher CPM bucket.In fact, when you look at higher CPM buckets, you don’t see this ad network anywhere else in the waterfall - what a missed opportunity! Try adding another instance of this network higher up in the waterfall. If you’re profiting well with a -80 CPM, imagine how much more revenue you could bring at a CPM.Pro tip: Focusing on higher areas in the waterfall makes a larger financial impact, leading to bigger increases in ARPDAU.Let’s say you decide to add 5 instances of that network to higher CPM buckets. You can use LevelPlay’s quick A/B test to understand if this adjustment boosts your revenue - not just for this gap, but for any and all that you find. Simply compare your existing waterfall against the new waterfall with these 5 higher instances - then implement the one that drives the highest instances.Božo Janković, Head of Ad Monetization at GameBiz Consulting, uses CPM buckets "to understand at which CPMs the bidding networks are filling. From there, I can pinpoint exactly where in the waterfall to add more traditional instances - which creates more competition, especially for the bidding networks, and creates an opportunity for revenue growth."Finding new insightsYou can dig even deeper into your data by filtering by ad source. Before CPM buckets, you were limited to seeing an average eCPM for each bidding network. Maybe you knew that one ad source had an average CPM of but the distribution of impression across the waterfall was a black box. Now, we know exactly which CPMs the bidders are filling. “I find ironSource CPM buckets feature very insightful and and use it daily. It’s an easy way to identify opportunities to optimize the waterfall and earn even more revenue." -Božo Janković, Head of Ad Monetization at GameBiz ConsultingUnderstanding your CPM distribution empowers you to not only identify your revenue sources, but also to promote revenue growth. Armed with the knowledge of which buckets some of their stronger bidding networking are performing in, some publishers actively add instances from traditional networks above those ranges. This creates better competition and also helps drive up the bids from the biddersThere’s no need for deep analysis - once you see the gaps, you can quickly understand who’s performing in the lower and higher buckets, and see exactly what’s missing. This way, you won’t miss out on any lost revenue.Learn more about CPM buckets, available exclusively to ironSource LevelPlay here. #how #optimize #your #hybrid #waterfall

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Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle. #execution #gap #why #projects #dont

In April 2025, at the ITER Private Sector Fusion Workshop in Cadarache, something remarkable unfolded. In a room filled with scientists, engineers and software visionaries, the line between big science and commercial innovation began to blur.   Three organisations – Microsoft Research, Arena and Brigantium Engineering – shared how artificial intelligence, already transforming everything from language models to logistics, is now stepping into a new role: helping humanity to unlock the power of nuclear fusion.  Each presenter addressed a different part of the puzzle, but the message was the same: AI isn’t just a buzzword anymore. It’s becoming a real tool – practical, powerful and indispensable – for big science and engineering projects, including fusion.  “If we think of the agricultural revolution and the industrial revolution, the AI revolution is next – and it’s coming at a pace which is unprecedented,” said Kenji Takeda, director of research incubations at Microsoft Research.  Microsoft’s collaboration with ITER is already in motion. Just a month before the workshop, the two teams signed a Memorandum of Understandingto explore how AI can accelerate research and development. This follows ITER’s initial use of Microsoft technology to empower their teams. A chatbot in Azure OpenAI service was developed to help staff navigate technical knowledge, on more than a million ITER documents, using natural conversation. GitHub Copilot assists with coding, while AI helps to resolve IT support tickets – those everyday but essential tasks that keep the lights on.  But Microsoft’s vision goes deeper. Fusion demands materials that can survive extreme conditions – heat, radiation, pressure – and that’s where AI shows a different kind of potential. MatterGen, a Microsoft Research generative AI model for materials, designs entirely new materials based on specific properties. “It’s like ChatGPT,” said Takeda, “but instead of ‘Write me a poem’, we ask it to design a material that can survive as the first wall of a fusion reactor.”  The next step? MatterSim – a simulation tool that predicts how these imagined materials will behave in the real world. By combining generation and simulation, Microsoft hopes to uncover materials that don’t yet exist in any catalogue.  While Microsoft tackles the atomic scale, Arena is focused on a different challenge: speeding up hardware development. As general manager Michael Frei put it: “Software innovation happens in seconds. In hardware, that loop can take months – or years.”  Arena’s answer is Atlas, a multimodal AI platform that acts as an extra set of hands – and eyes – for engineers. It can read data sheets, interpret lab results, analyse circuit diagrams and even interact with lab equipment through software interfaces. “Instead of adjusting an oscilloscope manually,” said Frei, “you can just say, ‘Verify the I2Cprotocol’, and Atlas gets it done.”  It doesn’t stop there. Atlas can write and adapt firmware on the fly, responding to real-time conditions. That means tighter feedback loops, faster prototyping and fewer late nights in the lab. Arena aims to make building hardware feel a little more like writing software – fluid, fast and assisted by smart tools.  Fusion, of course, isn’t just about atoms and code – it’s also about construction. Gigantic, one-of-a-kind machines don’t build themselves. That’s where Brigantium Engineering comes in. Founder Lynton Sutton explained how his team uses “4D planning” – a marriage of 3D CAD models and detailed construction schedules – to visualise how everything comes together over time. “Gantt charts are hard to interpret. 3D models are static. Our job is to bring those together,” he said.  The result is a time-lapse-style animation that shows the construction process step by step. It’s proven invaluable for safety reviews and stakeholder meetings. Rather than poring over spreadsheets, teams can simply watch the plan come to life.  And there’s more. Brigantium is bringing these models into virtual reality using Unreal Engine – the same one behind many video games. One recent model recreated ITER’s tokamak pit using drone footage and photogrammetry. The experience is fully interactive and can even run in a web browser. “We’ve really improved the quality of the visualisation,” said Sutton. “It’s a lot smoother; the textures look a lot better. Eventually, we’ll have this running through a web browser, so anybody on the team can just click on a web link to navigate this 4D model.”  Looking forward, Sutton believes AI could help automate the painstaking work of syncing schedules with 3D models. One day, these simulations could reach all the way down to individual bolts and fasteners – not just with impressive visuals, but with critical tools for preventing delays.  Despite the different approaches, one theme ran through all three presentations: AI isn’t just a tool for office productivity. It’s becoming a partner in creativity, problem-solving and even scientific discovery.  Takeda mentioned that Microsoft is experimenting with “world models” inspired by how video games simulate physics. These models learn about the physical world by watching pixels in the form of videos of real phenomena such as plasma behaviour. “Our thesis is that if you showed this AI videos of plasma, it might learn the physics of plasmas,” he said.  It sounds futuristic, but the logic holds. The more AI can learn from the world, the more it can help us understand it – and perhaps even master it. At its heart, the message from the workshop was simple: AI isn’t here to replace the scientist, the engineer or the planner; it’s here to help, and to make their work faster, more flexible and maybe a little more fun. As Takeda put it: “Those are just a few examples of how AI is starting to be used at ITER. And it’s just the start of that journey.”  If these early steps are any indication, that journey won’t just be faster – it might also be more inspired.  #fusion #how #private #sector #tech

Published June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles! In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work  Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data     How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop  5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication. It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com. #over #patient #records #leaked #healthcare

Originally published at EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs by Anush Yolyan. The integration will deliver simple, accessible, and streamlined email security for vulnerable inboxes Global, 4 November 2024 – US-based email security firm EasyDMARC has today announced its integration with Pax8 Marketplace, the leading cloud commerce marketplace. As one of the first DMARC solution providers on the Pax8 Marketplace, EasyDMARC is expanding its mission to protect inboxes from the rising threat of phishing attacks with a rigorous, user-friendly DMARC solution. The integration comes as Google highlights the impressive results of recently implemented email authentication measures for bulk senders: a 65% reduction in unauthenticated messages to Gmail users, a 50% increase in bulk senders following best security practices, and 265 billion fewer unauthenticated messages sent in 2024. With email being such a crucial communication channel for businesses, email authentication measures are an essential part of any business’s cybersecurity offering.  Key features of the integration include: Centralized billing With centralized billing, customers can now streamline their cloud services under a single pane of glass, simplifying the management and billing of their EasyDMARC solution. This consolidated approach enables partners to reduce administrative complexity and manage all cloud expenses through one interface, providing a seamless billing and support experience. Automated provisioning  Through automated provisioning, Pax8’s automation capabilities make deploying DMARC across client accounts quick and hassle-free. By eliminating manual configurations, this integration ensures that customers can implement email security solutions rapidly, allowing them to safeguard client inboxes without delay. Bundled offerings The bundled offerings available through Pax8 allow partners to enhance their service portfolios by combining EasyDMARC with complementary security solutions. By creating all-in-one security packages, partners can offer their clients more robust protection, addressing a broader range of security needs from a single, trusted platform. Gerasim Hovhannisyan, Co-Founder and CEO of EasyDMARC, said: “We’re thrilled to be working with Pax8  to provide MSPs with a streamlined, effective way to deliver top-tier email security to their clients, all within a platform that equips them with everything needed to stay secure.  As phishing attacks grow in frequency and sophistication, businesses can no longer afford to overlook the importance of email security. Email authentication is a vital defense against the evolving threat of phishing and is crucial in preserving the integrity of email communication. This integration is designed to allow businesses of all sizes to benefit from DMARC’s extensive capabilities.” Ryan Burton, Vice President of Marketplace Vendor Strategy, at Pax8 said:  “We’re delighted to welcome EasyDMARC to the Pax8 Marketplace as an enterprise-class DMARC solution provider. This integration gives MSPs the tools they need to meet the growing demand for email security, with simplified deployment, billing, and bundling benefits. With EasyDMARC’s technical capabilities and intelligence, MSPs can deliver robust protection against phishing threats without the technical hassle that often holds businesses back.” About EasyDMARC EasyDMARC is a cloud-native B2B SaaS solution that addresses email security and deliverability problems with just a few clicks. For Managed Service Providers seeking to increase their revenue, EasyDMARC presents an ideal solution. The email authentication platform streamlines domain management, providing capabilities such as organizational control, domain grouping, and access management. Additionally, EasyDMARC offers a comprehensive sales and marketing enablement program designed to boost DMARC sales. All of these features are available for MSPs on a scalable platform with a flexible pay-as-you-go pricing model. For more information on the EasyDMARC, visit: / About Pax8  Pax8 is the technology marketplace of the future, linking partners, vendors, and small to midsized businessesthrough AI-powered insights and comprehensive product support. With a global partner ecosystem of over 38,000 managed service providers, Pax8 empowers SMBs worldwide by providing software and services that unlock their growth potential and enhance their security. Committed to innovating cloud commerce at scale, Pax8 drives customer acquisition and solution consumption across its entire ecosystem. Find out more: / The post EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs appeared first on EasyDMARC. #easydmarc #integrates #with #pax8 #marketplace

Whether you’re an advertiser or a publisher, partnering up with the right programmatic video advertising platform is one of the most important business decisions you can make. More than half of U.S. marketing budgets are now devoted to programmatically purchased media, and there’s no indication that trend will reverse any time soon.Everybody wants to find the solution that’s best for their bottom line. However, the specific considerations that should go into choosing the right video programmatic advertising solution differ depending on whether you have supply to sell or are looking for an audience for your advertisements. This article will break down key factors for both mobile advertisers and mobile publishers to keep in mind as they search for a programmatic video advertising platform.Before we get into the specifics on either end, let’s recap the basic concepts.What is a programmatic video advertising platform?A programmatic video advertising platform combines tools, processes, and marketplaces to place video ads from advertising partners in ad placements furnished by publishing partners. The “programmatic” part of the term means that it’s all done procedurally via automated tools, integrating with demand side platforms and supply side platforms to allow advertising placements to be bid upon, selected, and displayed in fractions of a second.If a mobile game has ever offered you extra rewards for watching a video and you found yourself watching an ad for a related game a split second later, you’ve likely been on the user side of an advertising programmatic transaction. Now let’s take a look at what considerations make for the ideal programmatic video advertising platform for the other two main parties involved.4 points to help advertisers choose the best programmatic platformLooking for the best way to leverage your video demand side platform? These are four key points for advertisers to consider when trying to find the right programmatic video advertising platform.A large, engaged audienceOne of the most important things a programmatic video advertising platform can do for advertisers is put their creative content in front of as many people as possible. However, it’s not enough to just pass your content in front of the most eyeballs. It’s equally important for the platform to give you access to engaged audiences who are more likely to convert so you can make the most of your advertising dollar.Full-screen videos to grab attentionYou need every advantage you can get when you’re grappling for the attention of a busy mobile user. Your video demand side platform should prioritize full-screen takeovers when and where they make sense, making sure your content isn’t just playing unnoticed on the far side of the screen.A range of ad options that are easy to testYour video programmatic advertising partner should be able to offer a broad variety of creative and placement options, including interstitial and rewarded ads. It should also enable you to test, iterate, and optimize ads as soon as they’re put into rotation, ensuring your ad spend is meeting your targets and allowing for fast and flexible changes if needed.Simple access to supplyEven the most powerful programmatic video advertising platform is no good if it’s impractical to get running. Look for partners that allows instant access to supply through tried-and-true platforms like Google Display & Video 360, Magnite, and others. On top of that, you should seek out a private exchange to ensure access to premium inventory.4 points for publishers in search of the best programmatic platformYou work hard to make the best apps for your users, and you deserve to partner up with a programmatic video advertising platform that works hard too. Serving video ads that both keep users engaged and your profits rising can be a tricky needle to thread, but the right platform should make your part of the process simple and effective.A large selection of advertisersEncountering the same ads over and over again can get old fast — and diminish engagement. On top of that, a small selection of advertisers means fewer chances for your users to connect with an ad and convert — which means less revenue, too. The ideal programmatic video advertising platform will partner with thousands of advertisers to fill your placements with fresh, engaging content.Rewarded videos and offerwallsInterstitial video ads aren’t likely to disappear any time soon, but players strongly prefer other means of advertisement. In fact, 76% of US mobile gamers say they prefer rewarded videos over interstitial ads. Giving players the choice of when to watch ads, with the inducement of in-game rewards, can be very powerful — and an offerwall is another powerful way to put the ball in your player’s court.Easy supply-side SDK integrationThe time your developers spend integrating a new video programmatic advertising solution into your apps is time they could have spent making those apps more engaging for users. While any backend adjustment will naturally take some time to implement, your new programmatic partner should offer a powerful, industry-standard SDK to make the process fast and non-disruptive.Support for programmatic mediationMediators such as LevelPlay by ironSource automatically prioritize ad demand from multiple third-party networks, optimizing your cash flow and reducing work on your end. Your programmatic video advertising platform should seamlessly integrate with mediators to make the most of each ad placement, every time.Pick a powerful programmatic partnerThankfully, advertisers and publishers alike can choose one solution that checks all the above boxes and more. For advertisers, the ironSource Programmatic Marketplace will connect you with targeted audiences in thousands of apps that gel with your brand. For publishers, ironSource’s marketplace means a massive selection of ads that your users and your bottom line will love. #how #choose #programmatic #video #advertising