A transformation model is a refection of an organization’s data-driven management. But for complex multinationals, it’s not easy for talent to implement new technologies, nor data scientists to grasp the big business picture. So Mitsui & Co., one of Japan’s leading general trading, investment, and service companies, is focused on growing the company-wide knowledge base to strengthen its digital ambitions. source

擁有177年歷史的醫學護膚品牌PHYSIOGEL於昨日舉行以「醫學美肌之旅」為主題的品牌活動，展示品牌三大系列產品，包括：抗敏紓緩系列、全天候水分修復系列及SCIENCEUTICALS醫學美肌系列。其中，SCIENCEUTICALS醫學美肌系列的美白淡斑逆齡精華更是首次閃亮登場，吸引了眾多媒體和護膚愛好者的關注。 皮膚科醫生推薦品牌PHYSIOGEL特別針對乾燥脆弱的敏感肌，以革命性科研為肌膚研發具有卓越效果的護膚品。利用先進的BioMimic科技，研發出與肌膚結構及成分相近的產品。除了皇牌抗敏紓緩系列及全天候水分修復系列，品牌更推出了SCIENCEUTICALS 醫學美肌系列，將專業拓展至醫學美容護膚產品。 昨天邀請了因電視劇《企業強人》而備受矚目的女演員龔嘉欣（Katy）出席活動。Katy忙於發展事業同時不會忽略肌膚保養，使用了品牌最近推出的SCIENCEUTICALS醫學美肌系列的美白淡斑逆齡精華，蘊含Even Toning Complex ™淨澈亮白複合物，能高效抗氧、美白淡斑、淡化黑色素同時鎖水提亮，令皮膚時刻維持最佳狀態，使Katy在鏡頭前能自信展現年輕、光滑肌。 「PHYSIOGEL醫學美肌之旅」活動不僅展示品牌專業的護膚理念，身心靈水晶擴香石工作坊讓更多人了解到如何在繁忙生活中，保持肌膚健康與美麗的秘訣。Katy更為PHYSIOGEL活動增添光彩，展現護膚與自信之間的密切關係。 K11 Musea 6樓咖啡店Ukiyo推出期間限定「士多啤梨亮白美肌窩夫套餐」 此外，由11月7日至11月28日期間，PHYSIOGEL更聯同日系咖啡店Ukiyo為新品美白淡斑逆齡精華推出期間限定「士多啤梨亮白美肌窩夫套餐」，惠顧即可獲贈「PHYSIOGEL醫學美肌體驗套裝」乙份。 * yuu 會員專享 yuu會員於咖啡店Ukiyo享用限定聯乘「士多啤梨亮白美肌窩夫套餐」，展示yuu App內會員ID QR code ，可額外獲得皇牌逆齡抗氧精華液體驗裝及供應商$20 現金優惠券 (總值$129)。 LinkedIn Email Facebook Twitter WhatsApp source

Generative AI is as trendy as it has ever been. This year, research into AI was awarded Nobel Prizes, and the largest tech companies in the world pumped AI into as many products as possible. The U.S. government promoted AI as a driver in creating a clean-energy economy and a strategic pillar for federal spending. But what’s next for 2025? The trend of generative AI in the last few months of 2024 points to a greater push for adoption from tech companies. Meanwhile, the results as to whether AI products and processes see ROI for enterprise software buyers are mixed. While it’s difficult to foresee how AI will continue to shape the tech industry, experts have offered predictions based on current trends. Respondents to an IEEE study in September rated AI as one of the top three areas of technology that will be most critical in 2025 in 58% of cases. Conversely, nearly all respondents (91%) agree that 2025 will see “a generative AI reckoning” regarding what the technology can or should do. Expectations for generative AI are high, but the success of projects leveraging it remains uncertain. 1. AI agents will be the next buzzword Based on my research and observations, the use of AI agents will surge in 2025. AI agents are semi-autonomous generative AI that can chain together or interact with applications to carry out instructions in an unstructured environment. For example, Salesforce uses AI agents to call sales leads. As with generative AI, the definition of an agent’s capabilities is unclear. IBM defines it as an AI that can reason through complex problems, such as OpenAI o1. However, not all products billed as AI agents can reason that way. Regardless of their capabilities, AI agents and their use cases will likely be at the forefront of generative AI marketing in 2025. AI “agents” could be the next stage of evolution for this year’s AI “copilots.” AI agents could spend time working through multi-stage jobs independently while their human counterpart handles another task. 2. AI will both help and hurt security teams Both cybersecurity attackers and defenders will continue to take advantage of AI in 2025. 2024 has already seen the proliferation of generative AI security products. These products can write code, detect threats, answer thorny questions, or serve as a “rubber duck” for brainstorming. But generative AI may present information that is inaccurate. Security professionals may spend as much time double-checking the output as they would if they had performed the work themselves. Failing to review such information can lead to broken code and even more security issues. “As AI tools like ChatGPT and Google Gemini become deeply integrated into business operations, the risk of accidental data exposure skyrockets with new data privacy challenges,” Jeremy Fuchs, cyber security evangelist at Check Point Software Technologies, said in an email to TechRepublic. “In 2025, organizations must move swiftly to implement strict controls and governance over AI usage, ensuring the benefits of these technologies don’t come at the cost of data privacy and security.” Generative AI models are susceptible to malicious actors like any other software, particularly via jailbreak attacks. “AI’s growing role in cyber crime is undeniable,” Fuchs explained. “By 2025, AI will not only enhance the scale of attacks but also their sophistication. Phishing attacks will be harder to detect, with AI continuously learning and adapting.” Generative AI can make conventional methods of identifying phishing emails — poor grammar or out-of-the-blue messages — obsolete. Disinformation security will become more important as AI-generated videos, audio, and text proliferate. As a result, security teams must adapt to both using and defending against generative AI — just as they have adapted to other significant changes in business technology, such as the large-scale migration to the cloud. 3. Businesses will evaluate whether AI delivers ROI “The pendulum has swung from ‘new AI innovation at any cost’ to a resounding imperative to prove ROI in board rooms across the world,” Uzi Dvir, global CIO at digital adoption platform company WalkMe, said in an email. “Similarly, employees are asking themselves if it’s worth the time and effort to figure out how to use these new technologies for their specific roles.” Organizations struggle to determine whether generative AI adds value and to what use cases it can make the most difference. Organizations that adopt AI often face high costs and unclear goals. It can be difficult to quantify the benefits of generative AI use, where those benefits manifest, and what to compare them to. This challenge is a side effect of the integration of generative AI into many other applications. It makes some decision-makers wonder whether generative AI add-ons truly boost the value of those applications. AI tiers can be costly, and over the next year, more companies are expected to rigorously test — and sometimes discard — the features that don’t deliver results. Many companies that are incorporating generative AI at a large scale are seeing success. At its Q3 earnings call, Google attributed this result to its AI infrastructure and products such as AI Overviews. However, Meta reported that AI may significantly increase capital expenditures, even as user numbers decline. SEE: Google Cloud is previewing its sixth generation of the AI accelerator Trillium. 4. AI will make a major impact on scientific research Along with impacting enterprise productivity, contemporary AI has seen significant movement in science. Four of 2024’s Nobel Prize winners used AI: Demis Hassabis and John Jumper of Google DeepMind won the Nobel Prize for Chemistry for predicting the structure of proteins with AlphaFold2. John J. Hopfield and Geoffrey Hinton won the Nobel Prize for Physics for their decades-spanning work developing neural networks. The White House held a summit on Oct. 31 and Nov. 1 about the use of AI in life sciences, highlighting how AI enables solutions to complex challenges in ways that impact the world. This trend is likely to continue into next year as generative AI models grow and mature. 5. The environmental tools made with

Enterprise IT leaders face a daunting challenge: delivering innovative solutions through new applications, data services, and AI investments while adhering to tight budgets. Cloud computing, often at the heart of these initiatives, presents a particularly uncertain landscape, especially regarding storage costs, which can significantly impact IT budgets. Rising expenses in cloud data storage have prompted many organizations to reconsider their strategies, leading to a trend of repatriation as enterprises seek more control during these unpredictable economic times. A February 2024 Citrix poll revealed that 94% of organizations had shifted some workloads back to on-premises systems, driven by concerns over security, performance, costs, and compatibility. In response, senior business and finance leaders might consider a swift transition back from the cloud to curb expenses. However, cloud repatriation carries its own set of risks, including potential egress fees, the need for new hardware, security investments, and other infrastructure costs. Additionally, companies may face the challenge of re-hiring staff previously laid off. Furthermore, there’s a significant opportunity cost associated with missing out on enhanced collaboration, innovation, agility, and access to advanced cloud-native tools and services, including AI and machine learning. Optimize Your Cloud Strategy Before You Repatriate Deloitte analyzed anonymized data from several FinOps engagements to assess optimization efforts, finding that businesses can save up to 45% (15% on average) on cloud costs by optimizing across waste management, consumption management, and purchasing best practices levers. Common tactics of re-architecting applications, managing cloud sprawl and monitoring spend using the tools each cloud provides are a great first start. However, these methods are not the full picture. Storage optimization is an integral piece. Focusing on cloud storage costs first is a smart strategy since storage constitutes a large chunk of the overall spend. More than half of IT organizations (55%) will spend more than 30% of their IT budget on data storage and backup technology, according to our recent State of Unstructured Data Management report. The reality is that most organizations don’t have a clear idea on current and predicted storage costs. They do not know how to economize, how much data they have, or where it resides. By gaining a thorough understanding of data and its needs, IT can place high-priority data on top-performing storage while moving older, less important data to cheaper storage. The point is that if you don’t efficiently manage data over its lifecycle, both options will be expensive. Six Ways to Cut Storage Costs and Optimize Cloud Investments Get holistic visibility on data to make the best cloud decisions. Understanding the characteristics of enterprise data—which is primarily file or object data not sitting in a database—is critical to optimizing cloud investments and right-place data. Top metrics include top data owners, most common file type, most common file size, total data, data growth rate, and data by time of last access (which indicates active or hot data versus inactive or cold data). Metadata searches can also highlight files containing PII, IP, or other sensitive data that have unique storage and security requirements. Calculate current storage costs across all storage technologies in your data centers and/or the cloud. Since most organizations have a hybrid cloud approach, you need to calculate the cost of both on-premises storage and backups as well as cloud storage. Calculating this across various accounts, buckets, and storage silos can be time-consuming and laborious. Look for automated ways to deliver these costs, such as through a data management solution. Predict future storage costs based on data growth rates. Unstructured data typically grows at 20% or more each year, so when looking at how much you can save, consider current costs and future projections. An ongoing data management strategy is needed to save costs as data continues to pile up. Include backup and disaster recovery costs in your analysis. Even in the cloud, most organizations create additional data copies for backups, snapshots, and multi-site redundancy. Be sure to include these costs in your analysis to get the full understanding of your true costs and potential savings. Model new storage plans for savings opportunities. Your data management analysis should detail how much you can save by leveraging the various cloud storage tiers and right-placing cold data at the appropriate lower tier. In most clouds, the cheaper storage tiers are often 20x less expensive than the performance tiers. Create an ongoing data lifecycle management plan. Rather than moving data to the cloud in a “set and forget” fashion, long-term savings require continuous refinement to accommodate data as it ages or when other conditions materialize, such as the need to move data under compliance rules to secure archival storage. With more than 12 classes of storage on some of the popular clouds, you’ll want to leverage them all at the right time. Don’t keep data in top-tier file storage once it is no longer in active use, such as at the completion of an analytics project or marketing campaign. Ensure that users can access tiered data from the lower storage tier without having to bring it back to a more expensive tier so that you don’t lose the savings. A Final Word on Cloud Storage As organizations look to reduce cloud waste this year, attaining a data-centric perspective has multitude of benefits. Analysis can indicate data growth rates, hot versus cold data, compliant data, and more so that IT can make the best decisions balancing data requirements, business needs, and budget. This way, you can continue to embrace the cloud for digital business initiatives without starting alarm bells in the CFO’s office. source

Decades ago, the alcohol industry launched its ubiquitous “Drink responsibly” marketing campaign. In 2024, it’s time to “AI responsibly” in marketing technology (martech). There are parallels between drinking and using generative AI (genAI): People often start because others are trying it; it might make things look more appealing; and you could embarrass yourself if you’ve had too much. Now is the perfect time to be methodical with genAI. Despite the hype, genAI in martech is still in its relative early stages. Last year, we envisioned the evolution of genAI use cases in martech playing out in multiple stages over time:   This is still an accurate picture of where we are today. Marketers are still dabbling in creative design, with only limited adoption for the analytics, insights, and operational assistants identified in the midterm. So this month, we published two research pieces to help marketers “AI responsibly” when planning for and incorporating new genAI capabilities into their martech ecosystems. Incorporating these learnings and resources should help marketers move past early-stage adoption stagnation. 1. Prioritizing GenAI Use Cases In Martech The B2C Martech AI Use Cases Planning Tool provides definitions for 26 martech use cases and helps marketers define the scope of their genAI adoption. The interactive tool allows marketers to select which use cases are in current use vs. prioritizing which go on the martech roadmap. The most common use cases today are content generation as well as natural language interfaces and application assistants within tools. Forrester also offers a B2B Revenue Technology Use Case Template, which can be used as a guide for creating outcome-focused use cases to gain buy-in for AI and other technology requests. 2. Operationalizing GenAI In Martech Shift Generative AI In Martech From Theory To Reality guides B2C and B2B marketers on genAI activation across four critical aspects: People. GenAI adoption is a group project across key stakeholders. Identify your core personas, which typically will span the marketer, IT, data scientist, and steward personas. Process. You’ll need an iterative approach to incorporating genAI. Follow five steps: ideate, forecast, prototype, prioritize, and activate. Implementation. There are multiple ways to access genAI for the many martech use cases. Consider genAI tools embedded in third-party technology, open or closed public large language models (LLMs), or building your own LLM. Measurement. Make a plan now for how you’ll measure genAI’s impact. Too many marketers lack defined metrics. They should measure both efficiency and effectiveness goals. There’s a lot to consider with genAI and martech, so let’s continue the conversation. Schedule a guidance session or inquiry with Katie Linford, Joe Stanhope, Rusty Warner, or Jessica Liu. source

When Apple’s version of AI, branded as Apple Intelligence, rolls out in October to folks with the company’s latest hardware, the response is likely to be a mix of delight and disappointment. The AI capabilities on their way to Apple’s walled-garden will bring helpful new features, such as textual summaries in email, Messages and Safari; image creation; and a more context-aware version of Siri. But as Apple Intelligence’s beta testing has already made clear, the power of these features falls well below what is on offer from major players like OpenAI, Google and Meta. Apple AI won’t come close to the quality of document summary, image or audio generation easily accessed from any of the frontier models. But Apple Intelligence will do something none of the flagship offerings can do: change perceptions of AI and its role in ordinary life for a large portion of users around the world. The real impact of Apple AI won’t be practical but moral. It will normalize AI, make it seem less foreign or complex. It will de-associate AI from the idea of cheating or cutting corners. It will help a critical mass of users cross a threshold of doubt or mystification about AI to forge a level of comfort and acceptance of it, even a degree of reliance. Overcoming early doubts Generative AI has faced two problems since ChatGPT was unveiled in 2022. Many have wondered what it’s really for or whether it’s truly useful, given hallucinations and other issues that are rooted in training data. Others have doubted the ethics of using AI, seeing it as a form of cheating or copyright infringement. But as we have learned in recent months, language models are most effective when they work on our own documents and data, as with platforms like NotebookLM or GPT4o, which can now handle upwards of 50 to 100 books’ worth of material we upload. Customers at the Apple Store on 5th Ave. in New York on Sept. 20, 2024. (AP Photo/Ted Shaffrey) The output of the prompts we run — in the form of article or lecture summaries, reports, slide decks and even podcasts — is much more accurate and useful than what came out of earlier chatbots. Apple Intelligence capitalizes on this insight by pointing most of its AI functionality at user data, rather than data on the web. Domesticating AI With Apple Intelligence working mainly on our own data, much of its output will likely mirror the higher quality of output we’re seeing with tools like NotebookLM — compared to AI that works mainly on large bodies of anonymous training data, like ChatGPT in its early days. Having AI work mostly on user data — and doing it frequently — will forge a new association in people’s minds between generative AI and personal information, rather than miscellaneous training data. It will likely cause us to see AI as something integral to our personal routines, like reading email or the morning news. This, in turn, will make using more powerful tools like GPT4o or Claude more socially and ethically acceptable. Once we’re in the habit of using AI to summarize or edit our email, condense articles on the web into pithy summaries or edit images in Photos, we’ll think less about the propriety of using NotebookLM to prepare a first draft of a memo or report, or using Dall-E to create images. ‘AI for the rest of us’ Apple has a long history of making complex technologies more accessible to everyday users, and that is their goal for AI. When word processors first appeared in the late 1970s and early 1980s, there was similar uncertainty about the propriety of using them to help us write things — a belief that something authentic or human about writing by hand would be lost. Read more: Think tech killed penmanship? Messy handwriting was a problem centuries before smartphones For many, computers themselves were too daunting to embrace. But Apple’s Macintosh personal computer helped domesticate and normalize using computers to write with its graphic user interface and WYSIWYG feature (“what you see is what you get”). Eventually, writing would become so closely associated with word processing that we find it hard to imagine the one without the other. Former Apple CEO Steven P. Jobs, left and President John Sculley presenting the new Macintosh Desktop Computer in January 1984 at a shareholder meeting in Cupertino, Calif. (AP Photo) Apple Intelligence could do for generative AI what the Mac or graphic user interface did for personal computers: help tame it, and make it seem ordinary and acceptable. Apple’s marketing team hints at this in their tagline for Apple Intelligence, “AI for the rest of us.” If history is any guide, Apple will play a key role in changing how we think about AI. Doing many of our basic tasks without it may soon seem unthinkable. source

This summer, the Federal Bureau of Investigation (FBI), Cybersecurity and Infrastructure Security Agency (CISA), and the Department of Defense Cyber Crime Center (DC3) released a joint advisory on Iran-based threat actors and their role in ransomware attacks on organizations in the US and other countries around the globe.   With the US presidential election coming to a close, nation state activity from Iran could escalate. In August, Iranian hackers compromised Donald Trump’s presidential campaign. They leaked compromised information and sent stolen documents to people involved in Joe Biden’s campaign, CNN reports.   What are some of the major threat groups associated with Iran, and what do cybersecurity stakeholders need to know about them as they continue to target US organizations and politics?   Threat Groups  A number of advanced persistent threat (APT) groups are affiliated with the Islamic Revolutionary Guard Corps (IRGC), a branch of the Iranian armed forces. “[Other] relatively skilled cyber threat actor groups … maintain arm’s distance length from the Iranian government,” says Scott Small, director of cyber threat intelligence at Tidal Cyber, a threat-informed defense company. “But they’re … operating pretty clearly on behalf [of] or aligned with the objectives of the Iranian government.”   Related:2024 Cyber Resilience Strategy Report: CISOs Battle Attacks, Disasters, AI … and Dust These objectives could be espionage and information collection or simply disruption. Hack-and-leak campaigns, as well as wiper campaigns, can be the result of Iranian threat actor activity.  And as the recent joint advisory warns, these groups can leverage relationships with major ransomware groups to achieve their ends.   “Look at the relationships [of] a group like Pioneer Kitten/Fox Kitten. They’re partnering and collaborating with some of the world’s leading ransomware groups,” says Small. “These are extremely destructive malware that have been extremely successful in recent years at disrupting systems.”  The joint advisory highlights Pioneer Kitten, which is also known by such names as Fox Kitten, Lemon Sandstorm, Parisite, RUBIDIUM, and UNC757, among others. The FBI has observed these Iranian cyber actors coordinating with groups like ALPHV (also known as BlackCat), Ransomhouse, and NoEscape. “The FBI assesses these actors do not disclose their Iran-based location to their ransomware affiliate contacts and are intentionally vague as to their nationality and origin,” according to the joint advisory.   Many other threat groups affiliated with Iran have caught the attention of the cybersecurity community. In 2023, Microsoft observed Peach Sandstorm (also tracked as APT33, Elfin, Holmium, and Refined Kitten) attempting to deliver backdoors to organizations in the military-industrial sector.   Related:Juliet Okafor Highlights Ways to Maintain Cyber Resiliency MuddyWater, operating as part of Iran’s Ministry of Intelligence and Security (MOIS), has targeted government and private sector organizations in the oil, defense, and telecommunications sectors.   TTPs   The tactics, techniques, and procedures (TTPs) leveraged by Iranian threat actor groups are diverse. Tidal Cyber tracks many of the major threat actors; it has an Iran Cyber Threat Resource Center. Small found the top 10 groups his company tracks were associated with approximately 200 of the MITRE ATT&CK techniques.   “Certainly, this is just one data set of known TTPs, but just 10 groups being associated with about a third of well-known TTPs, it just demonstrates … the breadth of techniques and methods used by these groups,” he says.   The two main avenues of compromise are social engineering and exploitation of unpatched vulnerabilities, according to Mark Bowling, chief information, security, and risk officer at ExtraHop, a cloud-native cybersecurity solutions company.   Social engineering conducted via tactics like phishing and smishing can lead to compromised credentials that grant threat actors system access, which can be leveraged for espionage and ransomware attacks.   Related:Beyond the Election: The Long Cybersecurity Fight vs Bad Actors Charming Kitten (aka CharmingCypress, Mint Sandstorm, and APT42), for example, leveraged a fake webinar to ensnare its victims, policy experts in the US, Europe, and Middle East.   Unpatched vulnerabilities, whether directly within an organization’s systems or its larger supply chain, can also be a useful tool for threat actors.   “They find that vulnerability and if that vulnerability has not been patched quickly, probably within a week, an exploit will be created,” says Bowling.  The joint advisory listed several CVEs that Iranian cyber actors leverage to gain initial access. Patches are available, but the advisory warns those will not be enough to mitigate the threat if actors have already gained access to vulnerable systems.   Potential Victims   Who are the potential targets of ongoing cyber campaigns of Iran-based threat actors? The joint advisory highlighted defense, education, finance, health care, and government as sectors targeted by Iran-based cyber actors.   “What is … the case with a lot of nation-state-sponsored threat activity right now, it’s … targeting a little bit of anyone and everyone,” says Small.   As the countdown to the presidential election grows shorter, threat actors could be actively carrying out influence campaigns. This kind of activity is not novel. In 2020, two Iranian nationals posed as members of the far-right militant group the Proud Boys as a part of a voter intimidation and influence campaign. Leading up to the 2024 election, we have already seen the hack and leak attack on the Trump campaign.     Other entities could also fall prey to Iranian threat actor groups looking to spread misinformation or to simply create confusion. “It’s possible that they may target government facilities, state or local government, just to add more chaos to this already divided general election,” says JP Castellanos, director of threat intelligence for Binary Defense, a managed detection and response company.   Vulnerable operational technology (OT) devices have also been in the crosshairs of IRGC-sponsored actors. At the end of 2023, CISA, along with several other government agencies, released an advisory warning of cyber activity targeting OT devices commonly used in water and wastewater systems facilities.   In 2023, CyberAv3ngers, an IRGC-affiliated group, hacked an Israeli-made Unitronics system at a municipal water authority in Pennsylvania. In the wake of the attack, screens at the facility read: “You Have Been Hacked. Down With Israel, Every Equipment ‘Made In Israel’ Is CyberAv3ngers Legal Target.”  The water authority booster station

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A common criticism of big tech is that their platforms treat users as little more than glassy eyeballs to be monetized with targeted ads. This will soon change, but not because tech platforms are moving away from aggressively targeting users. Instead, our ears are about to become the most efficient channel for hammering us with AI-powered influence that is responsive to the world around us. Welcome to the Whisperverse.    Within the next few years, an AI-powered voice will burrow into your ears and take up residence inside your head. It will do this by whispering guidance to you throughout your day, reminding you to pick up your dry cleaning as you walk down the street, helping you find your parked car in a stadium lot and prompting you with the name of a coworker you pass in the hall. It may even coach you as you hold conversations with friends and coworkers, or when out on dates, give you interesting things to say that make you seem smarter, funnier and more charming than you really are. These will feel like superpowers. The ‘Whisperverse’ will require highly advanced technology Of course, you won’t be the only one “augmented” with context-aware AI guidance. Everyone else will have similar abilities. This will create an arms race among the public to embrace the latest AI-powered enhancements. It will not feel like a choice, because not having these capabilities will put you at a cognitive disadvantage. This is the future of mobile computing. It will transform the bricks we carry around into body-worn devices that see and hear our surroundings and covertly offer useful information and friendly reminders at every turn. Most of these devices will be deployed as AI-powered glasses because that form-factor gives the best vantage point for cameras to monitor our field of view, although camera-enabled earbuds will be available too. The other benefit of glasses is that they can be enhanced to display visual content, enabling the AI to provide silent assistance as text, images, and realistic immersive elements that are integrated spatially into our world. Also, sensored glasses and earbuds will allow us to respond silently to our AI assistants with simple head nod gestures of agreement or rejection, as we naturally do with other people.   This future is the result of two technologies maturing and merging into one — AI and augmented reality. Their combination will enable AI assistants to ride shotgun in our lives, observing our world and giving us advice that is so useful, we will quickly feel like we can’t live without it. Of course there are serious privacy concerns, not to mention the risk of AI-powered persuasion and manipulation, but what choice will we have? When big tech starts selling superpowers, to not have these abilities will mean being at a disadvantage socially, professionally, intellectually and economically. ‘Augmented mentality’ changing our lives I’ve been writing about our augmented future for more than 30 years, first as a researcher at Stanford, NASA and the U.S. Air Force, and then as a professor and entrepreneur. When I first started working in the field we now call “augmented reality,” that phrase didn’t exist, so I described the concept as “perceptual overlays” and showed for the first time that AR could significantly enhance human abilities. These days, there is a similar lack of words to describe the AI-powered entities that will sit on our shoulders and coach us through our day. I often refer to this emerging branch of computing as “augmented mentality” because it will change how we think, feel and act.    Whatever we end up calling this new field, it is coming soon and it will mediate our lives, assisting us at work, at school or even when grabbing a late-night snack in the privacy of our own kitchen. If you are skeptical, you’ve not been tracking the massive investment and rapid progress made by Meta on this front and the arms race they are stoking with Apple, Google, Samsung and other major players in the mobile market. It is increasingly clear that by 2027, this will become a major battleground in the mobile device industry. The first of these devices is already on the market — the AI-powered Ray-Bans from Meta. Although currently a niche product, I believe it is the single most important mobile device being sold today. That’s because it follows the new paradigm that will soon define mobile computing: Context aware guidance. To enable this, the Meta Ray-Bans have onboard cameras and mics that feed a powerful AI engine and pumps verbal guidance into your ears. At Meta Connect in September, the company showcased new consumer-focused features for these glasses, such as helping users find their parked cars, translating languages in real-time and naturally answering questions about things you see in front of you. ‘Cute’ creatures rather than ‘creepy’ ones Of course, the Meta Ray-Bans are just a first step. The next step is to visually enhance your experience as you navigate your world. Also in September, Meta unveiled their prototype Orion glasses that deliver high quality visual content in a form factor that is finally reasonable to wear in public. The Orion device is not planned for commercial deployment, but it paves the way for consumer versions to follow. So, where is this all headed? By the early 2030’s, I predict the convergence of AI and augmented reality will be sufficiently refined that AI assistants will appear as photorealistic avatars that are embodied within our field of view. No, I don’t believe they will be displayed as human-sized virtual assistants who follow us around all day.  That would be creepy. Instead, I predict they will be rendered as cute little creatures that fly out in front of us, guiding us and informing us within our surroundings. Back in 2020, I wrote a short story (Carbon Dating) for a sci-fi anthology in which I refer to these AI assistants as

新地新城市廣場今年正式邁進40周年，特別舉辦為期兩個月的《沙田新城市同心同行40載》慶祝活動，一同締造40周年盛典及聖誕節慶活動，以答謝市民一直的支持，並為社區注入歡樂節日氣氛。為隆重其事，新城市廣場將於11月16日晚上8:30舉行《冬日閃亮花火祭》，一場全城矚目、歷時8分鐘的幻彩煙火匯演即將上演，為香港市民及沙田區居民呈獻獨一無二的盛事體驗！屆時，2,024枚璀璨煙火將首度於沙田市中心上空綻放。 市民及旅客身處在商場的所有戶外空間，或位處附近地區，均可欣賞到精彩奪目的煙火匯演，配合華麗燈飾及悠揚音樂，普天同慶! 當日商場更舉辦盛大狂歡嘉年華，邀請全城市民一同慶祝商場40周年的大日子！ 「夢幻聖誕國度」當晚同步亮燈  新城市廣場趁著聖誕佳節將至，更為市民匠心打造「夢幻聖誕國度」，亮燈儀式將於11月16日當晚同步舉行，整項節日主題活動將集合多元節慶元素，包括設置13米高巨型聖誕樹及二千呎室內飄雪溜冰場等，讓市民歡度聖誕。 當日中午12時起，場内會舉辦盛大狂歡嘉年華，與眾同樂，包括全日無間街頭音樂表演、臉部彩繪、魔術及小丑表演等，大派40周年主題氣球、棉花糖及爆谷，更會聯同Play Park商戶於商場一樓舉行創意工作坊，邀請市民一起製作40周年生日手作，大家在商場每個角落也能感受熾熱的喜慶氣氛。 同時，新城市廣場亦攜手場內過百家商店，特別為40周年誌慶推出逾300項低至2折的購物優惠，與全港市民一同開心迎接40周年。 LinkedIn Email Facebook Twitter WhatsApp source

As the automotive industry embraces the era of connectivity, telemetry data has emerged as a game changer for original equipment manufacturers (OEMs). While the technological complexity of telemetry data adds new challenges, such as ensuring data security and compliance with regulations, it also unlocks trillions of dollars in potential for manufacturers, with the promise of improving customer experiences, enhancing vehicle performance, and generating new revenue streams. However, despite the transformative potential of connected vehicle data, the industry continues to struggle in meeting driver expectations for personalized experiences and enhanced service offerings. To stay competitive, OEMs must integrate data from all sources—vehicles, drivers, services, and retail—to deliver tailored experiences and offers. The key to unlocking these opportunities lies in a comprehensive data strategy. 1. Initial assessment and evaluation The first step in unlocking the value of telemetry data for OEMs is to conduct a thorough strategic assessment of both risks and benefits. This assessment must prioritize regulatory compliance, ensuring that data collection practices align with local and global standards. Additionally, public perception plays a pivotal role; OEMs must build trust with customers by being transparent about how their data is collected and used. Any gaps in this process should be identified and addressed. Ethical concerns, such as data privacy and security, should also be top of mind, and any deficiencies should be noted during the evaluation stage, as mishandling these areas can lead to reputational damage and legal risks. Once these foundations are in place, the next step is to evaluate the maturity of telemetry data. This evaluation helps OEMs identify redundancies, address scalability challenges, and assess the feasibility of various use cases. 2. Connected data strategy and management After the initial assessment, OEMs must ensure appropriate data infrastructure and develop a comprehensive data strategy that aligns with their business goals. This step involves outlining low-risk, high-benefit use cases within the limits of the current infrastructure. Working with telemetry data requires a lifecycle approach that encompasses data strategy, data architecture, data engineering, and operations to ensure maximum value is derived from the data. A comprehensive governance framework includes key elements such as data risk management, data discoverability, and data trustworthiness. These components cover critical processes like consent management, compliance, data lineage, and privacy. By implementing these measures, OEMs can ensure not only compliance but also build long-term trust with their customers. 3. Strategic use case development for OEMs A focused approach to use case development is essential for accelerating time-to-value. By prioritizing high-impact use cases, OEMs can not only extract valuable insights from telemetry data but also ensure that future applications can be seamlessly integrated as technology and customer needs evolve. OEMs can explore key use cases in the following areas: Customer experience and safety: Telemetry data can significantly enhance both safety and convenience for drivers. Proactive maintenance alerts, real-time driver behavior analysis, and fatigue detection features can help prevent accidents and reduce vehicle downtime.  These proactive insights not only improve the overall driving experience but also create a deeper connection between the customer and the brand. Dealership enablement: Sharing telemetry data with dealerships transforms aftersales services. Dealerships can use real-time data for remote diagnostics, offering personalized service bundles tailored to individual driving habits, or optimizing used car valuations based on actual vehicle performance. Data monetization: The commercial opportunities from connected vehicles are vast. OEMs can establish partnerships with insurers to develop usage-based insurance (UBI) models, where drivers are charged based on their driving behavior. Other potential partnerships include sharing real-time traffic data with navigation providers or working with urban planners to provide insights into traffic flow and infrastructure needs. However, transparency is key—OEMs must clearly communicate who is receiving the data, how it’s being used, and for what purpose. Conclusion: A roadmap for success As the automotive industry undergoes a profound transformation driven by connectivity and telematics, OEMs stand at the forefront of unlocking unprecedented value from telemetry data. To effectively navigate this evolving landscape, OEMs should invest in infrastructure to build scalable and secure data architecture that supports the increasing volume and complexity of telemetry data. Furthermore, OEMs must embrace continuous improvement by regularly evaluating and refining data governance frameworks to ensure compliance with regulations and adapt to changing consumer expectations. Actively exploring and prioritizing innovative use cases that leverage telemetry data will allow OEMs to deliver personalized services and enhance vehicle performance. By taking these proactive steps, OEMs can meet the challenges posed by connected vehicles and lead the charge in shaping a safer, more efficient, and more customer-centric automotive future. The time to act is now embracing the potential of telemetry data will define the next era of automotive excellence. To learn more, visit us here. Nekhil Agrawal is analytics practice lead for the media and manufacturing practice at EXL, a leading data-and AI-led services, digital operations, and solutions company.  source