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Marketing campaign templates help you add structure and clarity to upcoming campaigns. They can also help ensure each campaign aligns with big-picture goals and contains a full plan on how to execute, track, and measure everything. Some campaigns are quick one-off emails while others last weeks or months and encompass multiple marketing channels. This post covers the best free templates for various tools and situations, from complex campaigns using project management tools to simpler approaches using a spreadsheet. monday.com: Manage campaigns, projects, and tasks in one Monday.com is a great project management tool that lets you plan campaigns and manage all of the work in the same place. You can even use it to track other types of projects, your budget, digital assets, content, and more. With built-in project management features, you’ll be able to easily create tasks, assign ownership to your team, and stay on top of everything. More monday.com coverage: monday.com Review | Trello vs monday.com | Asana vs monday.com.  monday.com makes it easy to plan, track, and execute campaigns alongside other types of projects in one platform. Image: monday.com One of the more unique aspects of this marketing campaign template is that you can import campaigns you’ve started in a spreadsheet. This makes it a great option if you’ve previously managed everything in Excel or Google Sheets and want an upgrade. The template also includes a timeline view for each campaign, automations that move tasks through the workflow, and team collaboration features — commenting, @ mentions, and prioritization capabilities to name a few. One of the biggest benefits is that you can use it to manage multiple campaigns. There are a few different ways you can set it up and you can add additional trackers in the same tool, giving you ultimate flexibility if you’re willing to customize a bit on your own. ClickUp: A high-volume marketing campaign template ClickUp also checks all the boxes for campaign planning and execution within a project management solution. It offers one of the most generous free plans with up to five spaces, unlimited users, and unlimited tasks. Beyond the free plan, it becomes more and more similar to monday.com. Both are just as capable of campaign management scale — many people use personal preference to decide between the two. More ClickUp coverage: ClickUp review | Asana vs ClickUp | ClickUp vs Notion.  You can use this ClickUp template to plan and manage all of your campaigns simultaneously. Image: clickup.com Although ClickUp will work just fine for simple campaign management, this template is more advanced, and better suited for planning and execution at scale. It’s not difficult to use but it does have a lot of functionality built in, allowing for easy management of dozens of concurrent campaigns and projects across an entire marketing department. The template comes with seven project views, 11 custom fields, built-in budget tracking, and automated task dependency warnings. Once you copy the template into your account, you’ll be able to define channel-specific objectives, map out entire campaigns, assign them to teams or individuals, set deadlings, and prioritize work however you’d like. But the best part is that you can track progress against one campaign, several campaigns, or all of them at once. Asana: A marketing campaign template for smaller teams Asana is another all-in-one project management software. It’s not as flexible or intimidating as the others we’ve covered so far, making it a better choice for smaller teams that need something a bit easier to use. Its free plan allows for up to 10 users and includes unlimited tasks, projects, storage, and team messages. It’s very generous and more than enough to get started. More Asana coverage: Asana review | Airtable vs Asana | Asana alternatives.  Watch your marketing strategy play out in real-time with Asana’s campaign management template. Image: asana.com The campaign management template from Asana has one of the best timeline views we’ve seen. It’s super clean, yet has all of the information you need for planning and tracking progress along the way. It’s one of the best ways to visualize the path and dependencies of different campaigns, tasks, and activities working towards the same goal. Beyond that, you’ll also be able to see all of the work in Kanban Gantt, calendar, and list view. Everyone can view their tasks in whatever way works best for them. Managers and supervisors can also create milestones to break goals into smaller objectives. One of the more unique capabilities is turning a brief into action items. You can easily turn everything into a task and assign it to the right person. Even though this template’s great for smaller teams, it’s just as good for those that are growing and those that are larger so you don’t have to worry about needing something else in the near future. Notion: A template for marketing campaign briefs Notion is a productivity platform that includes project management capabilities on top of a ton of other functionality. It’s a free-form place to take notes, manage to-do lists, create documents, assign work, and more. It requires a bit of work up front before you can use it. But templates help speed up and remove barriers from that process. If you’re working by yourself, Notion’s free plan is very generous — you’ll likely be able to use it for quite some time and possibly forever. Teams can try Notion for free but will need to upgrade to a paid plan at some point. More Notion coverage: Notion review | Obsidian vs Notion | Notion vs monday.com.  Use Notion’s campaign brief template to plan out your next campaign and ensure it aligns with your goals. Image: notion.com The foundation of every great marketing campaign is a detailed plan and strategy. Despite that, many businesses just start and end up feeling lost — I’ve definitely experienced this with my team. This Notion template comes with everything you need to lay that foundation early. Once you’ve created your own copy, you’ll be able to identify key

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia revealed new AI and simulation tools that will advance robot learning and humanoid development. The world’s biggest tech company by valuation (worth $3.432 trillion) said that the tools will enable robotics developers to greatly accelerate their work on AI-enabled robots, with tools revealed this week at the Conference for Robot Learning (CoRL) in Munich, Germany. The lineup includes the general availability of the Nvidia Isaac Lab robot learning framework; six new humanoid robot learning workflows for Project GR00T, an initiative to accelerate humanoid robot development; and new world-model development tools for video data curation and processing, including the Nvidia Cosmos tokenizer and Nvidia NeMo Curator for video processing. The open-source Cosmos tokenizer provides robotics developers superior visual tokenization by breaking down images and videos into high-quality tokens with exceptionally high compression rates. It runs up to 12 times faster than current tokenizers, while NeMo Curator provides video processing curation up to seven times faster than unoptimized pipelines. Also timed with CoRL, Nvidia released 23 papers and presented nine workshops related to robot learning, and also released training and workflow guides for developers. Further, Hugging Face and Nvidia announced they’re collaborating to accelerate open-source robotics research with LeRobot, Nvidia Isaac Lab and Nvidia Jetson for the developer community. Accelerating robot development with Isaac Lab Nvidia Isaac Lab Project GR00T Models Nvidia Isaac Lab is an open-source, robot learning framework built on Nvidia Omniverse, a platform for developing OpenUSD applications for industrial digitalization and physical AI simulation. Developers can use Isaac Lab to train robot policies at scale. This open-source unified robot learning framework applies to any embodiment — from humanoids to quadrupeds and collaborative robots — to handle increasingly complex movements and interactions. Leading commercial robot makers, robotics application developers, and robotics research entities around the world are adopting Isaac Lab, including 1X, Agility Robotics, The AI Institute, Berkeley Humanoid, Boston Dynamics, Field AI, Fourier, Galbot, Mentee Robotics, Skild AI, Swiss-Mile, Unitree Robotics, and Xpeng Robotics. Project GR00T: Foundations for general-purpose humanoid robots The humanoids are coming. Building advanced humanoids is extremely difficult, demanding multilayer technological and interdisciplinary approaches to make the robots perceive, move and learn skills effectively for human-robot and robot-environment interactions. Project GR00T is an initiative to develop accelerated libraries, foundation models and data pipelines to accelerate the global humanoid robot developer ecosystem. Six new Project GR00T workflows provide humanoid developers with blueprints to realize the most challenging humanoid robot capabilities. They include things such as GR00T-Gen for building generative AI-powered, OpenUSD-based 3D environments and more. “Humanoid robots are the next wave of embodied AI,” said Jim Fan, senior research manager of embodied AI at Nvidia, in a statement. “Nvidia research and engineering teams are collaborating across the company and our developer ecosystem to build Project GR00T to help advance the progress and development of global humanoid robot developers.” Today, robot developers are building world models — AI representations of the world that can predict how objects and environments respond to a robot’s actions. Building these world models is incredibly compute- and data-intensive with models requiring thousands of hours of real-world, curated image or video data. Nvidia Cosmos tokenizers provide efficient, high-quality encoding and decoding to simplify the development of these world models. They set a new standard of minimal distortion and temporal instability, enabling high-quality video and image reconstructions. Providing high-quality compression and up to 12 times faster visual reconstruction, the Cosmos tokenizer paves the path for scalable, robust and efficient development of generative applications across a broad spectrum of visual domains. 1X, a humanoid robot company, has updated the 1X World Model Challenge dataset to use the Cosmos tokenizer. “Nvidia Cosmos tokenizer achieves really high temporal and spatial compression of our data while still retaining visual fidelity,” said Eric Jang, vice president of AI at 1X Technologies, in a statement. “This allows us to train world models with long horizon video generation in an even more compute-efficient manner.” Other humanoid and general purpose robot developers including Xpeng Robotics and Hillbot are developing with the Nvidia Cosmos tokenizer to manage high-resolution images and videos. NeMo Curator NeMo Curator now includes a video processing pipeline. This enables robot developers to improve their world-model accuracy processing large-scale text, image and video data. Curating video data poses challenges due to its massive size, requiring scalable pipelines and efficient orchestration for load balancing across GPUs. Additionally, models for filtering, captioning and embedding need optimization to maximize throughput. NeMo Curator overcomes these challenges by streamlining data curation with automatic pipeline orchestration, reducing processing time significantly. It supports linear scaling across multi-node multi-GPU systems, efficiently handling over 100 petabytes of data. This simplifies AI development, reduces costs and accelerates time to market. Availability Nvidia Isaac Lab 1.2 is available now and is open source on GitHub. Nvidia Cosmos tokenizer is available now on GitHub and Hugging Face. NeMo Curator for video processing will be available at the end of the month. The new Nvidia Project GR00T workflows are coming soon to help robot companies build humanoid robot capabilities with greater ease. For researchers and developers learning to use Isaac Lab, new getting started developer guides and tutorials are now available, including an Isaac Gym to Isaac Lab migration guide. source

No technology in history has achieved an adoption curve that rivals generative AI (GenAI). Already, organizations use it for everything from chatbots and content creation to product design and software development. The technology boosts efficiency, trims costs, and unlocks innovation.  Yet for all the gains there’s still a good deal of pain. Too often, generative AI systems do not recognize basic facts and information that humans take for granted. For example, they might misinterpret or misclassify events and produce flawed output, struggle to generate desired content, or fall short on more complex tasks that require a combination of text, audio, and video.   That’s where multimodal AI enters the equation. “Multimodal AI models are trained with multiple types of data simultaneously, such as images, video, audio, and text. This enables them to create a shared data representation that improves performance for different tasks,” explains Arun Chandrasekaran, distinguished VP and analyst for artificial intelligence at Gartner.  Adds Scott Likens, US and global chief AI engineering officer at PwC: “Multimodal AI can tackle more complex challenges, create more personalized experiences, and help companies adapt more effectively. It’s about versatility and deeper insights, which are crucial to staying ahead.”  Related:IT Pros Love, Fear, and Revere AI: The 2024 State of AI Report Multimodal AI potentially touches chatbots, data analytics, robotics, and numerous other areas. According to research conducted by Gartner, only about 1% of companies were using the technology in 2023 but the figure is projected to jump to 40% by 2027. The technology will have a “transformational” impact on the business world, Gartner reports. “It enables use cases that previously weren’t possible,” Chandrasekaran says.  AI Comes to its Senses  What makes multimodal AI so appealing — and powerful — is its ability for AI to act more like a human being because it understands the world better. “Traditional machine learning uses a specific training set to predict output,” states Matthew Kropp, a partner and managing director at Boston Consulting Group. “Later, you look for ways to adjust the weights in the model. Multimodal AI expands the training data in the pursuit of more realistic results.”  PwC’s Likens compares multimodal AI to the human ability to multitask. “You can ask a question via audio and receive a written response or submit an image and then ask questions about it. The interoperability between mediums is seamless. For business leaders, that means making smarter decisions faster. You’re not just looking at text or just an image; you’re seeing the whole picture,” he says.  Related:Keynote Sneak Peek: Forrester Analyst Details Align by Design and AI Explainability The result is systems that are far better aligned to handle real world tasks — and tools that create more personalized experiences and deeper insights. For example, a chatbot might handle both text and images. This makes it possible for a user to describe a problem in words but also upload a photo of a broken product. A multimodal AI system might also understand video content and seamlessly extract cues that provide context — and answers.  The results can be impressive. Multimodal systems can introduce visual question-answering and even complex audio and video generation, Chandrasekaran explains. This includes creating AI podcasts and instructional materials. Organizations also are better equipped to tune into market and consumer sentiment through various types of data.  Over the next few years, the range of multimodal inputs will increase beyond text, images, and video, Chandrasekaran says. Systems are likely to incorporate a greater range of audio data, sensor and IoT data, log files, code snippets and more. This will boost the accuracy, contextual awareness, and overall utility of chatbots, robots, diagnostics systems, and predictive maintenance tools.  Related:Sidney Madison Prescott Discusses GenAI’s Potential to Transform Enterprise Operations Evolving Beyond the Bot  Multimodal models come with a major caveat: Stringing together a mélange of unimodal data models is not the same as constructing a purpose-built multimodal framework. “Multimodal data must be aligned and integrated. It is more complex because it has varying degrees of quality and comes in different formats than unimodal data,” Chandrasekaran explains.  Specific tools that aid in building multimodal frameworks are evolving rapidly. Cloud platforms AWS, Google, and Azure have introduced multimodal features into their toolkits. Pre-trained models like OpenAI’s CLIP (Contrastive Language-Image Pretraining) and BERT (Bidirectional Encoder Representations from Transformers) have appeared. And multimodal libraries and tools like MMDet (Multimodal Detection) and Hugging Face Transformers tie together diverse data sets.  CIOs and IT teams must take a hands-on approach to multimodal AI. An effective framework must fit an organization’s specific data and objectives, and data must be clean and clearly labeled. There’s also a need to address business risks that include data bias, privacy concerns, fairness standards, copyright concerns, and overall data accuracy. This requires appropriate training and evaluation techniques like cross-validation and accuracy metrics.  “Because multimodal AI involves diverse inputs — text, images, audio, and video — maintaining consistent data quality is key,” Likens notes. “Privacy concerns are equally critical, because multimodal data can reveal unintended patterns.” It’s also critical to keep humans in the loop. “Investing in responsible AI from the start helps companies manage risks, build trust, and stay ahead of government regulations,” he argues.  For now, organizations can benefit by reviewing applications, tools, and partners, Kropp says. This includes using open-source models and tools that help lower the entry barrier and reduce risks associated with major IT commitments. “Matching the model and the vendor with your desired use case is important. Different combinations result in different and potentially better results,” he notes.  Structural changes may also be in order, Chandrasekaran says. Among his suggestions? “Educate your AI team on multimodality, including the benefits and risks. Break up AI technical silos by encouraging AI experts to work on projects outside their area of technical specialization, such as natural language processing and computer vision. Expose AI teams to vendors that focus on multimodal models as part of the overall education process.”  Make no mistake, multimodal AI will emerge as a powerful force

（相左起）阿里雲國際業務副總裁、亞太北及東南亞大區總經理劉彬星、Red Hat香港及台灣合作夥伴主管李松鑫，以及Red Hat香港、台灣及澳門區域總經理文志鋒。 全球領先的電腦操作系統開源(open source)解決方案供應商Red Hat 宣佈「Red Hat 亞太區創新獎」香港得獎者 － 機場管理局和醫院管理局利用Red Hat解決方案以滿足不斷變化的客戶需求。 全球商業環境不斷變化，亞太區不但展現出其韌性，並且正在快速增長。憑藉其活躍的經濟活動、多元文化和龐大的消費者群，亞太區的潛力為大小企業帶來了增長機會。科技仍然是塑造商業環境其中一個關鍵因素，幫助企業拓展和創新。今年以「解鎖未來」為主題的「Red Hat亞太區創新獎」嘉許了利用開源技術驅動轉型和創新的客戶，這些客戶展示了機構如何應對基礎設施成本上升和業務需求變化的雙重挑戰。獎項還表揚了來自11個國家的31位得獎者，表現了該地區的企業如何成功利用Red Hat解決方案克服挑戰，並開創以客戶為中心的新解決方案。 根據Red Hat 2024年全球科技趨勢報告 (Red Hat 2024 Global Tech Trends)，亞太區企業的首要融資重點包括構建雲原生應用程式、改善數位使用者體驗以及加速應用程式/服務交付。 該獎項五個關鍵類別（數碼轉型、混合雲基礎設施、開發雲原生、自動化、韌性） 反映了企業應對當前商業挑戰的領域，而報告結果顯示出創新解決方案在這些方面非常重要。 得獎者憑藉有效地利用Red Hat解決方案，並為其商業目標帶來了重要貢獻而獲受嘉許。各機構均體現了開源技術所帶來的轉型潛力，如何升級業務流程、提高生產力、促進創新和增強面對挑戰的彈性。他們的成功故事進一步展示出Red Hat透過策略性部署開源解決方案，是幫助亞太區企業實現增長的關鍵角色。 LinkedIn Email Facebook Twitter WhatsApp The post 機管局和醫管局用Red Hat解決方案進行轉型和創新 appeared first on VeriMedia. source

“This is for people in the organization who have data and want to drive insights for the business and for their clients,” Beswick says. “I want to provide an easy and secure outlet that’s genuinely production-ready and scalable. The biggest challenge is data. It’s very fragmented, ownership is often unclear, quality is a variable, but we have teams really working on that and generating data faster than we can possibly catalog and clean up.” Marsh McLennan has been using ML algorithms for several years for forecasting, anomaly detection, and image recognition in claims processing. With Databricks, the firm has also begun its journey into generative AI. The company started piloting a gen AI Assistant roughly 18 months ago that is now available to 90,000 employees globally, Beswick says, noting that the assistant now runs about 2 million requests per month. Beswick is also preparing for extensive generative AI activity within the company based on Microsoft’s implementation of OpenAI, which offers security to his liking. The CIO is quick to point out that Marsh McLennan’s gen AI platform — like its development and analytics platforms — uses industry-standard products but its interface, tooling, core services, and enhanced capabilities, which go “beyond what the model can do on its own,” were built by MMTech at the company’s innovation center in Dublin, Ireland. source

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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The Department of Defense has awarded its first generative AI defense contract to Jericho Security, marking a strategic shift in military cybersecurity. The $1.8 million Small Business Technology Transfer (STTR) Phase II contract, announced through AFWERX, tasks the New York-based startup with developing advanced cybersecurity solutions for the Department of the Air Force. “This is one of the first generative AI contracts awarded in defense, marking a major milestone in how seriously our military is addressing AI-based threats,” Sage Wohns, CEO of Jericho Security, told VentureBeat in an exclusive interview How AI-powered phishing attacks target military personnel The company’s approach centers on simulating complex, multi-channel phishing attacks that mirror real-world scenarios. “In today’s landscape, phishing campaigns aren’t limited to just emails—they involve coordinated attempts across multiple platforms like text messages, phone calls, and even video calls,” Wohns explained, describing attacks that chain together multiple forms of communication to deceive targets. What sets Jericho’s technology apart is its focus on human vulnerability — widely considered the weakest link in cybersecurity. The company claims that up to 95% of data breaches stem from human error. Their platform creates personalized security training programs based on individual risk profiles, using generative AI to simulate sophisticated attacks including deepfake impersonations and AI-generated malware. Deepfake attacks and drone pilot targeting: The new frontier of military cybersecurity The contract comes at a critical time, as military personnel face increasingly targeted attacks. “There was a highly publicized spear-phishing attack targeting Air Force drone pilots using fake user manuals,” Wohns revealed, highlighting how the company helped evaluate vulnerabilities through attack simulation and specialized training. For a young company competing in the crowded cybersecurity market, landing a Defense Department contract represents a major validation. The deal positions Jericho Security to expand beyond its commercial roots into the lucrative government sector, where cybersecurity spending continues to grow amid escalating threats. Military contracts often require stringent security measures. Wohns emphasized that Jericho maintains “military-grade cybersecurity standards” including end-to-end encryption and isolated secure environments for handling sensitive military data. The next generation of AI defense: Predator and prey model Unlike traditional cybersecurity approaches that react to known threats, Jericho Security employs what Wohns calls a “predator and prey” model. “We started with attack simulation, giving us a continuous stream of real-time data to enhance both offensive and defensive capabilities,” he said. This dual approach allows their AI systems to evolve alongside emerging threats rather than merely responding to them. The Air Force contract, executed through AFWERX—the innovation arm of the Department of the Air Force—is part of a broader initiative to accelerate military adoption of private sector technology. AFWERX has awarded over 6,200 contracts worth more than $4.7 billion since 2019, working to strengthen the U.S. defense industrial base and speed up technology deployment. source

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