by Csongor Fekete | Dec 28, 2025 | AI, Business, Machine Learning
As multimodal AI systems become integral to next-gen search engines, image SEO is stepping into a pivotal role in digital marketing strategies. The recent article from Search Engine Land, “Image SEO for Multimodal AI,” highlights the increasing importance of optimizing visual content—not just for human audiences but also for AI systems that consume and interpret images alongside text.
The core takeaway is clear: traditional methods of SEO focused purely on keywords and metadata are now insufficient. Multimodal AI models, which fuse images, text, and other contextual signals, are elevating how search engines rank and present content. This evolution demands a holistic approach that considers how AI perceives and processes images. Proper file naming, alt-text accuracy, semantic relevance, and contextual alignment between visual and textual content are no longer optional—they’re strategic imperatives.
From a business perspective, this shift opens new value streams. A use-case such as developing a custom AI model to optimize product images for e-commerce platforms can significantly enhance discoverability, boost performance metrics like click-through rates, and increase customer satisfaction. Marketers leveraging AI consultancy services or AI agencies to restructure their image content strategy will gain a competitive edge in increasingly visual search environments.
By embedding AI expertise into martech stacks and focusing on improving multimodal search performance, businesses can drive more targeted traffic and ensure brand visibility in complex AI-driven discovery systems.
original article: https://news.google.com/rss/articles/CBMia0FVX3lxTFA5dWN4MnFvb3k0c2gzYjEzelI0a1lTSFNyam0zb1ZxNE5HaUYtYm0xODJoTkFLMFk0MzZ5SnNyTi1SQm03UkVjdWlYOFVrUzFaTTh6aGpQR2NLTmRFSGRPZWlScWxabnJsQ3Fr?oc=5
by Csongor Fekete | Dec 28, 2025 | AI, Business, Machine Learning
As AI continues to evolve, its intersection with SEO is reshaping how businesses approach online visibility. The article "AI & SEO: How to Prepare in 2025" from Exploding Topics underscores the urgency for marketers to adapt their strategies in anticipation of sweeping changes in search engine optimization powered by artificial intelligence.
Key highlights include Google’s increasing use of AI-powered search experiences, particularly through generative AI like the Search Generative Experience (SGE). Rather than traditional list-based results, users now see AI-generated summaries, changing the dynamics of click-through rates and organic traffic. This shift compels brands to optimize for “zero-click” exposure, focusing on concise, structured content and a presence in AI snapshots.
Additionally, the article emphasizes the importance of building topical authority and semantic relevance using machine-readable formats like schema markup, while cautioning against black-hat AI-generated content. The rise of conversational and multimodal search behavior demands that marketers meet users where they are—across voice search, video, and other rich media formats.
For a company like HolistiCrm focused on holistic marketing and martech innovation, there is immense business value in recognizing these shifts early. Developing custom AI models tailored to predict AI-generated snippet inclusion, or crafting ML-based tools to automatically evaluate semantic relevance, can enhance performance in this new SEO landscape. An AI expert or AI agency can build these models to prioritize high-satisfaction content that optimizes engagement in zero-click environments.
By embedding Machine Learning models into CRM and content strategy pipelines, businesses can future-proof their SEO while improving customer targeting and satisfaction metrics. Enterprises that leverage AI consultancy now for SEO transformation will lead the pack in 2025.
Read the original article here: https://news.google.com/rss/articles/CBMiVEFVX3lxTFBFQXBRXzBBc1pnVzhoMHNtYTJ0VXFXY01BR3p1R1BHRUVLU0tSdVoxUFFXNjUyNnlURkhsX1ZidHJXTXZ3cUxvNmhPSERmRDZoUGg0NQ?oc=5
by Csongor Fekete | Dec 27, 2025 | AI, Business, Machine Learning
Al Jazeera has unveiled a transformative AI initiative with the launch of its integrative AI engine, “The Core.” Designed to support newsroom efficiency and content personalization, The Core leverages a custom AI model to unify editorial workflows, automate metadata tagging, and boost audience targeting through real-time behavioral insights.
This development underscores a growing trend in martech where media companies invest in holistic AI strategies to enhance customer satisfaction and drive performance across content distribution. The Core stands out not only for its technical execution but also for its alignment with business outcomes like reduced production time and heightened audience engagement.
One of the key learnings from this initiative is the scalable value that tailored AI systems can bring when strategically implemented. A similar use-case within a company’s marketing function—such as building a custom Machine Learning model for dynamic customer segmentation and personalized outreach—can result in significant ROI. It enables faster campaign optimization, refined targeting, and ultimately a more loyal customer base.
For organizations exploring how custom AI models can improve content strategies, collaborating with an AI agency or AI consultancy can help identify practical applications tied to measurable KPIs. Holistic integration, like Al Jazeera’s model, ensures AI doesn't operate in silos but instead enhances cross-functional performance—from editorial to marketing.
original article: https://news.google.com/rss/articles/CBMimwFBVV95cUxQZm1NajVHV3czMGxab04yU3dkRnVKeFR0ZkVDYjFRTTN6em9xa3dXWTlrQ0N3cU5OaU0ydFRGSnpneVFXT3E0UFJSdUlBTkpsdnhEZ0JoZERkNXhIWlk0YncyNVFDQ3RoQ2hBMmNpNC12dk13a3dKalVEeHNmbjVWNDd0N2hYcnVzZ2ZsQ095ZkVwUFpZYV9Vb1Zpc9IBoAFBVV95cUxNcjZWVS1GS0lkOU1IY3NSVXBJYm56VEo1Wlg1WTRUM0FWSkJHbi01SE1GNlIzek4yN1hfNHUwTG9nQURfMnRxdW5wNGZ0UjZFdXBxR2NDaWUtRUVhT292STRqaERMQVpTQURVMmVMN3NoOHhxZHNIYnZJQ1hTcXBFWU5jRC1tQkY0eDB1QkY5LTNqQU5PbUJUd1VSY2dwaDIy?oc=5
by Csongor Fekete | Dec 27, 2025 | AI, Business, Machine Learning
The National Institute of Standards and Technology (NIST) has opened an AI Research Scientist position under its Center for Advanced Information Systems Integration (CAISI). This role addresses the growing demand to advance trustworthy AI systems, ensuring safety, transparency, and ethical standards in public sector technologies. The position is geared toward developing metrics, methods, and evaluation frameworks that support responsible and fair AI systems—aligning with the broader government objectives for secure, reliable artificial intelligence applications.
A key takeaway from this opportunity is the U.S. government’s prioritization of not just AI innovation, but the benchmarking and validation of those innovations across multi-dimensional performance indicators. This focus mirrors trends seen in the commercial and martech sectors, where companies increasingly require explainable, auditable AI systems that contribute directly to customer satisfaction.
For example, businesses working with an AI agency or consultancy like HolistiCrm can emulate this structured approach by developing custom AI models that prioritize both predictive power and interpretability—especially in areas like customer journey mapping, churn prediction, or sentiment analysis. A Holistic implementation of AI that includes automated knowledge validation, transparency, and compliance ensures not just performance, but trust—ultimately creating business value through enhanced customer loyalty and reduced operational risk.
The government’s investment in building a sustainable AI research backbone provides validation for enterprise martech initiatives that embed fairness and accountability into their machine learning models. As companies look to scale their AI efforts, drawing inspiration from institutional frameworks such as CAISI can enable better long-term outcomes in both marketing and customer intelligence environments.
original article: https://news.google.com/rss/articles/CBMiowFBVV95cUxNRFk3NVBtaVVOSnBCSFh2SThDRXV0d183UllDZHhVeGI1TjVfc3ZRcjI5bnI0TjZobHBrUE55SWliVi1YcWVxZk5oanBycldueGpKOEd2c0VZS3NEU0hRdkhyeDJMb3BMekZjX1hvWXhWbWtjSWpBN29WMk9MdU5KTzV3SmJlWjY3Qkp5aGtsdXRVdVh1M3VrZXFUZHdtUmhOc20w?oc=5
by Csongor Fekete | Dec 26, 2025 | AI, Business, Machine Learning
Meta’s latest AI initiative, a new image and video generation model code-named "Mango", represents a powerful leap forward in the martech landscape. As revealed in The Wall Street Journal, Mango aims to compete with leading models such as OpenAI’s Sora and Google DeepMind by generating hyper-realistic media content through advanced custom AI models. Currently in internal testing, Mango is a large multimodal generative AI system and part of Meta’s broader push to reassert itself in the AI race.
Key highlights from the article include:
- Mango will likely integrate into Meta’s products like Instagram and advertising tools.
- The custom AI model targets improvements in performance, realism, and dynamic output generation.
- Mango builds on Meta’s existing open-source models but is trained on significantly larger datasets.
- The initiative shows Meta’s strategic goal of reclaiming AI leadership by developing end-to-end proprietary technology.
For brands and marketers, the implications are wide-reaching. AI agencies and AI consultancies can harness such generative capabilities to transform marketing workflows: producing tailored ads, enhancing creative assets at scale, and automating visual storytelling. By applying machine learning models capable of image and video generation, companies can increase customer satisfaction through more personalized and visually captivating campaigns. Moreover, the holistic use of multimodal AI models like Mango paves the way for reducing production times and costs while boosting content relevance.
A practical use-case for HolistiCrm clients could be building a custom AI model inspired by Mango’s generative capabilities to automate campaign creatives for omnichannel marketing. By training this Machine Learning model on proprietary brand data, businesses can ensure coherent design, tone, and narrative across all digital touchpoints—driving performance and fostering deeper customer engagement.
Original article: https://news.google.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?oc=5
by Csongor Fekete | Dec 26, 2025 | AI, Business, Machine Learning
Meta is quietly developing a new AI image and video model codenamed “Mango,” aimed at elevating multimodal AI capabilities. According to The Wall Street Journal, Mango is designed to not only understand inputs like images and videos but also to generate new media content. This move further positions Meta in the generative AI space, alongside models like OpenAI’s Sora or Google’s Gemini.
The key development here is Meta's emphasis on creating a unified multimodal Machine Learning model capable of real-time, high-fidelity video generation. Mango is expected to integrate deeply with Meta’s broader AI ecosystem—including Llama-based chatbots and productivity tools–strengthening its presence in the evolving martech landscape.
For businesses exploring AI-driven performance and customer satisfaction, Mango’s technology unlocks use-cases such as personalized marketing campaigns powered by unique, AI-generated video content. With custom AI models tailored to specific industries or customer segments, brands can increase engagement rates and reduce dependency on generic stock content. An AI agency or AI consultancy like HolistiCrm, with expertise in deploying holistic Machine Learning models, can help integrate such technology into marketing workflows—driving automation, innovation, and ROI.
This development underlines an accelerating trend: the convergence of multimodal AI with practical business tools that enhance content creation and customer experience. As martech stacks grow increasingly intelligent, companies must act swiftly to align AI strategies with evolving customer expectations.
Read the original article here – original article.
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