by Csongor Fekete | Oct 10, 2025 | AI, Business, Machine Learning
As 2025 unfolds, marketers are increasingly moving from hype to hands-on implementation when it comes to artificial intelligence, according to a recent report by Social Media Examiner. The survey reveals a distinct shift: AI is now a core component of marketing operations, not just a trendy topic.
The key insight? AI tools are being used most effectively for content generation, marketing automation, and personalization. However, many marketers still struggle with tool overload—juggling multiple platforms without a unified strategy. The study also reveals that while over 80% of marketers are experimenting with AI, only a minority have integrated it into a holistic martech framework.
Another critical finding is the growing demand for custom AI models tailored to business-specific goals rather than generic solutions. This shift underscores the need for specialized AI consultancy and AI agency support focused on aligning AI with brand voice, customer personas, and lifecycle stages.
A high-impact use case touched on in the article involves leveraging Machine Learning models to personalize email marketing campaigns. By analyzing customer behavior across channels, businesses can use predictive AI to deliver hyper-relevant messaging at scale—dramatically improving engagement rates and customer satisfaction. For martech leaders, embedding such use cases into a holistic AI strategy is key to maximizing business performance in the coming years.
As marketing teams aim for differentiation in a crowded digital landscape, working with an AI expert to develop domain-specific solutions becomes not just advantageous but necessary. This is where a company like HolistiCrm can bridge the gap—by embedding finely tuned AI systems directly into the CRM and customer engagement ecosystem.
Read the original article: https://news.google.com/rss/articles/CBMiekFVX3lxTE9GQ1FxQjNaOHFDa00weEtuUnp6RXdmaklkSG5CVGhuTERQUmRGZjE2NUxUV3g0cDZCd2N4Z0xaRVo4bUdRUTlfV1NiOTJIbE5BbVFNNGs3NE4tX3VGOWp3MFhpYWJkVDRjMmI2bnZWVFEtb2N2QU9rQU13?oc=5
by Csongor Fekete | Oct 10, 2025 | AI, Business, Machine Learning
Tencent has taken the lead in AI image model development by surpassing Google’s Nano Banana on a global benchmark leaderboard. According to the South China Morning Post, Tencent’s new foundation model achieved this by demonstrating superior performance in multiple visual recognition tasks. The model excelled in understanding and generating accurate image content, reflecting the growing investment by tech giants into next-generation AI capabilities.
Key takeaways from this advancement:
- Tencent’s model is trained on over 10 billion parameters, enabling a deeper semantic understanding of images.
- The visual foundation model supports multimodal learning, integrating both image and text data to enhance interpretation.
- The achievement marks a shift in global AI competitiveness, with more players from Asia challenging incumbents like Google.
For businesses in marketing and martech, such innovation sets the stage for more holistic use of visual content in campaigns. By implementing custom AI models tailored for brand-specific datasets — including product imagery, user-generated content, and ad creatives — companies can automate asset tagging, improve visual search, and generate high-converting imagery.
At HolistiCrm, applying a custom Machine Learning model for marketing automation could serve as a transformational lever. Enhanced image recognition enables dynamically personalized visuals in campaigns based on customer profiles, driving better engagement and satisfaction while reducing creative workload. As an AI consultancy or AI agency, deploying high-performance, domain-specific AI tools is key to maintaining a competitive edge.
Full story at the original article: Tencent’s AI image model beats Google’s Nano Banana in leaderboard
by Csongor Fekete | Oct 9, 2025 | AI, Business, Machine Learning
Tencent’s latest advancement in AI underscores the shifting dynamics in the AI arms race, particularly in image generation. The Chinese tech giant’s Imagen competitor, called "Hunyuan DiT", has topped the Computer Vision Leaderboard by Hugging Face, beating Google’s well-known "Nano Banana" with superior performance in image-text understanding. This marks a critical milestone not just in AI research, but in broader applications across marketing, design, and martech spheres.
Key takeaways from the article include:
- Model performance supremacy: Tencent’s Hunyuan DiT outperforms highly publicized competitors, signaling a new level of capability in image generation tasks.
- Pretraining with real-world complexity: The model leverages contrastive learning and a massive proprietary dataset, bringing out the strengths of domain-specific pretraining.
- Strategic focus on AI leadership: This development ties into China’s national ambition to become a global AI leader by 2030. It also emphasizes the value of end-to-end control over data, model design, and infrastructure.
For businesses seeking an edge in performance-driven marketing, this development holds actionable insights. A custom AI model trained on a brand’s specific customer imagery—similar in spirit to Hunyuan DiT—can elevate customer satisfaction by generating hyper-personalized content at scale. An AI agency or AI consultancy like HolistiCrm can apply this approach to improve ad creatives, automate visual asset creation, or personalize experiences in real-time across touchpoints.
Embedding such holistic solutions into martech stacks enables new levels of automation, brand consistency, and engagement—turning advanced Machine Learning models from research milestones into business value engines.
Original article: https://news.google.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?oc=5
by Csongor Fekete | Oct 9, 2025 | AI, Business, Machine Learning
California Takes the Lead in Regulating Frontier AI Models: What It Means for Businesses
California has enacted a groundbreaking piece of legislation targeting the development of frontier artificial intelligence models. The new law introduces rigorous transparency, safety, and reporting obligations aimed at ensuring the responsible deployment of advanced AI systems. This development signals a major shift in the regulatory landscape, and it’s something any company operating in the AI or martech space needs to closely watch.
Key highlights from the legislation include:
- Mandatory Safety Testing: Developers of "frontier" Machine Learning models must conduct robust pre-release testing to assess risks such as model misuse and unintended consequences.
- Reporting Requirements: Organizations are required to submit regular updates on model performance, safety issues, and mitigation strategies.
- Transparency to Government: Companies must disclose development practices, data inputs, and safety measures to regulatory authorities.
This legislative change comes at a time when the use of custom AI models is reshaping customer engagement, personalization, and performance optimization across industries. For marketing and martech teams, this calls for a holistic approach to AI development—balancing innovation with accountability and trust.
A practical use-case: Consider a company using a generative Machine Learning model to automate customer service queries and personalize marketing CRM campaigns. Under the new California rules, this company must evaluate the model's potential for generating biased responses or misinformation and actively report on safeguards. This not only aligns with regulatory compliance but can directly enhance customer satisfaction by delivering more accurate, responsible, and trustworthy interactions.
By integrating AI governance principles early, businesses can future-proof their operations, mitigate reputational and legal risks, and improve overall technology performance. AI consultancies and AI experts must now help organizations adopt frameworks that embed transparency and responsibility into every custom model they deploy.
This regulatory shift underscores the need for businesses to embrace proactive AI consultancy and operational readiness. California's move may well be a harbinger of broader national or global regulations, making it essential for teams in every sector—from marketing to product development—to prepare now.
Read the original article: California adopts landmark AI law: new transparency, safety, and reporting requirements for frontier model developers.
by Csongor Fekete | Oct 8, 2025 | AI, Business, Machine Learning
In the evolving martech landscape, AI is undoubtedly a game-changer—but the recent ADWEEK article, “The Real Edge in AI Marketing is Human Thinking,” emphasizes an often-overlooked truth: human insight remains the cornerstone of truly powerful marketing.
The article highlights a critical shift: while custom AI models and machine learning algorithms can process massive datasets to predict trends and automate decisions, it's human creativity and strategic thinking that connect these insights to real customer value. AI is only as effective as the human minds guiding its direction—whether defining goals, crafting narratives or interpreting model outputs.
Key takeaways include the need for brands to avoid over-indexing on automated performance indicators and instead build marketing strategies informed by empathy, cultural relevance, and brand purpose. AI tools should amplify—rather than replace—the marketer's intuition.
For businesses exploring use-cases, this hybrid model of human-AI collaboration can drive significant business value. For example, integrating a Holistic Machine Learning model with human-led customer journey mapping enables companies to identify hidden patterns in customer behavior and combine them with emotional triggers and storytelling. This leads to more compelling, personalized, and effective campaigns—boosting customer satisfaction and ROI.
Organizations that partner with an AI consultancy or AI agency that understands both data science and storytelling can unlock performance not only through automation but also through resonance.
original article: https://news.google.com/rss/articles/CBMigwFBVV95cUxOSlIzcGJCbEhxbXpLLU11UnZZMGhmSXJ1djBVZlNXZ1RPZlgxZ1M0bHl6R1FOOE5TUUFpeE1jd0I2a0swVXVVejB2NllKTTFGdVlZaXNEX3V6UHJoQmFGT2p0SHR1cTY4bThlakt5VEl5TWlOSGlFdVVuR0dwejZTTUhxRQ?oc=5
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