by Csongor Fekete | Nov 25, 2025 | AI, Business, Machine Learning
The recent New York Times article "In the A.I. Race, Chinese Talent Still Drives American Research" highlights how Chinese-born researchers continue to play a pivotal role in advancing AI R&D in the United States. Despite geopolitical tensions and tightening immigration policies, the article reveals that Chinese expertise remains essential in sustaining innovation and global competitiveness in artificial intelligence.
Key takeaways include:
- Chinese researchers represent a considerable portion of contributors to top AI conferences in the U.S.
- Their work powers core advancements in machine learning model development, including language processors and AI infrastructure.
- U.S.-based institutions and tech giants heavily rely on this international talent to maintain innovation velocity.
- Restrictive visa policies and political strains could pose risks to the diversity and performance of the AI research ecosystem.
In a business context, these insights reaffirm the importance of global collaboration and talent mobility in building high-performing, holistic AI strategies. Enterprises seeking to harness AI should recognize the value in cross-cultural expertise when building custom AI models. For martech and marketing teams, this could mean collaborating with diverse talent pools to optimize customer satisfaction by designing models that reflect global behavioral patterns.
For example, a martech company leveraging a machine learning model for predictive customer engagement could benefit from the layered cultural insights embedded by a globally diverse team. This approach enhances the model’s adaptability across markets—driving higher performance and ROI.
HolistiCrm, as an AI consultancy and AI agency, emphasizes the integration of international expertise when supporting clients with AI initiatives. Understanding the broader talent ecosystem is vital for creating resilient, innovative business solutions in today's AI-driven economy.
Read the original article: https://news.google.com/rss/articles/CBMigwFBVV95cUxPb2sxOVgtOS1uRW1lWVFCZkJld1FySDloZ3IzbVFWZ3h1Ym44NWd3UDFKY3I2aXB3ZFQ4MnFHcFZDa01oVDBkOFMteFhjblB6SDI2eUpwUFQxY0RhU3IteDFQODVnWm5FU1JRUTVhcDZRV0p5M1FEeXpTZjdTVEl0M2dMNA?oc=5 (original article)
by Csongor Fekete | Nov 25, 2025 | AI, Business, Machine Learning
Google has taken a bold step in the evolution of search by launching Gemini 3, the latest iteration of its AI model — and embedding it directly into its core search functionality. This marks a seismic shift in how artificial intelligence can reshape user experience, content discovery, and digital marketing strategies.
Key takeaways from the launch:
- Gemini 3 delivers enhanced multi-modal capabilities, integrating text, code, and image understanding into a single platform.
- By embedding this new Machine Learning model into its search engine, Google aims to provide more efficient, context-aware, and conversational results.
- This move exemplifies the growing trend of embedding custom AI models deeply into consumer-facing products to improve performance and user satisfaction.
For martech leaders and marketing teams, this development signals a critical pivot. Integrating similar holistic AI capabilities into customer experience platforms can unlock significant value. Imagine a CRM system powered by a custom AI model that understands user intent across emails, chats, and browsing behavior in real-time — instantly crafting tailored responses or curated content suggestions. HolistiCrm helps companies deploy such solutions, enhancing both marketing automation and overall customer satisfaction.
A use-case example: A retail brand leveraging a Machine Learning model embedded in its CRM can identify high-intent leads from various channels, dynamically personalize offers, and optimize timing for maximum conversion. This level of AI-driven marketing intelligence improves campaign performance and builds deeper customer loyalty.
As Gemini 3 raises the bar for AI integration, businesses that embrace AI consultancy and expert-driven strategy will be better positioned to lead in the new martech landscape.
original article: https://news.google.com/rss/articles/CBMiwAFBVV95cUxPZDM3bGRBbm5FYmlvX1k3THdHUVo1U0RRYkp5Q1hFbmJRZ2hNdTZQQWpwUVZDNFVCSjYxdDVXZXY5WmlLQ2kzd1dwQ0d6dTBmV0VyNkc1SHBHTzQ5WE1Kc2VSZDhkYTBFVS14ckgydkpxckltdGh3TkUxem9raDlPLW93WURYcFR1VkJyZ1dRc3FaVU9FTnpIMm9hRzJsRDNsbjFMZGRVdlVKN1JVal9lTlpGQV9ubmZqQkRfeTdwWUw?oc=5
by Csongor Fekete | Nov 24, 2025 | AI, Business, Machine Learning
Google has unveiled its most intelligent search experience yet by integrating the Gemini 3 family of Large Language Models (LLMs) directly into Search. This marks a significant shift toward AI-first search, offering more reasoning, multi-step planning, and summarization capabilities. With these enhancements, users can get complex, synthesized answers instead of just a list of links. Features like AI Overviews and multi-step query handling improve not only speed and accuracy, but also information accessibility.
Key takeaways from the article include:
- A new Search experience powered by the Gemini 3 model, capable of understanding complex queries and delivering concise, insightful overviews.
- The ability to process multi-step tasks like trip planning or product comparison in a single prompt, streamlining workflows for users.
- Real-world rollout to users in the U.S., with plans for broader availability.
- A strong focus on responsible AI development, maintaining factual accuracy and minimizing hallucinations in generative responses.
For businesses, particularly in the martech space, this evolution presents an opportunity to develop their own Holistic search and recommendation systems powered by custom AI models. By implementing advanced reasoning and summarization through Machine Learning models and natural language processing, companies can enhance customer satisfaction through targeted content, faster discovery, and deeper personalization.
Consider a travel agency using a custom AI model to replicate Google's Gemini functionality: A customer could ask, “Plan a two-week family vacation in Italy including historical sites, kid-friendly activities, and hotel comparisons under €200/night.” Instead of navigating pages of content, a holistic system would return a complete itinerary and booking options—all through one interface. This boosts marketing performance, increases conversion, and elevates the brand as an AI expert in customer experience delivery.
For any AI agency or AI consultancy, the challenge now is to distill the potential of models like Gemini into vertical-specific solutions for enterprises—combining technical capability with contextual business understanding.
original article: https://news.google.com/rss/articles/CBMibEFVX3lxTE51a3JNdVZ6bi0wbWhvc0x4ajUtSU1NMWU5VER0MXhLaFZQdXVqS0NxRDN0Y0ZhNnFLeTNENVdpbUFYRzZKR2xuTTNUX1FuaTJ5QXFlY0tBTmRNc3g5OTRBUlFSaUJhWHBPZEQzZQ?oc=5
by Csongor Fekete | Nov 24, 2025 | AI, Business, Machine Learning
Google’s latest upgrade, Gemini 3, represents a significant step forward in embedding advanced intelligence directly into its Gemini app. This update introduces improved reasoning capabilities, context handling, and integration with tools and personal data, making interactions with AI more intuitive and productive. Key improvements include the ability to interpret longer inputs, nuanced image and audio recognition, and real-time collaboration features, such as coding assistance and document summaries.
A crucial learning from this development is the increasing role of custom AI models in enhancing user experience. The Gemini 3 model adapts contextually to user commands and leverages cross-functional APIs and personal data (such as calendar and Gmail) while preserving privacy and consent-based access. This enables intelligent assistance tailored to real-time business needs.
For martech companies and enterprises powered by AI consultancy services, this sets a strong benchmark. A valuable use-case inspired by Gemini 3 can be seen in customer support systems. By integrating a custom Machine Learning model with CRM platforms, businesses can automate responses, analyze sentiment, and provide personalized experiences—improving both performance and customer satisfaction. HolistiCrm’s holistic approach to building such AI-driven customer experiences can lead to measurable outcomes in engagement rates, marketing ROI, and operational efficiency.
As generative AI becomes more context-aware and multimodal, the need for businesses to partner with an expert AI agency that combines martech expertise with scalable AI architecture continues to grow.
original article: https://news.google.com/rss/articles/CBMiZ0FVX3lxTE1kNnJ4aHBKa1Rvc0RQak9WM1pFSTVSY2JJNHhZamljMHdfai1HMElBUVE5Ti1wUXp3dFlVY1QzMVdQdTYyY1B0Q1VVcW95eFVwQXlqcUVYTXgwSVV0VjRWQXg0NVVyeW8?oc=5
by Csongor Fekete | Nov 23, 2025 | AI, Business, Machine Learning
In the recent article “Generative UI: A rich, custom, visual interactive user experience for any prompt” by Google Research, the team introduces a groundbreaking approach to user interfaces powered by generative AI. Instead of relying on static, pre-designed screens, Generative UIs dynamically create visual elements in response to natural language prompts, enabling tailored experiences with high interactivity and responsiveness.
Key takeaways include:
- Generative UI offers a seamless, prompt-driven interaction layer that adapts based on user intent, creating real-time visual components.
- It leverages advanced large language models (LLMs) to not only interpret requests but also decide on UI components and layout generation.
- This approach drastically reduces manual UI coding, making frontend development more scalable, adaptive, and personalized.
- It demonstrates both flexibility and robustness, highlighting applications across productivity, data analysis, and web interfaces.
From a business perspective, this innovation can directly improve customer satisfaction and engagement, especially in martech and CRM applications. Imagine empowering users to generate personalized dashboards, reports, or campaign planners simply through natural language – no technical experience required. With Machine Learning models powering customized interfaces, companies can offer truly holistic user experiences that elevate performance.
A specific use case for HolistiCrm could be integrating a generative UI layer within the customer interaction modules. This would allow sales and marketing teams to ask for, and immediately receive, visual summaries or campaign projections using natural queries. A custom AI model tailored to the organization’s data and workflow could serve real-time visual tools, increasing productivity and reducing implementation costs. For a martech-driven AI consultancy or AI agency, the business value lies in radically faster deployments, higher adoption rates, and enhanced UX across customer touchpoints.
By adopting generative UI frameworks, enterprises can align closely with user behavior and preferences—key values that define the future of marketing platforms.
Read the original article: https://news.google.com/rss/articles/CBMiqwFBVV95cUxPMDVpZzF2WkMycWIxMHZRczlKWmtCRUxnUFFkV2xzTmZTaXVDaGUyOUl4cmxUOGpyTGlISmI3QmdIeGc2NmxuYV9iSU5yTkdzaUlDUTFaZXFYSzU2bmxOV3ZmWlZuNFdHUW9EVlk2YzRkQWd6bkxla2tlcmIwZ2VOTmJIYVoyZGhPRk5MRm1fTUF4al9tbGZYbzlBN19PMUFPNkxLR3BTVmJqREU?oc=5 (original article)
Recent Comments