by Csongor Fekete | Apr 23, 2025 | AI, Business, Machine Learning
Title: Pushing the Boundaries of Research with Custom AI Models
Anthropic’s recent update on Claude highlights the transformative impact of next-generation AI models in advanced research workflows. Claude, a sophisticated language model, is rapidly evolving how researchers interact with information, enabling deep analysis, faster synthesis of large datasets, and unprecedented insights across various domains.
Key takeaways from the article, Claude takes research to new places, include:
- Claude is enabling novel research methods by handling vast and complex document sets – including scientific papers, legal texts, and policy data – with unparalleled efficiency.
- Researchers are using Claude to extract actionable insights, summarize data, and generate hypotheses in minutes rather than days.
- The model's ability to understand nuanced contexts and produce clear, human-like summaries reduces cognitive load and increases overall productivity.
- Across fields like epidemiology, machine learning, and climate science, Claude accelerates the research process and enhances knowledge discovery.
From a business perspective, this trend signals a powerful opportunity for organizations to unlock value through custom AI models tailored to their specific domains. In customer-centric industries—especially in martech and CRM—AI-driven research tools can drive major improvements in market analysis, campaign measurement, and personalization strategies.
How HolistiCrm Creates Business Value
As an AI agency and AI consultancy passionate about holistic strategies, HolistiCrm helps businesses build and deploy custom Machine Learning models that optimize marketing and customer experience. One high-impact use-case would be enabling:
Automated Customer Insight Generation
By applying a Claude-like AI model fine-tuned for a company’s CRM and customer behavior data, departments can automatically generate segmentation insights, detect emerging patterns, and understand pain points in real time. Such capability drastically improves satisfaction and campaign performance across the board.
With a custom AI model integrated into a marketing tech (martech) stack, businesses aren’t just reacting—they’re anticipating. They move from lagging indicators to predictive insight, driving smarter decisions and higher ROI.
The takeaway? AI isn’t just for academic research—it's a vital tool that, when customized thoughtfully, can rejuvenate data-heavy functions and offer holistic improvements in business workflows.
For more details, read the original article: Claude takes research to new places – Anthropic
by Csongor Fekete | Apr 22, 2025 | AI, Business, Machine Learning
Title: How Google’s AI-Powered Research into Dolphin Communication Inspires Holistic Custom AI Solutions in Business
Google has recently introduced a groundbreaking AI model aimed at decoding the intricate communication patterns of dolphins, as reported by TechCrunch. The initiative is part of the SETI Institute’s Project CETI (Cetacean Translation Initiative), with the goal of using artificial intelligence to understand non-human communication.
Key Highlights from the Article:
- Google’s AI team collaborated with marine biologists to analyze decades of acoustic data collected from marine life, particularly bottlenose dolphins.
- The model leverages advanced machine learning techniques, akin to those used in large language models (LLMs) like ChatGPT, to identify patterns and structures in dolphin vocalizations.
- The research integrates diverse scientific disciplines, including linguistics, AI modeling, and biology, to facilitate a deeper understanding of animal language.
This project demonstrates not just technological innovation but also the versatility of Machine Learning models in decoding complex, unstructured data with real-world implications.
Business Implications and Use Case
This mix of cutting-edge AI modeling and holistic data integration offers valuable learnings for enterprises looking to enhance their martech capabilities. Custom AI models, similar to those used in marine biology, can be developed to interpret large volumes of customer data—such as voice interactions, sentiment in social media mentions, or support ticket logs.
For example, a customer-centric marketing team can deploy a tailored HolistiCrm Machine Learning model to identify “unstated needs” within customer service chats or helpline transcripts. These insights can then be used to improve performance in campaign personalization, refine product messaging, and increase overall customer satisfaction.
By applying a holistic AI consultancy approach, companies can go beyond basic analytics and build custom AI models that interpret nuanced consumer behaviors—just as Google's model listens to dolphins.
As an AI agency and martech expert, HolistiCrm encourages adopting similar interdisciplinary methods to unlock deeper data-driven decisions that create market differentiation and long-term customer loyalty.
Read the original article here: Google’s newest AI model is designed to help study dolphin ‘speech’ – TechCrunch (original article)
by Csongor Fekete | Apr 22, 2025 | AI, Business, Machine Learning
Title: Rethinking Martech with AI Agents: A New Era of Customer Experience
The recent Bain & Company article, Marketing’s New Middleman: AI Agents, highlights a seismic shift in how marketing teams engage with customers. Artificial Intelligence agents are emerging as the new intermediaries between brands and consumers—streamlining operations, personalizing outreach, and transforming the traditional role of marketers.
Key Insights from the Article:
- AI agents are automating routine marketing tasks, enabling faster, more tailored customer interactions.
- These virtual agents serve as both customer-facing assistants and internal operational tools, enhancing personalization and boosting performance across campaigns.
- Companies leveraging AI agents effectively are creating seamless, real-time user experiences that drive higher customer satisfaction and engagement.
- The integration of AI into go-to-market (GTM) strategies allows for dynamic testing, optimization, and rapid scale—transforming user behavior insights into actionable campaigns.
Turning Insights into Value: A Holistic CRM Use-Case
An AI consultancy or AI agency like HolistiCrm can extract significant business value by integrating custom AI models to act as personalized middlemen across the customer journey. For example, deploying AI agents within a CRM platform for lead qualification, customer support, and journey orchestration can:
- Improve marketing ROI through real-time decision-making and adaptive messaging.
- Enhance conversion rates by giving customers instant, context-relevant responses.
- Increase retention and satisfaction by learning from behaviors across all touchpoints.
Such a holistic implementation of AI—not just as a plugin, but as part of the foundational martech strategy—can dramatically elevate the performance of customer engagement.
HolistiCrm’s specialization in building Machine Learning models for the martech space ensures AI agents are not only efficient but aligned with unique organizational goals.
As AI evolves from automation to orchestration in marketing, brands that act early with AI expert support will stay ahead in experience, satisfaction, and competitiveness.
Read the original article: Marketing’s New Middleman: AI Agents – Bain & Company.
by Csongor Fekete | Apr 21, 2025 | AI, Business, Machine Learning
Title: Unlocking Business Value with U.S.-Made AI Supercomputers: What It Means for Custom AI Models and Holistic Marketing Strategies
NVIDIA's recent announcement to manufacture AI supercomputers in the United States marks a pivotal step for the AI and tech industry. For the first time, NVIDIA will produce next-generation AI systems in the U.S., enhancing both domestic competitiveness and technological resilience.
Key Highlights from the Article:
- NVIDIA will begin domestic manufacturing of AI supercomputers, starting with its DGX H100 systems at facilities in Silicon Valley.
- This move addresses the growing demand for high-performance computing systems driven by generative AI, large language models, and edge computing.
- The initiative is part of a broader strategy to re-shore advanced semiconductor and infrastructure development, reducing reliance on overseas supply chains.
- NVIDIA has partnered with several American companies, including Celestica and Foxconn Industrial Internet, ensuring a robust local value chain.
Original Article: NVIDIA to Manufacture American-Made AI Supercomputers in US for First Time
Implications for Business Value
For marketing teams, AI consultancies, and martech agencies focused on delivering customer-centric solutions, the introduction of locally built AI supercomputers translates into a new era of performance and operational efficiency. With shorter supply chains and reduced latency in AI development cycles, custom AI models can now be deployed and trained at scale faster than ever before.
Use Case: Holistic CRM with Custom AI in Marketing
A business looking to improve customer satisfaction through AI-powered personalization can significantly benefit from higher-performing, locally manufactured infrastructure. Consider a company using a HolistiCrm platform powered by Machine Learning models tailored to predict churn, segment audiences and optimize customer journeys. With access to high-performance AI computing resources made in the U.S., the company can iterate models quicker, fine-tune predictions more accurately, and scale its AI marketing strategies with confidence.
This setup not only boosts operational efficiency but also enables real-time insights that can improve customer experience and drive marketing ROI. A holistic approach to martech powered by custom AI models ensures adaptability in a constantly evolving digital landscape.
Conclusion
NVIDIA’s move is a significant milestone that deepens the capabilities of AI deployment in businesses across sectors. AI agencies and AI experts can now capitalize on this momentum to deliver high-speed, scalable, and locally compliant solutions, driving both economic and innovation benefits.
Read the original article: NVIDIA to Manufacture American-Made AI Supercomputers in US for First Time – NVIDIA Blog
by Csongor Fekete | Apr 21, 2025 | AI, Business, Machine Learning
🌊 Decoding Nature with AI: What Business Can Learn from Google’s Dolphin Communication Breakthrough
In a fascinating leap toward interspecies communication, Google researchers—collaborating with the SETI Institute’s Project CETI—have developed a custom AI model aimed at decoding dolphin communication. This initiative uses machine learning models to analyze the patterns and context of dolphin vocalizations, with the potential to identify what specific "clicks" and "whistles" correspond to in behavioral and environmental terms. The project applies natural language processing, unsupervised learning, and multimodal data (audio, motions, context) to decipher complex social signals of dolphins.
Key Learnings from This Initiative:
- Custom AI Models Can Crack Complex Data: Dolphins communicate using nonlinear vocalizations that humans can’t interpret intuitively. The AI model's ability to extract meaning from this chaotic data shows the power of customized AI models built for specific, niche domains.
- Multimodal Context Drives Understanding: By training the models on both contextual environmental data and audio recordings, researchers could improve model performance—an approach that can be translated to marketing technologies and customer interaction data.
- Machine Learning's Role in Niche Communication Patterns: This use case demonstrates that ML models can help decode hidden patterns in unconventional data types, an insight that can be applied to industries like health, fintech, and martech.
Business Value in a Marketing Context:
While decoding dolphin communication may seem oceans away from B2C enterprises, the strategic approach behind it provides valuable inspiration for holistic customer engagement strategies. Brands using martech systems often collect multimodal data—from email interactions to website clicks and CRM logs. A custom machine learning model, similar to Google’s dolphin AI but adjusted to customer behavior data, can identify latent patterns, predict intent, and optimize campaigns.
For example, an AI agency or consultancy could develop a custom model for a retail client that correlates specific email engagement patterns with purchasing behavior—unlocking predictive triggers that enhance customer satisfaction and marketing ROI. Context-aware AI models can understand not only what customers do but why—an edge that sets high-performing brands apart.
What marketers and AI experts can take from Google's work is that even the most slippery and nonlinear data can be modeled and interpreted with the right machine learning approach. Businesses ready to invest in holistic, domain-tuned AI solutions can see dramatic improvements in performance, engagement, and customer satisfaction.
Original article: https://news.google.com/rss/articles/CBMimgFBVV95cUxQTWpYMnRqQ1ZKRWVKZ3dyMy1FYkh3bHlic0FwaTBhSWZKWFV2eF9hOUVVbkhyM3ExOUp5SG5DU1BvdGxmVzVxaDlnQVFCVmp2S2czOUtSOXdBaHBZa1liT0hyaUxYa25MVVVETkRMaXczekVYVmljQmNtMmRNWTA3dUFuQ0x6bmZMcEVpUGZpWmR1dnM3b1ViRUdB?oc=5
Recent Comments