by Csongor Fekete | Jun 18, 2025 | AI, Business, Machine Learning
NVIDIA has announced strategic partnerships with top European model builders and cloud providers to supercharge the region's advancement in AI. The initiative focuses on creating a robust AI infrastructure that will empower Europe’s leading companies, researchers, and governments to design and deploy next-generation Machine Learning models locally. These collaborations streamline access to NVIDIA's cutting-edge computing platforms and software, accelerating AI adoption across manufacturing, healthcare, public services, and more.
Key takeaways from the collaboration:
- Enhanced access to NVIDIA’s full-stack AI platform through regional cloud providers.
- Support for the development of sovereign AI capabilities within Europe.
- Localized resources to address data residency, privacy, and compliance requirements.
- Collaboration with European research institutions to foster AI talent and innovation.
This has significant implications for integrating holistically designed, custom AI models into business operations. For companies aiming to elevate their marketing and customer engagement performance, high-performance AI infrastructure allows the development of localized, regulation-compliant martech tools. For instance, using models trained on regional behavior and preferences, a business can generate hyper-personalized content, optimize campaign delivery times, or even anticipate customer churn, boosting satisfaction and ROI.
At HolistiCrm, leveraging custom machine learning models within a secure, local cloud infrastructure enables scalable AI consultancy services. An AI expert can help transform this infrastructure advantage into competitive differentiation through advanced marketing automation, predictive analytics, and CRM optimization.
This expansion of Europe's AI ecosystem signals exciting opportunities for industries seeking to harness AI responsibly, efficiently, and holistically for strategic business value.
Source: original article
by Csongor Fekete | Jun 17, 2025 | AI, Business, Machine Learning
1X’s latest innovation, the NEO humanoid robot, marks a significant leap in autonomous robotics thanks to the incorporation of Redwood’s AI model. This integration empowers NEO with enhanced decision-making capabilities and situational awareness, enabling it to operate safely and independently in complex environments. The AI model allows the robot to carry out tasks with greater flexibility, mirroring human behavior patterns, and adapting to unstructured settings in real-time.
The key learning from this advancement lies in the shift toward holistic autonomy, where physical robotics merge with sophisticated custom AI models. Redwood’s approach enables NEO to learn from high-volume data inputs and continuously update its model performance, mimicking the adaptability of human cognition. This is a major step forward in AI consultancy, opening doors for a range of industries looking to automate dynamic environments.
For martech and marketing-centric companies, this AI breakthrough serves as a foundational use-case. Imagine deploying custom AI models that not only interpret customer behaviors but physically interact in environments such as retail or experience centers. This aligns with HolistiCrm’s vision of leveraging machine learning models not just for insight generation, but for tactile customer engagement. Increased customer satisfaction and operational efficiency can be achieved by combining high-touch interaction with intelligent automation—especially in sectors like retail, hospitality, and healthcare.
This shift towards embodied AI is not just a technological feat, but a business catalyst that redefines the interface between brands and their customers.
original article: https://news.google.com/rss/articles/CBMikwFBVV95cUxOUEhPR1hjOGZVR1Y1cWtMdzhEeVdmM3BEY2gxYkUzNXhiR0lSdUNfNTZJVkk3a0gwWkREUG5mTzZwWVdrd3hUSWRoQ3p2NGU3S1Z0dDFGY3Y3NDRtSndxa1ZMUGREUy15YlhwbWRieENndG5hWVF1c2JfVlR4dVY2RVhoaVNhLVBQeWUxcVM3cTczQ1U?oc=5
by Csongor Fekete | Jun 17, 2025 | AI, Business, Machine Learning
Apple’s latest reveal of upgraded AI models has sparked more questions than excitement. According to the TechCrunch article "Apple’s upgraded AI models underwhelm on performance," the tech giant’s new AI models show limited improvements in generative performance when compared to leading models like GPT-4 and Claude. While Apple is making efforts to catch up in the generative AI race, the models fall short of delivering substantial breakthroughs in benchmarks, impacting expectations around user satisfaction and innovation.
Key learnings from the article include:
- Apple’s AI models, while improved, notably lag behind top-tier alternatives in both quality and speed.
- Real-time use cases (like summarization or content generation) show limited enhancements, raising concerns over practical marketing or martech deployments.
- The models appear to be designed more for device-level integration than for transformative personalized experiences.
This underperformance highlights a crucial point for businesses: custom AI models can drive greater value than off-the-shelf solutions when tailored to specific customer data and business workflows. For instance, a marketing team can deploy a domain-trained Machine Learning model to personalize content generation for niche segments, outperforming generic tools in both engagement and effectiveness.
By leveraging a holistic approach to data and customer needs, businesses can increase customer satisfaction, automate high-value tasks, and fuel performance-centric growth strategies. AI consultancy and martech transformation partners, like HolistiCrm, can accelerate this journey using custom-built solutions aligned with business objectives instead of generic benchmarks.
Read the original article: https://news.google.com/rss/articles/CBMijwFBVV95cUxQaUVnOWxLbERldk96UVVTTVE0Qm9DQk5ndVYtaW0tREExSVFZWGdodkROZktYQ3NpdDJCLWlQOWZmZEZ5cDZ1WVBncUVVYWpSbjU1YzFVUFdIcUd5T0FCWWlYcW1GT1UzX1FvVnhGOE5pVzFLNDV6OVZTeFBmdHo5ODRtYkhXTWd6SkpvWWZVTQ?oc=5 (original article)
by Csongor Fekete | Jun 16, 2025 | AI, Business, Machine Learning
Apple's recent research paper sends strong ripples through the AI industry by highlighting how generative AI models tend to produce increasingly inaccurate outputs when trained on synthetic data—a phenomenon termed "Model Autophagy Disorder." The study shows that continual recycling of AI-generated data without human-validated inputs leads to rapid degradation in quality, threatening the performance and reliability of AI systems over time. This is particularly problematic as the appetite for large datasets grows and organizations begin using AI-generated content to train new models.
The findings reinforce a critical need for human feedback, curated data, and domain-specific knowledge in building effective Machine Learning models. For businesses, this is a wake-up call that not all AI solutions are sustainable or value-adding in the long run unless they’re developed with a holistic approach.
HolistiCrm emphasizes the importance of building custom AI models grounded in real, customer-validated data. In martech and performance-driven marketing environments, reliance on synthetic data can compromise campaign targeting, personalization, and ultimately, customer satisfaction. Integrating human-supervised learning cycles and maintaining original data sources ensures long-term model robustness and reliable marketing performance.
A relevant use-case: A CRM platform incorporates a Machine Learning model to segment leads based on predicted conversion behavior. Continual retraining on AI-synthesized user data—rather than verified behavioral data—may drift the model away from actual business dynamics. By engaging an AI consultancy to design custom models with integrated human oversight, businesses can maintain accuracy in lead scoring, campaign relevance, and drive revenue growth.
Building AI with discipline, transparency, and quality data generates enduring business value—beyond hype.
original article: https://news.google.com/rss/articles/CBMiY0FVX3lxTE8tb19iM0NxRmI5QmtmSGk5dVNfVzd1cGJxV0Rrb3NxWHdjYXF2R2pMMjNERDhINExublJCSXNxV2tmWFp1VXVweDBrWThuaGl3bGwyaU1JUXppODc3UVVDQks0MA?oc=5
by Csongor Fekete | Jun 16, 2025 | AI, Business, Machine Learning
A groundbreaking AI model is revolutionizing the field of medical diagnostics by accurately identifying over 170 tumor types, including some of the most challenging brain cancers. As reported by Inside Precision Medicine, this machine learning model leverages sequencing-based data to detect rare and hard-to-diagnose malignancies with unprecedented precision. It not only improves diagnostic accuracy, but also enhances early intervention, ultimately boosting survival rates and patient outcomes.
The key learnings from this innovation revolve around the integration of custom AI models into critical decision-making processes. The model’s high performance lies in its ability to analyze complex genomic data holistically, mirroring strategies that can be applied beyond healthcare—in business, marketing, and martech domains.
In the context of CRM and marketing, similar techniques can be used to classify customer behaviors, forecast trends, and personalize outreach with high accuracy. For example, a custom Machine Learning model developed by an AI consultancy or AI agency could identify niche customer segments that are otherwise difficult to distinguish using traditional analytics tools. This intelligence helps marketers design hyper-targeted campaigns, minimize acquisition costs, and significantly improve customer satisfaction.
Just as the medical AI model empowers clinicians with more informed insights, companies can harness AI expert solutions to unlock hidden patterns in customer data, delivering not just better outcomes—but measurable business value.
original article: https://news.google.com/rss/articles/CBMi2wFBVV95cUxOcTlscXpmZEEyOUZ0X2oxSEZranAyVDNoYURuRDNUQzNJOGVxalNlWExqT1FodWRIRWRHWkQxTW83cUR3eDVXc1d0azBSdWRLWTMxdThLM3FRdmZmeC1SRWNXTzVnSkZ0d1VCYnVQM1kzSjk1Wk5kb0UtNHltWVNVV3liMC1oQXY5U3NYbHExX1ZpVnZSZkNESFFsYXdJSndlWFF3N01UNVBESTVHOXA2NWZxUUtLdk9jc1RtUWVSbWs1MTF0WURzZmFWS3V5MlpIb2pxQXdPbzZSN2M?oc=5
by Csongor Fekete | Jun 15, 2025 | AI, Business, Machine Learning
Marketing teams are under-utilizing the full potential of AI, especially in areas that go beyond basic automation, according to a recent article from MarTech. While many teams have adopted AI for content generation and media buying, there are significant gaps in strategic use-cases like customer journey mapping, multichannel personalization, and predictive analytics.
A key learning is that marketing organizations often lack the internal alignment and expertise to implement AI in a holistic way. Most rely on plug-and-play tools that don't cater to their unique data structures or evolving KPIs. This opens space for custom AI models that are purpose-built and designed hand-in-hand with marketing objectives to bring real performance boosts.
One use-case with strong business value is the implementation of a Machine Learning model to predict customer churn by analyzing behavioral and transactional data. Martech leaders can leverage this model to trigger proactive retention campaigns, increasing customer satisfaction and long-term revenue. When paired with precision targeting, such use of AI can reduce acquisition costs and increase ROI — prime goals for any data-driven marketing team.
This highlights the importance of working with an AI agency or AI consultancy equipped to develop context-aware, custom models. Businesses aiming to close the AI utilization gap will benefit from embedding AI experts into their teams and putting data at the center of decision-making.
Read the original article: https://news.google.com/rss/articles/CBMic0FVX3lxTE01R2ZWeHVyTUFpQ0hGb25WU1VlTDJkaVNrbkw4MXpGTHNlaFRtWmVNUXprNW9oS0FXQmFnem03VDZaZmlDYWV1cUd4QnRaSC1yZkJ0c2RzOHhhLVBWc0pXekZWa0p3czJ3NmVQT0ZUX3NGckE?oc=5
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