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Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
Germany Oct 20, 2025 Country Members Virtual german
Die Realisierung des Potenzials von KI und datengesteuerten Strategien stellt nicht länger nur einen Wettbewerbsvorteil dar, sondern ist Heute auch entscheidend für den langfristigen Erfolg eines jeden Unternehmens. Unsere Wissensaustausch-Briefings "AI & Data Knowledge Transfer" zielen darauf ab, CIDOs und Senior Digital Leaders praktische Anwendungen aufzuzeigen und umsetzbaren Erkenntnissen von Fachexperten zu vermitteln, die den Weg für die transformative digitale Reise ebnen und beschleunigen.
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Belgium Oct 21, 2025 Invitation Only Physical english
In today's competitive landscape, customer expectations have never been higher. They demand a personalised, seamless experience at every touchpoint, from initial marketing contact to post-sale service. Unified data is at the heart of creating engaging customer experiences and is meant to fuel the 360 profile. However, for many organizations, a complete picture of the customer is fragmented, with critical data scattered in disconnected systems and departments. This exclusive roundtable will bring together Digital Leaders active in multiple industries to discuss a critical challenge: breaking down data silos to build a true 360° view of the customer. We will explore how to solve the complex integration challenges that prevent a unified view, and how to transform disparate data into a single source of truth. Join us to: Discover how to overcome the technical hurdles of integrating critical business systems, such as ERP and CRM platforms, to unify customer data. Explore real-world case studies on how organisations have successfully created unified customer insights to enhance personalisation and boost commercial and operational efficiency. Discuss best practices for turning fragmented data into actionable insights that can anticipate customer needs, drive revenue growth, and foster long-term loyalty. This is a unique opportunity for Digital Leaders who are ready to transform their customer engagement strategy and unlock the full potential of their data.
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Spain Oct 22, 2025 Country Members Physical spanish
Descubre cómo las organizaciones están utilizando la tecnología para impactar en el negocio a través de casos reales de uso y aprendizajes clave en áreas como ciberseguridad, automatización o data, contados por los protagonistas. Un espacio diseñado para inspirarte, conectar con expertos y potenciar la innovación en tu organización.
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Belgium Oct 22, 2025 Invitation Only Physical english
Enterprises are questioning whether private networks and stacked firewalls are still worthwhile investments. A newer approach operates on the open internet with Zero Trust, eliminates perimeter complexity, and reframes cybersecurity as a business performance metric for boards and audit committees. This is a closed-door, peer discussion, not a lecture. We’ll examine the promise and its pitfalls: Are the promised savings significant, or are they too good to be true? What risks do you introduce? How does this collide with your installed base, legacy OT, entrenched processes and team competencies, and how do you overcome that without breaking operations or credibility with the board? Two senior leaders from global companies will spark the dialogue with lived experience: Kurt De Ruwe, CIO AkzoNobel Frank Bolata, CIO Syensqo
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Poland Oct 23, 2025 Invitation Only Physical Polish
Cloud UP! ’25 to miejsce spotkań managerów, którzy chcą świadomie i skutecznie rozwijać swoje organizacje, wykorzystując najnowsze technologie. Nieformalnym hasłem tegorocznej edycji jest “Chmura gotowa na AI” - będziemy rozmawiać o tym, co sztuczna inteligencja naprawdę potrafi oraz pokazywać, jak wdrażać ją w praktyce. Wspólnie z ekspertami przeanalizujemy, jakie warunki muszą zostać spełnione, aby wdrożenia AI były zarówno skuteczne, jak i bezpieczne. Zerkniemy za kulisy najnowszych rodzimych produktów AI-owych, by zobaczyć ich możliwości, a także poznamy najciekawsze wdrożenia z wykorzystaniem Agentspace. Po raz kolejny spotkamy się w formule Share.Explore.Execute. Stawiamy na wymianę wiedzy i doświadczeń zdobytych podczas realizacji projektów. To one stanowią punkt wyjścia do odkrywania, testowania i skutecznej implementacji najlepszych rozwiązań w organizacjach. Cloud UP! ’25 to cztery ścieżki tematyczne, na które złożą się prezentacje, rozmowy, sesje live-demo oraz pogłębione dyskusje w formule roundtables: AI: Beyond the Hype Data Mastery Resilience & Regulatory Advanced Practitioners Dołącz do liderów chmurowych innowacji w Polsce i spotkaj się z nami już 23 października w Event Hall w Fabryce Norblina.
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Belgium Oct 23, 2025 Invitation Only Physical english
How to lead responsibly when technology can deceive better than a human? AI’s ability to shape our perceptions and create new realities is becoming increasingly sophisticated. While it opens significant opportunities, it also carries risks. What happens when AI goes beyond data and algorithms to influence - or even deceive - our senses? How does this change not only our understanding of reality but also the foundations of trust, creativity, and truth in business? AI isn’t just transforming business, it is altering how we experience and interpret everything around us. From AI-generated deepfakes to personalised experiences designed to influence behaviour, the line between truth and illusion is increasingly blurred. This event combines a roundtable discussion among peers with a hands-on sensory workshop, where you will experience illusions through sight, sound, taste, smell, and touch. Through these experiments, we will confront the ethical dilemmas that arise when AI has the power to fabricate realities and influence decisions.
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How Cohere is accelerating language model training with Google Cloud TPUs
Cohere is accelerating LLM training with Google Cloud TPUs to provide larger and more accurate LLMs to developers.
Machine Learning Engineer, Cohere
Sr. Product Manager
Over the past few years, advances in training large language models (LLMs) have moved natural language processing (NLP) from a bleeding-edge technology that few companies could access, to a powerful component of many common applications. From chatbots to content moderation to categorization, a general rule for NLP is that the larger the model, the greater the accuracy it’s able to achieve in understanding and generating language.
But in the quest to create larger and more powerful language models, scale has become a major challenge. Once a model becomes too large to fit on a single device, it requires distributed training strategies, which in turn require extensive compute resources with vast memory capacity and fast interconnects. You also need specialized algorithms to optimize the hardware and time resources.
Cohere engineers are working on solutions to this scaling challenge that have already yielded results. Cohere provides developers a platform for working with powerful LLMs without the infrastructure or deep ML expertise that such projects typically require. In a new technical paper, Scalable Training of Language Models using JAX pjit and TPUv4, engineers at Cohere demonstrate how their new FAX framework deployed on Google Cloud’s recently announced Cloud TPU v4 Pods addresses the challenges of scaling LLMs to hundreds of billions of parameters. Specifically, the report reveals breakthroughs in training efficiency that Cohere was able to achieve through tensor and data parallelism.
This framework aims to accelerate the research, development, and production of large language models with two significant improvements: scalability and rapid prototyping. Cohere will be able to improve its models by training larger ones more quickly, delivering better models to its customers faster. The framework also supports rapid prototyping of models that address specific objectives — for example, creating a generative model that powers customer-service chatbot — by experimenting and testing new ideas. The ability to switch back and forth among model types and optimize for different objectives will ultimately allow Cohere to offer models optimized for particular use cases.
The FAX framework relies heavily on the partitioned just-in-time compilation (pjit) feature of JAX, which abstracts the relationship between device and workload. This allows Cohere engineers to optimize efficiency, and performance by aligning devices and processes in the ideal configuration for the task at hand. Pjit works by compiling an arbitrary function into a single program (an XLA computation), that runs on multiple devices — even those residing on different hosts.
Cohere’s new solution also takes advantage of Google Cloud’s new TPU v4 Pods to perform tensor parallelism. which is more efficient than the earlier pipeline parallelism implementation. As the name suggests, the pipeline parallel approach uses accelerators in a linear fashion to scale a workload, like a single long assembly line. Accelerators must process each micro-batch of data before passing it along to the next one, and then run the backward pass in reverse order.
Tensor parallelism eliminates the accelerator idle time of pipeline parallelism, also known as the pipeline bubble. Tensor parallelism involves partitioning large tensors (mathematical arrays that define the relationship among multiple objects such as the words in a paragraph) across accelerators to perform computations at the same time on multiple devices. If pipeline parallelism is an ever-lengthening assembly line, tensor parallelism is a series of parallel assembly lines — one making the engine, the other the body, etc. — that simultaneously come together to form a complete car in a fraction of the time.
These computations are then collated, a process made practical thanks to Google Cloud TPU v4 VMs, which more than double the computational power of their v3 predecessors. The superior performance of v4 chips has enabled Cohere to iterate on ideas and validate them 1.7X faster in computation than before.
Aidan Gomez, CEO and co-founder, Cohere
As part of a multiyear technology partnership, Cohere leverages Google Cloud’s advanced AI and ML infrastructure to power its platform. Cohere develops and deploys its products on Cloud TPUs, Google Cloud’s custom-designed machine learning chips that are optimized for large-scale ML. Cohere’s recently announced their new model improvements and scalability by training an LLM using FAX on Google Cloud TPUs, and this model has demonstrated that transitioning from TPU v3 to TPU v4 has so far enabled them to achieve a total speedup of 1.7x . In addition to a significant performance boost, TPUs provide an excellent user experience with the new TPU VM architecture. Importantly, Google Cloud ensures that Cohere's state-of-the-art ML training is achieved with the highest standards of sustainability, powered by 90% carbon-free energy in the world's largest publicly available ML hub.
By adopting Cloud TPUs, Cohere is making LLM training faster, more economical, and more agile. This helps them provide larger and more accurate LLMs to developers, and put NLP technology in the hands of developers and businesses of all sizes.
To learn more about these LLM training advances, you can read the full paper, Scalable Training of Language Models using JAX pjit and TPUv4. To learn more about Cohere's best practices and AI principles, you can check this article co-authored with Open AI and AI 21 Labs.
Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
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Isabelle Droll - CIO for Airline, Corporate, Hotels & Resorts and Sustainability at TUI - Data, Diversity, and Destinations
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Sharon Prior - CIO in transition - How Great Tech Leadership Begins with Business Thinking
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José Antonio López, Group CIO at TOUS - Jewels, Data & AI: Inside the Digital Transformation of TOUS
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Tom Tanghe - General Manager ITC EMEA at Daikin Europe - Reinventing the CIO Role
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CIOFEST 2025 - From Order Taker to Proactive Disruptor
The role of the CIO has evolved from managing systems to shaping outcomes: growth, resilience, and competitive edge are now won or lost in the technology arena. Today ’ s CIOs must balance stability with innovation, control costs while attracting scarce talent, and modernise legacy infrastructure while adopting emerging technologies.
As AI transitions from a specialised tool to an all-pervasive force, understanding its profound implications for our human lives is no longer merely academic but an urgent imperative for social well-being and strategic preparedness.
Geopolitical tensions have dominated the headlines for over two years now. In this context, the cyber threat landscape is also evolving rapidly. The protection and security of critical infrastructure – both physical and digital – is becoming increasingly important.
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