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Google Cloud: A Front-Row Seat to What’s Next
Cloud Ops

Google Cloud: A Front-Row Seat to What’s Next

From immersive media technologies to personalized retail journeys and life-saving advancements in healthcare, each and every vertical is being transformed by the power of AI. So, what does that mean for industries—and for people? As we consider the ongoing and transformative impact of AI, let’s dive into insights from Google Cloud Next.  “What stood out this year at Google Cloud Next is how AI and agentic technologies are increasingly moving beyond tech and engineering teams. To truly scale, these initiatives must be fully aligned with business goals,” said Harlan Haught, Global Director of the GCP Studio at Globant. “Their success hinges on cross-team alignment and a focus on scalable AI from day one. Globant and Google are committed to helping our shared customers drive measurable value in just 6–8 months, rather than the traditional 1–2 year timeline.” From Insight to Action: Globant’s Take AI is no longer just a tech conversation. It’s a business conversation. As we saw last week, Google continues to optimize its AI models for performance, efficiency, and cost-effectiveness—giving businesses the flexibility to choose the models that best align with their success criteria. But with that flexibility comes complexity, especially when it comes to agentic workflows. To address this complexity, Google has introduced a wealth of pre-built 1P and 3P connectors for agentic AI solutions. However, the demand for industry-specific experiences remains high. As organizations look for tailored, scalable integrations, Globant stands ready to co-create these experiences, helping Google evolve into a true "industry cloud" leader. Globant’s diverse Studios, from Media to Retail, Healthcare to Gaming, are built to deliver AI-powered solutions. Our close collaboration with Google Cloud means we don’t just adopt the latest tech—we help shape how it’s used. Here’s how the latest technologies are leading the way in M&E, Retail, and Healthcare. Media & Entertainment: Designing for Participation, Not just Viewership From streaming services to live sports, the media landscape is constantly evolving. What’s driving it now? Google’s AI video model Veo 2 is raising the bar for creativity. With new advanced editing features like inpainting, outpainting, and interpolation, AI is embedded deeper into the creative workflow. One of the best demonstrations? Its application in producing immersive, cinematic content for Sphere—a testament to Google Cloud’s commitment to the M&E industry. As immersive storytelling gains ground, Globant is reimagining how we experience media. Through metaverse integration and smart stadium experiences (like the groundbreaking Intuit Dome project), we’re helping redefine how fans interact with their favorite teams and shows. We’re no longer designing for viewers. We’re designing for participants. See how we’re doing this with Gen AI and Google Cloud here. Retail: Brands That Understand Shoppers Better Than Ever Hyper-personalized recommendations. Real-time product discovery. Visual search that gets what you mean—not just what you type. These are no longer luxuries—they’re expectations. Globant’s Retail Studio is integrating AI-driven search and recommendation engines powered by Google Cloud to reshape consumer journeys. Retailers can now anticipate needs, respond in real-time, and deliver frictionless experiences both online and in-store. Personalized AI is changing how people shop, and Globant is helping retailers understand not just what people buy, but why they buy—and how to meet them there. From increasing conversion rates to driving long-term loyalty, AI in retail is evolving fast—and Globant is keeping clients ahead of the curve. Healthcare: Humanizing Care with Machine Intelligence In healthcare, the stakes are higher—and so is the impact of AI. AI is helping anticipate patient needs, streamline supply chains, and reduce treatment delays, bringing new levels of precision and care to the industry. Globant is partnering with Google’s technologies to help hospitals and healthcare systems optimize operations and improve patient outcomes. Intelligent AI agents are optimizing supply chain logistics, ensuring that critical medical supplies are available where and when they’re needed. This operational efficiency is vital to delivering timely care and improving quality across the board. It is about AI with a purpose, not just speeding up processes, but saving lives.  Driving Business Transformation through Partnership These transformations aren’t happening in isolation. They’re driven by our deep and long-standing collaboration with Google Cloud. Globant’s partnership with Google Cloud is a 360-degree collaboration that integrates Google Cloud infrastructure with Globant's deep industry expertise to enhance and bolster our ability to deliver at scale. “Being at Google Cloud Next is always a highlight, and this year was extra special—Globant was named 2025 Partner of the Year for Argentina. As the global lead for our Google relationship, this has been one of my most meaningful milestones. We work across the Alphabet ecosystem, from Google Cloud to Verily and automotive, across the US, EMEA, and APAC. Looking ahead, we’re focused on expanding with Google and delivering next-gen tech in the AI Agent space, and more.” — Raveen Mansharamani, Senior Vice President, Strategic Market and Cloud Business at Globant With over 19 years of partnership experience, over 1,000 GCP certifications, and industry-specific solutions with Data, Predictive AI, Generative AI integrations, infrastructure, and migrations—Globant and Google catalyze enterprises’ digital transformations and deliver next-generation digital products and experiences. Shaping the Future, Together with Google Cloud As AI continues to accelerate change across industries, partnerships like Globant and Google Cloud are critical to turning emerging technologies into real-world outcomes. From entertainment to retail to healthcare, we’re not just witnessing transformation—we're building it. Together, we're delivering business results, reshaping experiences, and preparing organizations to lead in a world shaped by AI-driven intelligence and personalization.

Beyond the Screen: Digital Transformation in Media That’s Impacting Customer Experience
Data & AI

Beyond the Screen: Digital Transformation in Media That’s Impacting Customer Experience

As consumers seek more hyper-personalized and hyper-scalable experiences, decision-makers in the media and entertainment industry are looking for ways to maximize the monetization of their assets and optimize costs. From virtual production and experiential entertainment to the usage of AI in almost every step of the chain, the sector is in an ever-evolving landscape that forces providers to think outside the box to remain competitive. Let’s take a look at some of the trends that are already shaping the future of media and entertainment and how their impact will remain tangible for the days to come. AI Takes the Spotlight: Revolutionizing Content and Engagement AI stepped out from behind the curtain and into the spotlight. This trend in media coincides with a much-needed mentality shift now that AI is much more prevalent across industries in our daily lives. “As a society, I think we tend to overestimate the impact of smart new technologies in the short term and underestimate their impact in the long term,” explains Globant’s Chief Technology Officer of North America, Nicolas Avila. “We need to assimilate the fact that the changes are going to be gradual, and one day we’ll wake up and realize—wow, AI has changed almost everything.” While process optimization remains a high priority for media and entertainment leaders, more and more suppliers are shifting to innovative uses of AI. This impacts areas like content creation, distribution, and audience engagement. AI speeds the analysis of various different data points for each individual, including user behavior, personal preferences, and viewing or listening history. After processing all this data, AI systems can provide tailored recommendations for all kinds of content, promotions, and ads to keep users engaged. Accelerating content production tied to tight timelines, AI also makes content distribution more accurate and efficient and bolsters monetization. For instance, AI in media predicts the best release schedules and platforms for maximum reach. AI in content creation is becoming the industry standard, with a predicted market growth of $22 billion. This is because it allows creators to produce high-quality content more swiftly in areas like scriptwriting and video editing, increasing efficiency.     But that’s not all: within the AI world, AI Agents are also enhancing media production workflows and audience interaction. Virtual Agents and assistants garner customer support, with 51% of consumers preferring an interaction with bots over humans when they need an immediate response. They also identify high-probability leads and optimize customer engagement by analyzing behavioral patterns. In addition, these Agents also streamline ad spending based on real-time performance metrics and identify the most relevant audience segments for specific campaigns. Major players are already investing in the opportunities and considering the risks associated with these emerging technologies—it’s time to decide to stay relevant or be left behind. “Proactive AI policies are essential, especially when it comes to copyrights for AI-generated content. We need human involvement in order for content to be protectable. AI should be a tool that enhances human creativity.” -Pablo Peranzola, Global VP of Technology, Globant. The Rise of Immersive Experiences: Blurring the Lines Between Digital and Physical One of the major trends is the realm that blends the physical and the digital worlds. As consumers seek more authentic, immersive, and interactive experiences, companies are investing in location-based entertainment to capture this momentum. From concerts to art exhibitions, immersive experiences are not only making a comeback but becoming more essential as parts of experiential assets in the industry. One outstanding example is Intuit Dome, the LA Clippers’ smart stadium built in partnership with Globant that completely innovates the fan experience. Globant's vision started with a simple idea: making the entertainment experience as frictionless as possible, from ticket purchase to personalized game day experiences. Together, they created an end-to-end technology stack with over 500 features, including fan profile-based experiences, a smart entry system with biometric data, grab-and-go technology for purchases inside the arena, and customized promotions and content. With a global market value of almost $1.9 billion, immersive experiences combine storytelling with cutting-edge technology to elevate consumer experiences to the next level. “Within the last few years the industry has made big strides, with better venue experiences to understand fans in a different way that creates a whole ecosystem within which we can better connect with fans.” -Nicolas Avila, CTO of North America, Globant. The New Era of Sports Broadcasting: Innovation Beyond the Stadium Cable television, in addition to old movies, has always had one thing in common: sports broadcasting. Nowadays, it’s still a must-have content for streaming providers, with the diversification of content keeping fans at the edge of their seats. Sports bundles, high-profile events, and on-demand broadcasting are some of the main trends shaping this innovation, with the integration of technology at the forefront to facilitate discovery and viewability.  Immersive technologies like augmented reality (AR) and virtual reality (VR) promise stadium-like views from anywhere, with an opportunity to personalize the fan experience even more. The strategic implementation of technology in the sports media value chain can unlock new revenue streams. For instance, AI can personalize content delivery, provide real-time game analysis and predictions, and create interactive fan experiences. Broadcasters and streaming platforms can engage new audiences and expand their reach by investing in dedicated coverage, such as women’s sports and emerging leagues. This includes tailoring advertising and sponsorship offerings to specific audience segments and identifying opportunities for premium content and experiences. Hybrid subscription models that combine elements of traditional subscriptions with flexible options can cater to the diverse preferences of consumers and ensure their continued engagement with sports media content. Digital-first platforms are dominating the market as major players secure broadcasting rights. A significant portion of global sports rights spending will be contributed by streaming platforms, reaching $12.5 billion.   “Sports in media, like so many other industries, is going through an interesting transformation. Traditionally, sports media was far removed from the consumer, and they didn’t know who was watching—they didn’t have visibility into their fanbase. And if they don’t know, they certainly can’t quantify it for better or stronger sponsorship. Now, they can focus on that connection and show sponsors the attribution.” -Nicolas Avila, CTO of North America, Globant. But as exciting as these trends can be, there are challenges surrounding their adoption. From ethical concerns to implementation costs, providers need to proceed with caution to leverage these technologies without disrupting existing operations or provoking rejection from their human teams. The goal is for human and AI Agent teams to synergize, becoming the workforce of the future. Some strategies to navigate this digital transformation include: A culture of continuous learning and upskilling: Investing in training programs that enhance employees’ digital competencies is crucial to keeping up with technology adoption and empowering staff to collaborate effectively with it. Promotion of human-AI collaboration: Finding the balance between AI’s handling of routine tasks and human expertise that guides creative and strategic decisions is essential to fostering trust and effective implementation of these technologies.  Implementation of inclusive change management practices: Involve diverse teams in the decision-making process and ensure that digital tools and workflows are accessible to all employees, fostering a culture of inclusivity during technological transitions.   Following these strategies will facilitate a seamless transition in the M&E sector, leveraging technology to enhance human capabilities and propel the industry to new, innovative heights. Thriving in the Evolving M&E Landscape The rapid advancement of technology and the increasing demand for superior user experiences, characterized by high quality and low latency, are driving significant changes in the media and entertainment landscape. As Globant’s Global VP of Technology Pablo Peranzola explains: "In order to navigate the complex technological ecosystems in the M&E industry, partnerships are essential. Collaborating with specialized organizations allows M&E companies to streamline operations, eliminate waste, and enhance efficiency, ultimately fostering innovation to meet market demands.” Also, the emergence of new players, such as sports companies, further intensifies the complexity of the ecosystem of platforms and solutions required to deliver these enhanced experiences. In this landscape, studios and providers need to remain competitive, but only those that move away from a traditional mindset and become global, diverse, and technology-driven players will be able to thrive. This approach was palpable on the floor at NAB 2025, where we had the opportunity to highlight our collaboration with AWS to deliver value across broadcasting and content production, sportainment engagement, media supply chain, and analytics. We also participated at the Microsoft booth, where we showcased our work in the sports industry, including our role as Intuit Dome’s digital transformation partner. At Globant, we specialize in creating frictionless, integrated solutions that resonate with even the most demanding audiences, taking media and entertainment companies ahead of the curve to deliver the smartest innovations across the globe. Check out what we can do for your company here.

Smarter AI for Specific Domains: How RAFT Supports Cancer Immunotherapy Research
Data & AI

Smarter AI for Specific Domains: How RAFT Supports Cancer Immunotherapy Research

In recent years, advancements in medical technology have captured our attention, but while they might represent breakthroughs in the industry, their applications may come with hefty challenges. Now, imagine the potential of every new discovery powered by an AI tool that not only understands complex medical text but also adapts to a specific domain. This is the promise of Retrieval-Augmented Fine Tuning (RAFT), an alternative to big tech, more generalist Large Language Models (LLMs), which has proven to perform better for certain use cases and domains by adapting a smaller model to different sectors. In this case, healthcare. This is especially important in specific areas, such as cancer immunotherapy, where different treatment protocols and patient data points are involved. In this context, organizations need AI solutions that can deliver precise answers while keeping sensitive information completely in-house. But does RAFT comply with these demands? In a recent research by Globant Enterprise AI’s technical team, they found interesting conclusions that answer this and more questions. Why Cancer Immunotherapy Needs Smarter AI Cancer immunotherapy utilizes the body’s immune system to combat cancer cells. Unlike traditional treatments, immunotherapy aims for a more targeted approach, potentially resulting in fewer side effects. That’s why the selection of this domain for the research was strategic, considering both its clinical importance and the highly sensitive, private nature of patient data involved in immunotherapy protocols. RAFT is a method that cleverly addresses these needs by fine-tuning smaller AI models for specialized tasks. Think of it as teaching a “small-yet-mighty” model more domain-specific knowledge, which other models may lack, so it can become an expert in cancer immunotherapy, or other industry-specific domains, without hogging resources. In a nutshell: Fine-tuning = The process of further training a pre-trained model on a specific dataset to specialize it for a particular task. In this instance, the specialization is for cancer immunotherapy.  Retrieval = Giving the model a “library” of specific, domain-relevant information whenever it needs it—like a digital reference desk. This approach allows organizations to maintain control over their data while still benefiting from advanced AI capabilities, reducing computational costs and minimizing the risk of data exposure.  Surpassing the “Big Guys” One of the study’s conclusions is that these models could achieve competitive performance compared to larger commercial models, demonstrating the potential for cost-effective and efficient AI solutions in healthcare. It’s kind of like a skilled craftsperson who masters a single, specialized trade rather than trying to do every job in the shop. By honing in on domain-specific data and carefully tuning the model’s parameters, the RAFT method allows these smaller AI systems to handle highly technical questions with remarkable accuracy, often at a fraction of the cost and computational load.  Even better, when plugged into a Retrieval-Augmented pipeline, these models consistently stay on point thanks to relevant medical references on the spot. This means they’re less likely to “hallucinate” answers, a common pitfall with large, generic AI systems. That’s huge news for businesses looking to reduce costly infrastructure needs, keep data completely under their own roof, and still deliver the same—or better—caliber of detailed, precision-focused answers. Globant Enterprise AI: Where Innovation Meets Accessibility This initiative was integrated into the Globant Enterprise AI (GEAI) platform, which serves as a hub for delivering advanced AI capabilities to clients. Through this exploration, Globant’s team aimed to refine their processes and enhance their ability to offer customized, efficient, and secure AI solutions that meet the specific needs of various industries. With multi-cloud capabilities and a design that effortlessly fits into enterprise environments, GEAI ensures businesses can seize the power of RAFT-ready models.  RAFT represents a new wave in AI, one where targeted expertise, budget-friendly deployments, and robust data privacy come together. Particularly for a field like cancer immunotherapy, but with the potential to expand to many more, this means faster and more accurate insights, minus the worries of sending sensitive patient information elsewhere. Organizations ready to harness AI breakthroughs for real, impactful change are primed to boost their edge with RAFT. And with Globant Enterprise AI on your side, you’ll have the tools and flexibility to bring these innovations to life, securely and scalably. Read the full research here and find out what Globant Enterprise AI can do for your business.

The future of investments is in the hands of AI Agents. Learn how they are changing the game.
Data & AI

The future of investments is in the hands of AI Agents. Learn how they are changing the game.

In the field of investment management, the use of AI is not just a passing trend, but a momentous change in the way investors analyze data, predict market trends and manage investment portfolios. The need for efficiency and accuracy in a fast-paced financial environment is driving companies to adopt this technology, which experienced 81.4% year-on-year growth in 2024.  AI Agents, fueled by data, minimize human error through algorithms, Machine Learning (ML) models and Natural Language Processing (NLP), producing fast, real-time results, updated to market needs. At Globant, our Investor Agent harnesses the power of data to perform in-depth analysis, allowing investors to navigate the financial market effectively and make increasingly informed and confident decisions. How our Investor Agent works to transform your investments The Investor Agent was designed to enhance investment strategies and maximize returns through advanced data analysis and complex Machine Learning algorithms. This AI Agent analyzes portfolios and the market in real time, provides data-driven recommendations, compares investment options and suggests specific actions to optimize returns and reduce risks. It's like a round-the-clock financial advisor who provides intelligent insights, eliminates guesswork and ensures superior performance through quick decisions. Investors gain a more strategic, informed approach and can better manage resources. AI as an ally in making financial decisions Investment management is evolving towards a greater reliance on AI Agents, leaving time and space for financial sector leaders to focus on more strategic tasks. The evolution of AI is marked by the emergence of advanced architectural models that promise to enhance the abilities of Machine Learning and Deep Learning and impact various sectors, including finance. While AI Agents perform more operational tasks, leaders will use these tools to drive the business to success. At Globant, we're leading this technological transformation, developing AI Agents that enable investment firms to quickly adapt to an increasingly competitive environment. Our approach integrates the latest in Machine Learning algorithms and models to help investors make informed, data-driven decisions with the goal of maximizing returns and reducing uncertainty. Ready to take your portfolio to the next level? Find out here how to make every decision count.

AI-Powered QMS Revolution for Medical Device Software
Data & AI

AI-Powered QMS Revolution for Medical Device Software

In today’s world, it’s nearly impossible to imagine an advanced medical device without software at its core. Whether the software is integrated into the device (SiMD) or is the device itself (SaMD), it is the driving force behind groundbreaking innovations that enhance patient care and operational efficiency. However, developing software for medical devices is a complex and rigorous process, as it must comply with strict regulatory standards to ensure safety and effectiveness. To understand the challenges and how we can address them, let's explore the role of large language models (LLMs) in transforming this process. Enhancing QMS Efficiency with LLMs Creating software for medical devices requires careful planning and extensive documentation. This documentation is managed through a quality management system (QMS)—a formalized framework outlining the structure, processes, roles, and procedures needed for effective quality control. A QMS includes key policies, procedures, forms, work instructions, and records that provide evidence that the system is being followed. For medical device manufacturers, it is essential that the QMS aligns with international standards to meet regulatory requirements in different markets. This results in a labor-intensive process, generating vast amounts of documentation that is often difficult to manage efficiently. Large language models (LLMs) have emerged as a transformative solution to manage exactly this type of challenge. They can process and generate large volumes of unstructured text quickly, offering the potential to reduce time that manual document creation takes and to enable real-time updates as global and regional regulations evolve. Imagine a system where a chain of AI agents works together seamlessly: one monitors and references regulatory guidelines; another compares these guidelines to the specific needs of a device; a third uses examples of past QMS documents to create new ones; and yet another analyzes design requirements to propose a risk matrix. Additionally, different AI Agents could be dedicated to different document types—such as the overall QMS, standard operating procedures, or software development plans—all working in concert to produce a fully compliant system. Reducing QMS Development Time: AI-Driven Innovation in Medical Software Traditional QMS development processes can take weeks or even months, especially in the case of complex medical software projects. From the initial document creation to full QMS implementation, the timeline can range from three to nine months. Given the complexities of regulatory compliance, this process is ripe for innovation. In life sciences, LLM-powered solutions have already been demonstrated to deliver significant time savings. For instance, leveraging its Globant Enterprise AI platform, Globant developed an AI Agentic solution to produce compliant marketing copy for Organon LAMEX, a leader in the pharmaceutical industry, resulting in 80% efficiency gains. This success suggests that a similar strategy could greatly accelerate the creation of a compliant QMS for medical device software. A Step Toward Revolutionizing QMS Development Admittedly, integrating LLMs into QMS development is not without challenges. Accurately interpreting complex regulations and ensuring the precision of generated documents remain significant concerns. Although advances in LLM technology have improved performance, human oversight will still be essential to guarantee quality and compliance. Nonetheless, the potential benefits are substantial, and the time to begin piloting this innovative approach is now. By embracing these strategies, businesses can move beyond traditional documentation methods and harness the full analytical and predictive power of LLMs, ultimately accelerating the development of safe and effective medical software. Discover more about LLMs applications in Healthcare & Life Sciences here.

What GTC 2025 Taught Us: Key Innovations and Globant’s Bold Bet on the Future
Data & AI

What GTC 2025 Taught Us: Key Innovations and Globant’s Bold Bet on the Future

Artificial intelligence is not the future—it is the present. And at GTC 2025, NVIDIA’s flagship event, this became clearer than ever: we are witnessing a new era where AI is redefining creativity, science, and business. From the moment Jensen Huang took the stage, the atmosphere buzzed with the promise of innovation. But among the groundbreaking technological revelations, a key question emerges: how can we harness this power to transform entire industries? At Globant, we are not just looking for answers—we are building that future. A Roadmap That Marks a Before and After In an unprecedented move, NVIDIA unveiled its roadmap for the next three years, revealing not only the chips set to launch this year but also those planned for 2026, 2027, and 2028. This marks a key strategic shift, as the company has never before been so transparent about its long-term plans. The structure is clear: in even-numbered years, we will see new processor architectures, while in odd-numbered years, improved versions of those technologies will be released. Last year, Blackwell was introduced; this year, Blackwell Ultra, and the trend will continue with incremental improvements and technological leaps in each cycle. This announcement not only reinforces NVIDIA’s position as a leader in accelerated computing but also provides a clear vision of how hardware will develop in the coming years, enabling companies like Globant to anticipate strategies and maximize these innovations. Beyond Computing: Toward Intelligent Connectivity What stood out most at GTC was not just NVIDIA’s continued push for raw computing power but its focus on the efficiency of distributed computing. It’s not just about faster processors but about how they communicate to operate as a unified intelligent system. A key announcement was the new hardware layer for network management and data transfer. Why is this so relevant? Because it not only enhances the speed and efficiency of current processing but also touches on one of the biggest future challenges: quantum computing. For quantum computing to become viable, we will need networks capable of operating at a quantum level, allowing multiple machines to work together as a single entity. This is crucial in a world where AI underpins everything from autonomous robots to intelligent systems making real-time decisions. While some AI processes occur directly on the device (on edge), others require connectivity to servers for collaborative data processing. NVIDIA and the Future of Networking: A Global Supercomputer NVIDIA is not just driving AI; it is also redefining the infrastructure that makes it possible. Its investment in high-performance networking aims to make data centers function as a single massive machine, maximizing efficiency and scalability. How is this achieved? Through advanced optimization of fiber-optic networks, reducing costs, energy consumption, and eliminating waste. Every watt not used in computing is wasted power, and in a world where energy is a scarce resource, every optimization matters. Jensen Huang made it clear that the future of computing depends not just on faster chips but also on smarter, more efficient networks. And NVIDIA is leading the way. Globant’s Key Initiatives at GTC Every breakthrough from NVIDIA redefines the industry and opens new opportunities. At Globant, we don’t just adopt these innovations—we enhance them. Digital Twins + AI: Modeling the World in Real-Time Our Digital Twins Studio combines AI with our expertise in gaming and immersion to create hyper-realistic virtual environments. From digital factories to Digital Humans, AI-driven 3D representations that interact naturally, this technology is revolutionizing industries. Physical AI and Robotics: Bringing AI to the Physical World Beyond software, AI is taking shape in autonomous robots and physical assistants. Globant has the expertise to develop solutions in this space that align with NVIDIA’s vision. Globant’s Innovations at GTC DocCast: From Reports to Intelligent Podcasts We leveraged NVIDIA’s Blueprint PDF to Podcast framework and enhanced it, enabling interaction among multiple voices in a dynamic format. VoiceShield: Advanced Conversational AI Security We developed an intelligent voice agent with NVIDIA Guardrails to prevent manipulations and attacks, ensuring secure interactions in contact centers and virtual assistants. Globant and NVIDIA are merging accelerated computing, AI, and immersive experiences to transform industries. And this is just the beginning. "In just one year, we have become a key player shaping NVIDIA's tech stack. We’re not just part of the conversation—we’re helping define the future." — Agustin Huerta, SVP of Digital Innovation at Globant The Future is Written at GTC, and Globant Holds the Pen GTC is not just a conference—it is the compass that guides the future of computing. Jensen Huang continues to push the boundaries of the industry, and at Globant, we align with that vision, exploring how these technologies can transform industries and revolutionize AI, robotics, and networking. Beyond the announcements, GTC reflects NVIDIA’s evolution from a graphics-focused company to an AI titan. This transition has expanded its audience from hardware manufacturers to software companies, professional services, and sectors like automotive and manufacturing. Balancing the event’s content remains challenging, but its impact is undeniable. For Globant, this was our second GTC as an NVIDIA partner, and the difference was tangible: more than spectators, we were key participants, actively collaborating in crucial spaces such as the AI Council for Enterprise Software and the GNI Tech Champion initiative. Additionally, our technical feedback has influenced the development of NVIDIA’s tech stack. We have witnessed how ideas we shared last year have been adopted and transformed. This strengthens not just our relationship but also our role in the evolution of AI and enterprise computing. Ultimately, GTC is not just an event—it is where the future is built. And Globant is ready to lead this transformation.

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