The Jensen Effect

Sector6  March 18, 2026 The bi-weekly newsletter by AIM that brings the biggest shifts shaping IT, AI, and GCCs. The Jensen Effect At NVIDIA's GTC 2026, Jensen Huang did more than launch new products. He reframed what AI is becoming. The shift may sound subtle, but its implications are enormous. AI is no longer primarily about training models. It is about running them, continuously, at scale, and everywhere.  By Mohit Pandey What Huang outlined is a future where intelligence is produced like electricity, measured in tokens, and consumed in real time. This is the Jensen Effect—the moment when infrastructure, software, and economics align to turn AI from a technical capability into a full-fledged industry. The clearest signal lies in where NVIDIA is placing its bets. The company is moving away from selling chips in isolation. It is now, instead, building full systems designed to generate intelligence at scale.  Huang described data centres not as storage or compute clusters, but as factories. Their output is tokens, the basic unit of AI work. Every response, every action, and every automated workflow becomes a product of this factory. The Vera Rubin platform embodies this shift. It is not positioned as a GPU upgrade, but as a tightly integrated system of CPUs, GPUs, networking, and storage, optimised for inference. That distinction matters. Training created the AI boom, but inference will monetise it. Running models at scale, with low latency and high efficiency, is where long-term value will be captured. This is also where NVIDIA is redrawing competitive boundaries. By introducing its own CPU, Vera, the company is moving deeper into territory long dominated by Intel and AMD.  Alongside hardware, NVIDIA is pushing its Dynamo software stack as the operating layer of these AI factories. Hardware alone no longer defines performance. Gains now come from how efficiently systems generate and distribute tokens. Latency, throughput, and energy efficiency are becoming the metrics that matter most. If the first phase of AI was about building models, the next phase would be about building economies on top of them. This is where agents come in. Huang's keynote made it clear that the interface of computing is changing. Applications are giving way to autonomous systems that can plan, reason, and execute tasks. AI is moving from generating answers to doing work. AIM Network Deep Dive >> In this Front Page episode, we navigate the major announcements from GTC 2026. We dive into the latest 'AI news' and 'tech news' from the event, underscoring NVIDIA's pivotal role in artificial intelligence infrastructure. The conversation highlights key trends in 'AI computing' and the broader 'AI industry' landscape. AIM, RPTech and NVIDIA partner to Host 'GenAI: From Build to Impact' Meetup in Hyderabad Rashi Peripherals Limited (RPTech), an NVIDIA partner, in association with AIM, is hosting GenAI: From Build to Impact, a developer meetup focused on building and scaling real-world generative AI applications, using its DGX Spark™ platform.  The event will showcase how developers can use NVIDIA DGX Spark™, the company's desk-side personal AI supercomputer, to accelerate the generative AI development lifecycle from model experimentation and fine-tuning to high-performance inference. Click here to find out more about GenAI: From Build to Impact The OpenClaw Affect "OpenClaw is number one. It's the most popular open source project in the history of humanity, and it did so in just a few weeks. It exceeded what Linux did in 30 years," Huang said. That comparison is deliberate. Linux technologies did not just improve software but reshaped how it is built and deployed. In Huang's view, OpenClaw has the potential to do the same for agentic computing. Its rapid adoption reinforces the point. Crossing 2,50,000 GitHub stars within weeks signals more than developer interest. It reflects a shift in how software is imagined. OpenClaw can break down tasks, spawn sub-agents, and execute workflows across tools and systems. It turns prompts into processes. However, it also exposes a critical gap. Autonomy without control is not viable in enterprise environments.  This is where NemoClaw comes in. NVIDIA is building the guardrails needed to make agents usable at scale, with sandboxing, policy controls, and secure runtimes. Together, OpenClaw and NemoClaw point to a new stack. One that treats agents as both the interface and the workforce. Huang repeatedly returned to the idea of tokens as a resource.  Companies will allocate token budgets the way they allocate cloud spend today. Engineers with access to more tokens will simply be more productive. Enterprises will both consume and produce tokens, turning AI into a two-sided market. The implications extend beyond software. NVIDIA is pushing AI into telecom networks, industrial systems, and even space. AI-RAN turns telecom infrastructure into distributed compute layers. Satellites and orbital data centres bring processing closer to data sources. Digital twins and simulation platforms make it possible to design AI factories before they are physically built. In creative tools and gaming, the same pattern appears. NVIDIA's work with Adobe on agentic workflows and its push into neural rendering show how structured systems and probabilistic AI are merging. This pattern will repeat across industries. What ties all of this together is a single idea: AI is becoming infrastructure. Huang called this the "Age of Inference". But, perhaps, it is more than that. What we are witnessing is the industrialisation of intelligence. In 2025, Osome tried a different route. Instead of simply adding another feature or two, the company rebuilt its experience based on customer feedback. Read more here. AIM Chess League is here!  AIM has spent years bringing the AI community together through Cypher, MLDS, MachineCon, research, and communities. Now we are launching something new: the AIM Chess League. India's largest chess tournament for AI and tech professionals. One lakh players. Months of competition. The final battle at Cypher 2026. Click here to find out more. Best Firm for Data Scientists – Showcase your leadership in data science and build a thriving workplace. Apply Now Join AIM Leaders Council – Connect with top data leaders and shape the future of AI. Check Eligibility Our Events – Be part of an exclusive event uniting North America's top data leaders. More Details AIM PeMa Quadrant – Discover the best in AI and data services with AIM's PeMa Quadrant. 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