Shun Lin

NVIDIA announced a chip that runs a 120B-parameter AI model locally, plays AAA games at 1440p, and renders 90GB 3D scenes. All on a laptop. Here's what that actually means 👇 At COMPUTEX TAIPEI 2026, Jensen Huang unveiled RTX Spark — a superchip pairing a 20-core Grace ARM CPU with a Blackwell RTX GPU (6,144 CUDA cores), up to 128GB unified memory, and 1 petaflop of AI performance. The pitch: everything you could do in a data centre, now privately on your own machine. How does it stack up against Apple Silicon? Same unified memory idea. Very different execution. → RTX Spark wins on raw AI compute, CUDA ecosystem, and gaming → Apple Silicon wins on memory bandwidth, battery life, and macOS integration Neither is better. They're redefining what a personal computer can be. Swipe through the carousel for the full breakdown ↑ Who do you think wins the AI laptop war — NVIDIA or Apple? Drop it in the comments 👇 #NVIDIA #RTXSpark #AppleSilicon #AI #Computex2026 #TechTrends #ArtificialIntelligence

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NVIDIA CEO Jensen Huang's Bold Prediction: OpenAI Set to Be the Next Multi-trillion Hyperscaler NVIDIA CEO Jensen Huang gives a comprehensive outlook on OpenAI's potential to become a multi-trillion-dollar hyperscaler, fueled by explosive AI infrastructure growth and strategic partnerships. Jensen Huang, the pioneering CEO of NVIDIA, recently shared his insights on the meteoric rise of AI infrastructure and its implications for the future. Huang believes that OpenAI stands at the forefront of an AI revolution that could transform it into a multi-trillion-dollar hyperscaler. According to Huang, "AI is the most powerful technology force of our time, propelling OpenAI to potentially unprecedented heights." AI infrastructure is evolving at an exponential rate, thanks to advancements in computational power and innovative scaling laws. OpenAI is leveraging these advancements to expand its capabilities and explore new frontiers. The company's ability to process vast amounts of data allows it to develop groundbreaking AI models, making it a leading contender in the tech industry's next evolution. The success of OpenAI can be attributed to its strategic partnerships and collaborations with key industry players. These alliances enhance resource sharing, research exchange, and foster innovation. By joining forces with companies like Microsoft and leveraging NVIDIA's cutting-edge hardware, OpenAI is in a prime position to reshape the digital landscape. As AI rapidly advances, the competitive landscape becomes increasingly challenging. OpenAI differentiates itself through a focus on ethical AI development and transparent business practices. By prioritizing responsible AI, OpenAI attracts investments and garners trust from both consumers and industry stakeholders. Scaling laws are a driving force behind OpenAI's enhanced functionalities and operational efficiencies. By utilizing optimized algorithms, OpenAI is able to scale without compromising quality. This transformative approach allows the company to generate AI solutions faster and more efficiently, catering to a wide array of industries. Geopolitical factors play a crucial role in shaping AI development and deployment strategies. As nations vie for technological supremacy, OpenAI's global reach and strategic presence in key markets enhance its standing as a leader in AI innovations. By aligning itself with international standards and remaining adaptable, OpenAI is poised for sustained success. The future of AI is brimming with potential, and OpenAI is well-positioned to capitalize on this opportunity. By continuing to push boundaries and innovate, the company could redefine what is possible in the tech industry. As more breakthroughs occur and AI becomes increasingly integrated into daily life, OpenAI's journey is one to watch. For those interested in exploring further, consider checking out these additional resources: #CurrentTrendsInTechnology Source : Next Big Future

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inference is eating ai. 40%+ of nvidia’s revenue now comes from inference workloads.. jensen huang says it’ll scale “a billion times” as chain-of-thought models go mainstream. the bottleneck isn’t chips anymore. it’s watts….performance-per-watt is the governor. huang claims even if rivals gave GPUs away for free, customers would still pick nvidia because blackwell = 30x more tokens per watt than hopper. what does this mean for the rest of us? 1) if you’re building infra-adjacent: efficiency is your narrative. every buyer cares about energy-per-outcome. 2) sellers need to frame solutions as part of ai factories.. not point tools. buyers want orchestration + integration, not another silo. 3) investors: watch inference-heavy categories and sovereign ai buildouts. this is where the multi-trillion upside lives. plus>> when the c-suite realizes watts = revenue, every board deck will start looking more like an energy strategy than a product roadmap. this is take place as more workflows start to move from human capital to agents — ps > more of this on my substack.. link in comments.

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The future of AI isn’t just about models. It’s about who owns the real-world data layer. Waymo. Zoox. ROVR. Different approaches. Watch the comparison 👇

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