Watch Jensen Huang unveil the latest breakthroughs in AI, robotics, accelerated computing, and more in the #GTC25 keynote. Now live ⬇️.

RT @nvidia: We’re proud to partner with @OpenAI and continue powering the foundation of their work.

RT @NVIDIAEU: 🌱 From energy-efficient architectures to real-world environmental impact, Josh Parker explores how transparency, innovation,….

RT @NVIDIAEU: Join us for an Arabic-language webinar to learn how the Arab world is accelerating AI adoption—from pilot projects to product….

@getalembic Want to understand the future of marketing, AI, and creativity?. 🎙️ Listen to Tomas Puig on the NVIDIA AI Podcast.

@getalembic Why does this matter now?. Because AI is reshaping every function in business. And with it, creative teams can finally prove their value in boardrooms.

@getalembic This tech doesn’t just help with performance marketing. It helps measure and justify the value of bold creative — pop-ups, events, brand campaigns — the things traditional tools overlook. If it drives results, Alembic wants you to see it.

@getalembic Human creativity still matters. Puig puts it bluntly:. “The only thing you can’t increase is a person’s heartbeats.”. Every brand is competing for the same limited attention. AI helps teams focus that effort where it counts most.

@getalembic Their tech stack includes:.⚡ Spiking Neural Networks (SNNs) for detecting patterns over time.🔗 Causal inference for pinpointing what caused a result.🧠 A private compute cluster — not in the cloud — for full control of performance + data. All to answer: “What actually worked?”.

@getalembic Why is this hard?. Because most of the tools we use to measure marketing were built on math from the 1970s. Meanwhile, other industries — like weather, drug discovery, and finance — are using supercomputing and deep learning to model complex systems. Puig asks: Why not.

@getalembic Alembic isn’t just building better dashboards. They’re using AI to help CMOs see the full picture — quantifying the impact of every creative decision, from Super Bowl ads to surprise pop-ups. Why? Because today’s marketers are dealing with incomplete data.

🧵 Marketing is one of the most human parts of business—so what happens when you bring advanced AI into it?. Tomas Puig, CEO of @getalembic, joined the NVIDIA AI Podcast to explain how causal AI and spiking neural networks are turning marketing into a data-driven science. 👇.

📈 93% of retailers are increasing AI investment in 2025. Generative AI is reshaping retail marketing, from smarter content to sharper targeting, it’s powering marketing that resonates. Unpack the trends in the State of AI in Retail and CPG: 2025 Trends report 👉

RT @NVIDIADC: 📣 @CoreWeave announces the deployment of #NVIDIABlackwell Ultra for AI inference at scale. The NVIDIA GB300 NVL72 systems wi….

Smarter and more profitable inference isn’t just about optimization—it’s the new engine of enterprise value in the AI era. As reasoning models grow bigger and more powerful, the cost to run them increases. To stay competitive, AI infrastructure must get more efficient,

🎙️New NVIDIA AI Podcast: Alembic + NVIDIA on the intersection of AI, data, and marketing. 🧠Learn from Tomás Puig, CEO of @getalembic, how advanced #AI and mathematics help brands make faster and smarter #marketing decisions, reduce risks, and invest confidently. 🎧Listen now:

🤖 Industrial work sites can be challenging and hazardous for human workers. See how @anybotics' AI-powered autonomous robots navigate complex environments, capturing vital visual, thermal, and acoustic data to boost safety and productivity. Watch the full video on YouTube ➡️

Data centers put pressure on power grids as demand for AI grows. See how @EmeraldAi_ accelerated by NVIDIA GPUs, lets AI factories flex energy use—reducing power by 25% during grid stress while maintaining performance. This can help reduce grid stress while meeting the

With these laws, physical and agentic AI can autonomously perform multistep reasoning unlocking the smartest and most powerful AI yet. 📖 Learn more:

#3: Test-time scaling uses extra compute during inference to reason through complex problems—like a professional thinking deeply before making a big decision.

#2: Post-training fine-tunes that general knowledge for a specific task—like training to become a doctor, lawyer, or coder.