In this episode of Synnth, we delve into NVIDIA's Blackwell platform, a groundbreaking advance in AI and computing efficiency. Named after mathematician David Harold Blackwell, this platform is a leap forward, enabling real-time generative AI on an unprecedented scale with its innovative architecture and six transformative technologies. Explore how Blackwell's 208 billion transistor GPU, crafted with a 4NP TSMC process, is revolutionizing various sectors by significantly reducing the energy and cost footprint of large language models. Discover the impact of trillion-parameter models on industries like healthcare, finance, and autonomous systems, and learn how Blackwell, coupled with the GB200 NVL72 system, is redefining AI's capabilities, offering a glimpse into a future where AI's potential is fully unleashed.
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Join us on this episode of Synnth, a journey through the transformative world of artificial intelligence, where each episode delves into the latest advancements and the brilliant minds shaping the future. From groundbreaking AI models capable of generating videos from text to the philosophical and practical implications of AI in our society, we explore the intersections of technology, policy, and human aspiration. Guided by insights from pioneers like Sam Altman, we discuss how AI could redistribute wealth, reshape economies, and redefine what it means to live in a rapidly evolving digital age. Synnth is your portal to understanding how AI is not just changing the way we live and work, but also offering a vision for a more equitable and prosperous future for all. Tune in to navigate the ever-expanding horizons of artificial intelligence, where innovation meets insight, and where every breakthrough brings us closer to understanding the complex tapestry of our digital and physical worlds.
Welcome to the first episode of Synnth!
Article source & credit: MIT News
What to do about AI in health?
Although artificial intelligence in health has shown great promise, pressure is mounting for regulators around the world to act, as AI tools demonstrate potentially harmful outcomes.
Alex Ouyang | Abdul Latif Jameel Clinic for Machine Learning in Health MIT News - https://news.mit.edu/2024/what-to-do-about-ai-in-health-0123
Reprinted with permission of MIT News - http://news.mit.edu/
