GPU Technology Conference Keynote Oct 2020 | Part 4: "AI: Software that Writes Software"

TL;DR

AI is rapidly advancing, with increasing complexity and capabilities, as shown by the exponential growth in computation required to train state-of-the-art models. NVIDIA is democratizing AI and expanding its reach to more industries and cloud service providers.

Transcript

AI is writing software that achieves results no human-written software can. The scalability of this approach has started a race to create ever larger, more complex and more capable AI. The chart shows the number of days to train a model on a 1 PetaFLOPS computer. Computation required to train state-of-the-art models has increased 30,000 times in ... Read More

Key Insights

• 🚂 AI models require exponentially increasing amounts of computation to train, showcasing the rapid growth and complexity of the field.
• ✈️ NVIDIA has developed remarkable AI applications in various domains, including natural language understanding, quantum chemistry, and drone flight control.
• ❓ The democratization of AI through NVIDIA's offerings empowers companies and researchers to utilize AI more efficiently and effectively.
• 🫠 The scalability and capabilities of AI are evident in reading comprehension tests, where AI surpassed average human scores.
• 🥺 AI has the potential to revolutionize industries like healthcare, robotics, video conferencing, and fraud detection, leading to significant cost savings and improved user experiences.
• 😶‍🌫️ NVIDIA's presence in the AI market continues to expand, with their AI inference compute surpassing that of all cloud CPUs.
• 😶‍🌫️ The integration of NVIDIA's NGC platform into major cloud service provider marketplaces ensures consistent and optimized AI performance.

Questions & Answers

Q: What is the exponential growth in computation required to train state-of-the-art AI models?

The computation needed to train such models has increased 30,000 times in less than five years, doubling every couple of months. This demonstrates the scalability and complexity of AI development.

Q: How does NVIDIA's AI technology perform on reading comprehension tests compared to humans?

NVIDIA's Natural Language Understanding AI achieved a score of 91% on the RACE reading comprehension test, outperforming the average human score of 73%. Although expert humans scored 95%, it demonstrates the high capabilities of AI in this domain.

Q: How has AI been utilized in quantum chemistry?

Researchers at Caltech have successfully used deep learning in quantum chemistry to predict molecular-protein reaction energy. This advancement has accelerated simulations by 1000 times, showing the potential of AI in the field.

Q: What AI-related services does NVIDIA offer for cloud service providers?

NVIDIA provides AI application frameworks, pre-trained models, transfer learning tools, and runtime engines to support self-driving cars, robotics, drug discovery, conversational AI, and recommender systems. Their NGC cloud platform is being integrated into Azure, AWS, and GCP marketplaces.

Summary & Key Takeaways

• AI is evolving at an unprecedented pace, with models requiring 30,000 times more computation to train in just five years.

• NVIDIA has developed remarkable AI applications, such as natural language understanding, drone flight control, quantum chemistry prediction, and protein structure prediction.

• NVIDIA offers three pillars of AI: data processing and training, inference with tools like TensorRT and Triton Inference Server, and AI application frameworks for various industries.