NVIDIA Launches NIM Microservices for Generative AI in Japan, Taiwan

by Latest Updates

NVIDIA Launches NIM Microservices for Generative AI in Japan, Taiwan

Nations around the world are pursuing sovereign AI to produce artificial intelligence using their own computing infrastructure, data, workforce and business networks to ensure AI systems align with local values, laws and interests.

In support of these efforts, NVIDIA announced the availability of four new NVIDIA NIM microservices that enable developers to more easily build and deploy high-performing generative AI applications.

The microservices support popular community models tailored to meet regional needs. They enhance user interactions through accurate understanding and improved responses based on local languages and cultural heritage.

In the Asia-Pacific region alone, generative AI software revenue is expected to reach $48 billion by 2030 — up from $5 billion this year, according to ABI Research.

Llama-3-Swallow-70B, trained on Japanese data, and Llama-3-Taiwan-70B, trained on Mandarin data, are regional language models that provide a deeper understanding of local laws, regulations and other customs.

Training a large language model (LLM) on regional languages enhances the effectiveness of its outputs by ensuring more accurate and nuanced communication, as it better understands and reflects cultural and linguistic subtleties.

Nations worldwide — from Singapore, the United Arab Emirates, South Korea and Sweden to France, Italy and India — are investing in sovereign AI infrastructure.

The new NIM microservices allow businesses, government agencies and universities to host native LLMs in their own environments, enabling developers to build advanced copilots, chatbots and AI assistants.

AI Chases the Storm: New NVIDIA Research Boosts Weather Prediction, Climate Simulation

by Today's Fables

As hurricanes, tornadoes and other extreme weather events occur with increased frequency and severity, it’s more important than ever to improve and accelerate climate research and prediction using the latest technologies.

Amid peaks in the current Atlantic hurricane season, NVIDIA Research today announced a new generative AI model, dubbed StormCast, for emulating high-fidelity atmospheric dynamics. This means the model can enable reliable weather prediction at mesoscale — a scale larger than storms but smaller than cyclones — which is critical for disaster planning and mitigation.

Detailed in a paper written in collaboration with the Lawrence Berkeley National Laboratory and the University of Washington, StormCast arrives as extreme weather phenomena are taking lives, destroying homes and causing more than $150 billion in damage annually in the U.S. alone.

It’s just one example of how generative AI is supercharging thundering breakthroughs in climate research and actionable extreme weather prediction, helping scientists tackle challenges of the highest stakes: saving lives and the world.

NVIDIA Earth-2 — a digital twin cloud platform that combines the power of AI, physical simulations and computer graphics — enables simulation and visualization of weather and climate predictions at a global scale with unprecedented accuracy and speed.In Taiwan, for example, the National Science and Technology Center for Disaster Reduction predicts fine-scale details of typhoons using CorrDiff, an NVIDIA generative AI model offered as part of Earth-2.

CorrDiff can super-resolve 25-kilometer-scale atmospheric data by 12.5x down to 2 kilometers — 1,000x faster and using 3,000x less energy for a single inference than traditional methods.

That means the center’s potentially lifesaving work, which previously cost nearly $3 million on CPUs, can be accomplished using about $60,000 on a single system with an NVIDIA H100 Tensor Core GPU. It’s a massive reduction that shows how generative AI and accelerated computing increase energy efficiency and lower costs.

The center also plans to use CorrDiff to predict downwash — when strong winds funnel down to street level, damaging buildings and affecting pedestrians — in urban areas.

Now, StormCast adds hourly autoregressive prediction capabilities to CorrDiff, meaning it can predict future outcomes based on past ones.

A Global Impact From a Regional Focus

Global climate research begins at a regional level.

Physical hazards of weather and climate change can vary dramatically on regional scales. But reliable numerical weather prediction at this level comes with substantial computational costs. This is due to the high spatial resolution needed to represent the underlying fluid-dynamic motions at mesoscale.

Regional weather prediction models — often referred to as convection-allowing models, or CAMs — have traditionally forced researchers to face varying tradeoffs in resolution, ensemble size and affordability.

CAMs are useful to meteorologists for tracking the evolution and structure of storms, as well as for monitoring its convective mode, or how a storm is organized when it forms. For example, the likelihood of a tornado is based on a storm’s structure and convective mode.

NVIDIA researchers trained StormCast on approximately three-and-a-half years of NOAA climate data from the central U.S., using NVIDIA accelerated computing to speed calculations.

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Indegene Announces Strategic Collaboration with Microsoft to Help Life Sciences Companies Scale Up Generative AI Adoption and Accelerate Business Impact

by Latest UpdatesToday's Fables

Princeton, NJ, and Bengaluru, KA, July 11, 2024: Indegene today announced a strategic collaboration with Microsoft to empower global life sciences companies to scale up the adoption of purpose-built, enterprise-grade Generative AI (GenAI) services, thereby driving faster innovation at scale.

Indegene and Microsoft have committed to developing resources in highly specialized and skilled medical and technology tools to co-innovate generative AI services and workflows across commercial, medical, regulatory, and clinical functions.

“GenAI presents a once-in-a-decade opportunity for life sciences companies to modernize business processes and reimagine the effectiveness and efficiency of their operations throughout the value chain. Using GenAI, we’re closely working with many of our clients to solve specific business problems, with nearly 50 real-world use cases already in an advanced pilot stage”, said Tarun Mathur, CTO, Indegene. “As we double down on efforts to strengthen our innovation prowess, we will keep exploring opportunities for greater collaboration with key technology providers. We remain focused on helping our clients harness the potential of GenAI with targeted solutions to address some of their most pressing operational challenges and make their business future-ready.”

Alok Lall, Chief Operating Officer, Microsoft India & South Asia, said, “Generative AI is profoundly shaping every industry, including life sciences, by offering unprecedented avenues for healthcare technology advancements. According to a Microsoft-commissioned study conducted by IDCi, a staggering 79% of healthcare organizations have now embraced AI. This demonstrates that the tangible business value of this transformation is indisputable. By seamlessly integrating Indegene’s domain knowledge with Microsoft Azure OpenAI Service and Microsoft Copilot, we stand at the forefront of advancing generative AI within the life sciences sector. This collaborative effort empowers life sciences companies to fully harness AI’s capabilities, fostering innovation and scalability within the industry.”

Some of the key use cases the strategic collaboration focuses on in the first phase, include:

1.Content Super App: Using Azure OpenAI Service, the modular content value chain simplifies content creation and tagging for life sciences companies. This integrated approach offers a holistic view of the content value chain, enabling greater velocity, personalized content, and adoption of new conversation form factors. It also streamlines creative and video transformation while effectively engaging healthcare professionals (HCPs), patients and payers

2.Future-ready medical content value chain: Generative AI capabilities are revolutionizing the medical content value chain. From sourcing content from relevant literature articles to authoring core documents such as Clinical Study Reports (CSRs) and Protocols, Indegene’s solutions accelerate authoring processes and help ensure compliance across clinical and regulatory domains

3.Data Management and Analytics for Clinical Trials: Using Microsoft Fabric, Indegene’s solutions enhance the process of data ingestion and refinement, facilitate effortless reporting, and guarantee governance. This leads to proficient analytics, adherence to compliance, and nimbleness in business operations. It revolutionizes the way sales users work and provides a competitive advantage in the marketplace

Indegene counts 20 of the world’s top 20 biopharma companies among its clients. The company brings a practitioner’s perspective to enable organizations to become AI-powered companies. With patients and their health outcomes being the key, Indegene powers clients’ ambition with a practitioner’s expertise in leveraging GenAI, at scale. “With a focus on the right use cases, a responsible and compliant approach to scaling up, and shared learnings, we put generative AI to work for our clients”, added Tarun.

To develop a future-ready workforce, Indegene has also instituted the ‘GenAI @ Work’ initiative, where all its 5,000+ employees will be trained on various facets of GenAI to enhance automation and productivity, allowing its employees to focus on higher-value tasks. As part of this initiative, Indegene has deployed Microsoft Copilot in several of its core business processes and has already started seeing significant productivity improvements.

About Indegene

Indegene Limited (BSE: 544172, NSE: INDGN) is a digital-first, life sciences commercialization company. It helps biopharmaceutical, emerging biotech, and medical device companies develop products, get them to the market, and grow their impact through the life cycle in a more effective, efficient, and modern way. Indegene brings together healthcare domain expertise, fit-for-purpose technology, and an agile operating model to provide a diverse range of solutions. These aim to deliver, amongst other outcomes, a personalized, scalable, and omnichannel experience for patients and physicians. It’s what drives Indegene’s team and their purpose to enable healthcare organizations to be future-ready