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A Wave Of Billion-Dollar Language AI Startups Is Coming

#artificialintelligence

In 1998, Larry Page and Sergey Brin founded the greatest language AI startup of all time. But a new ... [ ] generation of challengers is coming. Language is at the heart of human intelligence. It therefore is and must be at the heart of our efforts to build artificial intelligence. No sophisticated AI can exist without mastery of language. The field of language AI--also referred to as natural language processing, or NLP--has undergone breathtaking, unprecedented advances over the past few years. Two related technology breakthroughs have driven this remarkable recent progress: self-supervised learning and a powerful new deep learning architecture known as the transformer. We now stand at an exhilarating inflection point. Next-generation language AI is poised to make the leap from academic research to widespread real-world adoption, generating many billions of dollars of value and transforming entire industries in the years ahead. A nascent ecosystem of startups is at the vanguard of this technology revolution. These companies have begun to apply cutting-edge NLP across sectors with a wide range of different product visions and business models. Given language's foundational importance throughout society and the economy, few areas of technology will have a more far-reaching impact in the years ahead. The first category of language AI startups worth discussing is those players that develop and make available core general-purpose NLP technology for other organizations to apply across industries and use cases. Building a state-of-the-art NLP model today is incredibly resource-intensive and technically challenging.


A Wave Of Billion-Dollar Language AI Startups Is Coming

#artificialintelligence

In 1998, Larry Page and Sergey Brin founded the greatest language AI startup of all time. But a new ... [ ] generation of challengers is coming. Language is at the heart of human intelligence. It therefore is and must be at the heart of our efforts to build artificial intelligence. No sophisticated AI can exist without mastery of language. The field of language AI--also referred to as natural language processing, or NLP--has undergone breathtaking, unprecedented advances over the past few years. Two related technology breakthroughs have driven this remarkable recent progress: self-supervised learning and a powerful new deep learning architecture known as the transformer. We now stand at an exhilarating inflection point. Next-generation language AI is poised to make the leap from academic research to widespread real-world adoption, generating many billions of dollars of value and transforming entire industries in the years ahead. A nascent ecosystem of startups is at the vanguard of this technology revolution. These companies have begun to apply cutting-edge NLP across sectors with a wide range of different product visions and business models. Given language's foundational importance throughout society and the economy, few areas of technology will have a more far-reaching impact in the years ahead. The first category of language AI startups worth discussing is those players that develop and make available core general-purpose NLP technology for other organizations to apply across industries and use cases. Building a state-of-the-art NLP model today is incredibly resource-intensive and technically challenging.


10 essential ingredients for digital twins in healthcare

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This story looks at some of the fundamental building blocks that work together to build a digital twin infrastructure for medicine. It explains how promising techniques like APIs, graph databases, ontologies, electronic health records are being combined to unlock digital transformation in healthcare. Digital twins could transform healthcare with a more integrated approach for capturing data, providing more timely feedback, and enabling more effective interventions. The information required to allow for better simulations lies scattered across medical records, wearables, mobile apps, and pervasive sensors. Medical digital twins can use raw digital ingredients like natural language processing (NLP), APIs, and graph databases to understand all the data and cut through the noise to summarize what is going on.


What Are The Trends In Insurance Industry?

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The global insurance market is experiencing a metamorphosis to'digital-first' business models that may unlock new worth value billions of greenbacks Collaboration between ancient insurance and InsurTech companies can bring about to newer models and revenue streams, higher profitableness and reduced operational price. Artificial Intelligence (AI) plays a vital role in reworking the insurance business. Today, with the increasing quality of wearable devices, IoT, and sensible mobile apps, insurance organizations ar capable of optimizing advanced insurance selections and investigations. Intelligent tools and applications utilized by the insurance shoppers change insurance suppliers to access the dear data of their customers' health and provide custom-made insurance policies. In recent years, AI-based tending tools and applications have speedily optimized and hyperbolic the potency of insurance organizations across the world.


On top of the data mountain International Travel & Health Insurance Journal

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Few companies that deal with patients or insured clients don't gather and store gargantuan amounts of information every day. That data comes from multiple sources – claims data, electronic health records (EHR), scans, cost data that describes what services were provided and how they were reimbursed, real-time data on blood pressure, temperature and other vital signs from sensors – and this mountain of data keeps on growing. The reason that the amount of medical data continues to grow is partly down to the increasing digitisation of medical records. Certainly, their use has risen sharply in recent years. Just 30 per cent of US office-based physicians and hospitals used even basic electronic medical records in 2005.