Adapting to the changing employment landscape will be crucial for both people and organizations.
Founder of Projetech, Inc.
Nvidia, a leading technology company, recently announced a significant increase in earnings, with their revenue doubling due to the high demand for its AI chips that power new machine learning applications; teach and develop new artificial intelligence models and neural networks; and guide low-latency, real-time edge-of-network functions like Tesla’s autonomous driving feature. As AI evolves, it’s transforming the business landscape, touching industries like manufacturing, automotive, insurance, medicine, hospitality and even fast food.
The increasing demand for AI chips has led to a situation where supply needs to catch up with demand, with Nvidia struggling to produce enough chips to meet the market’s needs. This high demand for AI chips is not benefiting rivals like AMD and Intel, as Nvidia dominates the market with more than 70% of AI chip sales.
Tesla, a significant customer of Nvidia, pairs Nvidia chips with its proprietary Dojo chips to teach its cars to drive themselves. The “rollout” of the carmaker’s Full Self-Driving (FSD) driver-assistance system utilizes computer vision video processing and recognition to improve performance. The version 12 update to Tesla FSD will allow the product to launch out of beta and implement “end-to-end AI.”
The insurance industry has always been data-driven, and AI is changing every aspect of “business as usual.” When using these data to train an AI, the outcome is an exponential streamlining effect on payor distribution, underwriting and policy pricing, purchased and bound in near real time.
Soon, insurers will develop AI algorithms to create risk profiles based on individual behavior, leading to personalized insurance rates. Tesla has already introduced insurance based on driving habits in several states, with rates changing dynamically based on the driver’s performance in the last 30 days.
Another area where we see drastic advances attributed to the application of machine learning technology is with “hyperspace” cloud providers like Microsoft Azure, Amazon Web Services, IBM and Google Cloud.
