Recently, NVIDIA CEO Jensen Huang addressed passionately at Computex 2024 about how robots and simulation would revolutionize every aspect of life. From there, he mentioned Physical AI (PAI) and how Physical AI could be the next wave of the AI industry. In this blog, The Tech Robot will go through the important factors of Physical AI that Jensen Huang addressed.
Why Physical AI could be the next wave of AI industry
According to tech expert Huang, physical artificial intelligence (AI) will play a big role in every business since it will allow robots to respond to commands and carry out difficult jobs on their own.
He sees an ecosystem of robots, with NVIDIA depending on the Omniverse, where collaborative robots (cobots) construct robotic products.
Huang demonstrated how businesses are using Omniverse in robotic warehouses and other venues to train robots. Factory planners evaluate operations and optimize layouts in digital twins. Foxconn trains and tests NV, using it as a “robot gym.”
Benefits of physical AI
- PAI systems are not limited to robotics. One way to improve urban pollution detection capabilities is to set up networks of inexpensive mobile micro-sensors that may be installed in city electric vehicles.
- With their data, pollution levels may be immediately estimated, categorized, and integrated into mathematical models using sensor data.
- Sensor-equipped cars, for instance, may be purposefully directed to routes with more data by using suitable decision-making algorithms.
- AI techniques that use unique sensing and comprehension systems can improve the accuracy of pollution models.
- Crowds and moving vehicles are two examples of mobile pollution sources that city cameras can measure.
Challenges of physical AI
The same concern about AI, implies that technology will replace humans when, in fact, technology will help them, and the decision to create software companies rather than robotics is owing to the lengthy process.
They think it takes more creativity, business sense, finances, and patience to produce anything tangible.
Robot applications in the industries
1. AI for Manufacturing
AI is transforming the industrial sector by enhancing output, effectiveness, and decision-making. The analysis of equipment data maximizes maintenance plans and reduces downtime. Supply chain management is made better by machine learning algorithms that estimate demand and manage inventories.
Automation on the assembly line is improved by robotics and AI, which increases speed and accuracy. Consistency in products is ensured by quality control systems driven by AI. Artificial intelligence (AI) is used in smart manufacturing to monitor operations in real-time and make quick modifications to increase output and minimize waste.
AI in healthcare leverages deep learning, natural language processing, and machine learning technologies to improve patient and provider experiences.
Better resource management and proactive methods are made possible by these technologies, which help patients obtain prompt, individualized care, health managers find electronic health data more quickly, and physicians diagnose patients more accurately.
3. AI for Logistics
AI has greatly altered the logistics business; logistics organizations have actively embodied AI, resulting in up to a 50% decrease in operational expenses. AI can address conventional issues by lowering operational expenses by 50% and improving safety by 90%.
It also improves the handling of unexpected delays using predictive analysis, optimizes delivery routes, plans for unforeseen interruptions, and automates difficult processes. Experts believe that by 2035, AI will increase logistics productivity by more than 40%.
AI has helped solve difficult challenges and paved the path for more efficient operations, demonstrating the tremendous influence of smart technology.
4. AI in Finance
Banks, insurers, and financial institutions use AI for a variety of purposes, including fraud detection, auditing, and loan eligibility evaluation.
Traders have also made use of machine learning’s capacity to evaluate millions of data points all at once, allowing them to swiftly analyze risk and make informed investment decisions.
5. AI in Education
AI in education uses machine learning, natural language processing, and face recognition to digitize textbooks, detect plagiarism, and measure student moods, thereby customizing the learning experience to meet individual student needs.
6. AI in Customer Service
Most people dislike receiving robocalls; however, AI in customer service may deliver data-driven solutions that benefit both the client and the supplier. Chatbots and virtual assistants are examples of artificial intelligence systems used by customer service companies.
The best companies for physical AI
1. OpenAI
Elon Musk and Sam Altman launched OpenAI in 2015 to develop artificial intelligence through the development of systems that can comprehend natural language, gain experience, and eventually become intelligent enough to be like humans. Researchers, developers, and companies are drawn to ChatGPT because of its unique language model, which produces replies to text prompts that resemble those of a person. In just two months, OpenAI reached over 100 million monthly active users. To advance its mission, the organization is seeking bright, AI-passionate individuals.
2. Reclaim.ai
An AI-powered business called Reclaim.ai organizes and protects the calendars of busy professionals by emphasizing critical activities and setting priorities. By automatically scheduling activities, meetings, breaks, and routines at the most efficient times, the software can help users save up to 40% of their workweek. To provide the most intelligent, quick, conversational scheduling experience possible, as well as backend services, APIs, the persistence layer, interaction with collaboration platforms, and cloud infrastructure.
3. Hive
Hive is an artificial intelligence business that processes billions of API requests monthly and provides cloud-based solutions for content interpretation. Major corporations employ their portfolio of pre-trained AI models for OCR, logo identification, and content moderation.
Future of AI
Without question, Physical AI could be the next wave of AI industry, which is poised to take center stage in several developing technologies, including big data, robots, and the Internet of Things. In the upcoming years, it will keep innovating in technology.
Conclusion
To sum everything up, Physical AI could be the next wave of AI industry that has the potential to completely change a variety of industries, including manufacturing, healthcare, logistics, finance, education, and customer service. PAI uses cutting-edge robotics and simulation technology to allow autonomous, effective, and intelligent operations, as stated by NVIDIA CEO Jensen Huang at Computex 2024. The application of PAI in urban settings, such as smart manufacturing and pollution detection, shows how it might improve decision-making and efficiency. Notwithstanding obstacles, PAI’s cutting-edge uses and advantages highlight its capacity to influence the future and propel important breakthroughs in a range of sectors.
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