Artificial intelligence for USA insurance industry and risk protection

15 years of research into predicting and risk research with using neural networks has revealed the incredible difficulty of accurately predicting random
events and risks. These years of experience became the foundation for the creation of a newclass of AI artology.

Why is AI LMM so valuable to people and investors in USA?

Risk management: LMM AI can more accurately predict insurance events, natural disasters, wars, traffic accidents, financial crisis, and other risks, and allows it to take preventative measures and minimize the damage in money, and lives.

Drug development: accelerating the analysis process by 555 times, will help you to create new drugs by analyzing massive amounts of data and uncovering hidden connections between molecules and neurons in order to reduce the HUGE monetary costs of developing new drugs in the USA.

Autopilots: improving systems and algorithms for autonomous driving of vehicles using LMM AI, will allow you to make roads safer, which will help reduce the number of accidents, save money, cars, and lives of passengers.

Increasing the speed of human learning: LMM AI will help to Optimize educational processes, both child and adult, by tailoring learning to the individual needs of each person, business

Scale: Our AI models are capable of processing huge amounts of data, which allows us to solve universal complex forecasting tasks. It can't yet, because we will first, with the help of investors and customers, accumulate resources, and then move codes and algorithms to industrial servers and integrate algorithms into mobile applications.

Accuracy: Through years of research, we have achieved high prediction accuracy. While the maximum recognition rate is 87.5% with a global brute force of 1.2%, the predictive phalanx gives 0.01% brute force, which reduces the computational cost and thus reduces the computational requirements and is cheaper to operate.

Flexibility: Our models can be adapted to different applications. The LMM model is capable of treating the world as 1 or 0, translating your solutions into vector multidimensional models. But this requires server capacity to train AI on a variety of big data.

Efficiency: Using AI can significantly reduce the time and cost of solving a prediction problem. But the process of training the AI model itself took a long 15 years of my life, and today an operator can learn, in 2-3 hours, to interact with AI bypassing codes and conventional logic, giving humans the creative part of decision making.

Funding a startup is a game or an AI analyst's prediction elaborate billion-dollars.