Chinese prodigy Ke Jie battles against AlphaGo, May 25, 2017.（Photo/DeepMind Screenshot)
Healthcare is one of the most important applications of deep learning through artificial neuralnetworks as well. The expenditure in healthcare represents 10% of the world's GDP, according to World Bank statistics, and at least 10% of which is for medical diagnosis such as cancer detection, plaque detection in arteries, X-ray analysis, etc. That is worth about 1'000 billion USD per year. Given this huge market, many startups are now focusing on improving diagnosis by AI, as well as established companies such as IBM & Google. Professor Jürgen Schmidhuber believes that partial automation of medical diagnosis will not only save billions of dollars, but also make expert diagnostics accessible to many who currently cannot afford it. Thanks to AI and deep learning and LSTM etc, people will live longer and healthier.
In 2012, Professor Jürgen Schmidhuber's team won the first place of a medical imaging competition through deep learning. The application was cancer detection in human tissue, and his lab's methods became over 1000 times faster than previous methods. At the time Professor Jürgen Schmidhuber's team (led by Dan Ciresan) won the contest, computing was still 10 times more expensive than it is today. In other words, the computing power is 10 times as much for the same price today, with 10 time's bigger neural networks (NNs), and 10 times more data. This trend has held since Konrad Zuse built the first working program-controlled computer between 1935 and 1941. Today, 75 years later, hardware is roughly a million billion times faster per unit price. Professor Jürgen Schmidhuber believes that it will be possible to have cheap devices with the raw computational power of a human brain in near future. In addition, all of medical diagnosis through NNs method will be superhuman, and law makers in many countries will make it mandatory.
NNAISENSE is an outgrowth of Professor Jürgen Schmidhuber's academic labs in Munich and in Switzerland. NNAISENSE is pronounced like "nascence," because it's about the "birth of a general purpose Neural Network-based Artificial Intelligence (NNAI). It has 5 co-founders (Professor Jürgen Schmidhuber , CEO Faustino Gomez, Jan Koutnik, Jonathan Masci, Bas Steunebrink, and myself), brilliant advisors (Sepp Hochreiter, Marcus Hutter, Jaan Tallinn), outstanding employees, and revenues through ongoing state-of-the-art applications in industry and finance", as Professor Jürgen Schmidhuber explained. The five co-founders of NNAISENSE believe that the current commercial success of LSTM algorithm is just the beginning, and that they can go far beyond what's possible today, through novel variants of meta-learning, artificial curiosity and creativity, optimal program search and large reinforcement learning recurrent neural networks, to pull off the big practical breakthrough that will change everything. Professor Jürgen Schmidhuber says he believes that such an AGI will affect every business, and eventually transcend humankind.
Currently, the business model of NNAISENSE is cooperating with various industry partners, and designing solutions for them. And from each job, the neural network-based AI of NNAISENSE learns new skills, and to become a more and more general problem solver. NNAISENSE's destination is to create an AGI that continuously learn new skills on the bases of the existing skills, and that learn faster and faster. Some of those problem-solving skills will be created by AI itself through curiosity (Professor Jürgen Schmidhuber has proposed and developed the theory of AI curiosity and creativity since 1991).
