JURGEN SCHMIDHUBER

Meet Professor Jürgen Schmidhuber, a visionary in the AI landscape whose journey towards creating an AI surpassing his own intelligence began when he was just 15. His ultimate aspiration is to see this goal achieved before retiring. The transformative power of Deep Learning Neural Networks (NNs) developed in his lab has propelled AI and machine learning into new realms.

His lab’s landmark achievements are a testament to his innovation. The CTC-trained Long Short-Term Memory (LSTM) recurrent NN, crafted by his team, achieved a remarkable milestone by securing first place in international pattern recognition challenges in 2009. Pioneering fast and deep feedforward NNs on GPUs in 2010, his group demonstrated remarkable performance improvements without relying on unsupervised pre-training, a concept he himself pioneered in 1991.

In 2011, his team’s DanNet established a new standard by being the first feedforward NN to triumph in computer vision competitions, showcasing an extraordinary level of capability. By mid-2010, the NNs crafted in his lab were instrumental across the digital landscape, powering billions of devices and interactions daily. These innovations manifested in applications like enhancing speech recognition in smartphones, revolutionizing machine translation on platforms like Facebook and Google Translate, and refining virtual assistants like Apple’s Siri and Amazon’s Alexa.

The unveiling of the Highway Net in 2015 marked a new era in truly deep feedforward NNs, boasting hundreds of layers. This achievement paved the way for the ResNet, an open-gated version, which has become one of the most referenced NNs in the 21st century, even surpassing LSTM in influence.

The impact of Jürgen Schmidhuber’s work extends beyond technology into healthcare and medicine, where his NNs contribute to enhancing and extending human life. His contribution to AI includes groundbreaking concepts such as artificial curiosity-inducing meta learning machines, unsupervised generative adversarial neural networks, and neural fast weight programmers.

Diving into the realms of creativity, art, science, music, and comedy, he presents a formal theory encompassing enjoyment, curiosity, and creativity. His wide-ranging ideas also encompass Low-Complexity Art, an innovative form of minimal art tailored to the information age, alongside theories in physics and algorithmic information.

As the Chief Scientist of NNAISENSE, he leads the charge in crafting the first practical general-purpose AI. His endeavors are adorned with accolades and he is a sought-after speaker at prominent events, sharing insights and advising governmental clients on AI strategy. Professor Jürgen Schmidhuber’s journey has indelibly shaped the landscape of AI, leaving an indomitable mark on the world of technology and innovation.