Artificial Intelligence has newer breakthroughs every moment in current times. 2019 saw many new approaches and technologies being introduced and as this year closes, here are some of the most talked-about turning points and innovative technologies in AI seen in 2019.
Technological Breakthroughs that made Waves in the AI field in 2019
Generative Adversarial Networks
As per Guy Caspi, the CEO of Deep Instinct, the primary and most exciting area in AI is Generative Adversarial Networks. The researchers at Samsung showcased a GAN based system that can produce videos of a person speaking with the help of a single photo of the person. Another demonstration was of neural melody generation from the lyrics with the help of the conditional GAN- LSTM. The GAN System helped create a large dataset of 121917 MIDI songs that were created with original lyrics.
Reinforcement Learning
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Reinforcement learning attains speed this year at the areas where the training data is limited. RL has established concurrence wherein a demonstration of solving a Rubik’s cube was made with the Robotic hand. AI implementation is now mainstream, and most of the companies are now adopting techniques based on classical economics to validate their AI models. The companies take the methods to decipher the value of training datasets provided to the Artificial Intelligence modes.
Machine Learning
Machine Learning is spreading more and more these days, and people are adopting machine learning to empower themselves. A lot of enterprises are engaging with various technologies to create inhouse AI solutions. Machine learning is one of the most successful AI technologies that businesses are adopting in the coming years.
Augmented Reality
Augmented Reality is one of the most transitional and growing AI technology, which helps the enterprises explicitly for decision making. Augmented Intelligence helps to drive the businesses by helping monitor and summaries to help build solutions for a better future.
GLUE
The large-scale language models such as BERT and ROBERT showcased a hugely successful creation in the Natural Learning Processing (NLP) to attain massive performance General Language Understanding Evaluation. The NLP can help teams create solutions for critical issues like Fake news detection.
TensorFlow
TensorFlow created waves in the data science world; however, it also has challenges like integrating multiple components like Keras. The TensorFlow 2.0 and the integration with Keras help the developers to develop models.
Unsupervised machine translation
One would need to have a large number of datasets for training the machines to do language translation prudently. There is a need for many topics and language pairs for this. However, in a paper presented by Facebook AI researchers, they showcased how technology has made it possible to use Unsupervised learning, without using translation data and unrelated fragments of text in different languages. The systems can reach the level of high-quality translation without using the translation datasets.
These technological approaches have created much uproar in 2019 due to their future implications and potential to develop a humungous impact on the tech world in the coming years.