Hundreds of laboratories worldwide are working on thousands of AI concepts.

By all accounts, 2021 is going to be an exciting year for those working on improving Artificial Intelligence (AI) applications. There is no chance that any other technology is going to beat AI in the coming years. The recent market has understood the concept of AI and industries are quickly adopting the technology to get better performance. AI is also not disappointing them. The latest achievements in AI have reached an unbelievable stance where people went awe for a moment.

The past fifty years have witnessed a revolution in computing and related communication technologies. Since the dawn of computing in the early 20th century, researchers realised that people need a much more advanced technology that could think and act like humans. Before we talk about AI accomplishments, it is important to mention that a lot of work has been done in the tech sector since its conceptualisation. The sudden outbreak of Covid-19 pandemic has pushed and fast tracked technology more than expected. The development in AI that was anticipated to come in three to five years made its starring in 2020. Unlike previous cycles of AI's rise and fall in which the industry receded into its periodic downturn without making any notable impact on lives, today's AI technologies have become pivotal to many of the things we do. Inspiring innovations in reinforcement learning, neural networks and much more are bringing in further possibilities. Statista has predicted that revenue from AI software will exceed US$22 billion in 2020. Hundreds of laboratories worldwide are working on thousands of AI concepts. As AI is continuously evolving, it is very hard to track down every milestone it has fixed. Henceforth, Analytics Insight brings you a list of AI achievements that is worth your attention.

Top Artificial Intelligence Achievements

AI in diagnosing diseases

Besides coronavirus, there are a lot of diseases that need instant treatment. Let us take lung cancer into account. According to World Health Organisation (WHO), lung cancer caused 9.6 million deaths in 2018 worldwide. Lung cancer is the most common type of cancer. The disease can be diagnosed through scanning, X-ray, sputum test and biopsy which are complex, painful and remarkably expensive.

Scientists from Google AI and Northwestern Medicine, Chicago collaborated in a project to deploy AI for fast, cheap and accurate predictions of lung cancer. Initially, the computer program was trained with 42,290 CT lung scan images from 14,851 patients. The AI module was tested against specialist radiologists. Results revealed that AI outperformed the radiologists with 5% boosting and 11% false-positive reduction.

AI-induced face detection

Face detection is one of the futuristic technologies that made landfall in recent times. With its extreme influence, face recognition is at everyone's hand in form of smartphones or laptops. Face recognition is also used for security purposes.

Facebook has launched its object recognition program (Computer Vision Library), powered by AI that is used to detect the types of objects. It was named as Facebook's Detectron. In 2019, Facebook's AI Research (FAIR) department has launched Detectron 2 powered by PyTorch. Previously, its predecessor was built on Caffe2 that did not promise faster project iteration. Detectron 2 is used to detect shapes with faster speed. It can easily distinguish between human and a dog. In the future, more data models will be fed to the program to enhance recognition abilities. Besides, this AI image recognition technology is highly beneficial to blind people. Image recognition is availed in mobile applications which make the technology both handy and economic.

Advanced AI text summarization, recognition and generation

It is not just AI that is seeing development. Subfields like Natural Language Processing (NLP), and text generation and recognition are also seeing various doors opening at their front. The automatic summarization of text has always been a challenge to AI researchers. Google Brain and Imperial College London team have successfully devised a system called 'Pre-training with Extracted Gap-sentences for Abstractive Summarization Sequence-to-sequence or PEGASUS. The program has been tested for twelve summarisation tasks including news, scientific literature, stories, information, emails, patents and legislative bills.

TalkToTransform.com, a sire created by Canadian engineer Adam King is a slimmed-down, accessible version of text generation. The underlying base comes from research lab OpenAI. It is accessible only by selected journalists and scientists.