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  /  Project   /  Blog: Problems Deep Learning will probably solve by 2019

Blog: Problems Deep Learning will probably solve by 2019


It is hyperbole to say deep learning is achieving state-of-the-art results across a range of difficult problem domains. A fact, but also hyperbole. In this post, you will discover recent applications of deep learning.

Deep Learning for Forecasting Nuclear Accidents

Forecasting is one of the many applications where machine learning techniques have established a firm footing. With the deep learning networks getting better with each passing day, the move to entrust these networks with something as sophisticated and incredibly powerful as nuclear plants are in progress. The external instabilities like Tsunamis and extremist activities like terrorism cannot be forecasted with certainty. But what happens within a nuclear plant can be controlled and should be.

Deep learning for diagnosis and prognosis

A piece of news published two days ago claims that deep learning can analyze lung cancer histopathology slides in less than 30 seconds.

Deep learning to eradicate suicide

In a recent NYU study wherein scientists built a natural language processing AI, basically, the same technology that runs Alexa, Assistant, and Siri that can detect PTSD in veterans with 89 percent accuracy just by listening to audio recordings of the person’s speech.

Deep Learning to Save Lives

The rapid advances in computer vision due to the application of AI starting in 2012, have led to predictions of the imminent demise of radiologists, to be replaced by better diagnosticians — Deep Learning algorithms. These algorithms will help “automate every visual aspect of medicine,” going beyond radiology to pathology, dermatology, dentistry, and to all situations where “a doctor or a nurse are staring at an image and need to make a quick decision.” This “automation” does not mean replacing doctors. Rather, it means the augmentation of their work, providing consistent, accurate, and timely assistance. We need all the doctors we have in the world and we will need 10X more because of the aging population.

AI-Based System to cut process time for abnormal X-Rays

Deep Learning can help a Sales Team Thrive

Machine Learning, specifically Deep Learning, fills in gaps that human intuition never could. Put to use across a team of eager sales pros, its innate advantages add a layer of intelligence to any crew’s knowledge base. As a tool, deep learning provides insights by spotting and naming patterns in millions of unstructured data points. Deep Learning bridges gaps in the sales pipeline by determining who is most likely to convert to the next stage in the sales funnel. Using Deep Learning, sales leaders can not only identify a good-fit potential customer, but also predict the possible deal size, deal cycles, and other insights.

Conclusion

There are many cases where AI and Deep learning can revolutionize a particular field. The list would go on and on. There are a plethora of applications. By the end of 2019, we will witness a wide variety of problems solved by AI.

Source: Artificial Intelligence on Medium

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