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12:00 AM - 29th ECCMID
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29th ECCMID
2019-04-13 - 2019-04-16    
All Day
Welcome to ECCMID 2019! We invite you to the 29th European Congress of Clinical Microbiology & Infectious Diseases, which will take place in Amsterdam, Netherlands, [...]
4th International Conference on  General Practice & Primary Care
2019-04-15 - 2019-04-16    
All Day
The 4th International Conference on General Practice & Primary Care going to be held at April 15-16, 2019 Berlin, Germany. Designation Statement The theme of [...]
Digital Health Conference 2019
2019-04-24 - 2019-04-25    
12:00 am
An Innovative Bridging for Modern Healthcare About Hosting Organization: conference series llc ltd |Conference Series llc ltd Houston USA| April 24-25,2019 Conference series llc ltd, [...]
International Conference on  Digital Health
2019-04-24 - 2019-04-25    
All Day
Details of Digital Health 2019 conference in USA : Conference Name                              [...]
16th Annual World Health Care Congress -WHCC19
2019-04-28 - 2019-05-01    
All Day
16th Annual World Health Care Congress will be organized during April 28 - May 1, 2019 at Washington, DC Who Attends Hospitals, Health Systems, & [...]
Events on 2019-04-13
29th ECCMID
13 Apr 19
Amsterdam
Events on 2019-04-24
Events on 2019-04-28
Articles

How Deep Learning Can Help Drive Your Tech Business

deep learning machines

How Deep Learning Can Help Drive Your Tech Business

Tech companies are facing new and growing challenges daily to plan, think, and deliver faster. Technology innovations and advancements are moving so fast that when by the time a company first announces a new product, that very product may already be already outdated as another company will be working on getting ahead. This game of leapfrog will continue for many years to come. One area that has grown through this competition is the concept of deep learning to process data faster. What is deep learning, and how can this advanced concept help drive your tech business?

Deep Learning Encompasses Artificial Intelligence

The concept of deep learning utilizes technology to expand batch analysis and decision-making at a higher, more efficient, and faster level. Deep learning software learns by the examples it observes through training inputs.
The primary comparison point for deep learning technology is the human brain. The human brain can process multiple items simultaneously and piece together memories and thoughts to formulate images and actions. Whereas the human brain is a self-contained machine with quick access to all training inputs it needs, deep learning relies upon silicon computing chips of a set limit distributed across multiple devices. As the need for more efficient deep learning has increased, the demand has intensified for expanded computing-chip technology to handle an increased neural network batch size.

Deep Learning Drives Speed and Performance Results

Deep learning is an intensive process built on speed and computing power. Machines are replacing tasks handled by humans for many years thanks to the speed and efficiency they can handle certain functions, and deep learning is becoming a critical computational tool. Companies build extensive neural networks to handle simultaneous tasks and speed up calculations.

The primary way to achieve the acceleration of calculations is to increase the size of the computer cores. With more or larger cores, more calculations can be accomplished in less time. When the processing time is reduced, you also increase the output. For any technology to work efficiently, direct and close reliable access to memory and bandwidth will reduce the idling time between each process stage. As silicon chips are increased in size, they become more able to meet speed goals. If a single chip can hold all the data, the bottlenecks involved with multiple chip systems will disappear.

Deep Learning Delivers High-Quality Results

A deep learning machine learns through training and depends on the examples and data fed into the system. With the correct raw data delivered as input, the system can learn to provide quality results exponentially faster than a human brain. The system doesn’t become fatigued like a human and instead can continue to run with the potential of mistakes eliminated. The realization of the return on investment comes as the deep learning system evaluates the variations across an organization to find areas to cut costs. Deep learning removes the need for feature engineering. The system learns and correlates feature data independently, removing the need to do this in advance.

Deep Learning Removes the Need for Labeling Data

Data labeling is a time-consuming process that is open to human errors. Examples of data labeling challenges are in the photography and medical fields. In deep learning, the computer system is trained on inputs of example data to teach how humans label the data, photos, or other information. Once the system has generated its calculations and learned by example, it will automatically apply labels to raw data inputs.
The training process is a constant learning exercise as humans evaluate any fallout items and resubmit the information until the system fully understands processing and labeling all items. In the end, the time savings and data labeling reliability will be a massive win for an organization from utilizing the deep learning process.
There are many items to review to understand what is best for your business when evaluating overall deep learning benefits. With powerful, fast computer chips, your company can take advantage of all modern artificial intelligence has to offer.