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63rd ACOG ANNUAL MEETING - Annual Clinical and Scientific Meeting
2015-05-02 - 2015-05-06    
All Day
The 2015 Annual Meeting: Something for Every Ob-Gyn The New Year is a time for change! ACOG’s 2015 Annual Clinical and Scientific Meeting, May 2–6, [...]
Third Annual Medical Informatics World Conference 2015
2015-05-04 - 2015-05-05    
All Day
About the Conference Held each year in Boston, Medical Informatics World connects more than 400 healthcare, biomedical science, health informatics, and IT leaders to navigate [...]
Health IT Marketing &PR Conference
2015-05-07 - 2015-05-08    
All Day
The Health IT Marketing and PR Conference (HITMC) is organized by HealthcareScene.com and InfluentialNetworks.com. Healthcare Scene is a network of influential Healthcare IT blogs and health IT career [...]
Becker's Hospital Review 6th Annual Meeting
2015-05-07 - 2015-05-09    
All Day
This ​exclusive ​conference ​brings ​together ​hospital ​business ​and ​strategy ​leaders ​to ​discuss ​how ​to ​improve ​your ​hospital ​and ​its ​bottom ​line ​in ​these ​challenging ​but ​opportunity-filled ​times. The ​best ​minds ​in ​the ​hospital ​field ​will ​discuss ​opportunities ​for ​hospitals ​plus ​provide ​practical ​and ​immediately ​useful ​guidance ​on ​ACOs, ​physician-hospital ​integration, ​improving ​profitability ​and ​key ​specialties. Cancellation ​Policy: ​Written ​cancellation ​requests ​must ​be ​received ​within ​120 ​days ​of ​transaction ​or ​by ​March ​1, ​2015, ​whichever ​is ​first. ​ ​Refunds ​are ​subject ​to ​a ​$100 ​processing ​fee. ​Refunds ​will ​not ​be ​made ​after ​this ​date. Click Here to Register
Big Data & Analytics in Healthcare Summit
2015-05-13 - 2015-05-14    
All Day
Big Data & Analytics in Healthcare Summit "Improve Outcomes with Big Data" May 13–14 Philadelphia, 2015 Why Attend This Summit will bring together healthcare executives [...]
iHT2 Health IT Summit in Boston
2015-05-19 - 2015-05-20    
All Day
iHT2 [eye-h-tee-squared]: 1. an awe-inspiring summit featuring some of the world.s best and brightest. 2. great food for thought that will leave you begging for more. 3. [...]
2015 Convergence Summit
2015-05-26 - 2015-05-28    
All Day
The Convergence Summit is WLSA’s annual flagship event where healthcare, technology and wireless health communication leaders tackle key issues facing the connected health community. WLSA designs [...]
eHealth 2015: Making Connections
2015-05-31    
All Day
e-Health 2015: Making Connections Canada's ONLY National e-Health Conference and Tradeshow WE LOOK FORWARD TO SEEING YOU IN TORONTO! Hotel accommodation The e-Health 2015 Organizing [...]
Events on 2015-05-04
Events on 2015-05-07
Events on 2015-05-13
Events on 2015-05-19
Events on 2015-05-26
2015 Convergence Summit
26 May 15
San Diego
Events on 2015-05-31
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.