⸿ooper Applied Technology.com   (TM SM R)

 We Write & Validate Pseudocode for Algorithm Instructions & Rules for Specified Computer Code


Our focus is on DeepFakes Detection of synthetic media

Ŕlgorithmsare the basis of

Artificial Intelligence (AI)---Computer Machine Learning (ML)---Generative Artificial Intelligence (GenAI),

 computer programming, electronic devices, robotics


emailto: richardcooper@frontier.com  or 5852561449 us, we are real people

How do humans learn? education, experience & practice.

   How do computer systems learn? Algorithm Instructions & Rules, training data,

 data mining & practice.

We write pseudocode for algorithms to plan out the logic & validation needed for

   artificial intelligence (AI), computer machine learning (ML), generative AI (GenAI),

electronic devices and robotics to follow a set of algorithmic instructions

 to perform a task or multiple tasks.


Supervised learning for machine Learning algorithms is given a set of data examples by

  the programmer with a known data set that includes desired inputs and outputs and the algorithm.

Unsupervised computer machine learning algorithms make predictions from untagged data

 where there is no ground truth or known output.

Reinforced computer machine learning algorithms follow a regimented learning process of trial

 & error. The machine learning algorithm explores different options and possibilities within

redefined algorithm instructions & rules to make decisions, perform tasks, verifies & monitors

 operating results on their own more efficiently than human intelligence.

 Our focus is on DEEPFAKES Detection of synthetic media


Deepfakes is a type of synthetic media primarily created using deep learning algorithms,

  particularly generative adversarial networks (GANs) or convolutional

 neural networks (CNN).

 These technologies identify and learn from large amounts of data to generate

 realistic-looking fake media. CNNs are effective in recognizing and replicating patterns

 in images, such as facial features. On the other hand, GANs is a set of two neural networks.

 One for generating the image and another for making it appear real. 

DeepFakes pose a considerable threat to the authenticity of online content that can be used to

 spread misinformation, damage reputations & create discord. 

  Deepfakes AI-generated misinformation has a person saying something they did not say, appearing

in a manner different from authentic visuals or diverging from reality somehow,

 with the purpose of fooling the media viewer or a technology system.

DeepFakes Detection 

DeepFakes Detection is the task of detecting fake media that has been digitally AI-generated using

 agorithms to manipulate or replace parts of an original video, image, text or audio. 

DeepFakes detection we are developing, for example is designed to identify & detect deepfakes

  Images is to analyze & determine manipulation focusing on the dull shadows around the eyes,

 unrealistic facial hair, overly smooth or wrinkled skin, fictitious moles & unnatural lip color.

  DeepFakes Detection methods we can also apply to audio, video, social media, text & real-time.

Ask yourself, Is it too good to be true? 


Cooper Applied Technology (USA, family business) has transformed from an outdated inefficient analog company into a development to deployment technology team to

write pseudocodes to plan out the logic needed in the design & validation of

 Algorithm Instructions & Rules & our focus is on DeepFakes Detection of synthetic media


I acquired my practical & business technology knowledge & experience

 as a Director, CEO, CTO, VP, employee of various companies before joining

  Cooper Applied Technology  (SM TM R)

I earned BS degrees in Accounting & Electrical Engineering at RIT,

  MBA degrees in Finance & Economics at Syracuse University.

Richard Cooper CEO  CTO

 Cooper Applied Technology updates our web page as Technology continues to update.

 Real People here not an AI ChatGPG



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Cooper Applied Technology  67 willowcrest dr  ste 1449

Rochester, NY 14618  USA   V: 585-256-1449

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