⸿ooper Applied Technology.com   (TM SM R)

Applied Technology---think before you CLICK

 Pseudocode programming Instructions & Rules written for

Algorithms

the basis of

Artificial Intelligence (AI) & sub-sets Machine Learning (ML), AI powered robotics, Generative Artificial Intelligence (GenAI), Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNN), Natural Language Processing (NLP), computer systems, electronic devices

&

 Cybersecurity detecting, preventing & mitigating cyberthreats on internet-connected systems, networks, programs, electronic devices & digital information

Detection & Exposure of DeepFakes & Face Swapping in Social Media

Email: RichardCooper@frontier.com  or  V: 5852561449    *no cookies here*

 Pseudocode is a way to describe the logic and structure of algorithms in a human-readable format that's not tied to a specific programming language. Pseudocode is a step-by-step

 set of instructions, rules & digital Information for programming Algorithms. 

 Algorithm programmers translate the pseudocode into the required programming language

 & coding logic for the algorithm’s specific application. Tests the algorithm applications

 to verify they execute correctly & debug & fix any issues before the release

 of the artificial intelligence (AI) algorithms.

  Artificial Intelligence (AI) & Sub-Sets

1.    Artificial Intelligence (AI) algorithm computational power & sub-sets can instruct

 computer systems to learn to operate on their own & make decisions by

 mimicking the cognitive functions associated with human intelligence to

 see, understand & respond to spoken & written language. To analyze digital

 information & make recommendations that normally require human intelligence

 such as visual perception, speech recognition, video & graphics.

2. Machine learning (ML) is a sub-set of AI written by engineers for computer systems

 & devices to use AI algorithms learning to predict & generate human language a

 key component of natural language processing (NLP). Enabling computers to use

  statistical models & analyze, draw inferences, develop patterns from data

 bases to learn & adapt on their own NLP instructions.

3. Generative AI (GenAI) is a sub-set of AI) capable of generating text, images, video,

  sounds, animation, 3D models, music, Q&A summarizations & other types of

 informational data using generative AI.

 GenAI technologies can mimic human intelligence in nontraditional computing

 tasks like image recognition, manipulate & comprehend human language,

 respond to conversations & complex subject matter.

4. Cybersecurity & Generative AI (GenAI) Algorithms together are essential in detecting,

 preventing & mitigating cyberthreats on internet-connected systems, networks,

 programs, electronic devices & digital information to establish a baseline

 to alert & flag deviations,

 e.g.

1.    detecting & classifying attacks

2.    removing noisy & irrelevant data

3.    detecting malware

4.    facial recognition verification

5.    predicting network security

6.    fraud detection to expose social media if it

 has been computer-generated & fake

7.    network & systems intrusion detection

8.    detecting & classifying phishing attacks

9.    classifying, detecting & predicting blacklisted IP addresses &

 port addresses, SQL Injection (executing malicious SQL

statements into data base servers), denial-of-service attacks

 & insider threats.

  DeepFakes

      DeepFakes media is computer-generated for the purpose of fooling the media

 viewer & internet-connected systems to create discord, impersonate leaders,

 enable fake verification access to computer systems & sensitive information.

Creating fake media (propaganda) manually has been done over many

years & now by using artificial intelligence (AI) algorithms.

 Generative Adversarial Networks (GANs) are neural learning networks

  designed to imitate the structure & function of the human brain.

 GANs use two trained neural networks to generate fake media

    from given databases. One neural network is generating fake

   media & the other neural network for verifying the

  generated fake media looks, reads & sounds like real.

   How Can you tell if It’s Real or Fake?

  Think before you CLICK!

We use the following detection & exposure methods:

e.g.

 Facial and body movement

Facial Biometrics

Lip-sync detection

Inconsistent -- or lack of -- eye blinking

Irregular reflections or shadowing

Pupil dilation

Artificial audio noise

 Audio-Visual Synchronization

   We can detect Face Swapping & DeepFakes—can you?

ABOUT US

Cooper Applied Technology (USA, family business) has transformed from an outdated

 inefficient analog company into a consultant & development to deployment IT

 company for pseudocode programming instructions & rules for

 Cybersecurity---Generative AI (GenAI) Algorithms &

Detection & Exposure of DeepFakes & Face Swapping in Social Media.

Think before you CLICK

  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

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Email: RichardCooper@frontier.com

https://cooperappliedtechnology.com  *no cookies here*

Cooper Applied Technology  67 willowcrest dr  ste 1441

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

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