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▼⸿ooper Applied Technology.com
(TM SM R) Pseudocode developers of coding
logic & end-to-end Instruction & Rules for Algorithms Algorithms…are the basis of Artificial Intelligence (AI) &
subsets: Machine Learning (ML), Generative Artificial Intelligence (GenAL), Generative Adversarial Networks (GANs), Convolutional Neural
Networks (CNN), Natural
Language Processing (NLP), computer systems, electronic devices, robotics. -------- Detection &
Exposure of DeepFakes & Face Swapping How Can you
tell if it’s REAL or Artificial Intelligence (AI) generated? Ask us. -------------- emailto:
richardcooper@frontier.com or 5852561449 us, we are real people |
Pseudocode is a planning method &
simplified representation of an algorithm that uses the
English language that programmers can use to
organize & outline their coding logic.
We
are developers of Pseudocode step by step list of instructions & rules for
Algorithms
primarily to describe various coding actions &
their correct sequence written in the form of
annotations & information text for
the development of the algorithm. Programmers can interpret
each line of pseudocode & create
algorithms using their preferred coding language for
Artificial Intelligence (AI) & subsets: Machine
Learning (ML), Generative Artificial
Intelligence (GenAL),
Generative
Adversarial Networks (GANs), Convolutional
Neural Networks (CNN), Natural Language Processing (NLP), computer systems,
electronic devices, robotics.
Turning an algorithm into a program involves five main
steps,
1. understanding the algorithm, 2. picking a programming
language,
3. coding the algorithm into that language, 4. testing to
make sure it works correctly,
5. debugging to fix
any issues.
Algorithms are the basis throughout all areas of IT, electronic
devices, robotics.
Artificial
Intelligence (AI) & Machine Learning (ML)
Artificial
Intelligence (AI) is developed by Identifying the problem, defining the
goals,
algorithm development, collecting data,
training the algorithm, evaluation of the
AI system & deployment of the AI solution.
Artificial
intelligence (AI) gives
computer systems the ability to mimic cognitive
functions associated with human intelligence,
such as being able to see, understand &
respond to spoken or written language, to
analyze data & make recommendations.
.Machine learning (ML) is a sub-set of
artificial intelligence (AI) & computer science focusing
on using algorithms & data on it’s own to be able to imitate the
way that humans learn by
gradually improving its accuracy & ability over
time to make informed decisions.
.Generative AI (GenAI) is a sub-set of Artificial Intelligence (AI) can generate
new content
including text, images, videos, sounds, animation, 3D models, music,
Q&A summarizations & other types of data.
GenAI technologies can mimic human intelligence in
nontraditional computing tasks
like image
recognition, the ability to interpret,
manipulate & comprehend
human language & respond to conversations & any complex
subject matter
from new data
& reuse training data to solve new problems.
GenAI is trained to recognize patterns & structures in data
& enable users to quickly
generate new content based
on a variety of inputs using neural networks
both unsupervised &
semi-supervised learning or training.
For example, GenAL can learn English vocabulary & create a poem from
the words
it processes,
respond to chatbots, media creation, product development & design
&
additional needs your mind can conceive.
Misinformation
& Deception---D Day 1944
A crucial part of their preparations for D-Day 6 June 1944,
the Allies developed
a deception plan to
draw attention away from the Normandy Invasion,
code named Operation 'Fortitude' & part of a larger overall deception strategy
Operation 'Bodyguard'.
The
PLAN: misinformation & deception & fake radio traffic and decoy
equipment
including
inflatable tanks and dummy landing craft mimicked preparations for
a large-scale invasion for
the Pas de Calais.
Lieutenant M.E. Clifton James was employed, an
Australian actor who bore
a striking resemblance to Bernard Montgomery
to impersonate the British general.
James donned one of the general’s uniforms
& black berets & flew to Gibraltar on
May 26, 1944 & then to Algiers where
German intelligence was sure to spot him.
German Intelligence surmised that no attack
across the English Channel could be
imminent with the Allied general scouting the
Mediterranean.
Double agents delivered misinformation to the enemy to reinforce this deceit
before the Normandy
landings.
This misinformation,
deception & fake scheme saved thousands of allied lives.
DeepFakes Generative Artificial Intelligence (GenAI)
DeepFakes are created with generative artificial
intelligence (GenAI) for misinformation
& deception & can be an image, video,
audio, voice or text.
The “deep” is “deep learning,” a method of training computer systems on
massive
amounts of data to perform human-like tasks.
The “fake” indicates that the media is
computer-generated by
algorithm instructions
& rules for generative artificial
intelligence (GenAI) & generative
adversarial networks (GANs) to make fakes difficult to distinguish
from human-generated media.
Creating fake content manually has been done over many years
but now by AI.
Generative Adversarial Networks (GANs)
are neural learning networks specifically
designed to imitate
the structure & function of the human brain. GANs
use
two trained neural networks to
compete against each other to generate
fake media from a given training dataset. One multilevel neural network is
for generating fake images from existing databases & the second multilevel
neural network for verifying generated images
look real deepfakes.
DeepFakes pose a considerable threat to the
authenticity of both online & offline
content & is difficult to differentiate fake content from
authentic content.
DeepFakes objective is
to fool the media viewer or a technology system
to create
discord, threaten an
organization’s brand, impersonate leaders, enable access to
networks & sensitive information just to
mention a few nefarious objectives.
How can you tell if It
Real or Fake? Detect & Expose DeepFakes
DeepFakes uses artificial
intelligence (AI) that created it & can be used to detect
deepfakes. Deepfakes detection can prevent the spread of fake
content by
analyzing & comparing the content to
inclusive training datasets & large
amounts of reference data, for ways to detect & expose the media if it
has been digitally manipulated into
synthetic media.
Hints to spot a
deepfakes
We use several of
the following manual deepfake detection & exposure methods
in addition to algorithms, generative artificial
intelligence (GenAI), generative
adversarial networks (GANs) to identify
unnatural patterns that signify that
the content has
been modified or artificially created.
Examples:
Facial and body
movement
Facial Biometrics
Lip-sync detection
Inconsistent -- or
lack of -- eye blinking
Irregular
reflections or shadowing
Pupil dilation
Artificial audio
noise
More Examples:
Visual Artifacts Analysis
Audio-Visual Synchronization
Texture Analysis
Contextual Analysis
Convolutional Neural Network (CNN)*
*Convolutional Neural
Network (CNN) is a machine
learning (ML) algorithm used for
image recognition & processing
typically to blur & sharpen images & perform
manipulative operations.
Prior to CNN, Adobe Photoshop developed Photoshop
Liquidity tool to detect
whether faces in photos were manipulated.
Face Swapping. How can you tell if it’s real or fake?
Face Swapping detection & exposure we learned with
Adobe Photoshop in 1987
& then
Photoshop Liquidity but before Convolutional Neural Networks (CNN) of today.
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Cooper Applied
Technology (USA,
family business) has transformed from an outdated inefficient analog company into a
development to deployment technology team for pseudocode instructions & rules, an exact step by step list in plain English for Algorithms.
Algorithms then convert the pseudocode instructions & rules into a specific computer program
language for either hardware or software-based routines or both. Algorithms are the
basis throughout all areas of IT & for
artificial intelligence (AI) and subsets. 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 We are Real People here not AI ChatGPG ------------------------------- E-mailto:
richardcooper@frontier.com https://cooperappliedtechnology.com*no cookies here* Cooper
Applied Technology
67 willowcrest dr
ste 1441 Rochester, NY 14618 USA V:
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