Image and Video Manipulation : The Impact of Deepfakes Tutorial

Dive into the world of "deepfakes" with our video exploring the impact of generative AI on visual trust. From the resurrection of cinema icons to the manipulation of leaders' speeches, discover the feats and dangers of this technology. Learn how technology combats deception in the face of risks to privacy and reputation. Stay vigilant in this era of digital illusions.

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Objectifs :

This document aims to explore the concept of deep fakes, their implications on reality and ethics, and the ongoing efforts to detect them. It highlights the dual nature of this technology, showcasing both its creative potential and the risks it poses to trust and privacy.

Chapitres :

  1. Introduction to Deep Fakes
    Since the inception of photography, image manipulation has been a part of its evolution. However, the digital era has ushered in a new level of sophistication in these manipulations, often challenging our perception of reality. Among these advancements, deep fakes have emerged as a particularly notable innovation.
  2. Understanding Deep Fakes
    The term 'deep fake' is a combination of 'deep learning' and 'fake', referring to videos or images generated by artificial intelligence algorithms. These creations are so realistic that they can easily be mistaken for authentic recordings.
  3. Creative and Malicious Potential
    The potential applications of deep fakes are vast. For instance, imagine iconic figures like Marilyn Monroe or James Dean being digitally resurrected to star in new films. Alternatively, envision world leaders delivering speeches they never actually made. The possibilities, whether for creative storytelling or malicious intent, are nearly limitless.
  4. Ethical Concerns
    Despite their intriguing possibilities, deep fakes raise significant ethical questions. In a time when 'seeing is believing', how can we trust our eyes when algorithms can flawlessly replicate reality? This blurring of the line between truth and falsehood undermines our trust in visual content.
  5. Implications for Privacy and Media
    The implications of deep fakes extend to privacy concerns as well. Videos can be fabricated to depict individuals in scenarios they have never encountered, potentially damaging reputations in an instant. In the media landscape, where truth is paramount, deep fakes can be weaponized to create false news, manipulate public opinion, and even sway election outcomes.
  6. Detection and Future Outlook
    Fortunately, the technology behind deep fakes also offers a glimmer of hope. Researchers and companies are developing tools to detect these manipulations. These solutions leverage AI to analyze videos and identify anomalies that indicate tampering. In this rapidly evolving landscape, the importance of remaining vigilant and informed cannot be overstated.

FAQ :

What are deep fakes?

Deep fakes are synthetic media created using AI algorithms that can convincingly replace one person's likeness with another in videos or images. They can be used for both creative and malicious purposes.

How do deep fakes affect trust in media?

Deep fakes blur the line between reality and fabrication, making it difficult for viewers to trust visual content. This erosion of trust can have serious implications, especially in journalism and public discourse.

What are the ethical concerns surrounding deep fakes?

Ethical concerns include the potential for deep fakes to be used for misinformation, defamation, and invasion of privacy. They raise questions about consent and the authenticity of media.

Can deep fakes be detected?

Yes, researchers and companies are developing AI-based tools to detect deep fakes by analyzing videos for anomalies that indicate manipulation.

What are some potential uses of deep fake technology?

Deep fake technology can be used in entertainment, such as bringing deceased actors back to life for new films, but it can also be misused to create false news or manipulate public opinion.

Quelques cas d'usages :

Film and Entertainment

Deep fake technology can be used in the film industry to create realistic performances by deceased actors, allowing filmmakers to produce new content featuring iconic figures like Marilyn Monroe or James Dean.

Political Campaigns

In political contexts, deep fakes can be used to create misleading videos of candidates, potentially influencing public opinion and election outcomes. This raises the need for robust detection tools to maintain electoral integrity.

Media and Journalism

Journalists can utilize deep fake detection tools to verify the authenticity of video content, ensuring that the information they present to the public is accurate and trustworthy.

Privacy Protection

Individuals can use deep fake detection technologies to protect their reputations by identifying and challenging fabricated videos that misrepresent them in harmful ways.

Education and Training

Deep fake technology can be applied in educational settings to create realistic simulations for training purposes, such as in medical or emergency response training, enhancing learning experiences.

Glossaire :

Deep Fake

A deep fake is a synthetic media in which a person in an existing image or video is replaced with someone else's likeness using artificial intelligence (AI) algorithms. This technology combines deep learning techniques with fake media to create highly realistic but fabricated content.

Deep Learning

Deep learning is a subset of machine learning that uses neural networks with many layers (deep networks) to analyze various factors of data. It is particularly effective in recognizing patterns and making predictions based on large datasets.

AI Algorithms

AI algorithms are sets of rules or instructions given to an AI system to help it learn on its own. These algorithms enable machines to perform tasks that typically require human intelligence, such as visual perception, speech recognition, and decision-making.

Ethical Questions

Ethical questions refer to the moral implications and considerations that arise from the use of technology, particularly regarding its impact on society, privacy, and trust.

Manipulation

Manipulation in this context refers to the alteration or distortion of media content to mislead or deceive viewers, often for malicious purposes.

Anomalies

Anomalies are deviations from the expected pattern or behavior in data. In the context of deep fake detection, they refer to inconsistencies in videos that may indicate manipulation.

résultat(s)
00:00:05
Since the dawn of photography,
00:00:07
image manipulation has existed,
00:00:09
but the advent of the digital
00:00:11
era has opened the way for
00:00:14
more advanced manipulations,
00:00:15
sometimes challenging our
00:00:16
perception of reality.
00:00:18
Among these innovations,
00:00:19
the deep fake stands out.
00:00:21
Particularly this term,
00:00:22
a fusion of deep learning and
00:00:25
fake refers to videos or images
00:00:28
generated by AI algorithms.
00:00:29
These creations are so convincing
00:00:31
that they can easily be
00:00:33
mistaken for genuine recordings.
00:00:36
The potential of deep fakes is vast.
00:00:38
Think of cinema icons like Marilyn
00:00:41
Monroe or James Dean who come
00:00:43
back to life to act in new films
00:00:46
or imagine world leaders giving
00:00:48
speeches they never actually made.
00:00:51
The possibilities,
00:00:52
whether creative or malicious,
00:00:53
are almost endless.
00:00:54
However,
00:00:55
these technological advances
00:00:56
raise serious ethical questions.
00:00:58
In an era where seeing was believing,
00:01:01
How can we still trust our eyes when
00:01:03
algorithms can perfectly reproduce reality?
00:01:06
The line between true and
00:01:08
false becomes blurred,
00:01:09
eroding
00:01:09
our trust in visual content.
00:01:11
The implications for privacy
00:01:13
are equally worrying.
00:01:14
Videos can be fabricated to
00:01:15
show people in situations
00:01:17
they have never experienced,
00:01:19
ruining reputations in an instant.
00:01:20
In the world of
00:01:22
media, where truth is crucial,
00:01:24
deep fakes can be used to create false
00:01:27
news, manipulate public opinion,
00:01:28
and even influence the course of elections.
00:01:31
Fortunately, the technology
00:01:32
itself offers a glimmer of hope.
00:01:34
Researchers and companies are working
00:01:36
on tools to detect deep fakes.
00:01:38
These solutions use AI to
00:01:40
analyze videos and spot anomalies
00:01:42
that betray manipulation.
00:01:44
In this evolving landscape,
00:01:45
one thing remains constant the need
00:01:48
to stay vigilant and informed.

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résultat(s)
00:00:05
Desde os primórdios da fotografia,
00:00:07
a manipulação de imagem existiu,
00:00:09
mas o advento do digital
00:00:11
O EEI abriu caminho para
00:00:14
manipulações mais avançadas,
00:00:15
por vezes desafiando o nosso
00:00:16
perceção da realidade.
00:00:18
Entre essas inovações,
00:00:19
o deep fake se destaca.
00:00:21
Particularmente este termo,
00:00:22
uma fusão de aprendizagem profunda e
00:00:25
fake refere-se a vídeos ou imagens
00:00:28
gerados por algoritmos de IA.
00:00:29
Estas criações são tão convincentes
00:00:31
que podem ser facilmente
00:00:33
confundido com gravações genuínas.
00:00:36
O potencial das deep fakes é vasto.
00:00:38
Pense em ícones do cinema como Marilyn
00:00:41
Monroe ou James Dean que vêm
00:00:43
De volta à vida para atuar em novos filmes
00:00:46
ou imagine líderes mundiais dando
00:00:48
discursos que nunca fizeram.
00:00:51
As possibilidades,
00:00:52
sejam eles criativos ou maliciosos,
00:00:53
são quase infinitas.
00:00:54
No entanto,
00:00:55
estes avanços tecnológicos
00:00:56
levantam sérias questões éticas.
00:00:58
Numa época em que ver era acreditar,
00:01:01
Como podemos ainda confiar nos nossos olhos quando
00:01:03
Os algoritmos podem reproduzir perfeitamente a realidade?
00:01:06
A linha entre verdadeiro e verdadeiro
00:01:08
false torna-se desfocado,
00:01:09
erosão
00:01:09
a nossa confiança no conteúdo visual.
00:01:11
As implicações para a privacidade
00:01:13
são igualmente preocupantes.
00:01:14
Os vídeos podem ser fabricados para
00:01:15
mostrar pessoas em situações
00:01:17
nunca experimentaram,
00:01:19
arruinando reputações num instante.
00:01:20
No mundo da
00:01:22
meios de comunicação social, onde a verdade é crucial,
00:01:24
Deep fakes podem ser usados para criar falsos
00:01:27
notícias, manipular a opinião pública,
00:01:28
e até influenciar o desenrolar das eleições.
00:01:31
Felizmente, a tecnologia
00:01:32
ela própria oferece um vislumbre de esperança.
00:01:34
Investigadores e empresas estão a trabalhar
00:01:36
em ferramentas para detetar deep fakes.
00:01:38
Essas soluções usam IA para
00:01:40
analisar vídeos e detetar anomalias
00:01:42
que traem a manipulação.
00:01:44
Neste cenário em evolução,
00:01:45
Uma coisa permanece constante: a necessidade
00:01:48
manter-se vigilante e informado.

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résultat(s)
00:00:05
Fin dagli albori della fotografia,
00:00:07
la manipolazione delle immagini è esistita,
00:00:09
ma l'avvento del digitale
00:00:11
era ha aperto la strada a
00:00:14
manipolazioni più avanzate,
00:00:15
a volte sfidando il nostro
00:00:16
percezione della realtà.
00:00:18
Tra queste innovazioni,
00:00:19
spicca il deep fake.
00:00:21
In particolare questo termine,
00:00:22
una fusione di deep learning e
00:00:25
falso si riferisce a video o immagini
00:00:28
generato da algoritmi di intelligenza artificiale.
00:00:29
Queste creazioni sono così convincenti
00:00:31
che possono essere facilmente
00:00:33
scambiate per registrazioni autentiche.
00:00:36
Il potenziale dei deep fake è enorme.
00:00:38
Pensate alle icone del cinema come Marilyn
00:00:41
Monroe o James Dean che vengono
00:00:43
tornare in vita per recitare in nuovi film
00:00:46
o immagina che i leader mondiali donino
00:00:48
discorsi che in realtà non hanno mai fatto.
00:00:51
Le possibilità,
00:00:52
siano essi creativi o malevoli,
00:00:53
sono pressoché infiniti.
00:00:54
Tuttavia
00:00:55
questi progressi tecnologici
00:00:56
sollevano seri interrogativi etici.
00:00:58
In un'epoca in cui vedere era credere,
00:01:01
Come possiamo fidarci ancora dei nostri occhi quando
00:01:03
gli algoritmi possono riprodurre perfettamente la realtà?
00:01:06
Il confine tra vero e
00:01:08
falso diventa sfocato,
00:01:09
erosione
00:01:09
la nostra fiducia nei contenuti visivi.
00:01:11
Le implicazioni per la privacy
00:01:13
sono altrettanto preoccupanti.
00:01:14
I video possono essere fabbricati per
00:01:15
mostrare persone in situazioni
00:01:17
non hanno mai sperimentato,
00:01:19
rovinando la reputazione in un istante.
00:01:20
Nel mondo di
00:01:22
media, dove la verità è fondamentale,
00:01:24
i deep fake possono essere usati per creare falsi
00:01:27
notizie, manipolare l'opinione pubblica,
00:01:28
e persino influenzare il corso delle elezioni.
00:01:31
Fortunatamente, la tecnologia
00:01:32
di per sé offre un barlume di speranza.
00:01:34
Ricercatori e aziende stanno lavorando
00:01:36
sugli strumenti per rilevare i deep fake.
00:01:38
Queste soluzioni utilizzano l'intelligenza artificiale per
00:01:40
analizzare i video e individuare le anomalie
00:01:42
che tradiscono la manipolazione.
00:01:44
In questo panorama in evoluzione,
00:01:45
una cosa rimane costante: la necessità
00:01:48
per rimanere vigili e informati.

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résultat(s)
00:00:05
С самого начала фотографии
00:00:07
манипуляция изображениями существует,
00:00:09
но появление цифровых технологий
00:00:11
эпоха открыла путь к
00:00:14
более совершенные манипуляции,
00:00:15
иногда бросая вызов нашим
00:00:16
восприятие реальности.
00:00:18
Среди этих инноваций
00:00:19
Выделяется глубокая подделка.
00:00:21
В частности, этот термин,
00:00:22
сочетание глубокого обучения и
00:00:25
под подделкой понимаются видео или изображения
00:00:28
генерируется алгоритмами искусственного интеллекта.
00:00:29
Эти творения настолько убедительны
00:00:31
что они легко могут быть
00:00:33
ошибочно принимают за подлинные записи.
00:00:36
Потенциал глубоких подделок огромен.
00:00:38
Подумайте о таких иконах кино, как Мэрилин
00:00:41
Приходят Монро или Джеймс Дин
00:00:43
вернуться к жизни, чтобы сниматься в новых фильмах
00:00:46
или представьте себе, что мировые лидеры дают
00:00:48
речи, которые они на самом деле никогда не произносили.
00:00:51
Возможности,
00:00:52
творческие или злонамеренные,
00:00:53
почти бесконечны.
00:00:54
Тем не менее,
00:00:55
эти технологические достижения
00:00:56
поднимают серьезные этические вопросы.
00:00:58
В эпоху, когда видеть означало верить,
00:01:01
Как мы все еще можем доверять своим глазам, когда
00:01:03
алгоритмы могут идеально воспроизводить реальность?
00:01:06
Граница между истиной и
00:01:08
ложь становится размытой,
00:01:09
размыв
00:01:09
наше доверие к визуальному контенту.
00:01:11
Последствия для конфиденциальности
00:01:13
вызывают не меньшее беспокойство.
00:01:14
Видеоролики могут быть сфабрикованы для
00:01:15
показывать людей в ситуациях
00:01:17
они никогда не сталкивались,
00:01:19
разрушение репутации в одно мгновение.
00:01:20
В мире
00:01:22
СМИ, где правда имеет решающее значение,
00:01:24
глубокие подделки могут быть использованы для создания лжи
00:01:27
новости, манипулирование общественным мнением,
00:01:28
и даже повлиять на ход выборов.
00:01:31
К счастью, технология
00:01:32
Сама по себе вселяет проблеск надежды.
00:01:34
Исследователи и компании работают
00:01:36
над инструментами для обнаружения глубоких подделок.
00:01:38
Эти решения используют искусственный интеллект для
00:01:40
анализируйте видео и выявляйте аномалии
00:01:42
которые свидетельствуют о манипуляциях.
00:01:44
В этом меняющемся ландшафте
00:01:45
одно остается неизменным — необходимость
00:01:48
сохранять бдительность и быть в курсе событий.

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résultat(s)
00:00:05
Desde los albores de la fotografía,
00:00:07
la manipulación de imágenes ha existido,
00:00:09
pero la llegada de lo digital
00:00:11
la era ha abierto el camino para
00:00:14
manipulaciones más avanzadas,
00:00:15
a veces desafiando a nuestros
00:00:16
percepción de la realidad.
00:00:18
Entre estas innovaciones,
00:00:19
destaca el Deep Fake.
00:00:21
Particularmente este término,
00:00:22
una fusión de aprendizaje profundo y
00:00:25
falso se refiere a vídeos o imágenes
00:00:28
generado por algoritmos de IA.
00:00:29
Estas creaciones son tan convincentes
00:00:31
que pueden ser fácilmente
00:00:33
confundido con grabaciones genuinas.
00:00:36
El potencial de las falsificaciones profundas es enorme.
00:00:38
Piensa en íconos del cine como Marilyn
00:00:41
Monroe o James Dean, ¿quién viene
00:00:43
vuelve a la vida para actuar en nuevas películas
00:00:46
o imagina a los líderes mundiales dando
00:00:48
discursos que en realidad nunca pronunciaron.
00:00:51
las posibilidades,
00:00:52
ya sean creativas o maliciosas,
00:00:53
son casi infinitas.
00:00:54
Sin embargo,
00:00:55
estos avances tecnológicos
00:00:56
plantean serias cuestiones éticas.
00:00:58
En una era en la que ver era creer,
00:01:01
¿Cómo podemos seguir confiando en nuestros ojos cuando
00:01:03
¿Los algoritmos pueden reproducir perfectamente la realidad?
00:01:06
¿La línea entre lo verdadero y
00:01:08
lo falso se vuelve borroso,
00:01:09
erosionando
00:01:09
nuestra confianza en el contenido visual.
00:01:11
Las implicaciones para la privacidad
00:01:13
son igualmente preocupantes.
00:01:14
Los vídeos se pueden fabricar para
00:01:15
mostrar personas en situaciones
00:01:17
que nunca han experimentado,
00:01:19
arruinando la reputación en un instante.
00:01:20
En el mundo de
00:01:22
los medios de comunicación, donde la verdad es crucial,
00:01:24
las falsificaciones profundas se pueden usar para crear falsificaciones
00:01:27
noticias, manipular la opinión pública,
00:01:28
e incluso influir en el curso de las elecciones.
00:01:31
Afortunadamente, la tecnología
00:01:32
en sí misma ofrece un rayo de esperanza.
00:01:34
Los investigadores y las empresas están trabajando
00:01:36
sobre herramientas para detectar falsificaciones profundas.
00:01:38
Estas soluciones utilizan la inteligencia artificial para
00:01:40
analizar vídeos y detectar anomalías
00:01:42
que delatan la manipulación.
00:01:44
En este panorama en evolución,
00:01:45
una cosa permanece constante: la necesidad
00:01:48
mantenerse vigilante e informado.

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résultat(s)
00:00:05
Sinds het begin van de fotografie
00:00:07
beeldmanipulatie bestaat,
00:00:09
maar de komst van het digitale
00:00:11
tijdperk heeft de weg geopend voor
00:00:14
meer geavanceerde manipulaties,
00:00:15
soms uitdagend onze
00:00:16
perceptie van de werkelijkheid.
00:00:18
Onder deze innovaties
00:00:19
de deep fake valt op.
00:00:21
Vooral deze term,
00:00:22
een samensmelting van diepgaand leren en
00:00:25
nep verwijst naar video's of afbeeldingen
00:00:28
gegenereerd door AI-algoritmen.
00:00:29
Deze creaties zijn zo overtuigend
00:00:31
dat ze gemakkelijk kunnen zijn
00:00:33
aangezien voor echte opnames.
00:00:36
Het potentieel van deep fakes is enorm.
00:00:38
Denk aan bioscoopiconen zoals Marilyn
00:00:41
Monroe of James Dean die komen
00:00:43
weer tot leven om in nieuwe films op te treden
00:00:46
of stel je voor dat wereldleiders geven
00:00:48
toespraken die ze eigenlijk nooit hebben gehouden.
00:00:51
De mogelijkheden,
00:00:52
of ze nu creatief of kwaadaardig zijn,
00:00:53
zijn bijna eindeloos.
00:00:54
Echter,
00:00:55
deze technologische vooruitgang
00:00:56
ernstige ethische vragen stellen.
00:00:58
In een tijdperk waarin zien en geloven was,
00:01:01
Hoe kunnen we onze ogen nog steeds vertrouwen als
00:01:03
kunnen algoritmen de werkelijkheid perfect reproduceren?
00:01:06
De grens tussen waar en
00:01:08
vals wordt wazig,
00:01:09
eroderen
00:01:09
ons vertrouwen in visuele inhoud.
00:01:11
De gevolgen voor de privacy
00:01:13
zijn even zorgwekkend.
00:01:14
Video's kunnen worden gefabriceerd om
00:01:15
mensen in situaties laten zien
00:01:17
ze hebben nog nooit meegemaakt,
00:01:19
reputaties in een oogwenk kapot maken.
00:01:20
In de wereld van
00:01:22
media, waar waarheid cruciaal is,
00:01:24
diepe vervalsingen kunnen worden gebruikt om valse
00:01:27
nieuws, de publieke opinie manipuleren,
00:01:28
en zelfs invloed hebben op het verloop van de verkiezingen.
00:01:31
Gelukkig is de technologie
00:01:32
op zichzelf biedt een sprankje hoop.
00:01:34
Onderzoekers en bedrijven zijn aan het werk
00:01:36
over hulpmiddelen om diepe vervalsingen op te sporen.
00:01:38
Deze oplossingen maken gebruik van AI om
00:01:40
video's analyseren en afwijkingen opsporen
00:01:42
die manipulatie verraden.
00:01:44
In dit evoluerende landschap
00:01:45
één ding blijft constant: de behoefte
00:01:48
om waakzaam en op de hoogte te blijven.

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résultat(s)
00:00:05
Od zarania fotografii,
00:00:07
istniała manipulacja obrazem,
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ale pojawienie się cyfrowego
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Era otworzyła drogę do
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bardziej zaawansowane manipulacje,
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czasami rzucając wyzwanie naszym
00:00:16
Postrzeganie rzeczywistości.
00:00:18
Wśród tych innowacji,
00:00:19
Głęboka podróbka wyróżnia się.
00:00:21
Szczególnie ten termin,
00:00:22
połączenie głębokiego uczenia się i
00:00:25
fałszywe odnosi się do filmów lub obrazów
00:00:28
generowane przez algorytmy AI.
00:00:29
Te kreacje są tak przekonujące
00:00:31
że z łatwością mogą być
00:00:33
pomylone z autentycznymi nagraniami.
00:00:36
Potencjał głębokich podróbek jest ogromny.
00:00:38
Pomyśl o ikonach kina, takich jak Marilyn
00:00:41
Monroe lub James Dean, którzy przyjeżdżają
00:00:43
powrót do życia, aby grać w nowych filmach
00:00:46
lub wyobraź sobie, że światowi liderzy dają
00:00:48
przemówień, których tak naprawdę nigdy nie wygłosili.
00:00:51
Możliwości,
00:00:52
czy to kreatywne, czy złośliwe,
00:00:53
są prawie nieskończone.
00:00:54
Jednakże,
00:00:55
Te postępy technologiczne
00:00:56
Powoduje poważne pytania etyczne.
00:00:58
W czasach, w których widzenie oznaczało wiarę,
00:01:01
Jak możemy nadal ufać naszym oczom, kiedy
00:01:03
Algorytmy potrafią doskonale odtworzyć rzeczywistość?
00:01:06
Granica między prawdą a
00:01:08
fałsz staje się zamazany,
00:01:09
erozja
00:01:09
zaufanie do treści wizualnych.
00:01:11
Implikacje dla prywatności
00:01:13
Są równie niepokojące.
00:01:14
Filmy mogą być wytwarzane do
00:01:15
pokazać ludziom w sytuacjach
00:01:17
nigdy nie doświadczyli,
00:01:19
Zrujnuje reputację w jednej chwili.
00:01:20
W świecie
00:01:22
media, gdzie prawda jest kluczowa,
00:01:24
głębokie podróbki można wykorzystać do tworzenia fałszywych
00:01:27
wiadomości, manipulowanie opinią publiczną,
00:01:28
A nawet wpływać na przebieg wyborów.
00:01:31
Na szczęście technologia
00:01:32
sama daje przebłysk nadziei.
00:01:34
Naukowcy i firmy pracują
00:01:36
na narzędziach do wykrywania głębokich podróbek.
00:01:38
Rozwiązania te wykorzystują sztuczną inteligencję do
00:01:40
analizuj filmy i wykrywaj anomalie
00:01:42
To zdradza manipulację.
00:01:44
W tym ewoluującym krajobrazie,
00:01:45
jedna rzecz pozostaje stała potrzeba
00:01:48
pozostać czujnym i poinformowanym.

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résultat(s)
00:00:05
A fotózás hajnalától kezdve,
00:00:07
létezett képmanipuláció,
00:00:09
De a digitális megjelenése
00:00:11
A korszak megnyitotta az utat
00:00:14
fejlettebb manipulációk,
00:00:15
néha kihívást jelent a mi
00:00:16
A valóság észlelése.
00:00:18
Ezen újítások közül,
00:00:19
a mély hamisítvány kiemelkedik.
00:00:21
Különösen ez a kifejezés,
00:00:22
a mély tanulás fúziója és
00:00:25
hamis videókra vagy képekre utal
00:00:28
AI algoritmusok által generált.
00:00:29
Ezek az alkotások annyira meggyőzőek
00:00:31
hogy könnyen lehetnek
00:00:33
Eredeti felvételekkel téveszik.
00:00:36
A mély hamisítványok potenciálja hatalmas.
00:00:38
Gondoljon olyan moziikonokra, mint a Marilyn
00:00:41
Monroe vagy James Dean, akik jönnek
00:00:43
Vissza az életbe, hogy új filmekben szerepeljen
00:00:46
vagy képzelje el, hogy a világ vezetői adnak
00:00:48
Beszédek, amiket valójában soha nem tartottak.
00:00:51
A lehetőségek,
00:00:52
legyen az kreatív vagy rosszindulatú,
00:00:53
szinte végtelenek.
00:00:54
Azonban,
00:00:55
Ezek a technológiai fejlődés
00:00:56
Komoly etikai kérdéseket vet fel.
00:00:58
Egy olyan korszakban, amikor a látás hitet jelentett,
00:01:01
Hogyan bízhatunk még a szemünkben, amikor
00:01:03
Az algoritmusok tökéletesen reprodukálhatják a valóságot?
00:01:06
A határ az igaz és
00:01:08
hamis elmosódik,
00:01:09
erodálja
00:01:09
a vizuális tartalom iránti bizalmunk.
00:01:11
A magánéletre gyakorolt következmények
00:01:13
Ugyanilyen aggasztóak.
00:01:14
A videók előállíthatók
00:01:15
mutasd meg az embereket a helyzetekben
00:01:17
Soha nem tapasztaltak,
00:01:19
Egy pillanat alatt tönkreteszi a hírnevet.
00:01:20
A világában
00:01:22
média, ahol az igazság döntő fontosságú,
00:01:24
mély hamisítványok felhasználhatók hamis létrehozására
00:01:27
hírek, manipulálják a közvéleményt,
00:01:28
És még befolyásolja a választások menetét is.
00:01:31
Szerencsére a technológia
00:01:32
Maga a remény csillogását kínálja.
00:01:34
A kutatók és a vállalatok dolgoznak
00:01:36
a mély hamisítványok észlelésére szolgáló eszközökön.
00:01:38
Ezek a megoldások mesterséges intelligenciát használnak
00:01:40
videók elemzése és anomáliák észlelése
00:01:42
Ez elárulja a manipulációt.
00:01:44
Ebben a fejlődő tájban,
00:01:45
egy dolog állandó marad, az igény
00:01:48
Éber és tájékozott maradjon.

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Mandarine AI: WHAT YOU SHOULD KNOW

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Part 02 - Societal and Ethical Implications of Generative AI

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