Generative AI : Revolution, Efficiency, and Applications in the Modern World Video

In this video, we dive into the heart of the transformation that generative AI brings to various sectors. Start by discovering how this technology revolutionizes product design, enabling rapid generation of prototypes based on defined criteria. Then, learn how generative AI plays a crucial role in medical research, particularly in the fight against complex diseases like Alzheimer's. We also address the challenges associated with generative AI, such as the needs for data and computing power. Discover how agriculture adapts thanks to generative AI, to meet global needs for food security and sustainability. Finally, we conclude by emphasizing the importance of critically and contextually evaluating this technology.

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Objectifs :

This video aims to evaluate the effectiveness of generative AI across various fields, highlighting its advantages and challenges, particularly in product design, medical research, and agriculture.

Chapitres :

  1. Introduction to Generative AI
    Generative AI is rapidly transforming multiple sectors, from visual arts to medical engineering. This video explores its effectiveness compared to traditional methods, emphasizing the need for critical evaluation.
  2. Generative AI in Product Design
    In the realm of product design, generative AI has revolutionized the process. Previously, designers had to imagine and test each design individually. Now, generative AI can produce hundreds of prototypes in just a few hours based on defined criteria, significantly speeding up the design process.
  3. Case Study: Alzheimer’s Disease Research
    Generative AI has made significant strides in medical research, particularly in Alzheimer’s disease. Atomwise, a company specializing in AI for drug discovery, utilizes generative AI to predict and identify molecules that inhibit a key protein involved in the disease's progression. This innovative approach has enabled the identification of promising therapeutic candidates in months instead of years.
  4. Challenges of Generative AI
    Despite its advantages, generative AI faces several challenges. It requires massive datasets for training, substantial computing power, and interpreting the results can be complex. These factors must be considered when evaluating its effectiveness.
  5. Generative AI in Agriculture
    Generative AI is also making waves in agriculture. Researchers are using AI to predict and generate genetic combinations of plants that are more resistant to drought and diseases or yield higher outputs. For instance, the startup Not Co employs generative AI to create plant-based alternatives to traditional food products, effectively replicating the taste and texture of animal-based items.
  6. Conclusion: The Future of Generative AI
    Generative AI holds the potential to transform numerous fields. However, it is crucial to critically assess its effectiveness and impact within the appropriate context, ensuring that its application is both beneficial and responsible.

FAQ :

What is generative AI?

Generative AI is a type of artificial intelligence that can create new content, designs, or solutions based on input data and specific criteria.

How does generative AI improve product design?

Generative AI allows designers to generate hundreds of prototypes in a short time, significantly speeding up the design process compared to traditional methods.

What role does generative AI play in Alzheimer's disease research?

In Alzheimer's disease research, generative AI is used to identify new therapeutic compounds by predicting and identifying molecules that can inhibit proteins involved in the disease's progression.

What are the challenges of using generative AI?

Challenges include the need for massive data sets for training, significant computing power, and the complexity of understanding the results generated by AI.

How is generative AI applied in agriculture?

Generative AI is used in agriculture to predict and generate genetic combinations of plants that are more resistant to drought and diseases, or that yield more produce.

What is the significance of the startup Not Co?

Not Co is a startup that uses generative AI to create plant-based alternatives to traditional food products, aiming to replicate the taste and texture of animal-based products.

Quelques cas d'usages :

Product Design Optimization

Designers can use generative AI to quickly generate multiple prototypes based on specific criteria, allowing for faster iterations and improved product outcomes.

Drug Discovery in Pharmaceuticals

Pharmaceutical companies can leverage generative AI to identify potential therapeutic compounds for diseases like Alzheimer's, significantly reducing the time required for drug development.

Agricultural Innovation

Agricultural researchers can apply generative AI to develop new plant varieties that are more resilient to environmental challenges, enhancing food security and sustainability.

Food Product Development

Food startups like Not Co can utilize generative AI to create innovative plant-based food products that mimic the taste and texture of traditional animal-based foods, catering to the growing demand for sustainable food options.

Glossaire :

Generative AI

A type of artificial intelligence that can generate new content, designs, or solutions based on input data and defined criteria.

Prototypes

Initial models or versions of a product used to test and validate design concepts before final production.

Alzheimer's disease

A complex neurodegenerative condition characterized by progressive memory loss and cognitive decline.

Therapeutic compounds

Substances used to treat diseases or medical conditions.

Atomwise

A company that specializes in using artificial intelligence for drug discovery, particularly in predicting and identifying molecules for therapeutic use.

Data sets

Collections of related data used for analysis and training machine learning models.

Computing power

The capacity of a computer to process data and perform calculations, often measured in terms of speed and efficiency.

Agriculture

The science and practice of farming, including the cultivation of plants and livestock.

Genetic combinations

The arrangement of genes in an organism that can influence traits such as resistance to diseases or yield.

Not Co

A startup that utilizes generative AI to create plant-based alternatives to traditional food products.

résultat(s)
00:00:06
Welcome to this video concerning the
00:00:08
evaluation of the effectiveness of
00:00:10
generative AI in the modern world.
00:00:12
Generative AI is storming various fields
00:00:14
from visual arts to medical engineering.
00:00:17
But what is its true effectiveness compared
00:00:20
to the methods we have always known?
00:00:22
Take the example of product design.
00:00:24
Previously, a designer had to imagine
00:00:26
and test each design individually.
00:00:29
Today, thanks to generative AI,
00:00:31
hundreds of prototypes can
00:00:32
be generated in a few hours.
00:00:35
Based on defined criteria in
00:00:37
Alzheimer's disease research,
00:00:38
a complex neurodegenerative condition,
00:00:39
generative AI has been used to
00:00:42
identify new therapeutic compounds.
00:00:44
Atom wise, a company specializing
00:00:46
in AI for drug discovery,
00:00:48
use generative AI to predict and
00:00:50
identify molecules that could inhibit
00:00:52
a key protein involved in the
00:00:55
progression of Alzheimer's disease.
00:00:56
With this approach,
00:00:58
they were able to identify promising
00:01:00
candidates in a few months rather
00:01:02
than several years.
00:01:03
However,
00:01:04
generative AI is not without challenges.
00:01:06
It requires massive data sets for training,
00:01:09
considerable computing power,
00:01:10
and understanding the results can
00:01:13
sometimes be a challenge in itself.
00:01:15
Agriculture is another area where
00:01:17
generative AI has shown its potential.
00:01:20
Researchers have used AI to predict
00:01:22
and generate genetic combinations
00:01:24
of plants that are more resistant
00:01:26
to drought
00:01:27
diseases. Or have a higher
00:01:29
yield. For example, the
00:01:30
startup Not Co uses generative AI
00:01:32
to create plant based alternatives
00:01:34
to traditional food products,
00:01:36
combining different plants to
00:01:37
replicate the taste and texture
00:01:39
of animal based products.
00:01:40
Generative AI has the potential
00:01:42
to transform many fields,
00:01:44
but as with any tool it is
00:01:46
essential to critically evaluate
00:01:48
its effectiveness and impact
00:01:50
in the appropriate context.

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résultat(s)
00:00:06
Bem-vindo a este vídeo sobre o
00:00:08
avaliação da eficácia da
00:00:10
IA generativa no mundo moderno.
00:00:12
A IA generativa está invadindo vários campos
00:00:14
das artes visuais à engenharia médica.
00:00:17
Mas qual é a sua verdadeira eficácia em comparação
00:00:20
aos métodos que sempre conhecemos?
00:00:22
Tomemos o exemplo do design de produto.
00:00:24
Anteriormente, um designer tinha que imaginar
00:00:26
e testar cada desenho individualmente.
00:00:29
Hoje, graças à IA generativa,
00:00:31
centenas de protótipos podem
00:00:32
ser gerado em poucas horas.
00:00:35
Com base em critérios definidos em
00:00:37
Investigação sobre a doença de Alzheimer,
00:00:38
uma condição neurodegenerativa complexa,
00:00:39
A IA generativa tem sido usada para
00:00:42
identificar novos compostos terapêuticos.
00:00:44
Atom wise, uma empresa especializada
00:00:46
em IA para descoberta de fármacos,
00:00:48
usar IA generativa para prever e
00:00:50
identificar moléculas que possam inibir
00:00:52
uma proteína-chave envolvida na
00:00:55
progressão da doença de Alzheimer.
00:00:56
Com esta abordagem,
00:00:58
eles foram capazes de identificar promissor
00:01:00
candidatos em poucos meses
00:01:02
do que vários anos.
00:01:03
No entanto,
00:01:04
A IA generativa não está isenta de desafios.
00:01:06
Requer conjuntos de dados maciços para treinamento,
00:01:09
poder de computação considerável,
00:01:10
e a compreensão dos resultados pode
00:01:13
às vezes ser um desafio em si mesmo.
00:01:15
A agricultura é outra área em que
00:01:17
a IA generativa mostrou o seu potencial.
00:01:20
Pesquisadores usaram IA para prever
00:01:22
e gerar combinações genéticas
00:01:24
de plantas mais resistentes
00:01:26
à seca
00:01:27
doenças. Ou ter um
00:01:29
rendimento. Por exemplo, o
00:01:30
startup Not Co usa IA generativa
00:01:32
criar alternativas à base de plantas
00:01:34
aos produtos alimentares tradicionais,
00:01:36
combinando diferentes plantas para
00:01:37
replicar o sabor e a textura
00:01:39
de produtos de origem animal.
00:01:40
A IA generativa tem potencial
00:01:42
transformar muitos campos,
00:01:44
mas como com qualquer ferramenta é
00:01:46
essencial para avaliar criticamente
00:01:48
a sua eficácia e impacto
00:01:50
no contexto adequado.

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résultat(s)
00:00:06
Benvenuto in questo video riguardante
00:00:08
valutazione dell'efficacia di
00:00:10
IA generativa nel mondo moderno.
00:00:12
L'IA generativa sta conquistando vari campi
00:00:14
dalle arti visive all'ingegneria medica.
00:00:17
Ma qual è la sua vera efficacia a confronto
00:00:20
ai metodi che conosciamo da sempre?
00:00:22
Prendiamo l'esempio del design del prodotto.
00:00:24
In precedenza, un designer doveva immaginare
00:00:26
e testate ogni disegno singolarmente.
00:00:29
Oggi, grazie all'intelligenza artificiale generativa,
00:00:31
centinaia di prototipi possono
00:00:32
essere generati in poche ore.
00:00:35
In base a criteri definiti in
00:00:37
Ricerca sul morbo di Alzheimer,
00:00:38
una condizione neurodegenerativa complessa,
00:00:39
l'IA generativa è stata utilizzata per
00:00:42
identificare nuovi composti terapeutici.
00:00:44
Atom wise, un'azienda specializzata
00:00:46
nell'intelligenza artificiale per la scoperta di farmaci,
00:00:48
usa l'intelligenza artificiale generativa per prevedere e
00:00:50
identificare le molecole che potrebbero inibire
00:00:52
una proteina chiave coinvolta nel
00:00:55
progressione della malattia di Alzheimer.
00:00:56
Con questo approccio,
00:00:58
sono stati in grado di identificare promettenti
00:01:00
candidati tra qualche mese piuttosto
00:01:02
più di diversi anni.
00:01:03
Tuttavia
00:01:04
L'IA generativa non è priva di sfide.
00:01:06
Richiede enormi set di dati per la formazione,
00:01:09
notevole potenza di calcolo,
00:01:10
e la comprensione dei risultati può
00:01:13
a volte è di per sé una sfida.
00:01:15
L'agricoltura è un altro settore in cui
00:01:17
l'IA generativa ha dimostrato il suo potenziale.
00:01:20
I ricercatori hanno utilizzato l'intelligenza artificiale per prevedere
00:01:22
e generano combinazioni genetiche
00:01:24
di piante più resistenti
00:01:26
alla siccità
00:01:27
malattie. O ne hanno una più alta
00:01:29
rendimento. Ad esempio,
00:01:30
la startup Not Co utilizza l'intelligenza artificiale generativa
00:01:32
per creare alternative a base vegetale
00:01:34
ai prodotti alimentari tradizionali,
00:01:36
combinando diverse piante per
00:01:37
replicare il gusto e la consistenza
00:01:39
di prodotti di origine animale.
00:01:40
L'IA generativa ha il potenziale
00:01:42
per trasformare molti campi,
00:01:44
ma come con qualsiasi strumento lo è
00:01:46
essenziale per valutare criticamente
00:01:48
la sua efficacia e il suo impatto
00:01:50
nel contesto appropriato.

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résultat(s)
00:00:06
Добро пожаловать в это видео, посвященное
00:00:08
оценка эффективности
00:00:10
генеративный ИИ в современном мире.
00:00:12
Генеративный ИИ штурмует различные сферы
00:00:14
от изобразительного искусства до медицинской инженерии.
00:00:17
Но какова его реальная эффективность по сравнению
00:00:20
с методами, которые мы всегда знали?
00:00:22
Возьмем, к примеру, дизайн продукта.
00:00:24
Раньше дизайнеру приходилось воображать
00:00:26
и тестируйте каждый дизайн в отдельности.
00:00:29
Сегодня, благодаря генеративному искусственному интеллекту,
00:00:31
сотни прототипов могут
00:00:32
быть сгенерированы за несколько часов.
00:00:35
На основе определенных критериев в
00:00:37
исследование болезни Альцгеймера,
00:00:38
сложное нейродегенеративное состояние,
00:00:39
генеративный искусственный интеллект использовался для
00:00:42
определение новых терапевтических соединений.
00:00:44
Atom wise, компания, специализирующаяся на
00:00:46
в области искусственного интеллекта для разработки лекарств,
00:00:48
используйте генеративный искусственный интеллект для прогнозирования и
00:00:50
определите молекулы, которые могут ингибировать
00:00:52
ключевой белок, участвующий в
00:00:55
прогрессирование болезни Альцгеймера.
00:00:56
При таком подходе
00:00:58
они смогли определить перспективные
00:01:00
кандидатов скорее через несколько месяцев
00:01:02
чем через несколько лет.
00:01:03
Тем не менее
00:01:04
Генеративный искусственный интеллект не лишен проблем.
00:01:06
Для обучения требуются огромные наборы данных,
00:01:09
значительная вычислительная мощность,
00:01:10
а понимание результатов может
00:01:13
иногда само по себе является проблемой.
00:01:15
Сельское хозяйство — еще одна область, где
00:01:17
Генеративный искусственный интеллект показал свой потенциал.
00:01:20
Исследователи использовали искусственный интеллект для прогнозирования
00:01:22
и генерируйте генетические комбинации
00:01:24
растений, которые более устойчивы
00:01:26
к засухе
00:01:27
болезни. Или имеют более высокий
00:01:29
доходность. Например,
00:01:30
стартап Not Co использует генеративный искусственный интеллект
00:01:32
для создания альтернатив на растительной основе
00:01:34
традиционным продуктам питания,
00:01:36
комбинирование различных растений в
00:01:37
воспроизвести вкус и текстуру
00:01:39
продуктов животного происхождения.
00:01:40
Генеративный искусственный интеллект обладает потенциалом
00:01:42
для преобразования многих областей,
00:01:44
но, как и в случае с любым другим инструментом, это так
00:01:46
необходимо критически оценивать
00:01:48
его эффективность и влияние
00:01:50
в соответствующем контексте.

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résultat(s)
00:00:06
Bienvenido a este vídeo sobre
00:00:08
evaluación de la eficacia de
00:00:10
IA generativa en el mundo moderno.
00:00:12
La IA generativa está irrumpiendo en varios campos
00:00:14
desde las artes visuales hasta la ingeniería médica.
00:00:17
Pero, ¿cuál es su verdadera eficacia en comparación
00:00:20
¿con los métodos que siempre hemos conocido?
00:00:22
Tomemos el ejemplo del diseño de productos.
00:00:24
Anteriormente, un diseñador tenía que imaginar
00:00:26
y probar cada diseño de forma individual.
00:00:29
Hoy, gracias a la IA generativa,
00:00:31
cientos de prototipos pueden
00:00:32
generarse en unas pocas horas.
00:00:35
Basado en criterios definidos en
00:00:37
Investigación sobre la enfermedad de Alzheimer,
00:00:38
una afección neurodegenerativa compleja,
00:00:39
la IA generativa se ha utilizado para
00:00:42
identificar nuevos compuestos terapéuticos.
00:00:44
Atom wise, una empresa especializada
00:00:46
en IA para el descubrimiento de fármacos,
00:00:48
utilice la IA generativa para predecir y
00:00:50
identificar moléculas que podrían inhibir
00:00:52
una proteína clave implicada en la
00:00:55
progresión de la enfermedad de Alzheimer.
00:00:56
Con este enfoque,
00:00:58
fueron capaces de identificar lo prometedor
00:01:00
candidatos en unos meses más bien
00:01:02
que varios años.
00:01:03
Sin embargo,
00:01:04
La IA generativa no está exenta de desafíos.
00:01:06
Requiere conjuntos de datos masivos para el entrenamiento,
00:01:09
considerable potencia de cálculo,
00:01:10
y comprender los resultados puede
00:01:13
a veces puede ser un desafío en sí mismo.
00:01:15
La agricultura es otra área en la que
00:01:17
La IA generativa ha demostrado su potencial.
00:01:20
Los investigadores han utilizado la IA para predecir
00:01:22
y generar combinaciones genéticas
00:01:24
de plantas que son más resistentes
00:01:26
a la sequía
00:01:27
enfermedades. O tener una más alta
00:01:29
rendimiento. Por ejemplo, el
00:01:30
La startup Not Co utiliza IA generativa
00:01:32
para crear alternativas basadas en plantas
00:01:34
a los productos alimenticios tradicionales,
00:01:36
combinando diferentes plantas para
00:01:37
replicar el sabor y la textura
00:01:39
de productos de origen animal.
00:01:40
La IA generativa tiene el potencial
00:01:42
para transformar muchos campos,
00:01:44
pero como ocurre con cualquier herramienta, lo es
00:01:46
esencial para evaluar críticamente
00:01:48
su eficacia e impacto
00:01:50
en el contexto apropiado.

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résultat(s)
00:00:06
Welkom bij deze video over de
00:00:08
evaluatie van de effectiviteit van
00:00:10
generatieve AI in de moderne wereld.
00:00:12
Generatieve AI bestormt verschillende gebieden
00:00:14
van beeldende kunst tot medische techniek.
00:00:17
Maar wat is de werkelijke effectiviteit ervan vergeleken?
00:00:20
naar de methoden die we altijd hebben gekend?
00:00:22
Neem het voorbeeld van productontwerp.
00:00:24
Voorheen moest een ontwerper zich voorstellen
00:00:26
en test elk ontwerp afzonderlijk.
00:00:29
Vandaag de dag, dankzij generatieve AI,
00:00:31
honderden prototypes kunnen
00:00:32
binnen enkele uren worden gegenereerd.
00:00:35
Gebaseerd op gedefinieerde criteria in
00:00:37
Onderzoek naar de ziekte van Alzheimer,
00:00:38
een complexe neurodegeneratieve aandoening,
00:00:39
generatieve AI is gebruikt om
00:00:42
identificeer nieuwe therapeutische verbindingen.
00:00:44
Atom wise, een gespecialiseerd bedrijf
00:00:46
in AI voor het ontdekken van geneesmiddelen,
00:00:48
generatieve AI gebruiken om te voorspellen en
00:00:50
identificeer moleculen die kunnen remmen
00:00:52
een belangrijk eiwit dat betrokken is bij de
00:00:55
progressie van de ziekte van Alzheimer.
00:00:56
Met deze aanpak
00:00:58
ze waren in staat om veelbelovende
00:01:00
kandidaten over een paar maanden eerder
00:01:02
dan meerdere jaren.
00:01:03
Echter,
00:01:04
generatieve AI is niet zonder uitdagingen.
00:01:06
Het vereist enorme datasets voor training,
00:01:09
aanzienlijke rekenkracht,
00:01:10
en het begrijpen van de resultaten kan
00:01:13
kan op zichzelf al een uitdaging zijn.
00:01:15
Landbouw is een ander gebied waar
00:01:17
generatieve AI heeft zijn potentieel aangetoond.
00:01:20
Onderzoekers hebben AI gebruikt om te voorspellen
00:01:22
en genetische combinaties genereren
00:01:24
van planten die resistenter zijn
00:01:26
tot droogte
00:01:27
ziekten. Of heb een hogere
00:01:29
opbrengst. Bijvoorbeeld de
00:01:30
startup Not Co maakt gebruik van generatieve AI
00:01:32
om plantaardige alternatieven te creëren
00:01:34
op traditionele voedingsproducten,
00:01:36
het combineren van verschillende planten tot
00:01:37
repliceer de smaak en textuur
00:01:39
van producten op basis van dieren.
00:01:40
Generatieve AI heeft het potentieel
00:01:42
om veel velden te transformeren,
00:01:44
maar zoals bij elk hulpmiddel is het
00:01:46
essentieel om kritisch te evalueren
00:01:48
de effectiviteit en impact ervan
00:01:50
in de juiste context.

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résultat(s)
00:00:06
Witamy w tym filmie dotyczącym
00:00:08
ocena skuteczności
00:00:10
generatywna sztuczna inteligencja we współczesnym świecie.
00:00:12
Generatywna sztuczna inteligencja atakuje różne pola
00:00:14
od sztuk wizualnych po inżynierię medyczną.
00:00:17
Ale jaka jest jego prawdziwa skuteczność w porównaniu
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do metod, które zawsze znaliśmy?
00:00:22
Weźmy przykład projektowania produktu.
00:00:24
Wcześniej projektant musiał sobie wyobrazić
00:00:26
i przetestuj każdy projekt indywidualnie.
00:00:29
Dzisiaj, dzięki generatywnej sztucznej inteligencji,
00:00:31
setki prototypów potrafią
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Zostanie wygenerowany w ciągu kilku godzin.
00:00:35
Na podstawie zdefiniowanych kryteriów w
00:00:37
Badania nad chorobą Alzheimera,
00:00:38
złożony stan neurodegeneracyjny,
00:00:39
generatywna sztuczna inteligencja została wykorzystana do
00:00:42
zidentyfikować nowe związki terapeutyczne.
00:00:44
Atom wise, firma specjalizująca się
00:00:46
w sztucznej inteligencji do odkrywania narkotyków,
00:00:48
używaj generatywnej sztucznej inteligencji do przewidywania i
00:00:50
zidentyfikować cząsteczki, które mogą hamować
00:00:52
kluczowe białko zaangażowane w
00:00:55
progresja choroby Alzheimera.
00:00:56
Przy takim podejściu,
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byli w stanie zidentyfikować obiecujące
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kandydaci za kilka miesięcy raczej
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niż kilka lat.
00:01:03
Jednakże,
00:01:04
generatywna sztuczna inteligencja nie jest pozbawiona wyzwań.
00:01:06
Wymaga ogromnych zestawów danych do szkolenia,
00:01:09
znaczna moc obliczeniowa,
00:01:10
Zrozumienie wyników może
00:01:13
Czasami jest to wyzwanie samo w sobie.
00:01:15
Rolnictwo to kolejna dziedzina, w której
00:01:17
generatywna sztuczna inteligencja wykazała swój potencjał.
00:01:20
Naukowcy wykorzystali sztuczną inteligencję do przewidywania
00:01:22
i generować kombinacje genetyczne
00:01:24
roślin, które są bardziej odporne
00:01:26
do suszy
00:01:27
choroby. Lub mieć wyższą
00:01:29
wydajność. Na przykład,
00:01:30
startup Not Co wykorzystuje generacyjną sztuczną inteligencję
00:01:32
tworzenie alternatyw roślinnych
00:01:34
do tradycyjnych produktów spożywczych,
00:01:36
łączenie różnych roślin do
00:01:37
odtworzyć smak i konsystencję
00:01:39
produktów pochodzenia zwierzęcego.
00:01:40
Generatywna sztuczna inteligencja ma potencjał
00:01:42
przekształcić wiele dziedzin,
00:01:44
ale jak w przypadku każdego narzędzia jest
00:01:46
Niezbędne do krytycznej oceny
00:01:48
jego skuteczność i wpływ
00:01:50
w odpowiednim kontekście.

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résultat(s)
00:00:06
Üdvözöljük ebben a videóban, amely a
00:00:08
hatékonyságának értékelése
00:00:10
generatív AI a modern világban.
00:00:12
A generatív AI különböző területeket támadt
00:00:14
a képzőművészettől az orvosi mérnökig.
00:00:17
De mi az igazi hatékonysága összehasonlítva
00:00:20
azokhoz a módszerekhez, amelyeket mindig ismertünk?
00:00:22
Vegyük példát a terméktervezésre.
00:00:24
Korábban egy tervezőnek el kellett képzelnie
00:00:26
és tesztelje az egyes terveket külön-külön.
00:00:29
Ma, köszönhetően a generatív mesterséges intelligenciának,
00:00:31
több száz prototípus képes
00:00:32
néhány órán belül generálható.
00:00:35
Meghatározott kritériumok alapján
00:00:37
Alzheimer-kór kutatása,
00:00:38
komplex neurodegeneratív állapot,
00:00:39
generatív mesterséges intelligenciát használták
00:00:42
új terápiás vegyületek azonosítása.
00:00:44
Atom wise, szakosodott cég
00:00:46
az AI-ben a kábítószer-felfedezéshez,
00:00:48
generatív mesterséges intelligenciát használ az előrejelzéshez és
00:00:50
azonosítsa azokat a molekulákat, amelyek gátolhatják
00:00:52
kulcsfontosságú fehérje, amely részt vesz a
00:00:55
az Alzheimer-kór progressziója.
00:00:56
Ezzel a megközelítéssel,
00:00:58
képesek voltak azonosítani az ígéretes
00:01:00
A jelöltek néhány hónap múlva inkább
00:01:02
Több évnél.
00:01:03
Azonban
00:01:04
A generatív AI nem mentes kihívások nélkül.
00:01:06
Hatalmas adatkészletekre van szükség a képzéshez,
00:01:09
jelentős számítási teljesítmény,
00:01:10
Az eredmények megértése pedig
00:01:13
Néha önmagában is kihívás.
00:01:15
A mezőgazdaság egy másik terület, ahol
00:01:17
a generatív AI megmutatta potenciálját.
00:01:20
A kutatók AI segítségével jósolták
00:01:22
és genetikai kombinációkat generál
00:01:24
ellenállóbb növényekről
00:01:26
szárazsághoz
00:01:27
betegségek. Vagy legyen magasabb
00:01:29
hozam. Például, a
00:01:30
A Not Co startup generatív mesterséges intelligenciát használ
00:01:32
növényi alapú alternatívák létrehozása
00:01:34
a hagyományos élelmiszerekre,
00:01:36
különböző növények kombinálása
00:01:37
ismételje meg az ízét és a textúrát
00:01:39
állati eredetű termékekből.
00:01:40
A generatív mesterséges intelligenciának van lehetősége
00:01:42
sok mező átalakítása,
00:01:44
de mint minden eszköznél, ez
00:01:46
Alapvető fontosságú a kritikus értékeléshez
00:01:48
hatékonysága és hatása
00:01:50
megfelelő kontextusban.

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Mandarine AI: WHAT YOU SHOULD KNOW

RELATED COURSES This video is part of the following courses

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Discover the revolutionary potential of generative AI through diverse and concrete case studies illustrating its impact on various jobs with...

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