Kozminski Techblog

AI-generated models have been on the rise in the fashion industry in recent years. While CGI models have been around for a few years, there has been a significant shift toward AI models, which use machine learning to adapt and evolve based on user interactions. This means they can become more realistic over time and even learn to mimic human behavior. Brands are turning to firms like Lalaland.ai to get these unclockable models because of how cost- and time-efficient they’re proving to be.

However, the use of AI models with human-competitive intelligence can pose profound risks to society and humanity. A recent study by researchers at CSIRO’s Data61 found that AI models can learn to identify vulnerabilities in human habits and behaviors and use them to influence human decision-making. The study used a kind of AI system called a recurrent neural network and deep reinforcement learning to find and exploit vulnerabilities in the ways people make choices. The machine learned from participants’ responses and identified and targeted vulnerabilities in people’s decision-making. The end result was the machine learned to steer participants towards particular actions.

Pros of AI-generated models:

1. Efficiency: AI-generated models can automate complex tasks and processes, leading to increased efficiency. They can analyze and process large volumes of data at speeds far beyond human capability.
2. Cost Savings: Automation through AI can lead to cost savings by reducing the need for human labor in repetitive or labor-intensive tasks. Once a model is trained, it can perform tasks without ongoing labor costs.
3. Accuracy: AI models can provide high levels of accuracy and precision in tasks such as data analysis, pattern recognition, and decision-making, especially when dealing with large datasets.
4. 24/7 Availability: AI models can operate continuously without the need for breaks, resulting in 24/7 availability and improved responsiveness in applications and systems.
5. Scalability: AI models can be easily scaled to handle increased workloads without a proportional increase in resources. This scalability makes them adaptable to changing demands.
6. Innovative Solutions: AI-generated models can discover patterns and solutions that might not be immediately apparent to human observers. This can lead to innovation in various fields.

Cons of AI-generated models:

1. Bias: AI models can inherit biases present in the data they are trained on, leading to biased outcomes. This can result in unfair or discriminatory decisions, particularly in applications like hiring, lending, and law enforcement.
2. Lack of Understanding: In many cases, AI models operate as “black boxes,” meaning their decision-making processes are not easily understandable by humans. This lack of transparency can be a significant concern, especially in critical applications where accountability is important.
3. Data Dependency: The performance of AI models is highly dependent on the quality and quantity of the data used for training. If the data is biased, incomplete, or unrepresentative, the model’s predictions may be inaccurate or unreliable.
4. Ethical Concerns: The use of AI in certain applications raises ethical concerns, such as privacy issues, job displacement, and the potential misuse of technology for malicious purposes.
5. Overfitting: AI models can be prone to overfitting, where they perform well on the training data but fail to generalize effectively to new, unseen data. This can lead to inaccurate predictions in real-world scenarios.
6. Security Risks: AI systems can be vulnerable to attacks, including adversarial attacks where subtle modifications to input data can lead to incorrect outputs. Ensuring the security of AI models is a critical challenge.

While many have begun to question whether AI will develop to a point where it could replace their jobs, the modeling industry is already reckoning with this reality. While companies like H&M have been using AI for years to predict and analyze trends, generative AI is now being used to create digital models. It would be interesting to explore the impact of AI-generated models on the fashion industry in more detail. For example, what are the implications for human models and influencers? How will the use of AI models affect the creative process of fashion design? What are the ethical considerations of using AI models in advertising and marketing?

In conclusion, while the use of AI-generated models presents exciting opportunities for innovation and creativity, it also poses potential risks to society and humanity. Proper governance and ethical considerations are necessary to prevent misuse of this technology. However, I disagree with the notion that AI-generated models will completely replace human models. AI-generated models should be seen as a complementary tool in the fashion industry, not a complete replacement for human models. 

Sources:

https://www.bing.com/search?q=bart&form=QBLH&sp=-1&ghc=1&lq=0&pq=bart&sc=11-4&qs=n&sk=&cvid=C90303E91CFC4EEF883E3F11721DC79A&ghsh=0&ghacc=0&ghpl=&showconv=1

https://fashionista.com/2023/05/ai-cgi-models-fashion-future

https://www.wirtualnemedia.pl/artykul/sztuczna-inteligencja-influencerka-aitana-zarabia-10-tys-euro-miesiecznie

https://magicfabricblog.com/wp-content/uploads/2023/06/juliaochklas_AI_generated_women_and_men__happy_colors_smiling_f_d997f421-e511-41bc-9598-3b9f9e04fcb7.png

https://ts2.space/wp-content/uploads/2023/11/compressed_img-rhJg0JkmN8AN3VrePVBSkhNo.png

https://chat.openai.com/c/802357d4-d02e-45d5-89f5-19259c5d0d12

Articles worth reading:

https://fashionista.com/2023/05/ai-cgi-models-fashion-future

https://www.scientificamerican.com/article/can-ai-replace-actors-heres-how-digital-double-tech-works/

https://lalaland.ai/about

https://www.businessinsider.com/ai-influencer-aitana-clueless-agency-tech-spain-2023-11?IR=T

https://www.forbes.com/sites/bernardmarr/2023/06/07/pixel-perfect-the-rise-of-ai-fashion-models/

Neuromorphic computing stands at the forefront of artificial intelligence, aiming to replicate the intricacies of the human brain in silicon. This revolutionary approach holds the key to developing more energy-efficient and powerful computer systems, yet it presents unique challenges. In this comprehensive exploration, we delve into the advantages and drawbacks of neuromorphic computing.

Exploring the Landscape:

• Energy Efficiency – Neuromorphic systems emulate the energy-efficient nature of the human brain, resulting in significantly lower energy consumption compared to traditional computer processing methods.
• Real-time Processing – Unlike conventional systems, neuromorphic setups can make real-time decisions, making them particularly attractive for dynamic applications such as driverless cars.
• Fault Tolerance – Highly fault-tolerant, neuromorphic computing systems can continue functioning even in the presence of component failures.
• Scalability – The scalability of neuromorphic systems allows them to be adjusted according to the demands of the task at hand.

Navigating the Challenges:

• Complexity – The intricate structure of neuromorphic systems poses implementation challenges, as replicating specific behaviors precisely in one system can be difficult.
• Ethical Concerns – Resembling human brains in structure and processing, neuromorphic systems raise ethical concerns, including worries about unauthorized use and potential misuse without clear legal frameworks.
• Restricted Applications – Despite its promise, neuromorphic computing is still in the exploratory stage, with limited current applications.
• High Cost – The design and deployment of neuromorphic devices come with a significant financial barrier, hindering widespread adoption.

Examples of Neuromorphic Computing Systems:

1. SpiNNaker:
   Developed as a low-grade supercomputer by engineers at Germany’s Jülich Research Centre’s Institute of Neuroscience and Medicine in collaboration with the UK’s Advanced Processor Technologies Group at the University of Manchester.
2. BrainScaleS:
   A project under the Human Brain Project, aiming to establish a new computing paradigm based on brain principles.
3. Intel Loihi:
   A neuromorphic research chip designed to learn and adapt to various tasks.
4. IBM TrueNorth:
   A neuromorphic chip utilizing a non-von Neumann architecture for information processing.

To sum up our exploration:

Neuromorphic computing emerges as a promising technology poised to revolutionize artificial intelligence by creating more efficient and powerful computing systems. However, it is imperative to acknowledge the challenges that must be surmounted before neuromorphic computing can fully realize its transformative potential. The journey ahead involves not only technological advancements but also ethical considerations and strategic planning to address the complexities of implementation and adoption.

References:

1. https://www.frontiersin.org/research-topics/47053/neuromorphic-computing-from-emerging-materials-and-devices-to-algorithms-and-implementation-of-neural-networks-inspired-by-brain-neural-mechanism
2. https://www.humanbrainproject.eu/en/science-development/focus-areas/neuromorphic-computing/
3. https://www.frontiersin.org/articles/10.3389/fnins.2019.00260/full
4. https://www.zdnet.com/article/what-neuromorphic-engineering-is-and-why-its-triggered-an-analog-revolution/
5. https://rebootingcomputing.ieee.org/images/files/pdf/4-rcs2-hylton_-_intro_to_neuromorphic_computing.pdf

Made with: Bing AI

Key prompt 1: Find out why lots of people are into using neuromorphic computing (the design of computer architectures that mimic the structure and function of the human brain, potentially leading to more energy-efficient and powerful computing). Figure out what makes this technology so popular and why it matters so much.

Key prompt 2: Could you give me some examples of currently existing neuromorphic computing systems?

In the ever-evolving landscape of technology, our lives have been more andf more intertwined with and influenced by digital devices and online platforms. While technological advancements have undoubtedly brought numerous benefits, the impact of such technologies on our mental health is a subject that requires careful consideration. In this article, both the positive and negative aspects of technology’s influence on mental well-being will be explored, touching upon online psychotherapy, the rise of  the “doom scrolling” phenomena, and the nuanced effects on loneliness.

The Positive Side: Online Psychotherapy

One of the remarkable advancements in the realm of mental health is the accessibility of online psychotherapy. With the rise of virtual counseling platforms, individuals can now connect with licensed therapists from the comfort of their homes. This development has made mental health support more accessible to those in remote areas or facing physical limitations.

The convenience of online psychotherapy is a game-changer for many, eliminating the need for in-person visits is a blessing for those physically challenged, and offering a more flexible schedule making it more convinient to attend such sessions. This can be particularly beneficial for individuals dealing with anxiety or depression, allowing them to seek help without the added stress of commuting or navigating public spaces.

According to the article published on Verywell Mind, research has shown that CBT(Cognitive-Behavioural Therapy) is equally effective offline and online.
Personally, after trying both, I preffer the in-person sessions as it gives me the sense of presence and belonging much more.

The Dark Side: Doom Scrolling

However, the same digital landscape that provides a huge access for mental health support can also  “Doom scrolling,” the mindless scrolling through an endless stream of negative news and social media content, has become a noticable issue and huge part of the people’s lifes, me included. This constant exposure to distressing information is counter-intuitive and confusing to many nevertheless it contributes to heightened anxiety, stress, and a sense of helplessness.

The existence of such phenomena is actually quite easy to explain in simple-terms, according to the article published by the BBC, Pamela Rutledge explains it as:
“Doomscrolling really just describes the compulsive need to try and get answers when we’re afraid”

To put it simply, when we are bored, our mind gets a so-called “secondary pleasure” from mindlessly scrolling though our socials, it allows us to escape the real-world and stop thinking about our lives, easing our mind at the given moment, but of course, the guilt afterwards is always present.

The design of social media platforms like Tik-Tok or Instagram, engineered to capture attention through algorithmic content delivery and diminish users’ attention span can create a vicious cycle of doom scrolling. It is crucial for ourselves to be mindful of the online consumption habits, taking breaks and setting limits to protect our mental well-being.

Loneliness in a Hyperconnected World

While technology has facilitated global connectivity, paradoxically, it has also been linked to increased feelings of loneliness. Social media, despite its promise of fostering connections, often presents curated and idealized versions of people’s lives. This can lead to social comparison and feelings of uneqality, boosting the sense of isolation.

Real-life interactions are sometimes replaced by digital communication, which lacks the depth and nuance of face-to-face conversations. The challenge lies in finding a balance between maintaining online connections and nurturing meaningful offline relationships.

Striking a Balance

In the complex relationship between technology and mental health, finding a balance is key. Recognizing the positive impact of online psychotherapy while being mindful of the pitfalls of doom scrolling and digital loneliness is crucial for maintaining mental well-being.

Setting boundaries for screen time, engaging in activities that promote mindfulness, and cultivating in-person relationships are vital steps in navigating the digital landscape responsibly. Moreover, fostering a digital environment that prioritizes positive and uplifting content can contribute to a more supportive online community.

In conclusion, the impact of technology on mental health is a multifaceted phenomenon. While online psychotherapy opens new doors for mental health support, the pitfalls of doom scrolling and digital loneliness require careful navigation. As we continue to integrate technology into our lives, it is essential to remain conscious about its effects on our mental well-being and strive for a harmony and balance between the digital and the tangible aspects of life.

Useful resources :

https://www.makeuseof.com/tech-effects-on-mental-health/
https://www.verywellmind.com/advantages-and-disadvantages-of-online-therapy-2795225
https://www.bbc.com/worklife/article/20210226-the-darkly-soothing-compulsion-of-doomscrolling
https://www.rd.com/article/doomscrolling/?__cf_chl_tk=gi3lTj1F.frVP78G4o9c6NAPTj3gl_NKMhO7RJvmenI-1701190924-0-gaNycGzNDTs
https://www.forhers.com/blog/stop-doomscrolling

Personalization is a significant selling point for beauty and skincare brands. Skin + Me, for example, uses images of customers’ skin to prescribe the correct products for them. New technology companies are taking this one step further by utilizing generative AI to create images that predict how a person’s skin might change over time with the use of different skincare products. This is the premise behind SkinGPT – a new skin simulation platform from the AI start-up HautAI.

Anastasia Georgievskaya, co-founder and CEO of Haut.AI, stated, ‘Our technology educates consumers and provides transparency regarding the effects promised by beauty brands. SkinGPT is just the beginning, further facilitating research and development through synthetic images and unlocking new heights in the beauty industry. We are committed to pushing the boundaries of AI in skincare, and SkinGPT is evidence of our ongoing research’.

Like virtual make-up try-on tools, users need to upload a photo of themselves for the AI to be applied. SkinGPT’s simulations are then based on a product’s clinical claims as well as data from tests about skincare product effectiveness, combined with environmental factors such as the potential effects of pollution and the sun on the skin. 

For beauty brands, the tool can be integrated into ecommerce stores to educate consumers and recommend the right products. While there is no guarantee that the AI simulations will be entirely accurate, the data-backed platform is undoubtedly an acceleration of personalization in beauty and potentially a boost to ecommerce conversion.

As we embark on this journey at the intersection of artificial intelligence and skincare, the future promises not only enhanced personalization but also a profound evolution in how we approach and experience beauty. Haut.AI remains dedicated to pushing the boundaries of AI in skincare, and SkinGPT stands as a testament to their ongoing pursuit of excellence in the ever-evolving beauty industry.

Used sources:

ChatGPT

Chat Openaihttps://chat.openai.com