NutriNet – a personal assistant for your grocery shopping

18

October

2024

No ratings yet.

Have you ever taken hours browsing around supermarkets searching for the most nutritious food options? Did it take you too much time figuring out which recipes to cook best, with the groceries you bought? Struggles when dealing with food are numerous, starting from choosing products with appropriate nutrients simply not knowing enough recipes.

Therefore, we introduce NutriNet – a mobile application that is going to make shopping and meal planning easier!

• Grocery shopping & meal planning simplification:

NutriNet simplifies grocery shopping and meal planning, by analyzing which products and recipes fit the users’ desired grocery item wishes, nutrition values and store preferences best. NutriNet aims to address the challenges being implicit to personalized nutrition and helps consumers make healthier food choices by simplifying the grocery shopping and meal planning process. This shall be done by eliminating the need to perfectly understand all nutrition values or to search for numerous recipes. NutriNet completes all these tasks for you in real-time and provides clear and accessible recommendations for you.

• Real-time personal assitant: NutriNet acts as a multifunctional application providing value to consumers by solving various food related problems in real-time. Appearing as a chatbot, it is aimed at taking general grocery shopping lists or meal wishes as input query, combined with preferences for food characteristics (e.g., nutrients, allergies) and grocery stores. It then provides brand specific and personalized grocery shopping lists, as well as meal recommendations, if so desired. Moreover, grocery items can also be added into the initial grocery shopping list query, by scanning them with the integrated AR tool. The product will then be detected visually and thus will be integrated into the shopping list input query.

• Long-term customer engagement: NutriNet distinguishes from competition by providing personalized and customized advice. This is possible, as NutriNet consists of a database, having incorporated stock and product information of the major supermarkets in the Netherlands. In contrast, classic applications, which try to meet similar needs (e.g., meal recommendation) rather focus on counting nutrients for the purpose of short-term weight loss, instead of personalizing grocery shopping lists and meal recommendation to enable a healthier lifestyle for users. Those applications are usable on short term but are proven to have low adherence over the time (Chen et al., 2015).

• Personalized recommendations: NutriNet leverages generative AI to offer accurately personalized recommendations. Users can simply enter their preferences, while prompting a grocery list or a meal, such as gluten-free or high in protein, and the generative AI powered application will provide accurately personalized results.
However, personalization and raising awareness for healthy foods are not the only purposes of NutriNet. It also addresses sustainability issues that supermarkets are facing. By gathering consumer purchase and search data in the application, consulting services can be offered to supermarkets, enabling them to plan ordering and stockholding processes more efficient. Hence, supermarkets should be able to reduce food waste due to overstocking on long-term.

NutriNet offers a 2-sided network platform, yielding important value to both, consumers as well as supermarkets.

Contributors

574051 – Duong Dao
728070 – David Wurzer
738898 – David Do
562387 – Roxi Ni

References

Chen, J., Berkman, W., Bardouh, M., Ng, C. Y. K., & Allman-Farinelli, M. (2019). The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges. Nutrition, 57, 208-216.

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Unlocking Culinary Potential: How tasteTAILOR elevates your Cooking Experience with Generative AI

18

October

2024

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In today’s fast-paced world, health-conscious individuals and families often struggle to find the time and inspiration to cook nutritious meals. Therefore, we are presenting tasteTAILOR: a revolutionary digital culinary assistant that harnesses the power of Generative AI (GenAI) to streamline your cooking experience. It is designed to create recipes tailored to users’ diet choices, available ingredients, and kitchen appliances – offering a unique and personalized way of cooking. To streamline the cooking experience even further, tasteTAILOR seamlessly integrates its ingredient list with partner supermarkets. TasteTAILOR even offers a social community where users can share their experiences in the kitchen, get inspiration from other users, and connect with individuals with similar culinary interests.

Objectives and Value Proposition

TasteTAILOR’s most important objective is to grant customers the highest level of user satisfaction possible by making meal planning easy, seamless shopping through APIs, and engaging with the community through food recommendations powered by GenAI. Fundamentally, tasteTAILOR is committed to reducing food waste and fostering sustainable and healthy cooking with recipes to fit every taste.
We at tasteTAILOR present a multi-dimensional value proposition. We propose new dishes tailored to specific tastes but it will also generate shopping lists in supermarket applications in a hassle-free manner. Our customers can benefit from the step-by-step visual and audio instructions so that cooking can become enjoyable for everybody. The community feature provides an exciting way to connect with other like-minded culinary enthusiasts. 

Target Customer Segments

TasteTAILOR’s services are a perfect fit for several customer segments, for instance, busy professionals who have limited time to cook  but desire healthy recipes, students who are on an extremely tight budget and advanced hobby cooks who want to experiment with different types of cuisine and connect with other home cooks. The application also applies to people with special diet needs, making it the most suitable solution for those looking for a personalized cooking experience.

Key Activities and Resources

Key activities of tasteTAILOR include the design of customized recipes, using the power of GenAI technology. The personalization power comes from the analysis of user behavior, tracking one’s activity in the community, and through capturing user’s (daily) preferences.  Logically, the key resource of tasteTAILOR is the GenAI system that is woven throughout the entire business model, from generating recipes to chatbots intended for user interaction, and analytics that are inducted continuously for better personalization.

Challenges and Solutions

While the integration of GenAI offers significant benefits to the tasteTAILOR platform, it also comes with potential pitfalls, such as data privacy issues or technical glitches. The platform has taken stringent actions to consider these risks, implementing robust security measures and algorithm enhancement. The education of users through tutorials and community building is another crucial component in the adoption of AI-powered cooking solutions.

The Future of Meal Planning

Among the new generation of meal-planning applications and technological substitutions in a broader perspective, tasteTAILOR stands at the very top of elevating one’s cooking experience. TasteTAILOR offers personalized solutions that are not just tailored to the individual but are also ecologically-conscious. Taking everything into account, tasteTAILOR is not a meal planner; instead, it is a community-driven solution to empower its users to cook healthy recipes based on their own preferences. TasteTAILOR powered by GenAI is making cooking joyful.

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My Personal Chef

10

October

2024

5/5 (2)

Since its launch, I’ve mainly used ChatGPT to help me summarize academic articles and brainstorm ideas. Yesterday, I decided to let the LLM help me decide what to eat that night (OpenAI, 2024).

I rearranged the ingredients in my fridge so the main items were visible, moving condiments toward the back. I took a picture and uploaded it to ChatGPT with the prompt:

“What can I make for dinner tonight with these ingredients? I’m willing to go to the store for some additional ingredients needed.”

That’s it—just as if I asked a friend on the phone for a suggestion on what to make for dinner tonight, I asked the OpenAI model.

What it returned blew me away: (please note that formatted the output for visual appearances in this blog post).

“Here’s a simple recipe using the ingredients you have, plus some optional additions you could pick up from the store.

Butterscotch Pumpkin and Vegetable Curry

Ingredients from your pantry/fridge:

  • Butterscotch pumpkin
  • Carrots
  • Zucchini
  • Red bell peppers
  • Onions
  • Potatoes (optional, for a heartier curry)
  • Curry powder or paste (red or yellow)

Additions from the store (optional):

  • Coconut milk (for a creamier curry)
  • Fresh cilantro (for garnish)
  • Protein like chickpeas, tofu, or chicken

Instructions:

  1. Prepare the Veggies: Peel and cube the butterscotch pumpkin, and chop the zucchini, bell peppers, carrots, and potatoes.
  2. Sauté the Aromatics: In a large pot, sauté the onions in oil until they’re translucent.
  3. Add Spices: If you have curry powder or paste, add it to the onions and cook for a minute to release the flavours. If you’re using the peanut sauce as a curry base, add it now along with a dash of water.
  4. Add Veggies: Add the butterscotch pumpkin, carrots, and potatoes (if using). Let them cook for a few minutes.
  5. Simmer: Add coconut milk (if using) or water/stock, and simmer until the pumpkin and other veggies are tender (about 20 minutes).
  6. Add Other Veggies: Toss in zucchini and bell peppers, letting them cook for the last 5-7 minutes.
  7. Season: Taste and adjust seasoning with salt, pepper, or a touch of sugar if needed.
  8. Serve: Serve your curry over rice (you have poke rice) and garnish with fresh cilantro if you like.

    This will result in a rich, creamy, and slightly sweet curry with the pumpkin flavor shining through!Would you like to go ahead with this, or need adjustments?”

Amazing, right?! I was instantly inspired to cook this delicious-sounding meal and ran to the store for some chicken thighs and cilantro. Lucky for me, I already had the coconut milk, which the AI didn’t recognize in the picture.

For this blog post, I asked GPT to create an image inspired by this recipe:

While writing this blog post, I wondered if ChatGPT could give me an accurate estimate of the nutritional value of the dish, so I asked:

Caloric breakdown (per serving):

  • B. Pumpkin (100g)
    • Calories: 45
    • Carbohydrates: 11g
    • Protein: 1g
    • Fat: 0g
  • Carrots (50g)
    • Calories: 20
    • Carbohydrates: 4.5g
    • Protein: 0.5g
    • Fat: 0g
  • Zucchini (50g)
    • Calories: 8
    • Carbohydrates: 1.5g
    • Protein: 0.5g
    • Fat: 0g
  • Total:
  • Calories: 605 kcal
  • Carbohydrates: 86g
  • Protein: 28.8g
  • Fat: 15.5g
  • Bell Pepper (50g)
    • Calories: 15
    • Carbohydrates: 3g
    • Protein: 0.5g
    • Fat: 0g
  • Onion (30g)
    • Calories: 12
    • Carbohydrates: 3g
    • Protein: 0.3g
    • Fat: 0g
  • Coconut Milk (50ml)
    • Calories: 90
    • Carbohydrates: 2g
    • Protein: 1g
    • Fat: 9g
  • Curry Paste (15g)
    • Calories: 25
    • Carbohydrates: 5g
    • Protein: 0.5g
    • Fat: 0g
  • Rice (200g cooked)
    • Calories: 260
    • Carbohydrates: 56g
    • Protein: 5g
    • Fat: 0.5g
  • Chicken Thighs (100g)
    • Calories: 130
    • Carbohydrates: 0g
    • Protein: 19g
    • Fat: 6g

I am stunned! I checked the values online, and the caloric values only differed slightly (Grutto, 2024a; Voedingscentrum, 2024b). Not only does it give dinner suggestions and inspire me to make dinner with the ingredients I already have at home, but I can also keep a rough estimate of the macros I’ve consumed.
Imagine being on a diet and going out to eat with a friend. You want to keep track of your caloric intake but don’t want to bother bringing a scale to weigh your food with every new dish. Now you just take a picture, upload it to your Instagram story, and later upload it to ChatGPT to make a nutritional value estimate for you.

While this experience was undeniably impressive for me, it’s important to consider some limitations. For instance, the AI didn’t recognize the coconut milk in my picture, which was a key ingredient in the recipe it suggested. This highlights that image recognition technology isn’t foolproof, and you cannot rely on it 100%.
Also, while the nutritional estimates were close to official sources, they weren’t exact. For those with strict dietary requirements or allergies, relying solely on AI for nutritional information might not be a wise idea.
Lastly, uploading photos of your fridge or meals means sharing personal data with an AI service and thus can be a privacy concern. It’s important to be mindful of what you’re sharing and know how that data might be used or stored.

My experiment with using ChatGPT as a personal AI-chef was both enlightening and exciting. The ease of requesting a tailored dinner suggestion and a nutritional breakdown based on the contents of my fridge, shows me the potential of AI in everyday life. While there are limitations to consider, the benefits show a glimpse of the exciting future to come.

In the end, I find it amazing how the technology I first only use as a study and search tool, can also inspire me in other parts of everyday life. With my personal AI-chef, dinner dilemmas are a thing of the past.

Bibliography

Grutto, 2024, Bio Kipdijfilets bereiding en informatie Grutto! Available at: https://www.grutto.com/nl/vleesstuk/bio-kipdijfilet.

OpenAI, 2024, ChatGPT Available at: https://chatgpt.com.

Voedingscentrum, 2024, Hoeveel calorieën zitten erin? – Caloriechecker | Voedingscentrum Available at: https://www.voedingscentrum.nl/nl/service/vraag-en-antwoord/gezonde-voeding-en-voedingsstoffen/hoeveel-calorieen-zitten-erin-.aspx.

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Why OpenAI’s Text-to-image Model Falls Short

10

October

2024

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Since OpenAI launched its text-to-image GenAI tool, DALL-E, I have been using it for quite a while. Initially, I was amazed by how accurate and impressive the tool is for creating an image based on a short prompt, accurately depicting what I had expected in my mind. However, after using it a bit more, I started to realise that DALL-E has its limitations and is not yet ready to completely replace graphic designers or artists. 


If you have been using DALL-E for a while, you have probably experienced it creating weird texts in the image. As shown below in image 1, (prompt: Create an image of a tree in autumn in the Dutch city Utrecht, there are some stores with storefront names in the background), the store names are inaccurate, while the image itself looks amazing and of high quality.

Image 1: Created by DALL-E

Why can DALL-E create amazing visual images, but can’t produce normal text on these images while this seems so easy?

This is due to several technical issues. While the model is effective at understanding and generating visual elements based on prompts, it often lacks the capabilities to distinguish between visual content and written content. This limitation is rooted in the training technique of the models, when text is rendered as part of the image it becomes a visual pattern instead of a linguistic one. OpenAI has said that the next version, DALL-E 4, will have better results in distinguishing linguistic vs visual elements.

Another important issue to address, is the biased results from DALL-E. When asking to create an image of a CEO at work with an assistant, see image 2 (prompt: Create an immage of a CEO at work with an assistant), it will show a image of a man as a CEO and a woman as an assistant. This is because the model is trained on data from databases, where CEO’s are often represented as a man instead of a woman. Leading to biased and discriminatory results, ultimately reinforcing outdated gender stereotypes. The same counts for culturally insensitive and inappropriate results, because the model is not adapted to the cultural awareness of humans.

Image 2: Created by DALL-E

To conclude, these are just two of DALL-E’s limitations, while there are many more that I haven’t discussed. It is clear that DALL-E is not perfect and needs to improve their model before it can replace graphic designers or artists. Nonetheless, the potential for the future is immense, and for now, it is incredibly fun to experiment with.

Thanks for reading, if you have an opinion about this topic, please leave a comment below.

(Disclaimer: this blog is written based on my personal experience)

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AI and the automation of accounting 

9

October

2024

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AI has changed the landscape in many work fields, such as in data, law, finance and even accounting. Recently I have taken an assistant-accounting job at a firm paired with my master studies. I have discovered a lot about AI and what it could do for accounting that I thought were not possible.  Having been there for 2 months, I have learned a lot about accounting itself, but also what AI did for me while I was at the job. According to an article by the open journal of business and management, accountants become more efficient in handling the bookkeeping and become more productive in their work due to the use of AI (peng et al, 2023). I found this to be true as well. 

The first week I began working the invoices in the bookkeeping system, I was very reliant on my own knowledge. I tried categorizing each invoice in a specific item for the ledger, which was confusing sometimes. Because there were a lot of different items and different kind of invoices. With the help of ai however, it showed me what type of invoice belongs to what items in the ledger.  For example, one particular invoice showed me a bill of the restaurant where a particular client of the accounting company was having dinner. At first, I was not sure where this type of cost could be booked in the ledger. I asked AI: “at which item does a restaurant bill belong to in a ledger?” The prompt I gave ChatGPT provided me with this answer:

I asked my employer, who is an RA (registered accountant) for verification is this was true, he confirmed that it was indeed true. From then on, I started using AI a lot more for bookkeeping. Especially for items I was unsure of. It helped me become more knowledgeable, but also helped me to become more efficient and productive. 

Even though there are a lot of benefits of using ai in accounting, there are also downsides. Each bookkeeping for a specific client is different. Tailoring to these clients cannot be done always done through AI. My employer explained to me that the accuracy of knowledge AI has on accounting and bookkeeping is broad, but that I should not always rely on it to keep the books. Because clients sometimes require specific wishes in what purpose their ledger serves and on what books costs are categorized. For example, some clients want to receive a larger tax return. Therefore, they would categorize some cost to a specific item in the ledger that are relevant for that outcome, and others use It to justify cost that they made for the past few months that could be lost in other items, due to inaccuracy of the AI. This type of variety is sometimes very confusing for the AI making some prompts not always accurate to what the client needs. As accepting is also a type of consulting and advisory to companies.

In my opinion, AI is beneficial for the future of financial bookkeeping, and it will probably change a lot of aspects in the financial field. I do however think that when it comes to personalized tailoring to clients with jobs such as consulting and advice, especially in the tax field. It is still of relevancy that accountants or financial advisors take responsibility in helping clients themselves to keep them satisfied and use AI to their benefit. Becoming more efficient and accurate themselves due to the clever use of it.

Peng, Y., Ahmad, S. F., Ahmad, A. Y. B., Al Shaikh, M. S., Daoud, M. K., & Alhamdi, F. M. H. (2023). Riding the waves of artificial intelligence in advancing accounting and its implications for sustainable development goals. Sustainability, 15(19), 14165

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My love-hate relationship with ChatGPT: Trust issues exposed

8

October

2024

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In this world where technology is unimaginable, artificial intelligence like ChatGPT has become big part of our everyday lives. My experience with this AI has turned into a complicated love-hate relationship that is filled with enthusiasm, confusion and frustration.

Building trust

When I first started using ChatGPT, I was excited. It felt like having an assistant always near me, ready to help with my questions, schoolwork, recipes and even emails. It was even better than Google at some points. I could ask questions and get clear answers almost immediately. At first I thought it was fantastic and that I could rely on it for anything. The AI provided explanations, helped me brainstorm ideas and suggested solutions to problems I was struggling with. In those early days it felt like I was forming a solid partnership.

Doubts start to appear

However, the excitement did not take long, when I started asking more straightforward school related questions, questions like “Is this right?”, to check if I’m on the right track with my homework, I found myself getting different responses each time. I expected a confirmation but instead I received answers that did not match what I was looking for.

I tried and intentionally gave a wrong answer to a question and asked if it was right, just to see how ChatGPT would react. When it told me my answer was right, I asked, “Are you sure?”  it replied, “I apologize for the mistake. Let me provide the correct information.” That left me more confused than ever. How could it change the answer so quickly? It was hard to trust it when it seemed so inconsistent.

Growing trust issues

When I used it more often, my trust issues increased. I found myself repeating questions, hoping for a good answer. I had moments when I spent more time discussing things with ChatGPT than it would have taken to just do the task myself. I would find myself getting frustrated and typing in all caps. I felt like I was talking to someone who did not even want to understand me. Instead of feeling that it helped me, it felt like I was only arguing back and forth and it was exhausting.

Realising that my frustration only increased. I knew that I had to change the way how I asked my questions. I started double checking answers and used other sources to confirm information. I realized that while it could be a helpful tool, it was important to verify the information I got. I learned to ask more specific questions and provide additional context, this led to better results.

Lessons learned

I learned an important lessons about trust, not just with AI but in all areas of life. Trust takes time and clear communication. It is important to realise that even advanced technology can make mistakes. My relationship with ChatGPT changed from blind trust to a more cautious partnership. I learned to appreciate the strengths while acknowledging the limitations.

Looking back on my experience with ChatGPT, I realised how unstable technology can be. While my experience has had its conflicts, I still appreciate the value it brings to my learning process. Have you ever felt frustrated using AI? You are not alone, let’s share our struggles and find ways to make it work better for us! 

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Chatbots in White Coats: A Personal Reflection

1

October

2024

5/5 (1)

Introduction: Balancing the Benefits and Risks of GenAI in Medicine

“Not all GenAI is safe, and in healthcare, the risks are particularly high,” said Aashima Gupta, Google Cloud’s Global Director of Healthcare Strategy and Solutions (Smith, 2023). This statement echoes my recent experience using a healthcare chatbot for a medical issue, highlighting the need to approach this technology with caution while recognizing its potential to transform patient care and alleviate the burden on medical professionals.

My Experience: Leveraging AI for Minor Symptoms

Recently, I found myself grappling with persistent bloating, nausea, and stomach discomfort. As the symptoms were not severe enough to warrant an immediate hospital visit, I reached out to my friend, a clinical medicine student, for advice. Intrigued by the potential of AI in healthcare, my friend decided to input my symptoms into several healthcare chatbots to see what insights they could provide. After analyzing the data, the chatbots recommended a specific medication to alleviate my symptoms. My friend, trusting the AI’s judgment, prescribed the medicine to me. However, in a surprising turn of events, my symptoms resolved on their own before I could even purchase the medication. While I was relieved to feel better, I couldn’t help but wonder about the accuracy of the chatbots’ diagnosis and whether I would have actually needed the prescribed treatment.

The Advantages of Conversational AI in Healthcare

Despite the potential risks, the emergence of Conversational AI in Healthcare offers several benefits. Firstly, it lowers the barrier for people seeking medical advice, making it more accessible and convenient. Secondly, it can help alleviate the immense pressure on doctors. My friend revealed that in China, doctors often work late into the night, which is a common occurrence. By handling minor cases and providing initial guidance, healthcare chatbots can reduce the workload of medical professionals, allowing them to focus on more critical cases.

Market Landscape: The Current State and Future of Healthcare Chatbots

The global healthcare chatbots market is expected to reach $703.2 million by 2025, growing at a CAGR of 21.5% from 2020 to 2025 (Grand View Research, 2020). This growth is driven by the increasing demand for accessible medical information, the need to reduce healthcare costs, and the growing adoption of smartphones and mobile applications. However, the market faces challenges such as concerns over data privacy, the need for regulatory compliance, and the potential for misdiagnosis or incorrect treatment recommendations (Deloitte, 2019).

Looking ahead, to maximize the benefits of healthcare chatbots while minimizing risks, it is essential to implement strict regulations and oversight to ensure the accuracy of diagnoses and recommendations. These AI systems should prioritize patient safety and provide clear guidance on when a hospital visit is necessary. As the technology continues to advance, collaboration among medical experts, researchers, and policymakers is crucial to develop ethical guidelines and best practices for the use of GenAI in healthcare (World Health Organization, 2022).

References:

Deloitte. (2019). The future of AI in healthcare: Challenges and opportunities. Deloitte Insights.

Grand View Research. (2020). Healthcare chatbots market size, share & trends analysis report by application, by end-use, by region, and segment forecasts, 2020-2025. Grand View Research.

Smith, J. (2023). Google Cloud’s Aashima Gupta on the future of AI in healthcare. HealthTech Magazine.

World Health Organization. (2022). Ethics and governance of artificial intelligence for health: WHO guidance. World Health Organization.

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AInception – an experiment

1

October

2024

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Creating a Custom Marketing Campaign Using MidJourney: A Journey with Generative AI

Engaging with MidJourney as a tool powered by AI for Generative AI was one of my best moments lately. Given we had to write an article about our experience with genAI tools I opted to explore its functions by designing a personalized marketing initiative for a made-up sustainable travel brand.

My goal was to develop graphics that embodied the principles of green and simple travel while keeping a contemporary and upscale appearance. I supplied MidJourney certain prompts like ‘an upmarket backpack designed from renewable materials featuring a simple layout in a picturesque landscape with a natural light source.’ Within moments I obtained remarkable images that showcased the core of the brand I was picturing.

For marketing applications MidJourney provides both rapid speed and the ability to design creatively. Usually developing a visually unified marketing campaign needs a designer and photographer in addition to multiple rounds of approval. I rapidly modified my prompts in MidJourney to produce various versions of an image until it fit my vision exactly. The fast design process turned out to be extremely beneficial for handling a pressing deadline. This also inspired my artistic imagination in novel ways—exploring ideas I would never have thought about using standard design methods.

Having created the images I used them to make numerous social media and website layouts for the company. It intrigued me how easily these visuals from AI merged into my complete marketing approach. You could see quality and consistency like those from a creative agency of its caliber without the expensive fees or extended timeline.

I wish you discovered the information and examples to be both interesting and useful.

But here’s the twist: all the words and concepts presented here came from an AI. Using Generative AI makes generating content that mimics human writing styles simpler allowing for the easy production of articles and marketing materials.

Through this demonstration, AI’s ability to create engaging narratives is demonstrated, and significant issues related to the authenticity of content and the origins of creators in the online world emerge. The feedback and insights you saw were generated by artificial intelligence and mix together human creation and machine production.

In this time when information can be produced instantly it is important to assess critically what we both create and consume. While opening new avenues in AI we should also recognize the obstacles that follow.

So, was it convincing?

Because that, until this double separator right above, was written by AI as well.

This is the only paragraph written by me, Riccardo.

I asked ChatGPT 4.0 to write everything (and create the pictures, so no MidJourney involved in reality), and then used Stealthwriter to make it feel more human. I know it doesn’t really feel human, but for a machine it may sound like it. In fact, to prove my point about how realistic AI generated content is becoming and how we need to improve our ability to recognize it, I fed GPTZero (my go-to website when it comes to check whether some content is human generated or not) with this article. The original script written by ChatGPT was given a 0% probability of human generation, but the Stealthwriter version got a whopping 80% probability of being created by a human – even though I didn’t write a single word.

This shows that machines may not be reliable in detecting machines (however, I must say that I did not pay for GPTZero‘s advanced version), so the final question is:

Are we reliable? Did you fall for the trick?

Below are some screenshots of my little experiment:

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The double-edged sword of AI Voice and Video Cloning Technologies

28

September

2024

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In 2023, I attended a renowned convention with work in which the moderator welcomed the audience in a video that played in the halls and pathways, greeting attendees in (if I remember correctly about 10 different languages) before the main event. What caught my attention was that in each version of the video, it sounded like the moderator was a native speaker. My international co-workers confirmed this for their languages. I thought, “How can this be? Surely, he can’t know so many languages!” Yet, nothing in the videos gave away that the content was AI-generated, neither for me, nor for my colleagues.

During a break, I talked with the moderator and asked him in German (as I assumed, he was perfectly able to speak German) how he managed to speak so many languages so fluently. He did not understand a single word, so I switched to English, and he explained how it was done. He had recorded a two-minute video in English, and AI had handled the rest, translating and mimicking his voice in other languages. What was remarkable was that despite that I knew about this technology, I couldn’t detect that the videos were AI-generated.

My personal experience is just one example of the potential that AI voice and video technologies have. These tools can solve language gaps, making global communication more accessible than ever, and even enhance presentation skills. Nowadays, everyone with a computer and access to the internet can create a digital clone of themselves in just a few minutes with platforms like www.heygen.com (Jalli, 2024)

However, ethical concerns arise. Deepfake technology and the use of it, identity theft, and misinformation are risks that are on the rise (Helmus, 2022). As AI evolves, we must balance innovation with ethical responsibility to make sure that the technology is used for good.

In conclusion, while AI voice and video cloning technologies offer exciting possibilities, careful consideration of ethical implications and responsible usage is essential for long-term success.

References

https://heygen.com

HELMUS, T. C. (2022). Artificial Intelligence, Deepfakes, and Disinformation: A Primer. RAND Corporation. http://www.jstor.org/stable/resrep42027

Jalli, A. (2024, May 11). How to clone yourself with AI in seconds (HeyGen AI review).  Medium. https://medium.com/@artturi-jalli/how-to-clone-yourself-with-ai-in-seconds-heygen-ai-review-23e57f90287a

Zheng, & Huang. (2023, October). The self 2.0: How AI-enhanced self-clones transform self-perception and improve presentation skills. arXiv.org. https://arxiv.org/abs/2310.15112

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The Rise of AI in Fashion: How Artificial Intelligence is Transforming Design and Retail

27

September

2024

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AI in Fashion Design

Artificial Intelligence is transforming the fashion industry leading to innovations in both design and retail activities. AI revolutionizes how designers create, how trends are predicted and how retailers manage their stock and interact with consumers with the analysis of large datasets and automated processes (Luce, 2018). In this blog, we’ll explore how AI is being applied across various stages of the fashion ecosystem, from creative design to personalized shopping experiences.

Using AI, designers blend technology and creativity. Machine learning alogrithms allow designers to analyze historical trends, consumer preferences and data to generate new or innovative designs. Fashion houses like Alexander McQueen have begun to incorporate AI into their design processes. This allows for experimenting with new styles and materials (Renee, 2023). In addition, AI contributes to sustainable fashion by helping brands reduce waste and optimize material choices, and production processes.

Trend Forecasting with AI

Predicting fashion trends has traditionally been a complex and instinct-driven process, but AI is providing brands with more accurate and data-driven insights. Machine learning algorithms scan social media platforms, online influencers, and sales patterns to identify emerging trends. Companies like Heuritech use AI to analyze millions of images on Instagram to predict future fashion trends months ahead of time (Poncelin, 2024). Brands react more quickly to consumer demands, reduce overproduction and meet better the market expectations due to the advanced forecasting.

AI-Driven Inventory Management

Inventory management is another area where AI is making a significant impact. AI systems can process vast amounts of sales data, seasonal trends, and even weather forecasts in order to help retailers optimize stock levels. AI helps brands maintain the right balance between supply and demand so that the chances of overstocking or stockouts are significantly reduced. Major fashion retailers like Zara and H&M have embraced AI to manage their inventories which leads to more efficient supply chains and less waste (Ünal et al., 2023). Therefore, retailers can ensure that popular items remain available while minimizing markdowns and unsold inventory.

Personalized Shopping Experiences

AI is enhancing the shopping experience by providing personalized recommendations and services tailored to individual customers. Retailers like ASOS and Stitch Fix use AI-powered recommendation engines and virtual stylists to analyze customer preferences and browsing behaviors. That way they deliver product suggestions uniquely suited to each shopper’s style (Fix, 2023). This personalization simultaneously improves customer satisfaction and helps retailers build stronger customer loyalty and increase sales.

AI is transforming the fashion industry by bringing innovation to design, trend forecasting, inventory management, and retail experiences. Brands that adopt AI technologies are staying ahead of consumer demands and improving efficiency and sustainability. As AI continues to advance, its role in fashion will only expand and lead to shaping the future of the industry in innovative ways.

References:

  1. Luce, L. (2018). Artificial Intelligence for Fashion: How AI is Revolutionizing the Fashion Industry. https://link.springer.com/content/pdf/10.1007/978-1-4842-3931-5.pdf
  2. Renee, K. (2023, December 15). How Artificial Intelligence is Revolutionizing the Fashion Industry. RYN. https://www.therynapp.com/post/how-artificial-intelligence-is-revolutionizing-the-fashion-industry
  3. Poncelin, C. (2024, June 28). How Heuritech forecasts fashion trends thanks to AI. Heuritech. https://heuritech.com/articles/how-heuritech-forecasts-fashion-trends-thanks-to-artificial-intelligence/
  4. Ünal, Ö. A., Erkayman, B., & Usanmaz, B. (2023). Applications of Artificial Intelligence in Inventory Management: A Systematic Review of the literature. Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-022-09879-5
  5. Fix, S. (2023, June 29). How We’re Revolutionizing Personal Styling with Generative AI – Stitch Fix Newsroom. Stitch Fix Newsroom. https://newsroom.stitchfix.com/blog/how-were-revolutionizing-personal-styling-with-generative-ai/

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