Testing interior and architectural design generating tools

17

October

2023

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I have always been passionate about architecture, furniture, and interior design. Therefore it is interesting for me to see all the AI-created images in this creative field on social media platforms as Instagram, TikTok and Pinterest.

Several generative AI tools, such as Interior AI, DALL-E and Midjourney can create visuals by turning text into pictures. Besides that, specific tools, like ‘This House Does Not Exist’, that are focused explicitly on architectural design (Nelson, 2023).

Trying to test the tools myself, I came to the following conclusions.

First, I tested the tool This House Does Not Exist. The tool generates a new image showing mainly the exterior of the house. You can generate houses by clicking in the top right ‘Tap image to let AI generate a new house’. After generating a house, you can give it a vote.  I generated three random visuals. You cannot give any input for the generated outcome.

Picture generated from  https://thishousedoesnotexist.org/

Picture generated from  https://thishousedoesnotexist.org/

Picture generated from  https://thishousedoesnotexist.org/

In my opinion, using this tool is fun, yet a bit unrealistic. I think it is pretty interesting to stumble upon a beach house with a beach in Paris. Therefore, I regard the tool as appropriate for inspiration, entertainment and expanding your boundaries.

The second tool to try and test is Interior AI. However, this tool cannot be used without paying for a subscription. Therefore I moved on to the third tool I tried, which was airoomplanner.com. I inserted a picture of an area of my room. After inserting a picture of a room, you can choose from a wide range of categories of rooms and interior themes. I did not experience the tool as convenient. Only after generating a few rooms did the tool finally generate a few rooms that were kind of close to the actual snippet of my room. I experienced that it helped to play with the categories defining the function of your room. Nevertheless, there are fun categories like ‘Christmas’ which you can use. The rooms uploaded from https://airoomplanner.com/ are in the themes of a Christmas study room, a modern attic, and a tropical attic.

Picture generated by https://airoomplanner.com/

Picture generated by https://airoomplanner.com/

Picture generated by https://airoomplanner.com/

The last tool I tried was from Bing. You can give detailed descriptions of what you would like to be generated. I really like that, since this gave me some direction for the generated visual and therefore I could use the tool more efficiently for my own purpose.

I inserted the following instructions: “I would like to see the design of the interior of a barista cafe. I would like the design to be based on the interior design style of interior designer Kelly Wearstler. I want to see earth tones and a mix of materials. Additionally I would like to see the color green, mirrors and red chairs”

Pictures generated from www.bing.com/images/create

The tool generated the following images. I think the tool followed my instructions pretty well. I prefer the interior of the café in the bottom left the most. This tool is suitable for idea generation and inspiration. Even though I like the generated visuals, I get the impression that I have seen these interiors before.

A person might experience the generated interior missing a human touch, and the AI might not always understand subjective parts of a particular room or design. Besides that, the generated visual depends on the data inserted, and tools have limits regarding accuracy. Lastly, generative AI design tools create visuals based on much the same prompts, increasing the risk of generating similar designs for more users (Theron, 2023).

I like the tools and regard them as fun. It is entertaining to play with, and I prefer a tool where I can give text as input as a direction for the visual that will be generated. The AI tool from Bing was the most convenient since it gave me the most authority over the result. However, I am still missing novel aspects in each generated visual. Do you see yourself using AI tools for generating interiors, and why (not)? Let me know!

Reference list

Theron, T. (2023, August 29). AI interior design: 10 best AI interior apps and tools for your room design in 2023 – Decorilla Online Interior Design. Decorilla Online Interior Design. https://www.decorilla.com/online-decorating/ai-interior-design-for-room-design/#RoomGPT

Nelson, T. (2023, February 9). Generative AI can help you see design in a new Way—Here’s how. Architectural Digest. https://www.architecturaldigest.com/story/generative-ai-can-help-you-see-design-in-a-new-way-heres-how

Tools used

https://thishousedoesnotexist.org/tribal-modern-house-with-exposed-circular-bamboo-biochar-bamboo-and-industrial-wall/29663686

https://interiorai.com/?ref=thdne

https://airoomplanner.com/interiorai/design

https://www.bing.com/images/create

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Generative AI: Increasing efficiency of drug design

16

October

2023

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Since the pandemic, the pharmaceutical industry has been redefining and reinventing its operations and implementing more digital innovations. Generative artificial intelligence is one of the digital technologies promising to accelerate and improve the drug discovery process. The drug discovery process is extensively complicated and requires significant investments of time and money. Realizing new drugs take, on average, between 12 to 18 years, costing approximately $2.6 billion. Eventually, only 10% of drugs make it to clinical trials. Several companies are extensively researching the possibilities of integrating generative AI to improve the efficiency of their drug discovery processes (GlobalData Healthcare, 2023). My interest in (holistic) health, medical innovations, and breakthroughs stems from my own medical journey, searching for remedies for my chronic condition. The possibilities shown by the technique of generative AI to support the development of new drug discovery genuinely intrigue me. Seeing through the years how innovations widen the possibilities in the medical landscape is exciting to me.

Companies train their artificial intelligence to inspect vast and complex chemical and biological data sets. Subsequently, generative models process all this data to locate new targets for treating diseases and create new molecular structures with suitable properties. The input of scientists is to look for specific molecules with particular characteristics to transform these into new drugs (Nouri, 2023).

One of the companies to use generative AI to discover new drugs is Insilico Medicine.  Insilico Medicine uses its generative AI platform, Pharma.AI, in each step during the drug discovery process. Traditional discovery of a drug for idiopathic pulmonary fibrosis would have cost over $400 million over six years. However, with the use of their generative models, the cost was $40 million, and the first phase of clinical trials began after 2.5 years. The generative approach to designing drugs thus increases time and cost efficiency (Yao, 2023).

Insilico Medicine even received IND approval from the U.S. Food and Drug Administration (FDA) to start their drug in the clinical validation stage(Insilico Medicine receives IND approval for novel AI-designed USP1 inhibitor for cancer, 2023). Besides, they have several other AI-designed drugs in their pipeline. Their lead drug for progressive idiopathic pulmonary disease is a breakthrough for entirely generated AI drugs since it is in phase II patient trials (Nouri, 2023).

Even though generative-designed drugs have a promising outlook, they also have barriers. Regulatory and ethical considerations may limit the design of drugs with the use of generative AI. Additionally, datasets must be high quality and large enough for machine learning (GlobalData Healthcare, 2023).

I believe using generative AI to design drugs will mature since it can shorten the discovery process of drugs and increase cost-efficiency. What do you think the future of healthcare will look like now that drugs can be created more efficiently with generative AI? Do you regard generative AI as a prescription for success in the future of healthcare?

References

GlobalData Healthcare. (2023, 3 augustus). Generative AI has the potential to revolutionise drug discovery. Pharmaceutical Technology. https://www.pharmaceutical-technology.com/comment/generative-ai-revolutionise-drug-discovery/?cf-view&cf-closed

Insilico Medicine receives IND approval for novel AI-designed USP1 inhibitor for cancer. (2023, 25 mei). EurekAlert! https://www.eurekalert.org/news-releases/990417

Nouri, S. (2023, 5 september). Generative AI drugs are coming. Forbes. https://www.forbes.com/sites/forbestechcouncil/2023/09/05/generative-ai-drugs-are-coming/

Yao, R. (2023, 27 juni). Insilico Medicine uses generative AI to accelerate drug discovery | NVIDIA blog. NVIDIA Blog. https://blogs.nvidia.com/blog/2023/06/27/insilico-medicine-uses-generative-ai-to-accelerate-drug-discovery/

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