Why Real Estate Needs a New Mindset to Succeed with Generative AI

Midjourney / Antony Slumbers

STOP!!!

I need you to take a deep breath and work through this step by step.

Those of you who, like me, spend too long talking to large language models, will recognise this counterintuitive phrase.

An instruction to an inanimate object to do something we know it cannot, but that weirdly, does produce superior outcomes.

What is going on? What delusion is being played out here? It’s a machine yet telling it to take a deep breath makes it work better.

What’s going on is that you ARE dealing with software, but not software that behaves as you have come to expect.

And that’s why, most likely, you are making mistakes in your plans to incorporate it into your business.

Historically software has been very deterministic. It does A, then B, then C. And it does the same thing over and over again. So we can easily decide what we want it to do and then expect it to do just that.

But large language models DO NOT behave like this. You don’t know if they will do A, then B, then C and you certainly do not know if they will do the same thing twice.

You also don’t know if they are going to tell you the truth. Ask the wrong sort of question, in the wrong sort of way, and they’ll give you an answer, a very plausible one. But it will have little to do with the truth.

Conversely, they will also make things up when you WANT them to - ‘give me 10 ideas about XYZ’.

So is that 'hallucination' bug actually a feature?

Can you have creativity without imagining things?

Either way, unless you have deeply internalised the actualité of what you are dealing with, you are going to come a cropper.

And you cannot deeply internalise the actualité of large language models unless you have used them extensively yourself, in a myriad of ways.

Which brings us back to STOP!!!

I am hearing and reading many accounts of real estate companies saying they are building this or that application, but doing so in a manner that suggests only a tendentious familiarity with the above. Not least of all a general lack of awareness as to what is generative and what is not generative AI (Generative AI is a creative tool, whereas Predictive AI is an analytical tool. That's quite some difference)

Which is of course understandable. Everyone is forever under pressure to deliver. And when we’re talking ‘flavour of the month’ the pressure can be intense.

But the outcomes will not be good. We need to approach generative AI from a different direction.

And that involves two things; practice and patience.

Practice in that you need to have as many people as possible within your company trying to incorporate using a language model in everything they do. You need to see what emerges from this. What works, what does not, what is surprising, what is disappointing. Where ‘might’ these things REALLY be useful? What should we get them to do, what should we do together, and what should we keep for ourselves?Where will they allow us to do something faster, better, cheaper? And much more importantly, where might they enable us to do something we could not do before? And what might that mean?

And patience in that Claude 3 has just been released but soon (in weeks maybe months, but not a year) we will have ChatGPT 5 and Gemini 2. And we’ve already been told, by Sam Altman himself, not to try and make certain hard and complicated things work today that the next version, coming soon, will happen right out of the box.

Bloomberg spend a fortune on BloombergGPT, their own customised version of GPT 3.5, only to find that today’s GPT 4 Turbo beats it for $20 a month.

So practice and be patient.

This is the fastest developing technology in history but it is more like an alien being than anything else we are familiar with. There is no user guide because the developers do not know what it can, or cannot, do. It is an emerging technology.

Ultimately, use of these tools will be embedded in everything your company does, and everyone in your company will use them in everything they do. But for now, the best advice is to use them, learn about them and see what comes from that. Only then should you be trying to productise them.

So ….. take a deep breath and let’s work through this step by step.

Why Real Estate Needs a New Mindset to Succeed with Generative AI

Midjourney / Antony Slumbers

STOP!!!

I need you to take a deep breath and work through this step by step.

Those of you who, like me, spend too long talking to large language models, will recognise this counterintuitive phrase.

An instruction to an inanimate object to do something we know it cannot, but that weirdly, does produce superior outcomes.

What is going on? What delusion is being played out here? It’s a machine yet telling it to take a deep breath makes it work better.

What’s going on is that you ARE dealing with software, but not software that behaves as you have come to expect.

And that’s why, most likely, you are making mistakes in your plans to incorporate it into your business.

Historically software has been very deterministic. It does A, then B, then C. And it does the same thing over and over again. So we can easily decide what we want it to do and then expect it to do just that.

But large language models DO NOT behave like this. You don’t know if they will do A, then B, then C and you certainly do not know if they will do the same thing twice.

You also don’t know if they are going to tell you the truth. Ask the wrong sort of question, in the wrong sort of way, and they’ll give you an answer, a very plausible one. But it will have little to do with the truth.

Conversely, they will also make things up when you WANT them to - ‘give me 10 ideas about XYZ’.

So is that 'hallucination' bug actually a feature?

Can you have creativity without imagining things?

Either way, unless you have deeply internalised the actualité of what you are dealing with, you are going to come a cropper.

And you cannot deeply internalise the actualité of large language models unless you have used them extensively yourself, in a myriad of ways.

Which brings us back to STOP!!!

I am hearing and reading many accounts of real estate companies saying they are building this or that application, but doing so in a manner that suggests only a tendentious familiarity with the above. Not least of all a general lack of awareness as to what is generative and what is not generative AI (Generative AI is a creative tool, whereas Predictive AI is an analytical tool. That's quite some difference)

Which is of course understandable. Everyone is forever under pressure to deliver. And when we’re talking ‘flavour of the month’ the pressure can be intense.

But the outcomes will not be good. We need to approach generative AI from a different direction.

And that involves two things; practice and patience.

Practice in that you need to have as many people as possible within your company trying to incorporate using a language model in everything they do. You need to see what emerges from this. What works, what does not, what is surprising, what is disappointing. Where ‘might’ these things REALLY be useful? What should we get them to do, what should we do together, and what should we keep for ourselves?Where will they allow us to do something faster, better, cheaper? And much more importantly, where might they enable us to do something we could not do before? And what might that mean?

And patience in that Claude 3 has just been released but soon (in weeks maybe months, but not a year) we will have ChatGPT 5 and Gemini 2. And we’ve already been told, by Sam Altman himself, not to try and make certain hard and complicated things work today that the next version, coming soon, will happen right out of the box.

Bloomberg spend a fortune on BloombergGPT, their own customised version of GPT 3.5, only to find that today’s GPT 4 Turbo beats it for $20 a month.

So practice and be patient.

This is the fastest developing technology in history but it is more like an alien being than anything else we are familiar with. There is no user guide because the developers do not know what it can, or cannot, do. It is an emerging technology.

Ultimately, use of these tools will be embedded in everything your company does, and everyone in your company will use them in everything they do. But for now, the best advice is to use them, learn about them and see what comes from that. Only then should you be trying to productise them.

So ….. take a deep breath and let’s work through this step by step.

5 Questions about AI and the Future of Architecture

Midjourney / Antony Slumbers

I was recently asked these five questions about the future of AI and the Architecture profession:

1.How do you envision AI impacting the architectural design process?

2.What are the most exciting benefits you see AI bringing to architectural design and construction?

3.What do you consider the biggest challenges architects will face when implementing AI technologies in their practices?

4.How can we achieve a balance between human creativity and intuition with AI-driven design solutions?

5.How do you see the role of architects changing in a future where AI plays a more prominent role?

Here are my answers:

1. How do you envision AI impacting the architectural design process?

AI will fundamentally transform the architectural design process by augmenting human creativity and enabling more efficient, optimised and responsive building design. Generative AI in particular will allow architects to rapidly explore a vast design space, generating countless design options based on specified parameters, constraints and goals around human-centricity, sustainability, adaptability, etc.

This will shift the architect's role from manually drafting designs to defining the right prompts, curating the generated options, and applying their human judgment, intuition and creativity to select and refine the best solutions. AI will be a powerful creative partner for architects.

2. What are the most exciting benefits you see AI bringing to architectural design and construction?

Some of the most exciting benefits I see AI bringing to architecture include:

Hyper-personalisation and human-centric optimisation of spaces.

By analysing granular data on environmental conditions, space utilisation, and individual occupant preferences, generative AI can create bespoke environments tailored to maximise user comfort, wellbeing and productivity. Spaces could dynamically adapt to changing needs.

Improved building performance and sustainability.

AI can help optimise energy efficiency, daylighting, natural ventilation and resource consumption by generating and simulating design options and control strategies. It can help achieve ambitious sustainability targets.

Expanded design exploration and innovation.

By rapidly generating and evaluating large numbers of design permutations, AI can help architects discover novel, high-performing solutions they may never have conceived of manually. It augments creativity.

Streamlined, accelerated workflows.

AI can automate tedious tasks, conduct rapid analyses and generate rich visualisations, freeing architects to focus on higher-level creative and strategic work. It can compress project timelines.

Continuous learning and adaptation.

With AI, buildings can become living entities that learn from occupant behaviour and self-optimise over time. Architecture can transcend static solutions to be dynamic and evolutionary.

3. What do you consider the biggest challenges architects will face when implementing AI technologies in their practices?

I see significant challenges architects must grapple with as they integrate AI:

Defining the right goals and guardrails.

Architects must frame the right optimisation objectives and constraints for AI to align with human values and priorities. Without clear ethical boundaries, we risk unintended negative consequences. Careful, values-based goal-setting is paramount.

Maintaining human agency and accountability.

As AI generates more of the design, architects must be vigilant to maintain authorship and creative control. Clear protocols will be needed for how to apply human oversight and when to override AI. Architects cannot abdicate responsibility for the end product.

Explicating and encoding design knowledge.

To leverage AI, architects must find ways to represent their domain expertise and design processes in machine-readable formats. This is not trivial and will require close collaboration with AI experts to create fit-for-purpose models.

Managing cultural acceptance and adoption.

Many architects may resist a technology they fear could devalue or displace their creative contributions. Firms will need change management strategies to build trust in AI as an enhancing rather than replacing force.

Up-skilling and re-skilling.

Architects will need to develop new competencies in data science, computational design, AI prompt crafting, etc. This will require significant investment in training and restructuring of architectural education.

4. How can we achieve a balance between human creativity and intuition with AI-driven design solutions?

Achieving a harmonious balance between human and AI in the creative process is perhaps the overarching challenge. I believe the key is pursuing AI as an augmenting tool for human designers, not an autonomous agent. The goal should be "centaur" teams where humans and AI work together to tackle creative problems, not AI creating in isolation.

This means keeping the human firmly in the loop - using AI to enhance our creative capabilities but reserving key decisions on design direction and refinement for human judgment. Architects should focus on the uniquely human skills of imagination, conceptualisation, aesthetic sensibility, and symbolic reasoning, while leveraging AI for exploration, optimisation, evaluation and crafting of details.

Organisationally, this points to integrated teams where AI specialists work hand-in-hand with designers, collaboratively evolving the AI to serve the human-centric design intent. There must be ongoing "meta-design" of the AI system itself as a living design tool attuned to the architects' creative preferences and needs.

5. How do you see the role of architects changing in a future where AI plays a more prominent role?

I see the role of architects elevating to be more akin to a "curator of AI-generated possibilities" or a "creative director of AI." Rather than drafting designs detail by detail, architects will specialise in:

• Developing the overall creative vision and design concepts

• Defining the parameters and criteria to guide AI-generated options

• Curating and selecting the most promising AI outputs

• Refining and synthesising selected options into coherent designs

• Overseeing the "training" and evolution of the AI based on project learnings

• Developing and communicating the story and experience of the spaces to clients and users

• Upholding the ethical, social and environmental integrity of the design

• Orchestrating the dynamic interplay of AI and human stakeholders

In many ways, AI will enable architects to transcend being just form-givers and problem-solvers to become stewards of holistic human-centered experiences. By offloading technical complexity to AI, architects can re-focus on the most humanistic aspects of design - the art, philosophy, psychology and beauty of the built environment.

They will be free to grapple with the deeper questions of what kinds of spaces we want to create for human flourishing, and to shape the AI towards those poetic and purposeful ends. In an AI-mediated world, maintaining that human point of view - keeping people and not just performance as the ultimate touchstone - will be the architect's most vital role.

In summary, while AI will undoubtedly disrupt and transform architecture in many ways, I believe it also offers tremendous opportunity to amplify the human-centric impact of their work. By wedding the efficiency and inventiveness of AI with the empathy and ethics of human creativity, we can create an architecture more responsive and uplifting to the human spirit than ever before.

The future is bright for firms that learn to wield AI towards profoundly human ends.

So you want to be in PropTech?

How to Ideate a PropTech Business using Generative AI

PropTech VC PI Labs released a report last week about ‘AI for a Greener Built World’ titled ‘Sustainably Intelligent’.

In it they broke down environmental use cases along the real estate value chain. In 7 Categories.

So I thought ‘how could AI help someone develop a business aimed at one of more of these defined use cases?’

I started with Category 1: Site Supply and Acquisition.

This listed six tasks required:

• Localised environmental data and analysis

• Identification and monitoring of biodiversity

• Biodiversity management and intervention

• Robotic insecticide alternatives

• Soil quality and health analysis

• Microclimate simulations

So for each of these I enlisted the help of Claude 3 Opus.

First off I defined to it what I meant by Generative and Predictive AI.

Then I asked the following questions, for each item:

• Might this benefit from Generative AI?

• Might this benefit from Predictive AI?

In every case there was a use for Generative and Predictive AI (this is not surprising with a GPT - a General Purpose Technology - they are pervasive)

So, then I needed to know:

• What ‘Actions’ could Generative AI take?

• What ‘Actions’ could Predictive AI take?

And

• What inputs (data) would be required so that these ‘Actions’ could be undertaken?

• What Data Sources are these inputs likely to come from?

Then finally I asked:

• What technology stack would we need?

• What would be the right evaluation metrics for this item?

• What integration requirements, with other systems, would we need?

Having done this I needed all this information formatted as a table and available to be downloaded.

I then took this into Google Slides, and cleaned it up a bit before ending up with the table below.

You’ve now got a strong set of data to start thinking about your proposed PropTech business.

You can see how Generative and Predictive AI can be woven together to provide analytics and presentation/communication layers. You can see what value there is to create, what data sources you would require to make this happen, and the technological skills your team would need access to.

From this you should be able to ascertain whether 1) it’s possible 2) You could make it happen and 3) Does it look like there’s enough value there for all the work involved?

Don’t like this category? Then work your way through the other 6.

Then you will have covered off environmental use cases for AI along the real estate value chain!

Is it a GO?

Using Midjourney to treat ‘similar’ spaces differently

Original image - Fora Shoreditch

Midjourney V6 has a new option - Consistent Characters - upload one image, use the parameter —cref URL (of that image) and you can have ‘consistent characters‘ - mostly this is aimed at people wanting the same ‘human‘ to be in a range of scenes but as you’ll see from the examples below it works pretty well for ‘fixing‘ a space and then applying different stylings to it.

It this case I took an image from Fora Shoreditch and then applied four treatments to it: Minimalist Zen, Industrial Chic, Eclectic Bohemian and Sleek and High-Tech. The full prompts I used are under each image.

It’s pretty good. Or certainly ‘good enough‘ to get a feel for how different looks would turn out.

Minimalist Zen: Clean lines, simple forms, and a neutral color palette create a calming and focused atmosphere. Incorporate elements such as light wood finishes, white walls, and subtle accent colors like soft greens or blues. Use natural materials like bamboo, stone, and linen to add texture. Include plants, a small indoor water feature, and uncluttered workspaces to promote a sense of tranquility and mindfulness.

Industrial Chic: Embrace the raw, unfinished look of industrial spaces with exposed brick walls, concrete floors, and metal accents. Incorporate vintage or repurposed furniture pieces, such as old factory carts or reclaimed wood tables. Use edison bulb lighting fixtures and metal shelving to add to the industrial vibe. Soften the look with cozy rugs, plush seating, and vibrant artwork to create a balance between edgy and inviting.

Eclectic Bohemian: Create a vibrant and creative space with a mix of colors, patterns, and textures. Incorporate mismatched furniture pieces, such as vintage armchairs, colorful ottomans, and patterned rugs. Use a variety of lighting sources, including floor lamps, table lamps, and string lights, to create a warm and inviting ambiance. Add plenty of plants, woven wall hangings, and eclectic artwork to complete the bohemian look.

Sleek and High-Tech: Design a modern, high-tech office with a focus on innovation and efficiency. Use a monochromatic color scheme with pops of bold, bright colors for accent pieces. Incorporate glass walls, sleek metal finishes, and minimalist furniture with clean lines. Include state-of-the-art technology, such as large digital displays, interactive whiteboards, and integrated charging stations. Use LED lighting and smart climate control systems to create a comfortable and energy-efficient environment.