Why AI Still Can't Fold My Laundry: The Limits of Machine Learning
Highlighting what AI still can’t do, using humor and real-world examples to humanize machine learning.
.png)
AI Is Brilliant, But It Still Can’t Fold My Laundry
Artificial Intelligence is changing the world. It’s diagnosing cancer, flying drones, writing poetry, composing symphonies, driving cars (mostly), and can even mimic your voice after listening to you speak for just a few minutes.
But despite these dazzling features, there's a daily chore that remains stubbornly untouched by the mighty power of AI: folding my laundry.
No, really.
You'd think that a technology that can beat humans at Go, detect early signs of Alzheimer’s, and write passable pickup lines could figure out how to fold a t-shirt. But here we are humans still wrangling warm socks while our machine overlords remain strangely absent from the laundry room.
So, what gives?
Let’s take a fun (and surprisingly enlightening) journey into why AI still can’t fold our laundry and what this says about the true limits of machine learning in 2025.
1. The Illusion of AI Supremacy
There’s a common misconception, thanks to sci-fi movies and sensational headlines, that AI is all-knowing, all-seeing, and infallible. But most AI today is more like a savant child with a very specific skillset: brilliant in narrow domains, clueless in others.
For Example:
GPT-4 can write a Shakespearean sonnet about tacos, but don’t expect it to physically recognize a crumpled sock from a flat one or fold a towel the way Marie Kondo would.
AI’s current state is narrow AI, systems trained for highly specific tasks. They can’t generalize knowledge the way we do. You can train a model to identify cats in images, but that same model won’t know what a cat is in real life, let alone pet one.
2. Folding Laundry Is Technically Complex (Yes, Really!)
Let’s break it down:
Every piece of laundry is different in shape, size, texture, and color
Clothes are often crumpled, twisted, or overlapping
The act of folding requires precision, motor coordination, spatial understanding, and sequencing
For humans, this feels intuitive. But for a robot, it's a nightmare of perception, manipulation, and decision-making.
Success Story?
In 2010, UC Berkeley’s PR2 robot successfully folded a towel. But it took over 20 minutes per towel. And it struggled with different kinds of fabrics.
Fast-forward to 2025, and yes, we’ve improved. Boston Dynamics robots can do backflips now but no one’s mass-producing affordable laundry-folding bots yet.
Why?
The problem is not just engineering. It’s the lack of generalizable intelligence.
3. The Curse of the Real World
Machine learning shines in controlled environments: digital spaces with defined rules. Think:
Chess
Spam detection
Recommender systems
But laundry folding? That’s messy, literally and figuratively.
ML models struggle when:
Data is inconsistent (e.g., no two t-shirts are folded the same way)
The environment is unstructured
Unseen objects or variables appear (e.g., dog hair on a sock!)
Real-life example:
Amazon’s fulfillment centers are legendary for robotics. But even they rely heavily on human workers for “random” tasks, like grabbing a single, oddly-shaped item from a pile. That’s because robots are still bad at dealing with unpredictability.
4. Why General Intelligence Is Still So Hard
The ultimate goal in AI is Artificial General Intelligence (AGI), a system that can think, reason, and adapt like a human across many tasks.
But we’re not there yet.
Why not?
Most ML models are trained on specific datasets. They don’t understand context or physical reasoning.
AI lacks common sense. A child knows not to place a freshly folded shirt in water. An AI? Not necessarily.
Physical interaction is insanely hard to model. Vision, touch, force feedback, and balance all have to work in perfect sync.
Case Study:
A 2022 project from MIT’s CSAIL trained a robot to fold clothes using deep imitation learning. It worked… but only on very specific garments under ideal lighting and surface conditions.
In the wild (i.e., your actual bedroom)? Chaos.
Let’s talk about Laundroid, a Japanese robot launched in 2015 that claimed to fold clothes using AI and robotics.
They raised $90 million in funding.
Their vision: you toss your clothes into a bin, and Laundroid folds them, sorts them, and stacks them.
Sounds dreamy, right?
The reality?
It took up to 10 minutes per item
It cost over $16,000
It required clothes to be laid out flat individually
It folded only certain types of clothing
In 2019, Laundroid filed for bankruptcy
What happened? They were too far ahead of the technology curve. AI wasn’t ready.
Moral of the story?
Folding clothes is a harder AI problem than driving a car.
6. Even AI That “Sees” Can’t “Feel”
Modern AI uses computer vision to identify objects, but that’s not enough. Folding laundry is a tactile experience. It requires:
Understanding material stiffness
Detecting folds by touch
Applying variable force
Humans have over 17,000 nerve endings in their hands. AI has… none.
We’re seeing research into robotic skin and haptic feedback systems, but they’re still crude.
MIT’s GelSight sensor mimics touch for robotic fingers, and it’s promising. But combining it with vision, decision-making, and coordination is a huge engineering mountain.
7. Humor, Context, and Human Weirdness
Let’s look at other things AI struggles with and how they relate back to folding laundry.
Sarcasm: AI still stumbles when someone says “Yeah, great job!” after a disaster.
Jokes: Most AI-generated jokes are awkward or nonsensical.
Creativity: AI can mimic styles but rarely innovates.
Context: AI can miss that “bank” means a financial institution, not a river’s edge.
Now, try folding your partner’s blouse with the wrong crease. That’s a warzone-level mistake. 😉
Laundry folding is full of unspoken context and personal preference things AI has no clue how to learn.
8. The Rise of Specialized Domestic AI (but not yet for laundry)
We are seeing AI in homes:
Robot vacuums (Roomba, Roborock): Use SLAM algorithms and object detection to avoid chairs and cats
Smart dishwashers: Learn wash cycles based on usage patterns
Voice assistants: Schedule, remind, control lights
But these are predefined tasks in structured settings. The step from vacuuming to folding clothes is like going from driving a car to piloting a spacecraft through an asteroid belt blindfolded.
9. What AI Can Do to Help With Laundry (Sort of)
Let’s be fair. AI hasn’t been totally useless in laundry.
Smart washers: Use AI to detect load size, fabric type, and soil level to optimize cycles
AI-powered clothing sorters (in labs): Can separate whites from colors
Clothing-recognition models: Help robots identify shirt vs. pants
Startup Highlight:
FoldiMate a company that created a partial folding assistant. It could fold shirts and pants with input but still needed human prep. They paused development due to high complexity and low demand.
10. The Hidden Lesson: AI’s Struggles Teach Us About Ourselves
Why does this matter?
Because it’s easy to believe AI is magic. But the folding problem reveals the boundaries between intelligence and experience, knowledge and wisdom, data and intuition.
Humans fold laundry not just with hands but with judgment, memory, culture, and learned habits.
The joke that “AI can drive a Tesla but not fold a towel” isn’t just funny, it’s a powerful reminder:
AI is only as smart as the data we feed it and some things, like warm socks and human touch, can’t be easily coded.
11. The Road Ahead: Will AI Ever Fold Laundry?
Yes… probably.
We’re moving closer. AI is:
Learning spatial dynamics better
Improving in haptics and manipulation
Being trained on synthetic and real-world interaction datasets
Prediction:
By 2030, we might see high-end robotic systems that can fold common clothing types with reasonable speed. But they’ll be expensive and probably still mess up your hoodie drawstrings.
And by then? Maybe we’ll have AI-powered self-folding clothes. (Hey, if sci-fi gave us AI, it owes us that too.)
The future of laundry-folding robots may not be as distant as we think, but it's not just about the technical hurdles. As AI advances, we’re seeing more cross-industry innovations that could eventually solve the laundry dilemma.
For instance,
AI and machine learning continue to break boundaries in sectors like agriculture, healthcare, and manufacturing, where precision and efficiency are critical. So, it’s only a matter of time before those advancements trickle into the domestic space, perhaps even improving the art of folding laundry.
The Evolution of Robotic Dexterity: From Tetris to Towels
A major hurdle to laundry folding is robotic dexterity. Robots, despite being able to execute complex tasks like assembling parts on a production line, still lack the finesse and touch needed to handle soft fabrics or delicate materials. But innovations like soft robotics in which robots are designed with flexible materials are bringing us closer to dexterous robots that could delicately fold clothes with the ease of a seasoned human.
One exciting development in the field is the use of AI-driven force sensors, which could help robots apply just the right amount of pressure when folding clothes. For example,
A shirt folded with too much pressure might end up with wrinkles, whereas one folded too lightly may not stay in place. These subtle adjustments are a key challenge for machine learning, but we're already seeing progress with specialized robots that can handle soft, flexible objects in constrained spaces.
One company, TOMORROW Labs, has been pioneering this concept, developing robotic arms equipped with machine learning algorithms to enable precise handling of clothing. Their prototypes, though not yet household-ready, show promise for eventually becoming consumer-friendly solutions. While they're still refining how these robots can fold a variety of fabrics, from t-shirts to bed linens, the improvements in their ability to understand and manipulate soft materials are impressive.
The Future of Laundry in a Smart Home World
We are increasingly entering a world of "smart homes" from fridges that know when you're low on milk to thermostats that learn your preferences. So, it’s not entirely out of the realm of possibility that future washing machines and dryers will integrate AI in ways that go beyond just adjusting wash cycles. Imagine if your washing machine could recognize fabrics and decide the best fold technique for your favorite sweater, followed by your dryer fluffing and smoothing them out. These machines could even recognize which clothes need ironing and activate an AI-assisted steamer.
This connected, holistic ecosystem would allow users to manage all aspects of laundry from sorting and washing to drying and folding through a single platform, perhaps using an app or even a voice assistant. As we begin to see innovations in 5G connectivity and the Internet of Things (IoT), syncing devices like washing machines, dryers, and potential folding robots will allow for real-time adjustments. These technologies will significantly reduce the need for human intervention and improve overall efficiency in the laundry process.
AI Integration with Personalization
Another potential game-changer is the personalization aspect. Imagine AI that not only folds your laundry, but also remembers your preferences, like how you like your towels folded, how tight you want your shirts, and which fabrics are sensitive to wrinkles. Over time, the system could learn your preferences and adapt its folding techniques to match your style. Think of it like a digital butler that anticipates your every need. One day, you might be able to interact with an AI system that can handle the minutiae of your wardrobe as seamlessly as Siri or Alexa handle your calendar.
Personalized AI could even take it a step further by helping organize your closet. For example, after folding your clothes, it could sort them by season, suggest outfits, or create a packing list for an upcoming trip. It might also offer suggestions based on what you’ve worn recently, an AI fashion assistant that ensures you're never wearing the same thing twice (unless you want to).
The Humbling and Heartwarming Power of Simplicity in the Age of AI
While it's easy to get caught up in the world-changing possibilities of AI, the laundry dilemma reminds us of the simple beauty of being human. Folding laundry, though mundane, is a task that involves patience, mindfulness, and a deep understanding of both the physical and emotional worlds. The AI that can fold our clothes will eventually come, but the reason we’re still doing it ourselves is a reflection of the fact that there are elements of human life, whether it’s the gentle touch, the cultural significance, or the emotional connection to the clothes we wear that are hard for AI to replicate.
This challenge is not an insult to AI’s abilities, but rather a celebration of human intuition. AI can beat us at chess, find us the best deals, and even drive our cars (well, sometimes). But when it comes to folding a sock just right, AI still has a lot to learn from us.
In the years ahead, as machine learning improves and AI becomes more adept at handling real-world tasks, perhaps it will be able to help with some of the most frustrating daily chores. Until then, we can rest assured that the laundry basket is still in human hands and that might not be such a bad thing after all.
Until that day comes, we'll hold on to our towels, knowing that while AI might fold our shirts someday, it can't fold our sense of humor or the joy we take in the simple, everyday moments of life.
Conclusion:
The Humble Beauty of What AI Can’t Do
AI has come a long way from mimicking Shakespeare to diagnosing diseases. But sometimes, it’s what AI can’t do that teaches us the most.
Folding laundry is a metaphor.
It represents:
The limits of data-driven learning
The value of embodied intelligence
The complexity of the physical world
And the beauty of simple, human moments that resist automation
So the next time you're standing over a mountain of mismatched socks, grumbling about your smart home, smart phone, and smart fridge, remember this:
You still fold better than a $10 million robot.
And that, dear reader, is worth something. ❤️