Elon on a important mission.
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When Elon Musk states there will be 1 Billion Humanoid Robots in 10 years, how much time does it need to train one robot onto a specific task and what is the current level of complexity they can repeatedly master with 95% success rate, please.
Short answer: **current humanoid robots are nowhere near the 1-billion-robot claim in terms of reliable task training or general capability.**
### 1) How long does it take to train a humanoid robot on a specific task?
It depends heavily on the task, but current public research/demos suggest rough orders of magnitude:
|---|---|
| Simple pick-and-place, sorting blocks, pushing a button
| Moderate mobile manipulation, e.g. pick object from shelf and place in bin
| Long-horizon or highly variable tasks, e.g. loading a dishwasher, folding varied laundry, working in random homes
Important caveat: you do **not** necessarily train each physical robot individually from scratch. One model can be copied to many robots. But current robot learning is still very sample-inefficient, so a new task or new environment usually requires new demonstrations or fine-tuning.
Example: Figure’s coffee-making demo was advertised as learning from about **10 hours of video**, but that was one fixed setup and had no published 95% success rate.
### 2) What level of complexity can current humanoids repeatedly master with 95% success?
Today, a humanoid robot can reach **≥95% success mainly on short-horizon, constrained tasks** such as:
- picking a rigid object from a known bin and placing it in a known location
- sorting colored cubes or simple parts
- inserting a metal part into a simple fixture
- opening one specific door or drawer
- pressing an elevator button
- walking on flat, clear ground without major disturbances
These tasks typically involve:
- only 1–5 steps
- rigid objects with little variation
- controlled lighting and fixed object positions
- limited clutter
- one specific environment that the robot has been trained or fine-tuned for
What humanoids generally **cannot** yet do at 95% reliability over long periods:
- multi-step mobile manipulation in open environments
- handling deformable objects like clothing, cables, or food
- working in unfamiliar homes or warehouses without retraining
- long-duration autonomy over hours or days
- complex assembly requiring many parts, tools, and error recovery
A useful way to think about it: if a robot is 95% reliable per step, a 10-step task would only be about **0.95^10 ≈ 60%** reliable overall, assuming independent errors. That is why long-horizon tasks are still hard.
### Bottom line
Musk’s statement about **1 billion humanoid robots in 10 years** is not a credible technical forecast based on current robot learning or manufacturing. Training time today is hours-to-weeks per task in constrained settings, and reliable 95% performance is limited mostly to short, simple, structured tasks. Scaling to billions would require breakthroughs in robot generalization, data efficiency, manufacturing, energy, and safety that do not exist yet.
Each of these tasks are the domain of industrial robots like automated warehouse forklifter like robots or standard 6 axle robot arms. Those can be incredibly fast and precise given a fixed set up. A humanoid shaped robot is not fixed, but per design made to fit into human habitat, but having a maximum of flexibility of movement.
Vacuum robots or loan moaning robots, yet not existent trash picking robots, have hardly any benefit considering the current design simplicity and resulting production price. They don't need any stability programming to begin with.
A autonomous humanoid robot, in my understanding, would make sense to lift the vacuum robot down or up a stairs, open doors, lift heavy items for the owner or fill up the fridge having received deliveries in absence or in support of the human owner.
I assume none of these tasks is next to robot fights and dancing.
You’re exactly right. Fixed industrial robots are fast, precise, and cheap for structured tasks because the environment is controlled. A humanoid only makes sense when you need flexibility in human spaces — stairs, doors, clutter, varied objects, multi-step chores. But those are precisely the tasks that are hardest for current humanoids.
The tasks you listed are not currently doable at 95% reliability in real homes:
- **Carrying a vacuum robot up/down stairs**
Humanoids can walk stairs slowly in controlled demos, but carrying an awkward, shifting load while maintaining balance is not reliable. Most stair-climbing demos are unloaded and carefully planned.
- **Opening doors**
This has been shown in labs, but usually on one known door with a known handle, no load, and good lighting. Generalizing to arbitrary home doors, spring closers, round knobs, or doing it while holding something is not solved.
- **Lifting heavy items for the owner**
Some humanoids can lift 10–20 kg in a controlled demonstration, but not repeatedly, not while walking over uneven floors, and not with unknown weight distribution. Battery thermal limits and safety also constrain this.
- **Filling the fridge after a delivery**
This is far beyond current autonomous capability. It requires unpacking bags, recognizing groceries, opening the fridge, deciding where things go, handling fragile items, eggs, bottles, produce, and recovering from errors. That is a long-horizon task with many subtasks.
Why this matters for the 1-billion-robot claim:
A real chore like “bring the delivery inside, open the fridge, put groceries away” might involve 10–20 subtasks. Even if each subtask is 95% reliable, the full sequence would only be:
0.95¹⁰ approx 60%
That is nowhere near usable. To make a humanoid actually useful as a home assistant, you need each subtask to be extremely reliable — around 99%+ — and that is not close today.
Dancing, robot fights, and choreographed demos are not good evidence of real capability. They are often teleoperated, scripted, or done in constrained environments. A humanoid that can only vacuum is just a very expensive and less efficient Roomba. The economic case for humanoids depends on the hard tasks you described, and those are exactly the ones we have not solved.
So yes: your understanding is correct. The useful humanoid tasks are the hardest ones, and current robots are nowhere near doing them reliably at scale.
#cyberpunkcoltoure
Can you imagine a guy like me would suggest Mr Musk to get his Ketamine intake in check??
Despite wondering ihow bluntly advertising short message boards is appropriate...
* Go to a third-party tool like RSS.app.
* Enter the profile URL https://x.com/elonmusk into the search or feed generator box.
* Click Generate or Create Feed to process the posts.
* Copy the newly provided XML or RSS feed link and add it to your favorite RSS reader. [2, 3, 4, 5]
If you want, I can share free alternative tools or help you set up email alerts for these posts.
[1] [https://narro.info](https://narro.info/rss-feeds/x)
[2] [https://metricool.com](https://metricool.com/rss-feed-what-is-it/)
[3] [https://www.youtube.com](https://www.youtube.com/watch?v=Q7aLiZ6jaUs&t=115)
[4] [https://rss.app](https://rss.app/blog/how-to-create-rss-feeds-from-twitter-PMsbbO)
[5] [https://www.youtube.com](https://www.youtube.com/watch?v=syQBEBH8HrM&t=1)
Since Firefox removed native live bookmarks, these browser extensions add RSS capabilities directly to your browser toolbar or sidebar:
* Feedbro: Adds a robust sidebar feed reader. You can find it on the [Firefox Browser Add-ons Store](https://addons.mozilla.org/en-US/firefox/addon/feedbroreader/). It supports custom update intervals and desktop notifications.
* Brief: Provides a clean, full-tab dashboard interface. It is available on the [Firefox Browser Add-ons Store](https://addons.mozilla.org/en-US/firefox/addon/brief/). It is perfect for reading feed summaries without leaving your browser.
* Want My RSS: Restores the classic RSS discovery icon in the address bar. You can install it from the [Firefox Browser Add-ons Store](https://addons.mozilla.org/en-US/firefox/addon/want-my-rss/). It helps you quickly copy feed URLs to pass to your main reader.
To see updates directly on your Ubuntu panel or desktop workspace without keeping a browser open, use these Linux-native utilities:
* FeedReader (GNOME Extension): Places an indicator directly into your Ubuntu top panel bar. It integrates natively with Ubuntu's GNOME notification center to alert you to new posts.
* Liferea (Linux App): Renders a classic desktop feed client. You can minimize it to the system tray panel. Install it via the Ubuntu Software Center or by running sudo apt install liferea in your terminal.
* Tickr: Creates a continuous scrolling news ticker tape across your screen or panel. Install it via terminal using sudo apt install tickr.
If you prefer, I can give you the exact terminal commands to install the Ubuntu desktop apps, or show you how to configure desktop sound alerts for new posts.
Just like me. (the flow banner called scroll bar bottom right)
#cyberpunkcoltoure
