The race is on.


What was something that happened on a monthly basis is becoming weekly.  Anyone who is doubting the pace things are advancing is simply not in touch with reality.  There is a lot about [AI](https://inleo.io/@leoglossary/leoglossary-artificial-intelligence) and [robotics](https://inleo.io/@leoglossary/leoglosary-robotics-robots) that can be debated; the pace of advancement isn't really one of them.


Things are happening very quickly.


<center> https://i.imgur.com/7iqjhuj.png 


[Source](https://www.msn.com/en-us/money/news/figure-01-humanoid-robot-serves-up-a-storm-overshadows-teslas-optimus-in-coffee-skills/ar-AA1mCLUu)</center>


We last discussed the Figure robot operating a Keurig coffee machine.  This might seem like nothing to the average person yet it was a huge breakthrough for both robotics and AI.  


Now we have something even more impressive.  What about a robot that folds shirts?  This was contained in the latest [video](https://inleo.io/@leoglossary/leoglossary-video) put out by [Elon Musk](https://inleo.io/@leoglossary/leoglossary-elon-musk).  It shows Optimus pulling a shirt out of a box and folding it.


Again, to some this might not seem that impressive yet it is a major step forward.


## The Robot Race


What this is showing is how fast the robot race is heating up.  There are many companies involved in the field so do not ever [buy](https://inleo.io/@leoglossary/leoglossary-buy) into the idea there will be just one winner.  It is wide open with a lot of [money](https://inleo.io/@leoglossary/leoglossary-money) on the line.


The labor [market](https://inleo.io/@leoglossary/leoglossary-market) is estimated at $30 trillion.  This is a global figure, one that takes intoaccount all those working globally.


However, the [total addressable market](https://inleo.io/@leoglossary/leoglossary-total-addressable-market-tam) (TAM) is actually much bigger.  Roomba is an example of a robot (specialized) that didn't replace any paid labor.  It did, however, [sell](https://inleo.io/@leoglossary/leoglossary-sell) because people wanted to eliminate that task from their "to do" list.  That means the market is larger than these numbers are estimating.


Another example is cooking.  How many people would buy a robot to prepare their meals for them?  This is something that could be a huge seller.  


Of course, those working on this solution are going to target the [restaurant](https://inleo.io/@leoglossary/leoglossary-restaurant) market first.  This is where the initial wave of buyers will come since they can realize cost savings through this acquisition.


The same is true for Optimus.  Even if the folding of shirts is in its skillset, you are not going to have one anytime soon.


Here is the video:

<iframe width="1280" height="720" src="https://www.youtube.com/embed/gyURDZB7imo" title="Tesla Optimus Bot Folds Laundry" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>



## Larger Steps Forward


There are a few things that stand out about the video.


The first is that we are not looking at full automation.  Optimus is getting assistance here, something Musk [confirmed](https://inleo.io/@leoglossary/leoglossary-confirmed).  The important take away is that the learning is similar to that of the Figure robot.  With repetition, the robot will get the task down.


Another point with the video is we see other versions on the bot in the background.  There are obviously a number of stations set up.  Are they using Optimus v 1 to also train?  Another point is we have no idea how big this room is.  There might be this bot alone or there could be 30 more.  We honestly have no clue.


As stated in my last article, when it comes to tasks, the key is "learn once, know forever".  While folding a shirt isn't the more dire of [robotic](https://inleo.io/@leoglossary/leoglosary-robotics-robots) [application](https://inleo.io/@leoglossary/leoglossary-application), the video says it all.  The focus is upon those tasks that are boring, repetitive, and unsafe.


Obviously, we are dealing with a huge range of possibilities here.


## The Best of the Best


In the last article, we also discuss the notion of the exponential with tasks.  To quickly summarize, if 100 people each learn 1 task, that is 100 tasks (1 per person).  The same is true for robots except for the fact the system learned all 100.  That means, when the bots receive the updated [software](https://inleo.io/@leoglossary/leoglossary-software), the total is 10,000 tasks (100 per robot).


What we did not cover is the quality of the training.


While shirt folding is hardly a skill of epic proportions, we do know that department stores have a particular way they fold their merchandise for display.  What if those people were the ones who trained the software?


To take it a step further, let us go back to the cooking.  Instead of an average person doing the training, how about a world renowned [chef](https://inleo.io/@leoglossary/leoglossary-chef) being the basis?  That means the bots could be skilled at the level of the best humanity has to offer.


Referring back to the [Tesla](https://inleo.io/@leoglossary/leoglossary-tesla) video, we are not going to see this for domestic use anytime soon.  The industrial [applications](https://inleo.io/@leoglossary/leoglossary-application) are still the primary focus.  However, this demonstration means that would could see the in-[home](nleo.io/@leoglossary/leoglossary-home) market starting to be penetrated by the end of the decade.  


There is a word of caution here:


The breakthroughs are amazing but there is still a long way to go.  We have many facets of development on both the AI and physical side.  That said, it is likely that some Optimus bots are on the floors of Tesla [factories](https://inleo.io/@leoglossary/leoglossary-factory) by the end of the year.  This might only be a handful, offering the first generation of real world training, but my guess is we will see this.


From that, my guess is we start seeing come companies enter production in 2026.  Again, the numbers will not be overwhelming but they are going to start seeing use in industries such as [manufacturing](https://inleo.io/@leoglossary/leoglossary-manufacturing).  The advantage is the system can be trained on a customer's layout even before the robots arrive.


Just another day in the world of robotic research.


____


<center>[What Is Hive](https://inleo.io/@leoglossary/leoglossary-what-is-hive) </center>






Posted Using [InLeo Alpha](https://inleo.io/@taskmaster4450le/another-major-breakthrough-in-robotics)