So this is an important update that we are including at the beginning of March 2024.
Lon Chaney has recently announced the general availability of Lang Smith, their LM ops platform, and
they have described a the full LM application development cycle as they see it.
So you will see that for several reasons.
This announcement of Lang Chain, which also includes the last investment that a venture capital firm
has made in Lang Lang chain, $25 million.
This new information is a making Lang chain much more stronger than it was before this announced this
announcement for us.
So we thought it was important to share this information with you.
And as you will see, we have included a several new sections in the program.
At the end of the program, at the end of the LM ops, uh sections, in order to uh, include all the
new things that Lang Chain is, uh, presenting, uh, after this announcement.
So we have a very interesting section, several sections, in fact, uh, about Lang Smith and LM ops
and how all these, uh, new, uh, things that Lang Chain is announcing, uh, uh, means mean for,
for us, uh, artificial intelligence engineer.
So interesting development.
And I am going to give you a short, very short summary now, and we will go to, uh, more detail in
a next section at the end of the LM ops.
But right now, I just wanted to tell you that.
Yeah.
So we told you.
So, uh, we will talk a little bit about that.
Uh, we will, uh, made we will make a summary of the Lang chain announcement, and we will share with
you what are the main implications of this announcement in our opinion.
So this is a chart that you are going to see in the A sections where we talk about the new Lang Smith
platform.
If you remember, we have talked about Lang Smith briefly before.
Lang Lang Smith was a beta version until now.
So it was a just a promise.
Now Lang Smith is a reality.
And we are going to share with you what we have learned from the new Smith platform, everything they
have shared with us and how this is, is going to be very valuable for you as a artificial intelligence
engineer.
So you will see this chart later in the LM ops section where we talk about Lang Smith.
But now I just wanted to tell you that remember we told you so, uh, we are talking about when we are
talking about generative AI, we are talking about a field in a very, very, very early stage.
And this is a very fast moving industry.
So this is not the only change we are going to see on the way.
So you will see that this program is going to evolve very quickly as we see the industry, uh, moving
and changing and evolving.
And this is this is super exciting for us, but it is also an obligation for us to be very, very,
very, you know, uh, paying a lot of attention to what is happening and trying to incorporate all
the changes and all the new things for you as soon as we can.
And this applies to everything as you as you already know, this applies to to the code.
So as soon as we as soon as we load, you know, a new exercise, the code evolves.
We have new versions.
We we we we.
So it is a little bit, well, stressing, you know, uh, but I think it's a very interesting moment.
In fact, it is the best moment to be in the artificial intelligence, in the generative artificial
intelligence space.
It is the best moment.
So I think you are going to be very happy in a few years to, to, uh, to be here right now.
So first we told you so.
Second, how can we summarize the announcement Lang Chain made on February 15th, uh, 2024?
They say that a they announced the general availability of Lang Smith.
So the Lang Smith platform goes from beta to production.
Until now, if you wanted to use language Smith, you had to apply for a for a waiting list, etc..
And Lang Smith was, you know, just like a small promise.
But now it is a reality.
It's open for everybody.
They have three different versions and it is very interesting.
And as you will see at the end of the program, we have invested a lot of time studying the Lang Smith
platform and all the possibilities and, uh, all the advantages that it is going to offer you and it
is going to offer all the, uh, artificial intelligence engineers.
So this is the first important thing that Lang Chain told us at the at the end of February.
But the second important thing is that they have received $25 million from one of the top venture capital
firms in Silicon Valley.
So what does this mean?
First, the business model of Lang Chain seems now more clear.
And this is very important for us because until now, anyone can wonder, uh, how is Lang Chain making
money?
Because if this company is not able to make money, this framework is not going to stay for long.
So it is very important for us to see.
Okay, Lang chain is, uh, using right now a software, uh, subscription based, uh, model.
And they have right now a source of income.
They also have a, you know, a very important source of investment.
So this company is here to stay very important point.
Second point, the stability and the future of Lang chain are also more clear.
They have resources to invest on on their team, you know, on their research, you know, their platform,
etc. this is very good for us to know, very good for us to know.
I anticipate that we are going to see similar moves in other.
Players in the industry, but right now Lansing is leading the way.
So it's very important to know this third thing.
This is very interesting.
The announcement of a long chain is very interesting for us and for our boot camp and for our students,
because since the beginning, our main focus was the professional approach.
So if you remember, I told you that one of the the the things that made us start this bootcamp was
the fact that we were finding so many toy demos, so many courses, videos and and documents and people
talking about just a hobby, a LM applications.
And we were a e eager to find professional approaches.
Right.
So we wanted to have professional tools in order and professional courses and professional guidance
in order to build professional l lm applications.
So everything that calls for a professional approach gets our attention.
And in the announcement of Lang Smith, we have a lot of that because they don't just announce the general
availability of Lang Smith and the investment they got.
The big part of their announcement is to share with us what they have learned during the past year about
professional LM application development and all these lessons they have shared with us.
We have studied them, you know, intensively, and we are sharing them with you in the last part of
the program.
So in these blogs where you are going to see lm, lm lm ops Lang Smith, we have several blogs there
that we are including now in the program, you are going to see much more than the description and the
presentation and the details, because is a super a intensive presentation of the the the full Lang
Smith platform, I think right now is the best course you are going to find in Lang Smith or all over
the world.
It is really powerful.
But apart from presenting you the Lang Smith platform, what we are doing there is talking about the
lessons learned by the Lang Chain team during their first year of operations, and one of the main things
they have been doing is working with professional LM app development teams from all over the world.
So during one year they have been observing what teams are doing right, what teams are doing wrong,
what are their pain points, what are the things they need?
What are the benefits they are they are expecting for from a framework like like Lang Chain, but also
from a platform like Lang Smith.
So all these lessons learned that they share with us are extremely, extremely interesting.
So I really encourage you to, to to look at these, uh, sections, these new sections of the program
that we are including now talking about Lang Smith, because you are going to learn much more than a
the different details about this new platform.
So I think it is a very interesting announcement, and we are really excited to share this news with
you now.
Okay.
So this is what you are going to find in the in the New Language myth sections we have included, we
you are going to find one section talking about the the full cycle of building a professional applications.
This is super interesting.
What are the main challenges that a development teams are finding in each of the stages of the cycle,
and how language myth solves these challenges?
Then we see language myth in depth and we see Langs myth at work.
And this is super interesting because we start with a very basic project using language myth, and then
we go with one of the most sophisticated professional projects, LM app projects, uh, working with
language myth as well.
So I think a our program has, has gone much, much better with the inclusion of these new sections.
I'm really happy to share this with you.