July 8, 2025 • 16 mins
In a remote part of China's northwestern Xinjiang region, dozens of data centers rise from the desert. A Bloomberg analysis of investor and tax documents and company filings found Chinese companies plan to buy more than 115,000 high-tech Nvidia chips — chips the US has banned from being exported to China – to power these centers, which could then be used for training AI models.
On today’s Big Take Asia Podcast, host K. Oanh Ha talks to Bloomberg’s Andy Lin and James Mayger about the story, and what it means for China’s AI master plan.
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Speaker 1 (00:02):
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
Earlier this year, our colleague James Mager took a trip
to the middle of the desert in the remote region
of Shinjong, China.
Speaker 3 (00:16):
Shinjung is the western third of China. Basically it borders Mongolia, Kazakhstan,
Uzebekistan and where we went on this trip is situated
in a river valley. It's got these lovely snow capped
mountains overlooking the town. Really was a stunningly beautiful place,
but very hard to get to.
Speaker 2 (00:37):
James was there on a lead generated by Bloomberg's data
journalism team that a handful of Chinese companies were building
some forty data centers across the region and planned to
power them with tens of thousands of Nvidia chips. Chips
that the US banned from being exported to China in
twenty twenty two is as well. China has criticized the
(00:58):
US moves to expand restrictions one is access to sympiconductor technology,
saying that they will harm supply chains and the world economy.
Speaker 1 (01:05):
They want to build a AI industry that can go
head to head with the US.
Speaker 2 (01:13):
Bloomberg data reporter Andy Linn led the team's investigation.
Speaker 1 (01:17):
In modern warfares, AI is playing a larger role, so
the US is worried about China developing the AI capacity
with developing their high end military must be.
Speaker 2 (01:30):
In Since the Biding Administration's initial restrictions on advanced AI chips,
the US has tightened export controls, putting them at the
center of tensions with Beijing. Just last week, Bloomberg learned
of plans by the Trump administration to further restrict the
shipments of AI chips to Thailand and Malaysia, part of
(01:52):
an effort to prevent them from being potentially smuggled into China.
Speaker 1 (01:56):
So by building these data centers and build up the
computing power, they aim to build a local, domestic EI
industry that can go ahead to have with opening AI
Alphabet Amazon Meta in the US.
Speaker 2 (02:15):
This is the Big Take Asia from Bloomberg News. I'm Wanha.
Every week we take you inside some of the world's
biggest and most powerful economies and the markets, tycoons, and
businesses that drive this ever shifting region. Today on the show,
China's AI ambition rises from the desert. China is fast
(02:40):
becoming a world leader in artificial intelligence it's one of
the top consumers of semiconductors, and as Deepseek's latest model shows,
Chinese companies are hungry to create top tier AI technology
to rival international competitors. But Andy says the US government's
export controls have created a real problem for China by
(03:02):
limiting its access to Nvidia's priced semiconductors.
Speaker 1 (03:07):
Nvidia is the industrial standard for any AI training operations,
so for example, Open Ai, the most famous AI companies
in the world, use Nvidia chips for training the chat,
GPT models and whatever. You want to build a sophisticated
AI model, you need to use a lot of Nvidia chips.
(03:29):
So MVA chip is sought after across all the world
for all the AI development because every country wants their
own AI.
Speaker 2 (03:38):
Industry, and he says China's ultimate goal is to have
its own source of advanced AI chips, ones that are
on par with Nvidia's offerings. For now, though, in semiconductors
are the best product on the market and Chinese companies
are eager to access them.
Speaker 1 (03:56):
Since the US introduced these export controls, I heard sources
in China saying they are having a hard time getting
large volumes of Nvidia chips for their operations. I think
this slow China's access to these chips, but not stop
them from getting them outright.
Speaker 2 (04:18):
The US government has no official consensus on how many
restricted Nvidia chips are currently in China. Two senior Biding
officials estimated that China had around twenty five thousand chips,
but most of the people Bloomberg spoke to say there
isn't an agreed upon estimate. That's why when Andy found
documents laying out the volume of Nvidia chips that companies
(04:40):
hope to obtain for these data centers, he was.
Speaker 1 (04:42):
Surprised because most of the people I talked to would
say that they assume some developments of these data standard
using Nvidia chips is ongoing, but not like declaring to
the world that they're going to use band Nvidia chips
in this large volume.
Speaker 2 (05:03):
In the fourth quarter of last year, the Chinese government
approved a total of thirty nine data center investment projects
in Shinjan and the neighboring Chinghai province. They've built out
plans to use more than one hundred and fifteen thousand
Nvidia processors.
Speaker 1 (05:17):
If wanted to compare this scale to what the US
have usually the tech companies there will claim if you
have more than one undred thousand Nvidia chips in one place,
then you'ing in a place to develop a state of
the art models which can possibly compete with Gemini Chat JBT.
Speaker 2 (05:38):
These kind of models, there's no explanation in the official
documents of how companies plan to acquire the band in
Nvidia chips, and it could all be aspirational. In a
response from Nvidia, the company said that posting a web
page about restricted products is not the same as successfully licensing,
building and operating a data center, and that Nvidia does
(06:01):
not provide any support or repairs for restricted products. In
the meantime, the companies listed in the filings, state officials
and central government representatives in Beijing all declined to comment
when asked to explain. Still the building continues in the desert.
Most of these data centers are located in a single
(06:22):
compound in Ewu County, set up by the local government
in Shinjug. These data centers house big computers, servers, and
other components and are used to process, store, and distribute data.
And while they might be located far from big cities
like Shanghai or Shenzen, startups in these cities can send
their models to the data centers for training and optimization.
Speaker 1 (06:45):
Theoretically, any company in China can access that computing power. Essentially,
you can send a request to the data centers in
Shinjioan saying that, hey, we want to use how many
chips to train our models in the eastern regions, and
then the data centers and Shinjong will produce a result
to you, maybe in a few minutes or even a
(07:07):
few seconds. Yeah, so these are all connected because you
don't need to be present at the data center use
the computing power.
Speaker 2 (07:16):
Shinjong is an ideal location for large scale data centers.
Land is cheap and rental costs are low. The region
also has cool weather, which helps offset the heat generated
by the servers. Most importantly, it's a hub for green energy.
On the way to look for the data centers, James
Mager stumbled across miles and miles of renewable energy installations.
Speaker 3 (07:40):
The desert was just a dusty, rocky plane, and scattered
across the desert was just windmill after windmill, after solar
panel installation after solar panel installation, and then there was
also this power generation, which is where the company uses
mirrors to concentrate sunlight on tooward tower, which is filled
(08:00):
with molten sodium, and then that heat is generated by
concentrating all that sunlight is then used to generate electricity.
And you can see this like twenty thirty kilometers away
because the sunlight is so blinding as it's concentrated onto
this tower.
Speaker 2 (08:15):
This combination of green energy and advanced computing fits in
with Beijing's economic push for sustainable development. After the break,
what is China's master plan to build these data centers?
We zoom in on one company to find out. Bloomberg's
(08:44):
James Mager spent three days in Shinjung tracking down the
data centers. Andy Linn and his team had found on paper, Iwu.
Speaker 3 (08:52):
Is pretty remote, even in Shinjong, which is pretty remote
in China. To get there, it was a four hour
plane ride from Beijing to the city of Hami, and
then from Hami to Iwu is another three and a
half for our car ride up into the mountains.
Speaker 2 (09:09):
Using the data team's coordinates, James was able to locate
massive building complexes in the desert right where Andy said
the data centers were being built.
Speaker 3 (09:19):
There was a lot of construction in Eyu, and there
was some construction going on up in the area with
all the solar panels. I've never seen a data center before.
I mean, this is the first time I've seen a
data center. But they look like what I imagine a data center.
Speaker 1 (09:33):
Would look like.
Speaker 3 (09:34):
You have a large building which is three, four or
five stories tall, has almost no windows. They obviously don't
need a lot of light. Having a lot of windows
is going to make it harder to keep the temperature
inside the data center controlled at the proper level.
Speaker 2 (09:48):
It sounds like they had certainly all the hallmarks of
being a data center.
Speaker 1 (09:51):
Yes.
Speaker 2 (09:53):
Among all the projects examined in the investigation, one caught
the team's attention. It involves a company controlled by Nyocore,
an energy firm that's partially owned by the state government
based in Tianjin in northern China. Niacore's main business is
supplying solar and wind power. And I asked Andy, why
a green energy firm, of all companies, would be building
(10:16):
data centers.
Speaker 1 (10:17):
Yeah. So you don't usually think that green energy companies
delve into the data standard business, but in China, Beijing
has been encouraging green energy companies to invest into AI
data centers because they want to lower the carbon foot prints.
That will create a win win.
Speaker 2 (10:37):
According to the documents, Bloomberg found Nyacore plans to build
a data center with six hundred and twenty five servers.
Speaker 1 (10:44):
It is one of the largest projects we found in
the batch of the documents. Based on their investment approvals,
they need two thousand, one hundred GPU chips. This a
lot because if you imagine one at one hundred chips
cost around twenty thousand dollars, then well is a very
(11:05):
big amount of money just for mid sized green energy
company in China.
Speaker 2 (11:13):
Niacord is selling its computer power to infinitgens Ai, one
of the largest AI infrastructure companies in China. The company
has raised one billion yun or almost one hundred and
forty million dollars in funding since it was founded in
twenty twenty three. Niacord declined to comment and infinogens Ai
couldn't be reached for a response, but last year, the
(11:35):
CEO of infinogens Ai said in an interview with local
media that the goal is to make computing power more
accessible to AI companies all across China.
Speaker 1 (11:46):
Their CEO said they aim to create a computing power
system that allows AI developers across the main line to
just log into their system and get all the computing
power they want, just like opening a like water tap
and then you can get the water you want.
Speaker 2 (12:06):
Computer power on tap. But in order to make computer
power accessible anywhere, anytime, there's an issue that needs to
be addressed first. Shinjong is China's most western region. Most
of the AI companies that need the computing power are
based in big cities like Shanghai, far in the east.
(12:26):
That's more than two thousand miles apart, about the distance
from Chicago to Los Angeles. Andy says. The Chinese government
plans to bridge this supplied demand gap by building what
they call computing power corridors.
Speaker 1 (12:39):
You can think about this as the water resource management
system in China. They have been moving the water from
the southern region to the north region, which is suffering
from draft. So they have been moving crucial resources around
in the mainland, and now they want to move the
computing power.
Speaker 2 (12:57):
So in some ways they're thinking of a computing power
like a utility, right, and the computing power corridor would
be like the power grid.
Speaker 1 (13:06):
Yeah, yeah, that's what they are aiming for. They're building
infrastructure like more cables along the codors, so that they
can encourage more AI developers to build infrastructure in the
western regions.
Speaker 2 (13:19):
This is all part of China's plan to dominate in AI.
But in order for China to get there, it needs
all these things to come together. Its own high tech
chips that can rival in NVIDIAs, computer power on tap,
and an industry with cutting edge innovations. And Andy says
building such a national network could encourage more Chinese companies
(13:41):
to jump into the AI space without needing to build
their own data centers. That would help startups come up
with more innovations like Deepseek did with its chatbot, and
ultimately narrow the gap between the US and China.
Speaker 1 (13:56):
I think one of the most powerful aspect of this
utility for AI computing powers that it will not be
controlled by a couple of tech giants only. So if
you make a comparison between US and China. In the US,
computing power is mostly owned by a handful of tech giants.
Open ai madea alphabet, but if you make it as
(14:20):
a utility, every developer across the mainline can just log
into a system and then got as much computing power
as they want. Then it will create a very distributed
system for AI innovations, so that anyone who have the
idea can just create its own model, and then we'll
(14:43):
have a more collaborative environment for these developments, which is
totally different from what we have in the US.
Speaker 2 (14:50):
There's a lot of uncertainty about this model. Will China
be able to create a cheap and reliable power source
that everyone can tap into, will it be able to
acquire computer chips that AI development demands, and will China
be able to make those chips itself rather than relying
on a US company Like in video.
Speaker 1 (15:09):
What we found in Shinjiai and Shanghai for these scale
of data CENTTA development shows that Beijing is trying very
hard to nurture is on domestic AI industry so that
they can match the tech giants from the wests.
Speaker 2 (15:39):
This is The Big Take Asia from Bloomberg News. I'm wanha.
To get more from The Big Take and unlimited access
to all of Bloomberg dot Com, subscribe today at Bloomberg
dot com slash podcast offer. If you like the episode,
make sure to subscribe and review The Big Take Asia
wherever you listen to podcasts. It really helps people find
the show. Thanks for listening, See next time.
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
Earlier this year, our colleague James Mager took a trip
to the middle of the desert in the remote region
of Shinjong, China.
Speaker 3 (00:16):
Shinjung is the western third of China. Basically it borders Mongolia, Kazakhstan,
Uzebekistan and where we went on this trip is situated
in a river valley. It's got these lovely snow capped
mountains overlooking the town. Really was a stunningly beautiful place,
but very hard to get to.
Speaker 2 (00:37):
James was there on a lead generated by Bloomberg's data
journalism team that a handful of Chinese companies were building
some forty data centers across the region and planned to
power them with tens of thousands of Nvidia chips. Chips
that the US banned from being exported to China in
twenty twenty two is as well. China has criticized the
(00:58):
US moves to expand restrictions one is access to sympiconductor technology,
saying that they will harm supply chains and the world economy.
Speaker 1 (01:05):
They want to build a AI industry that can go
head to head with the US.
Speaker 2 (01:13):
Bloomberg data reporter Andy Linn led the team's investigation.
Speaker 1 (01:17):
In modern warfares, AI is playing a larger role, so
the US is worried about China developing the AI capacity
with developing their high end military must be.
Speaker 2 (01:30):
In Since the Biding Administration's initial restrictions on advanced AI chips,
the US has tightened export controls, putting them at the
center of tensions with Beijing. Just last week, Bloomberg learned
of plans by the Trump administration to further restrict the
shipments of AI chips to Thailand and Malaysia, part of
(01:52):
an effort to prevent them from being potentially smuggled into China.
Speaker 1 (01:56):
So by building these data centers and build up the
computing power, they aim to build a local, domestic EI
industry that can go ahead to have with opening AI
Alphabet Amazon Meta in the US.
Speaker 2 (02:15):
This is the Big Take Asia from Bloomberg News. I'm Wanha.
Every week we take you inside some of the world's
biggest and most powerful economies and the markets, tycoons, and
businesses that drive this ever shifting region. Today on the show,
China's AI ambition rises from the desert. China is fast
(02:40):
becoming a world leader in artificial intelligence it's one of
the top consumers of semiconductors, and as Deepseek's latest model shows,
Chinese companies are hungry to create top tier AI technology
to rival international competitors. But Andy says the US government's
export controls have created a real problem for China by
(03:02):
limiting its access to Nvidia's priced semiconductors.
Speaker 1 (03:07):
Nvidia is the industrial standard for any AI training operations,
so for example, Open Ai, the most famous AI companies
in the world, use Nvidia chips for training the chat,
GPT models and whatever. You want to build a sophisticated
AI model, you need to use a lot of Nvidia chips.
(03:29):
So MVA chip is sought after across all the world
for all the AI development because every country wants their
own AI.
Speaker 2 (03:38):
Industry, and he says China's ultimate goal is to have
its own source of advanced AI chips, ones that are
on par with Nvidia's offerings. For now, though, in semiconductors
are the best product on the market and Chinese companies
are eager to access them.
Speaker 1 (03:56):
Since the US introduced these export controls, I heard sources
in China saying they are having a hard time getting
large volumes of Nvidia chips for their operations. I think
this slow China's access to these chips, but not stop
them from getting them outright.
Speaker 2 (04:18):
The US government has no official consensus on how many
restricted Nvidia chips are currently in China. Two senior Biding
officials estimated that China had around twenty five thousand chips,
but most of the people Bloomberg spoke to say there
isn't an agreed upon estimate. That's why when Andy found
documents laying out the volume of Nvidia chips that companies
(04:40):
hope to obtain for these data centers, he was.
Speaker 1 (04:42):
Surprised because most of the people I talked to would
say that they assume some developments of these data standard
using Nvidia chips is ongoing, but not like declaring to
the world that they're going to use band Nvidia chips
in this large volume.
Speaker 2 (05:03):
In the fourth quarter of last year, the Chinese government
approved a total of thirty nine data center investment projects
in Shinjan and the neighboring Chinghai province. They've built out
plans to use more than one hundred and fifteen thousand
Nvidia processors.
Speaker 1 (05:17):
If wanted to compare this scale to what the US
have usually the tech companies there will claim if you
have more than one undred thousand Nvidia chips in one place,
then you'ing in a place to develop a state of
the art models which can possibly compete with Gemini Chat JBT.
Speaker 2 (05:38):
These kind of models, there's no explanation in the official
documents of how companies plan to acquire the band in
Nvidia chips, and it could all be aspirational. In a
response from Nvidia, the company said that posting a web
page about restricted products is not the same as successfully licensing,
building and operating a data center, and that Nvidia does
(06:01):
not provide any support or repairs for restricted products. In
the meantime, the companies listed in the filings, state officials
and central government representatives in Beijing all declined to comment
when asked to explain. Still the building continues in the desert.
Most of these data centers are located in a single
(06:22):
compound in Ewu County, set up by the local government
in Shinjug. These data centers house big computers, servers, and
other components and are used to process, store, and distribute data.
And while they might be located far from big cities
like Shanghai or Shenzen, startups in these cities can send
their models to the data centers for training and optimization.
Speaker 1 (06:45):
Theoretically, any company in China can access that computing power. Essentially,
you can send a request to the data centers in
Shinjioan saying that, hey, we want to use how many
chips to train our models in the eastern regions, and
then the data centers and Shinjong will produce a result
to you, maybe in a few minutes or even a
(07:07):
few seconds. Yeah, so these are all connected because you
don't need to be present at the data center use
the computing power.
Speaker 2 (07:16):
Shinjong is an ideal location for large scale data centers.
Land is cheap and rental costs are low. The region
also has cool weather, which helps offset the heat generated
by the servers. Most importantly, it's a hub for green energy.
On the way to look for the data centers, James
Mager stumbled across miles and miles of renewable energy installations.
Speaker 3 (07:40):
The desert was just a dusty, rocky plane, and scattered
across the desert was just windmill after windmill, after solar
panel installation after solar panel installation, and then there was
also this power generation, which is where the company uses
mirrors to concentrate sunlight on tooward tower, which is filled
(08:00):
with molten sodium, and then that heat is generated by
concentrating all that sunlight is then used to generate electricity.
And you can see this like twenty thirty kilometers away
because the sunlight is so blinding as it's concentrated onto
this tower.
Speaker 2 (08:15):
This combination of green energy and advanced computing fits in
with Beijing's economic push for sustainable development. After the break,
what is China's master plan to build these data centers?
We zoom in on one company to find out. Bloomberg's
(08:44):
James Mager spent three days in Shinjung tracking down the
data centers. Andy Linn and his team had found on paper, Iwu.
Speaker 3 (08:52):
Is pretty remote, even in Shinjong, which is pretty remote
in China. To get there, it was a four hour
plane ride from Beijing to the city of Hami, and
then from Hami to Iwu is another three and a
half for our car ride up into the mountains.
Speaker 2 (09:09):
Using the data team's coordinates, James was able to locate
massive building complexes in the desert right where Andy said
the data centers were being built.
Speaker 3 (09:19):
There was a lot of construction in Eyu, and there
was some construction going on up in the area with
all the solar panels. I've never seen a data center before.
I mean, this is the first time I've seen a
data center. But they look like what I imagine a data center.
Speaker 1 (09:33):
Would look like.
Speaker 3 (09:34):
You have a large building which is three, four or
five stories tall, has almost no windows. They obviously don't
need a lot of light. Having a lot of windows
is going to make it harder to keep the temperature
inside the data center controlled at the proper level.
Speaker 2 (09:48):
It sounds like they had certainly all the hallmarks of
being a data center.
Speaker 1 (09:51):
Yes.
Speaker 2 (09:53):
Among all the projects examined in the investigation, one caught
the team's attention. It involves a company controlled by Nyocore,
an energy firm that's partially owned by the state government
based in Tianjin in northern China. Niacore's main business is
supplying solar and wind power. And I asked Andy, why
a green energy firm, of all companies, would be building
(10:16):
data centers.
Speaker 1 (10:17):
Yeah. So you don't usually think that green energy companies
delve into the data standard business, but in China, Beijing
has been encouraging green energy companies to invest into AI
data centers because they want to lower the carbon foot prints.
That will create a win win.
Speaker 2 (10:37):
According to the documents, Bloomberg found Nyacore plans to build
a data center with six hundred and twenty five servers.
Speaker 1 (10:44):
It is one of the largest projects we found in
the batch of the documents. Based on their investment approvals,
they need two thousand, one hundred GPU chips. This a
lot because if you imagine one at one hundred chips
cost around twenty thousand dollars, then well is a very
(11:05):
big amount of money just for mid sized green energy
company in China.
Speaker 2 (11:13):
Niacord is selling its computer power to infinitgens Ai, one
of the largest AI infrastructure companies in China. The company
has raised one billion yun or almost one hundred and
forty million dollars in funding since it was founded in
twenty twenty three. Niacord declined to comment and infinogens Ai
couldn't be reached for a response, but last year, the
(11:35):
CEO of infinogens Ai said in an interview with local
media that the goal is to make computing power more
accessible to AI companies all across China.
Speaker 1 (11:46):
Their CEO said they aim to create a computing power
system that allows AI developers across the main line to
just log into their system and get all the computing
power they want, just like opening a like water tap
and then you can get the water you want.
Speaker 2 (12:06):
Computer power on tap. But in order to make computer
power accessible anywhere, anytime, there's an issue that needs to
be addressed first. Shinjong is China's most western region. Most
of the AI companies that need the computing power are
based in big cities like Shanghai, far in the east.
(12:26):
That's more than two thousand miles apart, about the distance
from Chicago to Los Angeles. Andy says. The Chinese government
plans to bridge this supplied demand gap by building what
they call computing power corridors.
Speaker 1 (12:39):
You can think about this as the water resource management
system in China. They have been moving the water from
the southern region to the north region, which is suffering
from draft. So they have been moving crucial resources around
in the mainland, and now they want to move the
computing power.
Speaker 2 (12:57):
So in some ways they're thinking of a computing power
like a utility, right, and the computing power corridor would
be like the power grid.
Speaker 1 (13:06):
Yeah, yeah, that's what they are aiming for. They're building
infrastructure like more cables along the codors, so that they
can encourage more AI developers to build infrastructure in the
western regions.
Speaker 2 (13:19):
This is all part of China's plan to dominate in AI.
But in order for China to get there, it needs
all these things to come together. Its own high tech
chips that can rival in NVIDIAs, computer power on tap,
and an industry with cutting edge innovations. And Andy says
building such a national network could encourage more Chinese companies
(13:41):
to jump into the AI space without needing to build
their own data centers. That would help startups come up
with more innovations like Deepseek did with its chatbot, and
ultimately narrow the gap between the US and China.
Speaker 1 (13:56):
I think one of the most powerful aspect of this
utility for AI computing powers that it will not be
controlled by a couple of tech giants only. So if
you make a comparison between US and China. In the US,
computing power is mostly owned by a handful of tech giants.
Open ai madea alphabet, but if you make it as
(14:20):
a utility, every developer across the mainline can just log
into a system and then got as much computing power
as they want. Then it will create a very distributed
system for AI innovations, so that anyone who have the
idea can just create its own model, and then we'll
(14:43):
have a more collaborative environment for these developments, which is
totally different from what we have in the US.
Speaker 2 (14:50):
There's a lot of uncertainty about this model. Will China
be able to create a cheap and reliable power source
that everyone can tap into, will it be able to
acquire computer chips that AI development demands, and will China
be able to make those chips itself rather than relying
on a US company Like in video.
Speaker 1 (15:09):
What we found in Shinjiai and Shanghai for these scale
of data CENTTA development shows that Beijing is trying very
hard to nurture is on domestic AI industry so that
they can match the tech giants from the wests.
Speaker 2 (15:39):
This is The Big Take Asia from Bloomberg News. I'm wanha.
To get more from The Big Take and unlimited access
to all of Bloomberg dot Com, subscribe today at Bloomberg
dot com slash podcast offer. If you like the episode,
make sure to subscribe and review The Big Take Asia
wherever you listen to podcasts. It really helps people find
the show. Thanks for listening, See next time.
Hosts And Creators
Sarah Holder
Saleha Mohsin
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Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.