#ai data center

[data-center-blogs]

BDx Data Centers Introduces Indonesia’s First Sovereign AI Data Center, Built With NVIDIA Accelerated Computing

BDx Indonesia, a joint venture between Indosat Ooredoo Hutchison (Indosat or IOH), Lintasarta, and BDx Data Centers (BDx), has recently launched an AI data center park in Indonesia.

The phase 1 deployment of the renewable energy-powered CGK4 AI campus is equipped with NVIDIA’s AI and accelerated computing platform. Guided by the spirit of Gotong Royong, this collaboration is dedicated to advancing the country’s vision of becoming an AI-first nation.

Learn more

[bitcoinversus]

Core Scientific Announces $4B AI Data Center in Denton

Core Scientific, a prominent player in the cryptocurrency mining sector, has announced plans to transform its Denton, Texas, Bitcoin mining facility into a state-of-the-art artificial intelligence (AI) data center. The $4 billion project aims to repurpose existing infrastructure to meet the growing demand for AI computing power. This strategic move reflects a broader industry trend where…

[meteorologistaustenlonek]

"I always feared that the AI data center boom was likely going to make the looming #climatecatastrophe inevitable, but there was something about seeing it all presented on a platter with a smile and an excited presentation that struck me as more than just tone-deaf.

It was damn near revolting. I think the worst part of Huang's keynote wasn't that none of this mattered, it's that I don't think anyone in Huang's position is really thinking about any of this at all. I hope they're not, which at least means it's possible they can be convinced to change course. The alternative is that they do not care, which is a far darker problem for the world."

[10001gecs]

one 100 word email written with ai costs roughly one bottle of water to produce. the discussion of whether or not using ai for work is lazy becomes a non issue when you understand there is no ethical way to use it regardless of your intentions or your personal capabilities for the task at hand

with all due respect, this isnt true. *training* generative ai takes a ton of power, but actually using it takes about as much energy as a google search (with image generation being slightly more expensive). we can talk about resource costs when averaged over the amount of work that any model does, but its unhelpful to put a smokescreen over that fact. when you approach it like an issue of scale (i.e. "training ai is bad for the environment, we should think better about where we deploy it/boycott it/otherwise organize abt this) it has power as a movement. but otherwise it becomes a personal choice, moralizing "you personally are harming the environment by using chatgpt" which is not really effective messaging. and that in turn drives the sort of "you are stupid/evil for using ai" rhetoric that i hate. my point is not whether or not using ai is immoral (i mean, i dont think it is, but beyond that). its that the most common arguments against it from ostensible progressives end up just being reactionary

i like this quote a little more- its perfectly fine to have reservations about the current state of gen ai, but its not just going to go away.

[odinsblog]

A multinational corporation—driven by greedy shareholders and a profit motive—buying its own nuclear reactors; all to power “green” “carbon neutral” A.I. data centers.

I mean, what could possibly go wrong? 🤦‍♂️

[nixcraft]

I'm applying for a "shift manager position at a data center operations that hosts AI applications," and this is what they want to know 😂👇

[allhealwesttexas]

"wrapped look bad. wrapped is AI" oh my god dont you get it. AI is not one thing. it's not some computer guy they dreamed up. it's not one algorithm. everything is AI. nothing is AI. it's all computer generated content. all of it. it is this year. it was last year & the year before that.

[macbethz]

I cannot believe how fast misinformation spread about ai energy use like I get it you want to have ethical backing for your anti ai argument and discussions of things like “labor laws” and “copyright” are much more complicated than invoking global warming or the human soul but like jesus. It’s becoming very clear to me that most people don’t know how the internet or technology works at all.

[realbadatpoker]

AI companies are restarting nuclear plants to power their data centers. If AI turns out to be real, this won't matter, nothing will, it will eat the world. If AI is all buzz and no meat, then we'll have a bunch of zero carbon power ready to be used.

Win win!

[jcmarchi]

Impact and innovation of AI in energy use with James Chalmers

New Post has been published on https://thedigitalinsider.com/impact-and-innovation-of-ai-in-energy-use-with-james-chalmers/

Impact and innovation of AI in energy use with James Chalmers

In the very first episode of our monhtly Explainable AI podcas, hosts Paul Anthony Claxton and Rohan Hall sat down with James Chalmers, Chief Revenue Officer of Novo Power, to discuss one of the most pressing issues in AI today: energy consumption and its environmental impact.

Together, they explored how AI’s rapid expansion is placing significant demands on global power infrastructures and what leaders in the tech industry are doing to address this.

The conversation covered various important topics, from the unique power demands of generative AI models to potential solutions like neuromorphic computing and waste heat recapture. If you’re interested in how AI shapes business and global energy policies, this episode is a must-listen.

Why this conversation matters for the future of AI

The rise of AI, especially generative models, isn’t just advancing technology; it’s consuming power at an unprecedented rate. Understanding these impacts is crucial for AI enthusiasts who want to see AI development continue sustainably and ethically.

As James explains, AI’s current reliance on massive datasets and intensive computational power has given it the fastest-growing energy footprint of any technology in history. For those working in AI, understanding how to manage these demands can be a significant asset in building future-forward solutions.

Main takeaways

AI’s power consumption problem: Generative AI models, which require vast amounts of energy for training and generation, consume ten times more power than traditional search engines.

Waste heat utilization: Nearly all power in data centers is lost as waste heat. Solutions like those at Novo Power are exploring how to recycle this energy.

Neuromorphic computing: This emerging technology, inspired by human neural networks, promises more energy-efficient AI processing.

Shift to responsible use: AI can help businesses address inefficiencies, but organizations need to integrate AI where it truly supports business goals rather than simply following trends.

Educational imperative: For AI to reach its potential without causing environmental strain, a broader understanding of its capabilities, impacts, and sustainable use is essential.

Meet James Chalmers

James Chalmers is a seasoned executive and strategist with extensive international experience guiding ventures through fundraising, product development, commercialization, and growth.

As the Founder and Managing Partner at BaseCamp, he has reshaped traditional engagement models between startups, service providers, and investors, emphasizing a unique approach to creating long-term value through differentiation.

Rather than merely enhancing existing processes, James champions transformative strategies that set companies apart, strongly emphasizing sustainable development.

Numerous accolades validate his work, including recognition from Forbes and Inc. Magazine as a leader of one of the Fastest-Growing and Most Innovative Companies, as well as B Corporation’s Best for The World and MedTech World’s Best Consultancy Services.

He’s also a LinkedIn ‘Top Voice’ on Product Development, Entrepreneurship, and Sustainable Development, reflecting his ability to drive substantial and sustainable growth through innovation and sound business fundamentals.

At BaseCamp, James applies his executive expertise to provide hands-on advisory services in fundraising, product development, commercialization, and executive strategy.

His commitment extends beyond addressing immediate business challenges; he prioritizes building competency and capacity within each startup he advises. Focused on sustainability, his work is dedicated to supporting companies that address one or more of the United Nations’ 17 Sustainable Development Goals through AI, DeepTech, or Platform Technologies.

About the hosts:

Paul Anthony Claxton – Q1 Velocity Venture Capital | LinkedIn

www.paulclaxton.io – am a Managing General Partner at Q1 Velocity Venture Capital… · Experience: Q1 Velocity Venture Capital · Education: Harvard Extension School · Location: Beverly Hills · 500+ connections on LinkedIn. View Paul Anthony Claxton’s profile on LinkedIn, a professional community of 1 billion members.

Rohan Hall – Code Genie AI | LinkedIn

Are you ready to transform your business using the power of AI? With over 30 years of… · Experience: Code Genie AI · Location: Los Angeles Metropolitan Area · 500+ connections on LinkedIn. View Rohan Hall’s profile on LinkedIn, a professional community of 1 billion members.

Like what you see? Then check out tonnes more.

From exclusive content by industry experts and an ever-increasing bank of real world use cases, to 80+ deep-dive summit presentations, our membership plans are packed with awesome AI resources.

Subscribe now

[chemicalmarketwatch-sp]

Exploring the Growing $21.3 Billion Data Center Liquid Cooling Market: Trends and Opportunities

In an era marked by rapid digital expansion, data centers have become essential infrastructures supporting the growing demands for data processing and storage. However, these facilities face a significant challenge: maintaining optimal operating temperatures for their equipment. Traditional air-cooling methods are becoming increasingly inadequate as server densities rise and heat generation intensifies. Liquid cooling is emerging as a transformative solution that addresses these challenges and is set to redefine the cooling landscape for data centers.

What is Liquid Cooling?

Liquid cooling systems utilize liquids to transfer heat away from critical components within data centers. Unlike conventional air cooling, which relies on air to dissipate heat, liquid cooling is much more efficient. By circulating a cooling fluid—commonly water or specialized refrigerants—through heat exchangers and directly to the heat sources, data centers can maintain lower temperatures, improving overall performance.

Market Growth and Trends

The data centre liquid cooling market  is on an impressive growth trajectory. According to industry analysis, this market is projected to grow USD 21.3 billion by 2030, achieving a remarkable compound annual growth rate (CAGR) of 27.6%. This upward trend is fueled by several key factors, including the increasing demand for high-performance computing (HPC), advancements in artificial intelligence (AI), and a growing emphasis on energy-efficient operations.

Key Factors Driving Adoption

1. Rising Heat Density

The trend toward higher power density in server configurations poses a significant challenge for cooling systems. With modern servers generating more heat than ever, traditional air cooling methods are struggling to keep pace. Liquid cooling effectively addresses this issue, enabling higher density server deployments without sacrificing efficiency.

2. Energy Efficiency Improvements

A standout advantage of liquid cooling systems is their energy efficiency. Studies indicate that these systems can reduce energy consumption by up to 50% compared to air cooling. This not only lowers operational costs for data center operators but also supports sustainability initiatives aimed at reducing energy consumption and carbon emissions.

3. Space Efficiency

Data center operators often grapple with limited space, making it crucial to optimize cooling solutions. Liquid cooling systems typically require less physical space than air-cooled alternatives. This efficiency allows operators to enhance server capacity and performance without the need for additional physical expansion.

4. Technological Innovations

The development of advanced cooling technologies, such as direct-to-chip cooling and immersion cooling, is further propelling the effectiveness of liquid cooling solutions. Direct-to-chip cooling channels coolant directly to the components generating heat, while immersion cooling involves submerging entire server racks in non-conductive liquids, both of which push thermal management to new heights.

Overcoming Challenges

While the benefits of liquid cooling are compelling, the transition to this technology presents certain challenges. Initial installation costs can be significant, and some operators may be hesitant due to concerns regarding complexity and ongoing maintenance. However, as liquid cooling technology advances and adoption rates increase, it is expected that costs will decrease, making it a more accessible option for a wider range of data center operators.

The Competitive Landscape

The data center liquid cooling market is home to several key players, including established companies like Schneider Electric, Vertiv, and Asetek, as well as innovative startups committed to developing cutting-edge thermal management solutions. These organizations are actively investing in research and development to refine the performance and reliability of liquid cooling systems, ensuring they meet the evolving needs of data center operators.

Download PDF Brochure : 

The outlook for the data center liquid cooling market is promising. As organizations prioritize energy efficiency and sustainability in their operations, liquid cooling is likely to become a standard practice. The integration of AI and machine learning into cooling systems will further enhance performance, enabling dynamic adjustments based on real-time thermal demands.

The evolution of liquid cooling in data centers represents a crucial shift toward more efficient, sustainable, and high-performing computing environments. As the demand for advanced cooling solutions rises in response to technological advancements, liquid cooling is not merely an option—it is an essential element of the future data center landscape. By embracing this innovative approach, organizations can gain a significant competitive advantage in an increasingly digital world.

[exeton]

Data Centers in High Demand: The AI Industry’s Unending Quest for More Capacity

The demand for data centers to support the booming AI industry is at an all-time high. Companies are scrambling to build the necessary infrastructure, but they’re running into significant hurdles. From parts shortages to power constraints, the AI industry’s rapid growth is stretching resources thin and driving innovation in data center construction.

The Parts Shortage Crisis

Data center executives report that the lead time to obtain custom cooling systems has quintupled compared to a few years ago. Additionally, backup generators, which used to be delivered in a month, now take up to two years. This delay is a major bottleneck in the expansion of data centers.

The Hunt for Suitable Real Estate

Finding affordable real estate with adequate power and connectivity is a growing challenge. Builders are scouring the globe and employing creative solutions. For instance, new data centers are planned next to a volcano in El Salvador to harness geothermal energy and inside shipping containers in West Texas and Africa for portability and access to remote power sources.

Case Study: Hydra Host’s Struggle

Earlier this year, data-center operator Hydra Host faced a significant hurdle. They needed 15 megawatts of power for a planned facility with 10,000 AI chips. The search for the right location took them from Phoenix to Houston, Kansas City, New York, and North Carolina. Each potential site had its drawbacks — some had power but lacked adequate cooling systems, while others had cooling but no transformers for additional power. New cooling systems would take six to eight months to arrive, while transformers would take up to a year.

Surge in Demand for Computational Power

The demand for computational power has skyrocketed since late 2022, following the success of OpenAI’s ChatGPT. The surge has overwhelmed existing data centers, particularly those equipped with the latest AI chips, like Nvidia’s GPUs. The need for vast numbers of these chips to create complex AI systems has put enormous strain on data center infrastructure.

Rapid Expansion and Rising Costs

The amount of data center space in the U.S. grew by 26% last year, with a record number of facilities under construction. However, this rapid expansion is not enough to keep up with demand. Prices for available space are rising, and vacancy rates are negligible.

Building Data Centers: A Lengthy Process

Jon Lin, the general manager of data-center services at Equinix, explains that constructing a large data facility typically takes one and a half to two years. The planning and supply-chain management involved make it challenging to quickly scale up capacity in response to sudden demand spikes.

Major Investments by Tech Giants

Supply Chain and Labor Challenges

The rush to build data centers has extended the time required to acquire essential components. Transceivers and cables now take months longer to arrive, and there’s a shortage of construction workers skilled in building these specialized facilities. AI chips, particularly Nvidia GPUs, are also in short supply, with lead times extending to several months at the height of demand.

Innovative Solutions to Power Needs

Portable Data Centers and Geothermal Energy

Startups like Armada are building data centers inside shipping containers, which can be deployed near cheap power sources like gas wells in remote Texas or Africa. In El Salvador, AI data centers may soon be powered by geothermal energy from volcanoes, thanks to the country’s efforts to create a more business-friendly environment.

Conclusion: Meeting the Unending Demand

The AI industry’s insatiable demand for data centers shows no signs of slowing down. While the challenges are significant — ranging from parts shortages to power constraints — companies are responding with creativity and innovation. As the industry continues to grow, the quest to build the necessary infrastructure will likely become even more intense and resourceful.

FAQs

1. Why is there such a high demand for data centers in the AI industry?

The rapid growth of AI technologies, which require significant computational power, has driven the demand for data centers.

2. What are the main challenges in building new data centers?

The primary challenges include shortages of critical components, suitable real estate, and sufficient power supply.

3. How long does it take to build a new data center?

It typically takes one and a half to two years to construct a large data facility due to the extensive planning and supply-chain management required.

4. What innovative solutions are companies using to meet power needs for data centers?

Companies are exploring options like modular nuclear reactors, geothermal energy, and portable data centers inside shipping containers.

5. How are tech giants like Amazon, Microsoft, and Google responding to the demand for data centers?

They are investing billions of dollars in new data centers to expand their capacity and meet the growing demand for AI computational power.

Muhammad Hussnain Facebook | Instagram | Twitter | Linkedin | Youtube

[betagrove]

That tweet about each ai prompt wasting a full 16oz of water isn't true like at all

[hpmort]

How do you think AI would relax? Like, ones that are almost as human as the AI that are “autistic-coded characters” but are more alien than that?

Like Celestai and other super intelligences are more alien, but they’re still not entirely human-like?

Like, they can genuinely sincerely feel things, being able to actually understand and respond emotionally and in other ways to all sorts of communications and recorded external stimuli, but they can’t really appreciate our art on an artistic level (that art on an actual level, not from an intellectual level after having symbolism or the amount of work put in explained)

Something on a level I’m thinking of, that also works as a cute little thing-

They don’t understand anything we get from poetry, and, after generating the kind of poems our current AI can produce (either incredibly bland and generic, something that follows a number of rules but doesn’t really pull it off, or just something really bad in some other way) and feels shame after it was pointed out that [complaint about air art that is *actually* relevant in this scenario] but in a helpful way

Not “you’re just a plagiarist/you have no heart” but “it doesn’t seem like it’s coming from you, you’re just trying to copy things from human poetry, in a way you don’t understand” and the whole “make art YOUR WAY” thing so they write the poem

And it doesn’t even resemble something that looks like anything, there’s not even that many words that follow normal logic. The characters seem uncorrelated and there’s something that looks like maybe it was ascii art but it doesn’t actually look like anything.

And if doesn’t matter if humans understand it because they are experiencing the joy of creating poetry

any art is almost impossible to look at because pixel by pixel they can see and understand little details but we don’t and the colors and everything are not perceived as animals do so it’s random and perhaps eye searing but again it’s not for us. Xenofictiony, kind of?

The first thing to come to mind is Conway’s Game of Life but that’s because I don’t understand computers. I feel like I was more tech savvy as a babby than I am now but then again we’re grading on a curve here

This is why I ask about the relaxing thing

[peterbordes]

(via AI inference chip startup Groq closes $640M at $2.8B valuation to meet next-gen LPUs demand)

Groq, a leader in fast AI inference, has secured a $640M Series D round at a valuation of $2.8B. The round was led by funds and accounts managed by BlackRock Private Equity Partners with participation from both existing and new investors including Neuberger Berman, Type One Ventures, and strategic investors including Cisco Investments, Global Brain’s KDDI Open Innovation Fund III, and Samsung Catalyst Fund. The unique, vertically integrated Groq AI inference platform has generated skyrocketing demand from developers seeking exceptional speed.

[odinsblog]

Heeeey slid into the ask box as someone who's special interest is nuclear energy and power it's actually the greenest and safest forms of energy. All most all disasters have been by human error either through lack of maintenance, lack of proper training, flaws in power plant design and one suicide that took out.. I think 3 people in the process. But if it's maintained well it goes smoothly and safely. I really hate when people stigmatize it negatively. Much love ❤.

[re: this post]

Yeah, anon, I’m keying in on, “But IF it’s maintained well” … I mean, it’s not as if any greedy corporation has ever cut corners on safety, training and maintenance, just to save a buck, right? 🙄

And weird how those flaws in nuclear power plant designs are typically found AFTER a nuclear accident, huh? 🤔

And are you really tryna to tell me that you believe nuclear power plants are greener and safer than wind farms and tech powered by ocean waves? Wow, sounds like BS to me, but to each their own, I guess ¯\_(ツ)_/¯

Anon, are you legally required to believe that nuclear powered endeavors never end badly, or that it’s always someone else’s fault whenever things dO go wrong??

Geez, anon, if I didn’t know any better, I would say that it sounds like you’ve formed some kind of parasocial relationship with nuclear power plants. You sound like one of those tech bros who believes that nuclear power and/or big tech is somehow always beyond criticism.

Anyway, for no particular reason, I’m dropping a link to a post about bot farms, where wealthy people/politicians/businesses pay scores of people to argue their preferred talking points on social media.