The staggering investments in artificial intelligence keep coming: Last week, AI chip giant Nvidia announced it would invest $100 billion to help OpenAI, the frontrunner in generative AI, build data centers.

How are these enormous sums possible when the returns on investments, at least for now, pale in comparison?

Huge investments

AI-related spending is soaring worldwide, expected to reach approximately $1.5 trillion by 2025, according to US research firm Gartner, and over $2 trillion in 2026—nearly 2% of global GDP.

Even though tangible returns fall short of the investments going in, the AI revolution appears unstoppable.

“There’s no doubt among investors that AI is the major breakthrough technology”—on par with harnessing electricity, said Denis Barrier, head of investment fund Cathay Innovation.

Silicon Valley’s mindset “is more about seizing the opportunity” than worrying about any risks, he said.

Geopolitical tensions are helping drive the frenzy, primarily to build massive data centers housing tens of thousands of expensive chips that require phenomenal electrical power and large-scale, energy-hungry cooling.

From 2013 to 2024, private AI investment reached $470 billion in the United States—nearly a quarter in the last year alone—followed by superpower rival China’s $119 billion, according to a Stanford University report.

Just a handful of giants are on the receiving end, with OpenAI first in line.

In March 2025, ChatGPT’s parent company raised approximately $40 billion, bringing its estimated valuation to around $300 billion, according to analysts.

‘Circular funding’

OpenAI is now the world’s most valuable company, surpassing SpaceX, worth $500 billion in a deal for employees to sell a limited number of shares.

The company led by CEO Sam Altman sits at the center of an AI investment bonanza: It oversees the Stargate project, which has secured $400 billion of the $500 billion planned by 2029 for Texas data centers spanning an area the size of Manhattan.

The White House-backed consortium includes Softbank, Oracle, Microsoft and Nvidia.

Nvidia, which completed over 50 venture capital deals in 2024 according to PitchBook data, is often chided for practicing “circular funding”—investing in startups that use the funds to buy its chips.

Some analysts criticize this as bubble-fueling behavior.

The OpenAI deal “will likely fuel those concerns,” said Stacy Rasgon, a Bernstein Research analyst.

In the first six months of 2025, OpenAI pulled in around $4.3 billion in revenue, specialist outlet The Information reported this week.

Therefore, unlike Meta or Google with substantial cash reserves, OpenAI and competitors like Anthropic or Mistral must be creative in their search for funds to bridge the gap.

For AI believers, an explosion in revenue is only a matter of time for a company whose ChatGPT assistant serves 700 million people—reaching nearly 9% of humanity less than three years after launch.

‘Up in smoke’

Nothing is certain, however.

Feeding AI’s computing appetite will cost up to $500 billion annually in global data center investments through 2030, requiring $2 trillion in annual revenues to make the expenses viable, according to consulting firm Bain & Company.

Even under optimistic assumptions, Bain estimates the AI industry faces an $800 billion deficit.

OpenAI itself plans to spend over $100 billion by 2029—meaning turning a profit is still a ways off.

On the energy front, AI’s global computing footprint could reach 200 gigawatts by 2030—the annual equivalent of Brazil’s electric consumption—half of that in the United States.

Despite the daunting figures, many analysts remain optimistic.

“Even with concerns about a possible ‘AI bubble’… we estimate the sector is in its 1996” moment during the internet boom, “absolutely not its 1999” before that bubble burst, said Dan Ives, a Wedbush Securities analyst.

Long-term, “many dollars will go up in smoke, and there will be many losers, like during the internet bubble, but the internet remained,” said the Silicon Valley investor.

© 2025 AFP

Residential heating, ventilation, and air conditioning (HVAC) systems constitute a significant proportion of energy usage in buildings, necessitating energy management optimization. In this context, occupancy-aware HVAC control is a promising option with 20–50% energy savings in homes. However, occupancy sensing technology suffers from long payback times, privacy issues, and poor comfort. Moreover, there is an increasing need for further advanced technologies that help regulate indoor air quality in addition to energy control.

To meet these expectations, scientists have recently turned to intelligent control methods such as quantum reinforcement learning (QRL)-based on quantum computing principles. Such approaches can notably accelerate the machine learning process as well as handle the complexity of real-world building dynamics.

In a new study, a group of researchers from the Republic of Korea, led by Sangkeum Lee, Assistant Professor of Computer Engineering at Hanbat National University, have presented the first demonstration of continuous-variable, quantum-enhanced reinforcement learning for residential HVAC and home power management. Their findings are published in the journal Energy and AI.

Dr. Lee says, “Unlike conventional reinforcement learning techniques, QRL leverages quantum computing principles to efficiently handle high dimensional state and action spaces, enabling more precise HVAC control in multi-zone residential buildings. Our framework integrates real-time occupancy detection using deep learning with operational data, including power consumption patterns, air conditioner control data, and external temperature variations.”

Furthermore, the proposed technology integrates features such as multi-zone cooling—to control the temperature of individual zones in a building—and clustering—to group similar data points and adjust cooling. In this way, a single controller jointly optimizes comfort, energy cost, and carbon signals in real time.

The researchers performed simulations based on real world data from 26 residential households over a three-month period. They found that QRL HVAC control significantly outperforms deep deterministic policy gradient method as well as proximal policy optimization algorithm, while maintaining thermal comfort, achieving 63% and 62.4% reductions in power consumption, respectively, and 64.4% and 62.5% decrease in electricity costs, respectively.

The present approach comes with many more benefits. It is retrofit-friendly and works with standard temperature, occupancy, and CO₂ sensors and common HVAC equipment and thermostats. It is also robust to uncertainty, easily handling noisy forecasts on weather and occupancy and device constraints. In addition, it has a generalizable framework that can be extended from apartments to small buildings and microgrids.

Dr. Lee says, “It can be utilized in smart thermostats and autonomous home energy management systems that co-optimize comfort, bills, and emissions without manual tuning and rooftop photovoltaics and home battery scheduling. Our framework is also useful for utility demand-response and time-of-use programs with automated control.”

QRL-based HVAC control can notably be applied at community or campus scale through grid-interactive efficient buildings and virtual power plants (VPPs). Herein, millions of homes can coordinate as VPPs to stabilize renewables-heavy grids. It can also ensure personalized indoor environmental quality within carbon budgets and integrate advanced intelligent control options.

As hardware matures in the coming years, quantum-accelerated policy research could facilitate faster training for complex multi-energy systems such as HVAC, electric vehicles, and energy storage systems. In the long term, this work is expected to guide the path toward standardized secure controllers that can be certified and deployed at a wide scale.

Provided by
Hanbat National University Industry–University Cooperation Foundation

Concrete already builds our world, and now it’s one step closer to powering it, too. Made by combining cement, water, ultra-fine carbon black (with nanoscale particles), and electrolytes, electron-conducting carbon concrete (ec³, pronounced “e-c-cubed”) creates a conductive “nanonetwork” inside concrete that could enable everyday structures like walls, sidewalks, and bridges to store and release electrical energy. In other words, the concrete around us could one day double as giant “batteries.”

As MIT researchers report in a new PNAS paper, optimized electrolytes and manufacturing processes have increased the energy storage capacity of the latest ec³ supercapacitors by an order of magnitude.

In 2023, storing enough energy to meet the daily needs of the average home would have required about 45 cubic meters of ec³, roughly the amount of concrete used in a typical basement. Now, with the improved electrolyte, that same task can be achieved with about 5 cubic meters, the volume of a typical basement wall.

“A key to the sustainability of concrete is the development of ‘multifunctional concrete,’ which integrates functionalities like this energy storage, self-healing, and carbon sequestration. Concrete is already the world’s most-used construction material, so why not take advantage of that scale to create other benefits?” asks Admir Masic, lead author of the new study, MIT Electron-Conducting Carbon-Cement-Based Materials Hub (EC³ Hub) co-director, and associate professor of civil and environmental engineering (CEE) at MIT.

The improved energy density was made possible by a deeper understanding of how the nanocarbon black network inside ec³ functions and interacts with electrolytes.

Using focused ion beams for the sequential removal of thin layers of the ec³ material, followed by high-resolution imaging of each slice with a scanning electron microscope (a technique called FIB-SEM tomography), the team across the EC³ Hub and MIT Concrete Sustainability Hub was able to reconstruct the conductive nanonetwork at the highest resolution yet. This approach allowed the team to discover that the network is essentially a fractal-like “web” that surrounds ec³ pores, which is what allows the electrolyte to infiltrate and for current to flow through the system.

“Understanding how these materials ‘assemble’ themselves at the nanoscale is key to achieving these new functionalities,” adds Masic.

Equipped with their new understanding of the nanonetwork, the team experimented with different electrolytes and their concentrations to see how they impacted energy storage density.

As Damian Stefaniuk, first author and EC³ Hub research scientist, highlights, “we found that there is a wide range of electrolytes that could be viable candidates for ec³. This even includes seawater, which could make this a good material for use in coastal and marine applications, perhaps as support structures for offshore wind farms.”

At the same time, the team streamlined the way they added electrolytes to the mix. Rather than curing ec³ electrodes and then soaking them in electrolyte, they added the electrolyte directly into the mixing water. Since electrolyte penetration was no longer a limitation, the team could cast thicker electrodes that stored more energy.

The team achieved the greatest performance when they switched to organic electrolytes, especially those that combined quaternary ammonium salts—found in everyday products like disinfectants—with acetonitrile, a clear, conductive liquid often used in industry. A cubic meter of this version of ec³—about the size of a refrigerator—can store over 2 kilowatt-hours of energy. That’s about enough to power an actual refrigerator for a day.

While batteries maintain a higher energy density, ec³ can in principle be incorporated directly into a wide range of architectural elements—from slabs and walls to domes and vaults—and last as long as the structure itself.

“The Ancient Romans made great advances in concrete construction. Massive structures like the Pantheon stand to this day without reinforcement. If we keep up their spirit of combining material science with architectural vision, we could be at the brink of a new architectural revolution with multifunctional concretes like ec³,” proposes Masic.

Taking inspiration from Roman architecture, the team built a miniature ec³ arch to show how structural form and energy storage can work together. Operating at 9 volts, the arch supported its own weight and additional load while powering an LED light.

However, something unique happened when the load on the arch increased: the light flickered. This is likely due to the way stress impacts electrical contacts or the distribution of charges.

“There may be a kind of self-monitoring capacity here. If we think of an ec³ arch at an architectural scale, its output may fluctuate when it’s impacted by a stressor like high winds. We may be able to use this as a signal of when and to what extent a structure is stressed, or monitor its overall health in real time,” envisions Masic.

The latest developments in ec³ technology bring it a step closer to real-world scalability. It’s already been used to heat sidewalk slabs in Sapporo, Japan, due to its thermally conductive properties, representing a potential alternative to salting.

“With these higher energy densities and demonstrated value across a broader application space, we now have a powerful and flexible tool that can help us address a wide range of persistent energy challenges,” explains Stefaniuk.

“One of our biggest motivations was to help enable the renewable energy transition. Solar power, for example, has come a long way in terms of efficiency. However, it can only generate power when there’s enough sunlight. So, the question becomes: How do you meet your energy needs at night, or on cloudy days?”

Franz-Josef Ulm, EC³ Hub co-director and CEE professor, continues, “The answer is that you need a way to store and release energy. This has usually meant a battery, which often relies on scarce or harmful materials. We believe that ec³ is a viable substitute, letting our buildings and infrastructure meet our energy storage needs.”

The team is working toward applications like parking spaces and roads that could charge electric vehicles, as well as homes that can operate fully off the grid.

“What excites us most is that we’ve taken a material as ancient as concrete and shown that it can do something entirely new,” says James Weaver, a co-author on the paper who is an associate professor of design technology and materials science and engineering at Cornell University, as well as a former EC³ Hub researcher.

“By combining modern nanoscience with an ancient building block of civilization, we’re opening a door to infrastructure that doesn’t just support our lives, it powers them.”

This story is republished courtesy of MIT News (web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and teaching.