Stay Ahead, Stay ONMINE

Do European M&Ms Actually Taste Better than American M&Ms?

(Oh, I am the only one who’s been asking this question…? Hm. Well, if you have a minute, please enjoy this exploratory Data Analysis — featuring experimental design, statistics, and interactive visualization — applied a bit too earnestly to resolve an international debate.) 1. Introduction 1.1 Background and motivation Chocolate is enjoyed around the world. […]

(Oh, I am the only one who’s been asking this question…? Hm. Well, if you have a minute, please enjoy this exploratory Data Analysis — featuring experimental design, statistics, and interactive visualization — applied a bit too earnestly to resolve an international debate.)

1. Introduction

1.1 Background and motivation

Chocolate is enjoyed around the world. From ancient practices harvesting organic cacao in the Amazon basin, to chocolatiers sculpting edible art in the mountains of Switzerland, and enormous factories in Hershey, Pennsylvania churning out 70 million kisses per day, the nuanced forms and flavors of chocolate have been integrated into many cultures and their customs. While quality can greatly vary across chocolate products, a well-known, shelf-stable, easily shareable form of chocolate are M&Ms. Readily found by convenience store check-out counters and in hotel vending machines, the brightly colored pellets are a popular treat whose packaging is re-branded to fit nearly any commercializable American holiday.

While living in Denmark in 2022, I heard a concerning claim: M&Ms manufactured in Europe taste different, and arguably “better,” than M&Ms produced in the United States. While I recognized that fancy European chocolate is indeed quite tasty and often superior to American chocolate, it was unclear to me if the same claim should hold for M&Ms. I learned that many Europeans perceive an “unpleasant” or “tangy” taste in American chocolate, which is largely attributed to butyric acid, a compound resulting from differences in how milk is treated before incorporation into milk chocolate.

But honestly, how much of a difference could this make for M&Ms? M&Ms!? I imagined M&Ms would retain a relatively processed/mass-produced/cheap candy flavor wherever they were manufactured. As the lone American visiting a diverse lab of international scientists pursuing cutting-edge research in biosustainability, I was inspired to break out my data science toolbox and investigate this M&M flavor phenomenon.

1.2 Previous work

To quote a European woman, who shall remain anonymous, after she tasted an American M&M while traveling in New York:

“They taste so gross. Like vomit. I don’t understand how people can eat this. I threw the rest of the bag away.”

Vomit? Really? In my experience, children raised in the United States had no qualms about eating M&Ms. Growing up, I was accustomed to bowls of M&Ms strategically placed in high traffic areas around my house to provide readily available sugar. Clearly American M&Ms are edible. But are they significantly different and/or inferior to their European equivalent?

In response to the anonymous European woman’s scathing report, myself and two other Americans visiting Denmark sampled M&Ms purchased locally in the Lyngby Storcenter Føtex. We hoped to experience the incredible improvement in M&M flavor that was apparently hidden from us throughout our youths. But curiously, we detected no obvious flavor improvements.

Unfortunately, neither preliminary study was able to conduct a side-by-side taste test with proper controls and randomized M&M sampling. Thus, we turn to science.

1.3 Study Goals

This study seeks to remedy the previous lack of thoroughness and investigate the following questions:

  1. Is there a global consensus that European M&Ms are in fact better than American M&Ms?
  2. Can Europeans actually detect a difference between M&Ms purchased in the US vs in Europe when they don’t know which one they are eating? Or is this a grand, coordinated lie amongst Europeans to make Americans feel embarrassed?
  3. Are Americans actually taste-blind to American vs European M&Ms? Or can they taste a difference but simply don’t describe this difference as “an improvement” in flavor?
  4. Can these alleged taste differences be perceived by citizens of other continents? If so, do they find one flavor obviously superior?

2. Methods

2.1 Experimental design and data collection

Participants were recruited by luring — er, inviting them to a social gathering (with the promise of free food) that was conveniently co-located with the testing site. Once a participant agreed to pause socializing and join the study, they were positioned at a testing station with a trained experimenter who guided them through the following steps:

  • Participants sat at a table and received two cups: 1 empty and 1 full of water. With one cup in each hand, the participant was asked to close their eyes, and keep them closed through the remainder of the experiment.
  • The experimenter randomly extracted one M&M with a spoon, delivered it to the participant’s empty cup, and the participant was asked to eat the M&M (eyes still closed).
  • After eating each M&M, the experimenter collected the taste response by asking the participant to report if they thought the M&M tasted: Especially Good, Especially Bad, or Normal.
  • Each participant received a total of 10 M&Ms (5 European, 5 American), one at a time, in a random sequence determined by random.org.
  • Between eating each M&M, the participant was asked to take a sip of water to help “cleanse their palate.”
  • Data collected: for each participant, the experimenter recorded the participant’s continent of origin (if this was ambiguous, the participant was asked to list the continent on which they have the strongest memories of eating candy as a child). For each of the 10 M&Ms delivered, the experimenter recorded the M&M origin (“Denmark” or “USA”), the M&M color, and the participant’s taste response. Experimenters were also encouraged to jot down any amusing phrases uttered by the participant during the test, recorded under notes (data available here).

2.2 Sourcing materials and recruiting participants

Two bags of M&Ms were purchased for this study. The American-sourced M&Ms (“USA M&M”) were acquired at the SFO airport and delivered by the author’s parents, who visited her in Denmark. The European-sourced M&Ms (“Denmark M&M”) were purchased at a local Føtex grocery store in Lyngby, a little north of Copenhagen.

Experiments were conducted at two main time points. The first 14 participants were tested in Lyngby, Denmark in August 2022. They mostly consisted of friends and housemates the author met at the Novo Nordisk Foundation Center for Biosustainability at the Technical University of Denmark (DTU) who came to a “going away party” into which the experimental procedure was inserted. A few additional friends and family who visited Denmark were also tested during their travels (e.g. on the train).

The remaining 37 participants were tested in Seattle, WA, USA in October 2022, primarily during a “TGIF happy hour” hosted by graduate students in the computer science PhD program at the University of Washington. This second batch mostly consisted of students and staff of the Paul. G. Allen School of Computer Science & Engineering (UW CSE) who responded to the weekly Friday summoning to the Allen Center atrium for free snacks and drinks.

Figure 1. Distribution of participants recruited to the study. In the first sampling event in Lyngby, participants primarily hailed from North America and Europe, and a few additionally came from Asia, South America, or Australia. Our second sampling event in Seattle greatly increased participants, primarily from North America and Asia, and a few more from Europe. Neither event recruited participants from Africa. Figure made with Altair.

While this study set out to analyze global trends, unfortunately data was only collected from 51 participants the author was able to lure to the study sites and is not well-balanced nor representative of the 6 inhabited continents of Earth (Figure 1). We hope to improve our recruitment tactics in future work. For now, our analytical power with this dataset is limited to response trends for individuals from North America, Europe, and Asia, highly biased by subcommunities the author happened to engage with in late 2022.

2.3 Risks

While we did not acquire formal approval for experimentation with human test subjects, there were minor risks associated with this experiment: participants were warned that they may be subjected to increased levels of sugar and possible “unpleasant flavors” as a result of participating in this study. No other risks were anticipated.

After the experiment however, we unfortunately observed several cases of deflated pride when a participant learned their taste response was skewed more positively towards the M&M type they were not expecting. This pride deflation seemed most severe among European participants who learned their own or their fiancé’s preference skewed towards USA M&Ms, though this was not quantitatively measured and cannot be confirmed beyond anecdotal evidence.

3. Results & Discussion

3.1 Overall response to “USA M&Ms” vs “Denmark M&Ms”

3.1.1 Categorical response analysis — entire dataset

In our first analysis, we count the total number of “Bad”, “Normal”, and “Good” taste responses and report the percentage of each response received by each M&M type. M&Ms from Denmark more frequently received “Good” responses than USA M&Ms but also more frequently received “Bad” responses. M&Ms from the USA were most frequently reported to taste “Normal” (Figure 2). This may result from the elevated number of participants hailing from North America, where the USA M&M is the default and thus more “Normal,” while the Denmark M&M was more often perceived as better or worse than the baseline.

Figure 2. Qualitative taste response distribution across the whole dataset. The percentage of taste responses for “Bad”, “Normal” or “Good” was calculated for each type of M&M. Figure made with Altair.

Now let’s break out some Statistics, such as a chi-squared (X2) test to compare our observed distributions of categorical taste responses. Using the scipy.stats chi2_contingency function, we built contingency tables of the observed counts of “Good,” “Normal,” and “Bad” responses to each M&M type. Using the X2 test to evaluate the null hypothesis that there is no difference between the two M&Ms, we found the p-value for the test statistic to be 0.0185, which is significant at the common p-value cut off of 0.05, but not at 0.01. So a solid “maybe,” depending on whether you’d like this result to be significant or not.

3.1.2 Quantitative response analysis — entire dataset.

The X2 test helps evaluate if there is a difference in categorical responses, but next, we want to determine a relative taste ranking between the two M&M types. To do this, we converted taste responses to a quantitative distribution and calculated a taste score. Briefly, “Bad” = 1, “Normal” = 2, “Good” = 3. For each participant, we averaged the taste scores across the 5 M&Ms they tasted of each type, maintaining separate taste scores for each M&M type.

Figure 3. Quantitative taste score distributions across the whole dataset. Kernel density estimation of the average taste score calculated for each participant for each M&M type. Figure made with Seaborn.

With the average taste score for each M&M type in hand, we turn to scipy.stats ttest_ind (“T-test”) to evaluate if the means of the USA and Denmark M&M taste scores are different (the null hypothesis being that the means are identical). If the means are significantly different, it would provide evidence that one M&M is perceived as significantly tastier than the other.

We found the average taste scores for USA M&Ms and Denmark M&Ms to be quite close (Figure 3), and not significantly different (T-test: = 0.721). Thus, across all participants, we do not observe a difference between the perceived taste of the two M&M types (or if you enjoy parsing triple negatives: “we cannot reject the null hypothesis that there is not a difference”).

But does this change if we separate participants by continent of origin?

3.2 Continent-specific responses to “USA M&Ms” vs “Denmark M&Ms”

We repeated the above X2 and T-test analyses after grouping participants by their continents of origin. The Australia and South America groups were combined as a minimal attempt to preserve data privacy. Due to the relatively small sample size of even the combined Australia/South America group (n=3), we will refrain from analyzing trends for this group but include the data in several figures for completeness and enjoyment of the participants who may eventually read this.

3.2.1 Categorical response analysis — by continent

In Figure 4, we display both the taste response counts (upper panel, note the interactive legend) and the response percentages (lower panel) for each continent group. Both North America and Asia follow a similar trend to the whole population dataset: participants report Denmark M&Ms as “Good” more frequently than USA M&Ms, but also report Denmark M&Ms as “Bad” more frequently. USA M&Ms were most frequently reported as “Normal” (Figure 4).

On the contrary, European participants report USA M&Ms as “Bad” nearly 50% of the time and “Good” only 18% of the time, which is the most negative and least positive response pattern, respectively (when excluding the under-sampled Australia/South America group).

Figure 4. Qualitative taste response distribution by continent. Upper panel: counts of taste responses — click the legend to interactively filter! Lower panel: percentage of taste responses for each type of M&M. Figure made with Altair.

This appeared striking in bar chart form, however only North America had a significant X2 p-value (p = 0.0058) when evaluating each continent’s difference in taste response profile between the two M&M types. The European p-value is perhaps “approaching significance” in some circles, but we’re about to accumulate several more hypothesis tests and should be mindful of multiple hypothesis testing (Table 1). A false positive result here would be devastating.

When comparing the taste response profiles between two continents for the same M&M type, there are a couple interesting notes. First, we observed no major taste discrepancies between all pairs of continents when evaluating Denmark M&Ms — the world seems generally consistent in their range of feelings about M&Ms sourced from Europe (right column X2 p-values, Table 2). To visualize this comparison more easily, we reorganize the bars in Figure 4 to group them by M&M type (Figure 5).

Figure 5. Qualitative taste response distribution by M&M type, reported as percentages. (Same data as Figure 4 but re-arranged). Figure made with Altair.

However, when comparing continents to each other in response to USA M&Ms, we see larger discrepancies. We found one pairing to be significantly different: European and North American participants evaluated USA M&Ms very differently (p = 0.000007) (Table 2). It seems very unlikely that this observed difference is by random chance (left column, Table 2).

3.2.2 Quantitative response analysis — by continent

We again convert the categorical profiles to quantitative distributions to assess continents’ relative preference of M&M types. For North America, we see that the taste score means of the two M&M types are actually quite similar, but there is a higher density around “Normal” scores for USA M&Ms (Figure 6A). The European distributions maintain a bit more of a separation in their means (though not quite significantly so), with USA M&Ms scoring lower (Figure 6B). The taste score distributions of Asian participants is most similar (Figure 6C).

Reorienting to compare the quantitative means between continents’ taste scores for the same M&M type, only the comparison between North American and European participants on USA M&Ms is significantly different based on a T-test (p = 0.001) (Figure 6D), though now we really are in danger of multiple hypothesis testing! Be cautious if you are taking this analysis at all seriously.

Figure 6. Quantitative taste score distributions by continent. Kernel density estimation of the average taste score calculated for each each continent for each M&M type. A. Comparison of North America responses to each M&M. B. Comparison of Europe responses to each M&M. C. Comparison of Asia responses to each M&M. D. Comparison of continents for USA M&Ms. E. Comparison of continents for Denmark M&Ms. Figure made with Seaborn.

At this point, I feel myself considering that maybe Europeans are not just making this up. I’m not saying it’s as dramatic as some of them claim, but perhaps a difference does indeed exist… To some degree, North American participants also perceive a difference, but the evaluation of Europe-sourced M&Ms is not consistently positive or negative.

3.3 M&M taste alignment chart

In our analyses thus far, we did not account for the baseline differences in M&M appreciation between participants. For example, say Person 1 scored all Denmark M&Ms as “Good” and all USA M&Ms as “Normal”, while Person 2 scored all Denmark M&Ms as “Normal” and all USA M&Ms as “Bad.” They would have the same relative preference for Denmark M&Ms over USA M&Ms, but Person 2 perhaps just does not enjoy M&Ms as much as Person 1, and the relative preference signal is muddled by averaging the raw scores.

Inspired by the Lawful/Chaotic x Good/Evil alignment chart used in tabletop role playing games like Dungeons & Dragons©™, in Figure 7, we establish an M&M alignment chart to help determine the distribution of participants across M&M enjoyment classes.

Figure 7. M&M enjoyment alignment chart. The x-axis represents a participant’s average taste score for USA M&Ms; the y-axis is a participant’s average taste score for Denmark M&Ms. Figure made with Altair.

Notably, the upper right quadrant where both M&M types are perceived as “Good” to “Normal” is mostly occupied by North American participants and a few Asian participants. All European participants land in the left half of the figure where USA M&Ms are “Normal” to “Bad”, but Europeans are somewhat split between the upper and lower halves, where perceptions of Denmark M&Ms range from “Good” to “Bad.”

An interactive version of Figure 7 is provided below for the reader to explore the counts of various M&M alignment regions.

Figure 7 (interactive): click and brush your mouse over the scatter plot to see the counts of continents in different M&M enjoyment regions. Figure made with Altair.

3.4 Participant taste response ratio

Next, to factor out baseline M&M enjoyment and focus on participants’ relative preference between the two M&M types, we took the log ratio of each person’s USA M&M taste score average divided by their Denmark M&M taste score average.

Equation 1: Equation to calculate each participant’s overall M&M preference ratio.

As such, positive scores indicate a preference towards USA M&Ms while negative scores indicate a preference towards Denmark M&Ms.

On average, European participants had the strongest preference towards Denmark M&Ms, with Asians also exhibiting a slight preference towards Denmark M&Ms (Figure 8). To the two Europeans who exhibited deflated pride upon learning their slight preference towards USA M&Ms, fear not: you did not think USA M&Ms were “Good,” but simply ranked them as less bad than Denmark M&Ms (see participant_id 4 and 17 in the interactive version of Figure 7). If you assert that M&Ms are a bad American invention not worth replicating and return to consuming artisanal European chocolate, your honor can likely be restored.

Figure 8. Distribution of participant M&M preference ratios by continent. Preference ratios are calculated as in Equation 1. Positive numbers indicate a relative preference for USA M&Ms, while negative indicate a relative preference for Denmark M&Ms. Figure made with Seaborn.

North American participants are pretty split in their preference ratios: some fall quite neutrally around 0, others strongly prefer the familiar USA M&M, while a handful moderately prefer Denmark M&Ms. Anecdotally, North Americans who learned their preference skewed towards European M&Ms displayed signals of inflated pride, as if their results signaled posh refinement.

Overall, a T-test comparing the distributions of M&M preference ratios shows a possibly significant difference in the means between European and North American participants (p = 0.049), but come on, this is like the 20th p-value I’ve reported — this one is probably too close to call.

3.5 Taste inconsistency and “Perfect Classifiers”

For each participant, we assessed their taste score consistency by averaging the standard deviations of their responses to each M&M type, and plotting that against their preference ratio (Figure 9).

Figure 9. Participant taste consistency by preference ratio. The x-axis is a participant’s relative M&M preference ratio. The y-axis is the average of the standard deviation of their USA M&M scores and the standard deviation of their Denmark M&M scores. A value of 0 on the y-axis indicates perfect consistency in responses, while higher values indicate more inconsistent responses. Figure made with Altair.

Most participants were somewhat inconsistent in their ratings, ranking the same M&M type differently across the 5 samples. This would be expected if the taste difference between European-sourced and American-sourced M&Ms is not actually all that perceptible. Most inconsistent were participants who gave the same M&M type “Good”, “Normal”, and “Bad” responses (e.g., points high on the y-axis, with wider standard deviations of taste scores), indicating lower taste perception abilities.

Intriguingly, four participants — one from each continent group — were perfectly consistent: they reported the same taste response for each of the 5 M&Ms from each M&M type, resulting in an average standard deviation of 0.0 (bottom of Figure 9). Excluding the one of the four who simply rated all 10 M&Ms as “Normal”, the other three appeared to be “Perfect Classifiers” — either rating all M&Ms of one type “Good” and the other “Normal”, or rating all M&Ms of one type “Normal” and the other “Bad.” Perhaps these folks are “super tasters.”

3.6 M&M color

Another possible explanation for the inconsistency in individual taste responses is that there exists a perceptible taste difference based on the M&M color. Visually, the USA M&Ms were noticeably more smooth and vibrant than the Denmark M&Ms, which were somewhat more “splotchy” in appearance (Figure 10A). M&M color was recorded during the experiment, and although balanced sampling was not formally built into the experimental design, colors seemed to be sampled roughly evenly, with the exception of Blue USA M&Ms, which were oversampled (Figure 10B).

Figure 10. M&M colors. A. Photo of each M&M color of each type. It’s perhaps a bit hard to perceive on screen in my unprofessionally lit photo, but with the naked eye, USA M&Ms seemed to be brighter and more uniformly colored while Denmark M&Ms have a duller and more mottled color. Is it just me, or can you already hear the Europeans saying “They are brighter because of all those extra chemicals you put in your food that we ban here!” B. Distribution of M&Ms of each color sampled over the course of the experiment. The Blue USA M&Ms were not intentionally oversampled — they must be especially bright/tempting to experimenters. Figure made with Altair.

We briefly visualized possible differences in taste responses based on color (Figure 11), however we do not believe there are enough data to support firm conclusions. After all, on average each participant would likely only taste 5 of the 6 M&M colors once, and 1 color not at all. We leave further M&M color investigations to future work.

Figure 11. Taste response profiles for M&Ms of each color and type. Profiles are reported as percentages of “Bad”, “Normal”, and “Good” responses, though not all M&Ms were sampled exactly evenly. Figure made with Altair.

3.7 Colorful commentary

We assured each participant that there was no “right “answer” in this experiment and that all feelings are valid. While some participants took this to heart and occasionally spent over a minute deeply savoring each M&M and evaluating it as if they were a sommelier, many participants seemed to view the experiment as a competition (which occasionally led to deflated or inflated pride). Experimenters wrote down quotes and notes in conjunction with M&M responses, some of which were a bit “colorful.” We provide a hastily rendered word cloud for each M&M type for entertainment purposes (Figure 12) though we caution against reading too far into them without diligent sentiment analysis.

Figure 11. A simple word cloud generated from the notes column of each M&M type. Fair warning — these have not been properly analyzed for sentiment and some inappropriate language was recorded. Figure made with WordCloud.

4. Conclusion

Overall, there does not appear to be a “global consensus” that European M&Ms are better than American M&Ms. However, European participants tended to more strongly express negative reactions to USA M&Ms while North American participants seemed relatively split on whether they preferred M&Ms sourced from the USA vs from Europe. The preference trends of Asian participants often fell somewhere between the North Americans and Europeans.

Therefore, I’ll admit that it’s probable that Europeans are not engaged in a grand coordinated lie about M&Ms. The skew of most European participants towards Denmark M&Ms is compelling, especially since I was the experimenter who personally collected much of the taste response data. If they found a way to cheat, it was done well enough to exceed my own passive perception such that I didn’t notice. However, based on this study, it would appear that a strongly negative “vomit flavor” is not universally perceived and does not become apparent to non-Europeans when tasting both M&Ms types side by side.

We hope this study has been illuminating! We would look forward to extensions of this work with improved participant sampling, additional M&M types sourced from other continents, and deeper investigations into possible taste differences due to color.

Thank you to everyone who participated and ate M&Ms in the name of science!

Figures and analysis can be found on github: https://github.com/erinhwilson/mnm-taste-test

Article by Erin H. Wilson, Ph.D.[1,2,3] who decided the time between defending her dissertation and starting her next job would be best spent on this highly valuable analysis. Hopefully it is clear that this article is intended to be comedic— I do not actually harbor any negative feelings towards Europeans who don’t like American M&Ms, but enjoyed the chance to be sassy and poke fun at our lively debates with overly-enthusiastic data analysis.

Shout out to Matt, Galen, Ameya, and Gian-Marco for assisting in data collection!

[1] Former Ph.D. student in the Paul G. Allen School of Computer Science and Engineering at the University of Washington

[2] Former visiting Ph.D. student at the Novo Nordisk Foundation Center for Biosustainability at the Technical University of Denmark

[3] Future data scientist at LanzaTech

Shape
Shape
Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Shape

Fortinet speeds threat detection with improved FortiAnalyzer

The package also now integrates with FortiAI, the vendor’s genAI assistant, to better support analytics and telemetry to help security teams speed threat investigation and response, the vendor stated. “FortiAI identifies the threats that need analysis from the data collected by FortiAnalyzer, primarily collected from FortiGates. By automating the collection,

Read More »

Aryaka adds AI-powered observability to SASE platform

Nadkarni explained that Aryaka runs unsupervised machine learning models on the data to identify anomalies and outliers in the data. For example, the models may detect a sudden spike in traffic to a domain that has not been seen before. This unsupervised analysis helps surface potential issues or areas of

Read More »

Exxon Plans to Ramp Up Guyana Gas Output, Sees Potential for Exports

Exxon Mobil Corp. outlined plans to increase natural gas production from oil-focused Guyana and is considering options to export the fuel to global markets, country manager Alistair Routledge said Wednesday.  Exxon’s developments off the coast of Guyana have turned the South American nation into the world’s fastest-growing major oil producer, but the company has faced pressure from the government to do more with the natural gas that’s found alongside its crude.  Routledge today presented a concept called “Wales Gas Vision” that would send gas from Exxon’s Longtail development to the shore for use in producing fertilizer and alumina as well as for powering data centers. Exxon plans to make a final investment decision on Longtail next year with a view to bringing it online by 2029. Gas production from the project could reach 1.2 billion cubic feet per day. Building a pipeline to nearby Trinidad, which has liquefied natural gas export capacity, would be “cost prohibitive,” but Exxon is exploring other ways to sell Guyana’s gas internationally, Routledge said at the Guyana Energy Conference in Georgetown.  “There is still a possibility of using liquefied natural gas technology connectors to global markets,” he said. “That is a further option that is on the table and being investigated.”  The Wales Gas Vision proposal is separate from Guyana’s gas-to-energy project, for which Exxon has already completed an underwater pipeline to supply fuel for power generation. Routledge cautioned the ideas depend on volume uptake, price and timing.  WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed. MORE FROM THIS AUTHOR Bloomberg

Read More »

DeepSeek called a net positive for data centers despite overcapacity worries

The global race to develop sophisticated, versatile AI models is driving a surge in development of the physical infrastructure to support them. Microsoft, Amazon, Meta and Google parent Alphabet — four of the AI industry’s biggest players — plan to invest a combined $325 billion in capital expenditures in 2025, much of it for data centers and associated hardware.  The technology giants’ spending plans mark a 46% increase from their combined 2024 capital investments, according to Yahoo! Finance, and track a doubling in proposed data centers’ average size from 150 gigawatts to 300 gigawatts between January 2023 and October 2024. In December, Meta said it would build a $10 billion, 4 million-square-foot data center in Louisiana that could consume the power output equivalent of two large nuclear reactors. The planned spending announcements came after the January release of the highly efficient, open-source AI platform DeepSeek, which led some experts and investors to question just how much infrastructure — from high-performance chips to new power plants and electrical equipment — the AI boom actually requires. But experts interviewed by Facilities Dive see AI efficiency gains as a net positive for data center developers, operators and customers in the long run, despite shorter-term uncertainty that could temporarily create overcapacity in some markets. “Every technology has gotten more efficient” DeepSeek’s late January commercial launch took many Americans by surprise, but the rise of a more efficient and capable AI model follows a well-worn pattern of technology development, said K.R. Sridhar, founder, chairman and CEO of power solutions provider Bloom Energy. “In 2010, it took about 1,500 watt-hours to facilitate the flow of one gigabyte of information,” Sridhar said. “Last year it took about one tenth of that … [but] the total growth of traffic, and therefore the chips and energy, has been twice

Read More »

FERC complies with major portions of Trump order on independent agencies: Christie

A White House executive order setting requirements for the Federal Energy Regulatory Commission and other independent agencies largely covers actions FERC already does, according to FERC Chairman Mark Christie. “A lot of this in the EO is basically putting in one place past practices that have been going on for years,” Christie said Thursday during a media briefing.  FERC, for example, submits its budget and strategic plans to the Office of Management and Budget for review, as required by the executive order, Christie said. The agency sends major rulemakings to the OMB’s Office of Information and Regulatory Affairs for review, FERC chairmen consult with White House officials and the commission has complied with executive orders for decades, according to Christie. Even so, Christie said he needed more information from the White House about certain aspects of the executive order. “Does this contemplate a role in proceedings outside of our ex parte rules?” Christie asked. Also, FERC works on more than 1,000 cases a year and it is unclear if any of them would undergo some sort of review because of the executive order, according to Christie. OMB is likely concerned about large, sweeping regulations issued by agencies, not routine cases that are initiated by third parties, Christie said. “We’re going to ask the appropriate places for more detail and see how this plays out,” Christie said. FERC’s activity is largely governed by the Federal Power Act, the Natural Gas Act, the Administrative Procedure Act, the National Environmental Policy Act and the Sunshine Act, Christie said. “At the end of the day, we follow the law,” he said. The executive order includes a clause stating that nothing in the document affects existing law or the authority of an agency under existing law, Christie noted. FERC was established under the Department of

Read More »

FERC launches colocation review, plus 6 other open meeting takeaways

The Federal Energy Regulatory Commission on Thursday launched a review of issues related to colocating large loads, such as data centers, at power plants in the PJM Interconnection. “There are tremendous implications for reliability and consumers, and we have to be fair,” FERC Chairman Mark Christie said during the agency’s monthly meeting. At the same time, utilities have an obligation to serve new customers, he said. FERC’s effort to clarify rules for colocated load comes amid a surge in data center development across the United States, partly driven by the growth of artificial intelligence. Colocating data centers at existing power plants provides a potential pathway to bringing data centers online quickly and at lower cost compared with “front of meter” options. However, new rules governing colocated resources in PJM likely won’t be approved by FERC until early next year, creating a period of uncertainty for independent power producers such as Talen Energy and Vistra by delaying deal announcements with data center operators, Capstone analysts said Thursday. FERC aims to approve new colocation rules for PJM this year, said Ben Williams, FERC director of the office of external affairs. The agency expects it will vote on a PJM proposal within three months of one being filed at the commission, he noted. The lack of near-term clarity on colocation is another negative development for IPPs and raises the potential that data center developers will prefer to work with regulated utilities instead of in competitive markets, Jeffries analysts said. Issues surrounding siting data centers at large power plants in PJM came to a head late last year. The agency in November rejected an amended interconnection service agreement that would have facilitated expanded power sales to a colocated Amazon data center from the Susquehanna nuclear power plant in Pennsylvania that is majority owned by

Read More »

Torus, Rocky Mountain Power sign MOU for 70-MW C&I demand response capability

Dive Brief: A memorandum of understanding between PacifiCorp subsidiary Rocky Mountain Power and Utah-based distributed energy solutions provider Torus could deliver 70 MW of commercial and industrial demand response capability to RMP’s Wattsmart Battery program within 12 to 18 months, Torus said on Feb. 7. Torus has already filled about one-third of the project’s expected capacity and is “in active permitting and approvals for the deployment of those assets today,” Torus founder and CEO Nate Walkingshaw said in an interview. The partnership “is a great example of Utah’s leadership in innovative energy solutions” as the state looks to double its power production capacity over the next 10 years while remaining a net energy exporter, Utah Gov. Spencer Cox, R, said last month. Dive Insight: The Wattsmart Battery program is “among the most advanced [virtual power plants] in the U.S. due to its degree of integration into the utility’s overall system operations and the wide array of use cases (grid services) of the battery aggregation,” the U.S. Department of Energy said last month in its updated Pathways to Commercial Liftoff: Virtual Power Plants report. The program is already in heavy use, with more than 130 response events in 2024, primarily to manage late afternoon and evening loads, Walkingshaw said. Other energy management providers participate in its residential component, but Torus is the only vendor working with C&I customers, he added. Under the MOU, Torus will deploy its hybrid flywheel battery energy storage systems behind the meter at commercial and industrial facilities across the Wattsmart program territory, which recently expanded from its Utah home base into Wyoming and parts of Idaho, Walkingshaw said. The company is focused on Utah but available to RMP customers in Wyoming and Idaho, a Torus spokesperson said. Customers can immediately use the storage systems to reduce utility

Read More »

U.S. Department of Energy Recognizes National Black History Month, 2025

WASHINGTON— U.S. Secretary of Energy Chris Wright released the following statement in recognition of National Black History Month – February 2025:  “Today, I am honored to join President Trump in recognizing February 2025 as National Black History Month. Throughout our history, Black Americans have strengthened our nation’s position as a global leader in energy production, science, and technology. Lewis Latimer’s contributions to electric lighting, Dr. George Washington Carver’s advancements in biofuels, and Dr. William Knox and Dr. Blanche Lawrence’s critical work on the Manhattan Project are just a few examples of the innovation and dedication to excellence that embody the American spirit—one of hard work, determination, and a relentless drive to achieve greatness.  “The Department of Energy remains committed to advancing bold, America-first energy policies that empower our workforce, fuel economic growth, and solidify our nation’s leadership on the world stage. This Black History Month, join us as we celebrate the patriots and pioneers who have contributed to America’s energy success and look forward to a future where we continue to lead the world in energy production, innovation, and strength.” ###

Read More »

Do data centers threaten the water supply?

In a new report, the Royal Academy of Engineering called upon the government to ensure tech companies accurately report how much energy and water their data centers are using and reducing the use of drinking water for cooling. Without such action, warns one of the report’s authors, Professor Tom Rodden, “we face a real risk that our development, deployment and use of AI could do irreparable damage to the environment.” The situation is a little different for the US as the country has large bodies of water offering a  water supply that the UK just does not have. It’s not an accident that there are many data centers around the Chicago area: they’ve also got the Great Lakes to draw upon. Likewise, the Columbia and Klamath Rivers have become magnets for data centers for both water supply and hydroelectric power. Other than the Thames River, the UK doesn’t have these massive bodies of water. Still, the problem is not unique to the UK, says Alan Howard, senior analyst with Omdia. He notes that Microsoft took heat last year because it was draining the water supply of a small Arizona town of Goodyear with a new AI-oriented data center.  The city of Chandler, Arizona passed an ordinance in 2015 that restricted new water-intensive businesses from setting up shop which slowed data center development.   “I believe some data center operators just bowed out,” said Howard.

Read More »

Ireland says there will be no computation without generation

Stanish said that, in 2023, she wrote a paper that predicted “by 2028, more than 70% of multinational enterprises will alter their data center strategies due to limited energy supplies and data center moratoriums, up from only about 5% in 2023. It has been interesting watching this trend evolve as expected, with Ireland being a major force in this conversation since the boycotts against data center growth started a few years ago.” Fair, equitable, and stable electricity allocation, she said, “means that the availability of electricity for digital services is not guaranteed in the future, and I expect these policies, data center moratoriums, and regional rejections will only continue and expand moving forward.” Stanish pointed out that this trend is not just occurring in Ireland. “Many studies show that, globally, enterprises’ digital technologies are consuming energy at a faster rate than overall growth in energy supply (though, to be clear, these studies mostly assume a static position on energy efficiency of current technologies, and don’t take into account potential for nuclear or hydrogen to assuage some of these supply issues).” If taken at face value, she said, this means that a lack of resources could cause widespread electricity shortages in data centers over the next several years. To mitigate this, Stanish said, “so far, data center moratoriums and related constraints (including reduced tax incentives) have been enacted in the US (specifically Virginia and Georgia), Denmark, Singapore, and other countries, in response to concerns about the excessive energy consumption of IT, particularly regarding compute-intense AI workloads and concerns regarding an IT energy monopoly in certain regions. As a result, governments (federal, state, county, etc.) are working to ensure that consumption does not outpace capacity.” Changes needed In its report, the CRU stated, “a safe and secure supply of energy is essential

Read More »

Perspective: Can We Solve the AI Data Center Power Crisis with Microgrids?

President Trump announced a$500 billion private sector investment in the nation’s Artificial Intelligence (AI) infrastructure last month. The investment will come from The Stargate Project, a joint venture between OpenAI, SoftBank, Oracle and MGX, which intends to build 20 new AI data centers in the U.S in the next four to five years. The Stargate Project committed$100 billion for immediate deployment and construction has already begun on its first data center in Texas. At approximately a half a million square feet each, the partners say these new facilities will cement America’s leadership in AI, create jobs and stimulate economic growth. Stargate is not the only game in town, either. Microsoft is expected to invest$80 billion in AI data center development in 2025, with Google, AWS and Meta also spending big. While all this investment in AI infrastructure is certainly exciting, experts say there’s one lingering question that’s yet to be answered and it’s a big one: How are we going to power all these AI data centers? This will be one of the many questions tackled duringMicrogrid Knowledge’s annual conference, which will be held in Texas April 15-17 at the Sheraton Dallas. “Powering Data Centers: Collaborative Microgrid Solutions for a Growing Market” will be one of the key sessions on April 16. Industry experts will gather to discuss how private entities, developers and utilities can work together to deploy microgrids and distributed energy technologies that address the data center industry’s power needs. The panel will share solutions, technologies and strategies that will favorably position data centers in the energy queue. In advance of this session, we sat down with two microgrid experts to learn more about the challenges facing the data center industry and how microgrids can address the sector’s growing energy needs. We spoke with Michael Stadler, co-founder and

Read More »

Data Center Tours: Iron Mountain VA-1, Manassas, Virginia

Iron Mountain Northern Virginia Overview Iron Mountain’s Northern Virginia data centers VA-1 through VA-7 are situated on a 142-acre highly secure campus in Prince William County, Virginia. Located at 11680 Hayden Road in Manassas, Iron Mountain VA-1 spans 167,958 sq. ft. and harbors 12.4 MW of total capacity to meet colocation needs. The 36 MW VA-2 facility stands nearby. The total campus features a mixture of single and multi-tenant facilities which together provide more than 2,000,000 SF of highly efficient green colocation space for enterprises, federal agencies, service providers and hyperscale clouds.  The company notes that its Manassas campus offers tax savings compared to Ashburn and exceptional levels of energy-efficiency as well as a diverse and accessible ecosystem of cloud, network and other service providers.  Iron Mountain’s Virginia campus has 9 total planned data centers, with 5 operational facilities to date and two more data centers coming soon. VA-2 recently became the first data center in the United States to achieve DCOS Maturity Level 3.    As we continued the tour, Kinra led the way toward the break room, an area where customers can grab coffee or catch up on work. Unlike the high-end aesthetic of some other colocation providers, Iron Mountain’s approach is more practical and focused on functionality. At the secure shipping and receiving area, Kinra explained the process for handling customer equipment. “This is where our customers ship their equipment into,” he said. “They submit a ticket, send their shipments in, and we’ll take it, put it aside for them, and let them know when it’s here. Sometimes they ask us to take it to their environment, which we’ll do for them via a smart hands ticket.” Power Infrastructure and Security Measures The VA-1 campus is supported by a single substation, providing the necessary power for its growing

Read More »

Land and Expand: DPO, Microsoft, JLL and BlackChamber, Prologis, Core Scientific, Overwatch Capital

Land and Expand is a periodic feature at Data Center Frontier highlighting the latest data center development news, including new sites, land acquisitions and campus expansions. Here are some of the new and notable developments from hyperscale and colocation data center developers and operators about which we’ve been reading lately. DPO to Develop $200 Million AI Data Center in Wisconsin Rapids; Strategic Partnership with Billerud’s CWPCo Unlocks Hydroelectric Power for High-Density AI Compute Digital Power Optimization (DPO) is moving forward with plans to build a $200 million high-performance computing (HPC) data center in Wisconsin Rapids, Wisconsin. The project, designed to support up to 20 megawatts (MW) of artificial intelligence (AI) computing, leverages an innovative partnership with Consolidated Water Power Company (CWPCo), a subsidiary of global packaging leader Billerud. DPO specializes in developing and operating data centers optimized for power-dense computing. By partnering with utilities and independent power producers, DPO colocates its facilities at energy generation sites, ensuring direct access to sustainable power for AI, HPC, and blockchain computing. The company is privately held. Leveraging Power Infrastructure for Speed-to-Energization CWPCo, a regulated utility subsidiary, has operated hydroelectric generation assets since 1894, reliably serving industrial and commercial customers in Wisconsin Rapids, Biron, and Stevens Point. Parent company Billerud is a global leader in high-performance packaging materials, committed to sustainability and innovation. The company operates nine production facilities across Sweden, the USA, and Finland, employing 5,800 people in over 19 countries.  The data center will be powered by CWPCo’s renewable hydroelectric assets, tapping into the utility’s existing 32 megawatts of generation capacity. The partnership grants DPO a long-term land lease—extending up to 50 years—alongside interconnection rights to an already-energized substation and a firm, reliable power supply. “AI infrastructure is evolving at an unprecedented pace, and access to power-dense sites is critical,” said Andrew

Read More »

Data center spending to top $1 trillion by 2029 as AI transforms infrastructure

His projections account for recent advances in AI and data center efficiency, he says. For example, the open-source AI model from Chinese company DeepSeek seems to have shown that an LLM can produce very high-quality results at a very low cost with some clever architectural changes to how the models work. These improvements are likely to be quickly replicated by other AI companies. “A lot of these companies are trying to push out more efficient models,” says Fung. “There’s a lot of effort to reduce costs and to make it more efficient.” In addition, hyperscalers are designing and building their own chips, optimized for their AI workloads. Just the accelerator market alone is projected to reach $392 billion by 2029, Dell’Oro predicts. By that time, custom accelerators will outpace commercially available accelerators such as GPUs. The deployment of dedicated AI servers also has an impact on networking, power and cooling. As a result, spending on data center physical infrastructure (DCPI) will also increase, though at a more moderate pace, growing by 14% annually to $61 billion in 2029.  “DCPI deployments are a prerequisite to support AI workloads,” says Tam Dell’Oro, founder of Dell’Oro Group, in the report. The research firm raised its outlook in this area due to the fact that actual 2024 results exceeded its expectations, and demand is spreading from tier one to tier two cloud service providers. In addition, governments and tier one telecom operators are getting involved in data center expansion, making it a long-term trend.

Read More »

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

Read More »

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

Read More »

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

Read More »

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

Read More »

Talking about Games

Game theory is a field of research that is quite prominent in Economics but rather unpopular in other scientific disciplines. However, the concepts used in

Read More »