Paul F. Clark, Penn State

Whole Foods workers at the Philadelphia flagship store in the city’s Art Museum area voted to unionize on Jan. 27, 2025. They are the first store in the Amazon-owned grocery chain to do so.

Paul Clark, a professor of labor and employment relations at Penn State University, talked to Kate Kilpatrick, The Conversation U.S. Philadelphia editor, about why this is happening – and why in Philly.

The Whole Foods workers in Philadelphia voted 130-100 in favor of unionizing. What do we know about their grievances?

From what I understand, these workers have felt that compensation, benefits and work conditions were not what they should be. Some are long-standing employees and say they struggle to afford their basic necessities.

Why did the union drive effort succeed now, and in Philly?

In the last five years, there has been a surge in union organizing. There are a number of reasons for this. First is the labor market. Low unemployment emboldens workers to take the risk of organizing a union. If workers feel their employer can’t replace them or that they can easily get a similar job, they are less fearful of angering the employer by trying to organize.

The second reason is that the Biden administration was a labor-friendly administration – perhaps the most in history. The U.S. president appoints a majority of members to the National Labor Relations Board, which interprets and enforces the labor law that governs organizing. Under Biden, the NLRB regularly issued decisions that provided greater protection to workers and held employers accountable when they violated workers’ rights. During Republican administrations, the board’s decisions are generally pro-business and provide less protection to workers. So workers had the wind at their back in that regard.

Also recent polling shows that 70% of Americans approve of unions, compared with less than half of Americans just 15 years ago. The generally favorable view of unions creates a more supportive environment for organizing.

And the last factor is that Generation Z, the youngest group of workers, clearly wants more out of their work and employment than previous generations. So we see a lot of young workers across the country organizing at Starbucks, Trader Joe’s, Apple and now at Whole Foods and other stores.

Why Philadelphia? Philadelphia is a relatively strong union town. The percentage of the workforce that is represented by a union is higher in Philadelphia than in most cities and areas of the country. So when workers express interest in organizing in Philadelphia they get a lot of support. Other unions might turn out members for their rallies, pressure the company to not oppose the organizing drive and offer other aid and assistance.

The starting wage at the Philadelphia Whole Foods store is US$16 an hour. Is that considered low when the city’s minimum wage is just $7.25 an hour?

The minimum wage in Philadelphia is $7.25 because that is the federal minimum wage. States can institute a higher minimum wage if they choose to, but Pennsylvania is one of the few Northeast states that hasn’t adopted a minimum wage higher than the federal minimum. The minimum wages in New Jersey, New York and Massachusetts, for example, are $15 or above.

But the minimum wage in Pennsylvania is almost irrelevant because of today’s labor market. Unemployment is low, and many employers have to offer significantly more than the minimum wage to get workers.

And the minimum wage is supposed to be a starting wage for workers with little experience or seniority. What workers want is a living wage. According to the MIT Living Wage Calculator, a single person in Philadelphia needs to earn around $24 per hour to cover the basic costs of living. And Whole Foods is a profitable business. It’s part of Amazon, one of the most profitable, largest companies in the world. I think workers at these companies believe that they play an important role in generating those profits because of the work they do. And they think they should get a fair share of those profits.

How might the Whole Foods workers expect the company to fight back?

When employees win an organizing election as the Whole Food workers have, they have won a battle but not the war. The purpose of forming a union is to improve wages and benefits and working conditions, and you do that by negotiating a contract with the company. That is the next step in the process. But the law only requires employers to bargain with employees – to meet at reasonable times and exchange proposals. It doesn’t compel them to agree to anything.

The typical strategy of companies that aggressively oppose their workers having a union is to drag their feet in bargaining and not sign a contract. That is technically illegal, but labor law in the U.S. is relatively weak, and with good legal advice you can drag out bargaining for a very long time.

We’ve seen this with the Starbucks campaign. The first Starbucks store unionized in 2021. Over 540 stores have organized since then. And Starbucks workers at those stores still do not have a contract.

Could the new Trump administration have any impact on how this plays out in Philly?

The fact that the Trump administration has taken over gives companies more confidence that the standard delay strategy will work.

On Jan. 28, 2025, President Donald Trump fired Jennifer Abruzzo, the general counsel of the NLRB. The general counsel is the official at the board who basically enforces the National Labor Relations Act. Abruzzo was very aggressive in holding employers accountable if they violated the act and in protecting the rights of workers who tried to organize.

Trump’s approach to labor law in his first four years in office was at the other extreme. He appointed as general counsel Peter Robb, who was seen as far less aggressive in protecting workers’ rights and his interpretations of the law were much more pro-business.

Under the Biden administration, if a company was coming to the bargaining table month after month and not agreeing to anything, the NLRB would eventually step in and cite the employer for not bargaining in good faith. The NLRB could find the employer guilty of unfair labor practices and genuinely put pressure on it to bargain a contract.

Based on the board’s actions during the first Trump administration, the board in the next few years will be more likely to allow companies to delay and delay in reaching a contract.

What leverage do the Whole Foods employees have?

They can go on strike. But Amazon has the resources to put up with a strike at one Whole Foods store forever.

Other Whole Foods stores may be considering union drives. The more stores that organize, the more momentum the Philadelphia store will have. But for now, these workers in Philly are going to have their work cut out for them.

That said, they won’t be alone. The Whole Foods workers organized with the UFCW Local 1776, which is basically a statewide union that’s been around for decades. It has a lot of resources and experienced and knowledgeable leaders, plus the resources of the national UFCW. So it’s going to lean into this fight, and these workers will also have a lot of support from the rest of the labor community in Philadelphia.

Earlier this month, three Congressional representatives from Pennsylvania wrote a letter to Jason Buechel, the Whole Foods CEO, and to Jeff Bezos, the Amazon founder, that expressed their concerns about efforts to suppress the union drive. Is that support typical?

It’s not unusual. But there is no legal basis for elected officials to intervene in a labor-management dispute. I’d put that under the heading of community support.

You have a lot of progressive elected officials in Philadelphia who are supportive of unions, and that’s true in Pennsylvania right up to the governor.

Paul F. Clark, Professor of Labor and Employment Relations, Penn State

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Timothy J McCoy, Smithsonian Institution and Sara Russell, Natural History Museum

A bright fireball streaked across the sky above mountains, glaciers and spruce forest near the town of Revelstoke in British Columbia, Canada, on the evening of March 31, 1965. Fragments of this meteorite, discovered by beaver trappers, fell over a lake. A layer of ice saved them from the depths and allowed scientists a peek into the birth of the solar system.

Nearly 60 years later, NASA’s OSIRIS-REx mission returned from space with a sample of an asteroid named Bennu, similar to the one that rained rocks over Revelstoke. Our research team has published a chemical analysis of those samples, providing insight into how some of the ingredients for life may have first arrived on Earth.

Born in the years bracketing the Revelstoke meteorite’s fall, the two of us have spent our careers in the meteorite collections of the Smithsonian Institution in Washington, D.C., and the Natural History Museum in London. We’ve dreamed of studying samples from a Revelstoke-like asteroid collected by a spacecraft.

Then, nearly two decades ago, we began turning those dreams into reality. We joined NASA’s OSIRIS-REx mission team, which aimed to send a spacecraft to collect and return an asteroid sample to Earth. After those samples arrived on Sept. 24, 2023, we got to dive into a tale of rock, ice and water that hints at how life could have formed on Earth.

The CI chondrites and asteroid Bennu

To learn about an asteroid – a rocky or metallic object in orbit around the Sun – we started with a study of meteorites.

Asteroids like Bennu are rocky or metallic objects in orbit around the Sun. Meteorites are the pieces of asteroids and other natural extraterrestrial objects that survive the fiery plunge to the Earth’s surface.

We really wanted to study an asteroid similar to a set of meteorites called chondrites, whose components formed in a cloud of gas and dust at the dawn of the solar system billions of years ago.

The Revelstoke meteorite is in a group called CI chondrites. Laboratory-measured compositions of CI chondrites are essentially identical, minus hydrogen and helium, to the composition of elements carried by convection from the interior of the Sun and measured in the outermost layer of the Sun. Since their components formed billions of years ago, they’re like chemically unchanged time capsules for the early solar system.

So, geologists use the chemical compositions of CI chondrites as the ultimate reference standard for geochemistry. They can compare the compositions of everything from other chondrites to Earth rocks. Any differences from the CI chondrite composition would have happened through the same processes that formed asteroids and planets.

CI chondrites are rich in clay and formed when ice melted in an ancient asteroid, altering the rock. They are also rich in prebiotic organic molecules. Some of these types of molecules are the building blocks for life.

This combination of rock, water and organics is one reason OSIRIS-REx chose to sample the organic-rich asteroid Bennu, where water and organic compounds essential to the origin of life could be found.

Evaporites − the legacy of an ancient brine

Ever since the Bennu samples returned to Earth on Sept. 24, 2023, we and our colleagues on four continents have spent hundreds of hours studying them.

The instruments on the OSIRIS-REx spacecraft made observations of reflected light that revealed the most abundant minerals and organics when it was near asteroid Bennu. Our analyses in the laboratory found that the compositions of these samples lined up with those observations.

The samples are mostly water-rich clay, with sulfide, carbonate and iron oxide minerals. These are the same minerals found in CI chondrites like Revelstoke. The discovery of rare minerals within the Bennu samples, however, surprised both of us. Despite our decades of experience studying meteorites, we have never seen many of these minerals.

We found minerals dominated by sodium, including carbonates, sulfates, chlorides and fluorides, as well as potassium chloride and magnesium phosphate. These minerals don’t form just when water and rock react. They form when water evaporates.

We’ve never seen most of these sodium-rich minerals in meteorites, but they’re sometimes found in dried-up lake beds on Earth, like Searles Lake in California.

Bennu’s rocks formed 4.5 billion years ago on a larger parent asteroid. That asteroid was wet and muddy. Under the surface, pockets of water perhaps only a few feet across were evaporating, leaving the evaporite minerals we found in the sample. That same evaporation process also formed the ancient lake beds we’ve seen these minerals in on Earth.

Bennu’s parent asteroid likely broke apart 1 to 2 billion years ago, and some of the fragments came together to form the rubble pile we know as Bennu.

These minerals are also found on icy bodies in the outer solar system. Bright deposits on the dwarf planet Ceres, the largest body in the asteroid belt, contain sodium carbonate. The Cassini mission measured the same mineral in plumes on Saturn’s moon Enceladus.

We also learned that these minerals, formed when water evaporates, disappear when exposed to water once again – even with the tiny amount of water found in air. After studying some of the Bennu samples and their minerals, researchers stored the samples in air. That’s what we do with meteorites.

Unfortunately, we lost these minerals as moisture in the air on Earth caused them to dissolve. But that explains why we can’t find these minerals in meteorites that have been on Earth for decades to centuries.

Fortunately, most of the samples have been stored and transported in nitrogen, protected from traces of water in the air.

Until scientists were able to conduct a controlled sample return with a spacecraft and carefully curate and store the samples in nitrogen, we had never seen this set of minerals in a meteorite.

An unexpected discovery

Before returning the samples, the OSIRIS-REx spacecraft spent over two years making observations around Bennu. From that two years of work, researchers learned that the surface of the asteroid is covered in rocky boulders.

We could see that the asteroid is rich in carbon and water-bearing clays, and we saw veins of white carbonate a few feet long deposited by ancient liquid water. But what we couldn’t see from these observations were the rarer minerals.

We used an array of techniques to go through the returned sample one tiny grain at a time. These included CT scanning, electron microscopy and X-ray diffraction, each of which allowed us to look at the rock at a scale not possible on the asteroid.

Cooking up the ingredients for life

From the salts we identified, we could infer the composition of the briny water from which they formed and see how it changed over time, becoming more sodium-rich.

This briny water would have been an ideal place for new chemical reactions to take place and for organic molecules to form.

While our team characterized salts, our organic chemist colleagues were busy identifying the carbon-based molecules present in Bennu. They found unexpectedly high levels of ammonia, an essential building block of the amino acids that form proteins in living matter. They also found all five of the nucleobases that make up part of DNA and RNA.

Based on these results, we’d venture to guess that these briny pods of fluid would have been the perfect environments for increasingly complicated organic molecules to form, such as the kinds that make up life on Earth.

When asteroids like Bennu hit the young Earth, they could have provided a complete package of complex molecules and the ingredients essential to life, such as water, phosphate and ammonia. Together, these components could have seeded Earth’s initially barren landscape to produce a habitable world.

Without this early bombardment, perhaps when the pieces of the Revelstoke meteorite landed several billion years later, these fragments from outer space would not have arrived into a landscape punctuated with glaciers and trees.

Timothy J McCoy, Supervisory Research Geologist, Smithsonian Institution and Sara Russell, Professor of Planetary Sciences, Natural History Museum

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Ambuj Tewari, University of Michigan

State-of-the-art artificial intelligence systems like OpenAI’s ChatGPT, Google’s Gemini and Anthropic’s Claude have captured the public imagination by producing fluent text in multiple languages in response to user prompts. Those companies have also captured headlines with the huge sums they’ve invested to build ever more powerful models.

An AI startup from China, DeepSeek, has upset expectations about how much money is needed to build the latest and greatest AIs. In the process, they’ve cast doubt on the billions of dollars of investment by the big AI players.

I study machine learning. DeepSeek’s disruptive debut comes down not to any stunning technological breakthrough but to a time-honored practice: finding efficiencies. In a field that consumes vast computing resources, that has proved to be significant.

Where the costs are

Developing such powerful AI systems begins with building a large language model. A large language model predicts the next word given previous words. For example, if the beginning of a sentence is “The theory of relativity was discovered by Albert,” a large language model might predict that the next word is “Einstein.” Large language models are trained to become good at such predictions in a process called pretraining.

Pretraining requires a lot of data and computing power. The companies collect data by crawling the web and scanning books. Computing is usually powered by graphics processing units, or GPUs. Why graphics? It turns out that both computer graphics and the artificial neural networks that underlie large language models rely on the same area of mathematics known as linear algebra. Large language models internally store hundreds of billions of numbers called parameters or weights. It is these weights that are modified during pretraining.

Pretraining is, however, not enough to yield a consumer product like ChatGPT. A pretrained large language model is usually not good at following human instructions. It might also not be aligned with human preferences. For example, it might output harmful or abusive language, both of which are present in text on the web.

The pretrained model therefore usually goes through additional stages of training. One such stage is instruction tuning where the model is shown examples of human instructions and expected responses. After instruction tuning comes a stage called reinforcement learning from human feedback. In this stage, human annotators are shown multiple large language model responses to the same prompt. The annotators are then asked to point out which response they prefer.

It is easy to see how costs add up when building an AI model: hiring top-quality AI talent, building a data center with thousands of GPUs, collecting data for pretraining, and running pretraining on GPUs. Additionally, there are costs involved in data collection and computation in the instruction tuning and reinforcement learning from human feedback stages.

All included, costs for building a cutting edge AI model can soar up to US$100 million. GPU training is a significant component of the total cost.

The expenditure does not stop when the model is ready. When the model is deployed and responds to user prompts, it uses more computation known as test time or inference time compute. Test time compute also needs GPUs. In December 2024, OpenAI announced a new phenomenon they saw with their latest model o1: as test time compute increased, the model got better at logical reasoning tasks such as math olympiad and competitive coding problems.

Slimming down resource consumption

Thus it seemed that the path to building the best AI models in the world was to invest in more computation during both training and inference. But then DeepSeek entered the fray and bucked this trend.

Their V-series models, culminating in the V3 model, used a series of optimizations to make training cutting edge AI models significantly more economical. Their technical report states that it took them less than $6 million dollars to train V3. They admit that this cost does not include costs of hiring the team, doing the research, trying out various ideas and data collection. But $6 million is still an impressively small figure for training a model that rivals leading AI models developed with much higher costs.

The reduction in costs was not due to a single magic bullet. It was a combination of many smart engineering choices including using fewer bits to represent model weights, innovation in the neural network architecture, and reducing communication overhead as data is passed around between GPUs.

It is interesting to note that due to U.S. export restrictions on China, the DeepSeek team did not have access to high performance GPUs like the Nvidia H100. Instead they used Nvidia H800 GPUs, which Nvidia designed to be lower performance so that they comply with U.S. export restrictions. Working with this limitation seems to have unleashed even more ingenuity from the DeepSeek team.

DeepSeek also innovated to make inference cheaper, reducing the cost of running the model. Moreover, they released a model called R1 that is comparable to OpenAI’s o1 model on reasoning tasks.

They released all the model weights for V3 and R1 publicly. Anyone can download and further improve or customize their models. Furthermore, DeepSeek released their models under the permissive MIT license, which allows others to use the models for personal, academic or commercial purposes with minimal restrictions.

Resetting expectations

DeepSeek has fundamentally altered the landscape of large AI models. An open weights model trained economically is now on par with more expensive and closed models that require paid subscription plans.

The research community and the stock market will need some time to adjust to this new reality.

Ambuj Tewari, Professor of Statistics, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.