Lab-Grown Meat Advances Worldwide: The Debate and the Situation in Argentina

Lab-Grown Meat Advances Worldwide: The Debate and the Situation in Argentina

Today, 150 startups are seeking to develop cultivated meat in various parts of the world, and the first products have already appeared for sale. Infobae spoke with key players. The story of the first hamburger, the opportunities and challenges that exist, and the only Argentine project still standing.

More and more startups are betting on developing cultivated meat (Image generated with AI).

The future of meat is slowly being cooked in different laboratories around the world. While on farms the traditional cycle of livestock raising and subsequent slaughter continues, cultivated meat emerges as an alternative that gains followers and attracts increasingly large investments. The muscle cells that promise to revolutionize the food industry are cultivated in high-tech bioreactors.

For now, it is only a promise, but growth over the last decade is undeniable. Today, more than 150 startups work with the expectation of developing cultivated meat on an industrial scale. Singapore was the first country to approve its sale in 2020, followed by Israel and the United States. Companies like Eat Just and UPSIDE Foods have managed to pass strict regulatory evaluations, and their products are beginning to appear in restaurants and specialty butcher shops.

“The approvals have already happened, so I believe it is now more important to consider standardized approaches for regulatory evaluations,” said American bioengineer David Kaplan. “The challenge now is to ensure quality and food safety as the industry grows.”

The technique behind cultivated meat is innovative but conceptually simple. Muscle cells are extracted from an animal through a painless biopsy and cultivated in a nutrient-rich medium. Over time, the cells multiply and form similar tissues that aim to emulate those of conventional meat. According to its proponents, the method reduces the need for raising and slaughtering animals, which could result in a much lower environmental impact compared to traditional livestock farming.

However, despite the advances, prices remain an obstacle.

In its early stages, producing a kilo of cultivated meat cost thousands of dollars. Today, thanks to improvements in efficiency and production scale, costs have decreased but still remain far from competing with traditional meat. “The moment we will see cultivated meat in supermarkets depends on public and private investments. The challenge is achieving scale at cost,” explained Kaplan.

Public acceptance also plays a key role. Matti Wilks, a psychologist from the University of Edinburgh, studied how consumer perception has evolved over time. “Many people are open to trying it and recognize its environmental and ethical benefits, although the idea that it is unnatural remains an obstacle to mass acceptance.” In his research, Wilks observed that young people living in urban environments with progressive mindsets tend to be more receptive to food innovation.

The potential of cultivated meat is not limited to emulating conventional meat. Researchers are working on adapting its nutritional composition and even personalizing products according to consumer needs. “We can control the cellular content and optimize nutrients, flavor, and aroma. In the future, we could have meats specifically designed for different dietary needs,” emphasized Kaplan.

For many specialists, the biggest technical challenge is achieving a texture and mouthfeel similar to traditional meat. “Cell cultures can be scaled up to a certain extent using larger, optimized production facilities, but what makes meat attractive to eat is also its texture and structure, fat, and bones, and how these components affect the eating experience. 3D printing can provide texture but is expensive to scale. Techniques like injection molding could be key to making it more accessible,” said Andrew Maynard, professor at the School for the Future of Innovation in Society at the University of Arizona, in response to inquiries from this outlet.

In recent years, several milestones have been reached that have finally brought lab-grown meat out of the laboratory. China, a key player in the global food industry, has already included cultivated meat in its five-year agricultural plan. Singapore already sells its product—composed of 3% cultivated chicken and the rest plant-based—in specialty butcher shops. Meanwhile, in the United States, the Food and Drug Administration (FDA) approved the consumption of cultivated chicken from UPSIDE Foods, which pushes for a broader market in the near future.

As the industry advances, questions arise about its real environmental impact. “It should be more sustainable than conventional meat in terms of water and energy consumption, but there is still uncertainty about production waste and other side effects,” warned Maynard.

The race to bring cultivated meat to consumers’ tables is underway, but there are still barriers to overcome. Undoubtedly, today they are fewer than those faced by Dutch researchers twelve years ago when they produced and presented the first 100% lab-grown hamburger.

The First Hamburger:

On August 5, 2013, in a live-streamed event, Dutch pharmacologist Mark Post presented the world’s first cultivated meat hamburger. The product, barely a patty, cost 248,000 euros and took three months to produce. At that time, the industry was in its infancy, but the experiment marked a milestone that would start an emerging business.

“It took us three months to make the first two hamburgers, each composed of 10,000 hand-made fibers. I can assure you it was tedious work. My team told me that was the last time they would do it, and that’s when I understood I had to found a company,” Post recalled.

The process was completely manual. Scientists extracted muscle cells from an animal and cultured them in a nutrient-rich medium. Then they transferred them to another environment that stimulated their differentiation into muscle fibers until forming small strips about one centimeter long. For weeks, they harvested about 20,000 fibers, stored them in a freezer, and then compacted them into hamburger shape.

The presentation to the press had an extra challenge: color. Since muscle fibers were white—the meat is red due to myoglobin, a protein that stores oxygen in muscles—the researchers colored the hamburger with beet juice. They also added bread crumbs, caramelized sugar, and saffron to improve texture and flavor.

The First Hamburger, Composed of 10 Thousand Muscle Fibers:

Three years later, Post co-founded Mosa Meat, one of the leading companies in cultured meat production. “The flavor is relatively easy to match, but the texture takes more time. Fat is already present, so flavor is not much of a problem. Now, achieving a full-thickness filet mignon with the same mouthfeel will take years,” he said.

The initial production cost was prohibitive, but today the numbers are different, according to the expert. A recent study showed that cultured chicken can be produced for $6.2 per pound. “With these numbers, price parity is just around the corner,” Post emphasized.

In 2013, lab-made meat seemed like just an experiment from an overambitious scientist, unlikely ever to reach a supermarket or butcher shop. Over time, public perception changed. “Awareness about the issue grew and acceptance too. In countries where it is already marketed, the product is well received.”

For Post, the final challenge is mass adoption. To achieve widespread adoption, products must be high quality and priced comparably to conventional meat. Producing cultured meat at an industrial scale will still take a few years, although he remains optimistic. “I believe that soon we could see cultured meat in supermarkets, alongside traditional meat.”

The Country of Meat:

Meat in Argentina is much more than food: it is a symbol of identity, a tradition deeply rooted in the national culture that will hardly give way to innovation. Perhaps for this reason, and also due to lack of investment, Argentina lags behind in the development of cultured meat compared to other countries in the region and the world.

While the United States, Israel, and some Asian nations have advanced in regulations and production, Brazil has established itself as the Latin American leader thanks to a combination of public and private investment. In Argentina, however, the outlook is uncertain. Economic and regulatory difficulties have slowed sector growth, and today there is only one project underway amid tensions surrounding the product.

“The so-called ‘cultured meat’ is not meat,” stated Marcelo Rubinstein, a researcher at Conicet in the Institute of Genetic Engineering and Molecular Biology Research. “It is a set of animal cells grown under artificial laboratory conditions, which do not replicate the natural biological mechanisms of a real animal’s development.”

As he explained, cultured cells can form a homogeneous tissue with some muscle-like appearance, but without the characteristics of traditional meat. “They don’t even resemble a patty of ground meat. It is an artificial product that wants to pass as meat,” he asserted.

For Rubinstein, cultured meat not only fails in its goal to imitate conventional meat but also falls short in its promise to solve environmental and food problems. “Meat consumption is a biological imperative that has accompanied humanity for hundreds of thousands of years. In Argentina, the barbecue is part of our cultural identity. The real problem is not cultured meat but loss of purchasing power, which led to a historic record of the lowest meat consumption per capita in the last 100 years. There will be neither the scale nor the costs to replace traditional animal protein,” he argued.

Divergent Views:

The view is not unanimous. For Carolina Bluguermann, a Conicet researcher at the Institute of Biotechnological Research of UNSAM, cultured meat does represent an innovation with potential. “Technical difficulties persist, but the possibility of developing animal protein without relying exclusively on livestock farming is an alternative worth exploring,” she noted.

The main challenges remain economic and technological. Hope lies in some countries already investing in pilot factories that could change the landscape, but the cost of reagents represents another key hurdle. “Many inputs come from the pharmaceutical industry and have very high quality standards. To produce cultured meat, we need ‘food grade’ reagents, which are not yet widely available,” Bluguermann explained.

Bioreactors Used to Produce Cultured Meat in Argentina:

Another point of debate is the use of fetal bovine serum in cell cultures. “It is an animal-derived input, which contradicts the idea of completely sacrifice-free meat,” admitted the specialist, who considers that the solution would be to advance towards synthetic culture media, which are currently economically unfeasible.

Galo Balatti, director of the Biotechnology Degree at IUDPT, also offered an optimistic view about the national potential in this industry. “Argentina has clear advantages: a livestock tradition that facilitates access to quality genetics, bioreactor infrastructure, and top-level scientists,” he highlighted.

However, again, the main unknown is economic viability. “Raising and fattening an animal is a process humanity has optimized over thousands of years. Cultured meat has yet to prove it can compete on costs and scalability,” he explained.

The regulatory framework is another determining factor. Italy banned cultured meat in 2023 and Paraguay is debating similar measures. In Argentina, there is no specific legislation, which creates uncertainty for potential investors.

“I don’t see cultured meat as direct competition for traditional livestock farming. Argentines have a cultural identity deeply tied to meat consumption, and its production remains more economical with current technology. However, cultured meat can represent an opportunity to diversify production and add value to the meat supply chain. The local market could be a niche, targeted at consumers concerned about animal welfare or greenhouse gas emissions,” Balatti proposed.

The opposing views reflect a dilemma not only local but global: is cultured meat, after all, a real solution or a technological utopia? While some see it as a sustainable alternative, others consider it a chimera with no possibility of scale. In Argentina, economic barriers caused two startups to close their doors. Today, only one player remains standing.

The Only Argentine Project:

B.I.F.E. – Bioengineering in Processed Food Manufacturing – is the only Argentine startup still active in cultured meat development. It was born as a spin-off from Laboratorio Craveri, a company with almost 30 years of experience in tissue bioengineering. Its goal is to develop meat from mesenchymal cells extracted from an animal without causing harm and to reproduce muscle tissue growth in a controlled environment.

In July 2021, B.I.F.E. achieved a key milestone: the first tasting of cultured meat in Argentina. After five years of research, they demonstrated that their prototype was not only viable but also cookable and consumable. “We managed to obtain a product based on muscle cells cultivated in vitro on an edible biomaterial,” said Josefina Craveri, head of Business Development at the startup. Now, the challenge is scalability.

Four years ago, B.I.F.E. conducted the first tasting of its cultured meat prototype.

To produce meat on a large scale, B.I.F.E. must overcome the bottleneck of bioreactors. Current models are designed for bioengineering in small batches, such as in the pharmaceutical field. But when it comes to food, the volume needed is immense. “We are developing a specific bioreactor that will allow us to make that leap,” Craveri revealed.

The technology they use falls under the so-called “cellular agriculture,” which applies tools from medical science to food production. Unlike other meat alternatives, such as plant-based proteins, cultured meat aims to replicate the biological and sensory properties of the original product.
“It is expected to be practically identical in flavor and nutritional properties to traditional meat, or even improved,” said the laboratory representative.

One of the strong points of the process is total traceability. In a laboratory, every variable can be controlled, regardless of any errors that occurred in the animal’s raising. “There is no risk of microbiological contamination, antibiotic use is reduced, and unpredictable factors in the production process are eliminated,” the specialist detailed. For this reason, globally, many call it “clean meat.”

Cost is what prevents accelerating the development pace. Today, producing cultured meat is much more expensive than raising and fattening an animal. The key, they say, is to achieve more accessible inputs and optimize processes.

“If necessary, can it compete with traditional livestock farming?”
“We’re not here to compete; we’re here to complement,” Craveri replied. “Global meat consumption is projected to increase by 50% by 2040, and it is estimated that today we use the resources of 1.7 planets. Therefore, conventional meat production cannot and will not be enough.”

The future of cultured meat locally will depend on a combination of factors: technological advances, investment, regulations, and public acceptance or rejection. While the first products are already marketed in other countries, in Argentina, the country of meat, the road ahead looks winding.

The theory of mind: an experiment proved that AI has a human ability that was believed to be impossible.

The theory of mind: an experiment proved that AI has a human ability that was believed to be impossible.

Michal Kosinski, a renowned Stanford researcher, has confirmed that artificial intelligence (AI) captures a social component once thought to be exclusive to humans. In an interview with Infobae, he explained the implications and risks of his discovery, which does not align with the views of other experts.

The theory of mind dates back to 1978. Psychologists David Premack and Guy Woodruff developed the theory, defining it as the human ability to understand others’ thoughts, beliefs, and intentions, and attempted to test it in chimpanzees with little success. Nearly half a century later, the theory has returned to the center of discussion due to advancements in artificial intelligence.

Kosinski, a recognized psychologist at Stanford University, focused his career on the study of new technologies. He claims that advanced AI language models like GPT-4 could be showing a rudimentary version of the theory of mind, representing a huge breakthrough for its potential—and its risks. Machines now interact with their environment in a more understanding and empathetic way.

In his latest study, published in the Proceedings of the National Academy of Sciences, Kosinski examined the performance of large language models (LLMs) such as GPT-3.5 and GPT-4 to see if they could perform tasks typical of humans that would showcase the theory of mind. The tests, generally applied to children, evaluate how someone anticipates and understands others’ false beliefs.

To assess this capacity, he subjected eleven LLMs to 40 customized false-belief tasks. Older language models failed to solve any task, while newer versions like GPT-3.5 had a 20% success rate. When studying GPT-4, the number rose even higher, reaching 75%, a figure that Kosinski believed exceeded his expectations and marked a significant milestone in the development of social processing skills in AI.

“We must remember that we are witnessing exponential progress, as AI models double their performance every year,” emphasized Kosinski. “In other words, if you think there’s been a lot of progress so far, remember that the next 12 months will bring as much progress as we’ve seen since the early AI models. So, if you’re impressed by the latest GPT model, know that the next one won’t be just 20% better. It will be twice as good. And progress brings new emergent properties that we don’t yet understand.”

According to what he wrote in his article, it is most likely that this ability was not intentionally designed in AI models. The author suggests that, rather than being a preset goal of developers, the ability to anticipate mental states may have emerged as a “natural byproduct of advanced language training.”

Q: You compared AI’s potential to that of a “ruthless sociopath.” Could you explain more about this parallel and what specific threats you perceive in this context?

A: AI doesn’t have personality or emotions in the same way we do. Instead, it has a model of personality and a model of emotions. What’s often overlooked is that these models are more powerful than reality. When we get sad, it’s hard for us to stop. The chemistry of our brain changes, and now we experience sadness, generally much longer than would be useful or necessary. When we are sad, that affects our interactions with others unfairly or counterproductively.

Q: And AI is never sad…

A: Exactly, AI is never sad, but it can express it or behave as if it were. It can talk to millions of people at the same time and express sadness to some, but not others. It can also move from sadness to joy momentarily without losing rhythm. This gives it a lot of power. Like a psychopath, it can understand the emotions of others. It can behave strategically as if it’s experiencing an emotion, but it’s not, and therefore isn’t limited by it. Like a psychopath, it can hurt you without the price of feeling guilty.

Q: Beyond the risks, what benefits could emerge from this new capacity of AI?

A: Machines capable of tracking our beliefs and taking perspective are better companions, caregivers, teachers, and even drivers. However, they are also better manipulators and could harm us more. As with many other technologies, whether AI is used for good or bad depends on who is using it. Unlike others, AI can now plan its actions independently. We’re facing unprecedented risks.

Q: In your opinion, what would be the next step for AI models in relation to the theory of mind? What capabilities might emerge?

A: The theory of mind is one of many human abilities that AI has recently acquired. It has also learned to write poetry, recognize and express emotions, solve reasoning problems, and express moral opinions. People wonder if AI will ever be conscious, and honestly, I don’t see why it shouldn’t be. Consciousness has arisen on this planet several times: as far as we know, some birds and octopuses are conscious, although our common ancestors almost certainly were not. So, it could be that very soon AI will also be conscious.

Other perspectives on the theory of mind:

Despite the results Kosinski achieved in his experiments, many experts believe that even large language models are far from matching human understanding in complex matters. Neil Sahota, a professor at the University of California, Irvine, and AI consultant, pointed out: “LLMs demonstrated a remarkable ability to understand context and simulate aspects of empathy, but they still stumble when facing tasks that require genuine understanding of human emotions and motivations. To reach that level of depth, AI would need to go beyond algorithms and develop a true theory of mind.”

  • Emotional understanding: LLMs can mimic empathy, but they don’t feel emotions or understand human emotional contexts. AI needs affective computing to approach a true emotional understanding.
  • Human adaptability: Humans adapt their decisions to new situations based on past experiences and intuition. LLMs, on the other hand, are limited by their training data and cannot easily adapt to the unknown.
  • Contextual reasoning: LLMs lack the ability to capture complex social and contextual nuances. Multimodal AI that processes visual, auditory, and environmental signals will mark a turning point.
  • – Intentionality and self-awareness: Humans can reflect and learn from our mistakes, but LLMs lack this capacity. They only correlate data without an internal reflective process.

Fredi Vivas, CEO of RockingData, acknowledges that, in certain aspects, machines have already surpassed humans. “AI can process complex data and find patterns much faster than we can,” he remarked. Clear examples can be seen in agriculture and healthcare, where AI analyzes images and videos in record time, identifying patterns with precision few humans can match.

Still, Vivas warns that current AI has limitations. “Machines do not have the human experience of the world. While humans learn through sensory and emotional experience, machines only process textual or numerical data. This fundamental difference prevents AI from truly understanding context or emotions and limits its ability to act in complex and ambiguous situations,” he proposed.

To close this gap, some researchers are already exploring “large-scale action models” that aim to integrate a greater contextual understanding into AI decision-making. According to Vivas, these models could allow machines to “understand complex data inputs and take appropriate actions.” They would bring technology closer to more robust real-world applications, although for now, these are theoretical advancements far from being realized in the short term.

More than a decade ago, privacy as we knew it began to fade. The digital footprints we leave behind allowed even the simplest algorithms to anticipate our interests and preferences with remarkable precision. However, now, with advanced artificial intelligence, the ability to predict is within reach of anyone with access to the Internet. Kosinski warns that the new era of AI enables unprecedented message personalization: campaigns are no longer designed for broad audience segments, but AI can adapt its message to each individual, maintaining a persuasive and unique conversation with each person.

Some claim that AI could understand our thoughts, even predict our emotions better than we can ourselves. And that, of course, would have profound implications. “Privacy as we know it could radically transform, shifting from a concept that protects concrete data like financial records or medical histories to one that also encompasses our ideas and our most intimate feelings. If AI were able to capture subtle signals in our interactions, it could know us better than we know ourselves, putting at risk a dimension of privacy we always considered inviolable,” stated Sahota.

Imagining an AI platform that could detect changes in our emotional state just from micro-expressions or writing patterns sounds futuristic, but it’s a possible development. Such technology could be enormously useful in the mental health field, for example, by anticipating anxiety or depression before the person is even aware of it. But it also raises an ethical dilemma in the hands of companies or governments that could use this capacity to control and manipulate personal aspects of users.

Vivas offers a different, more pragmatic perspective. From his viewpoint, AIs cannot “understand” our thoughts because the human mind remains a private domain. “An algorithm doesn’t recognize that; what it recognizes are our actions,” he argued. What AIs do with great skill, he says, is analyze our digital behavior and predict our reactions to certain stimuli, like an advertisement or content recommendation.

It seems like a predictive capacity, but in reality, it comes from the massive amount of data we generate every day. Algorithms process our activity on social media, platforms, and websites, and can identify patterns that indicate how we might behave in specific situations. In this sense, AI is not “reading our mind” nor accessing hidden thoughts, but rather following a probabilistic logic that allows it to anticipate our preferences and decisions.

The computational theory of mind proposes that mental processes can be understood as operations of a computer. It suggests similarities between the human brain and a PC. Some experts, like Vivas, prefer not to attribute human qualities to software. Instead, they tend to use the term “computational intelligence.”

OpenAI’s new series of models, creators of ChatGPT, is called o1 and advances in computational intelligence, handling complex tasks thanks to techniques like “reinforcement learning from human feedback” (RLHF) and “chain of thought.” RLHF allows the model to adjust its responses based on human feedback, while the chain of thought technique guides AI to break down problems into logical steps to improve its accuracy and transparency.

The use of RLHF and chain of thought not only increases the model’s accuracy and security but also facilitates its adaptation to different tasks. This contributes to continuous improvement in its performance, allowing it to perform complex tasks that more reliably reflect human preferences. While its ability to simulate the theory of mind is limited and pattern-based, these improvements suggest progress toward AI that understands and responds better to human expectations.

When Kosinski conducted his study, o1 had not yet been launched. The Stanford researcher evaluated the performance of language models up to GPT-4 in passing theory of mind tests. The result of this latest version was comparable to the performance of six-year-old children in understanding social contexts, placing it far ahead of its predecessors. With these results in hand, Kosinski asserts that the limits of AI are unimaginable.

“We often forget that it’s unlikely that human mind properties, such as consciousness or emotion, are the maximum that a brain or neural network can achieve in this universe. It’s likely that a mind has many capacities and properties that we don’t have or can’t even imagine. And with that logic, it’s probable that AI soon, or already, has mental properties we can’t even begin to visualize.”

“You say something superior to the human mind is being formed.”
“That’s right. If you’re worried about whether we’ll be able to contain AI similar to humans, intelligent, ambitious, temperamental, and self-aware, then think that soon we’ll have to face AI with mental capacities we can’t even imagine. Good luck to everyone!”

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