What is *Why Information Grows* by César Hidalgo about?

*Why Information Grows* redefines economic growth through the lens of physics and information theory, arguing that economies thrive by accumulating knowledge embedded in people, networks, and physical objects. Hidalgo identifies matter, energy, and "crystallized imagination" (knowledge stored in products) as key growth drivers, linking economic complexity to long-term prosperity. The book bridges atomic-level entropy principles with macro-scale societal innovation.

Who should read *Why Information Grows*?

Economists, policymakers, and enthusiasts of complexity science or innovation theory will find this book transformative. It’s ideal for readers seeking non-traditional perspectives on growth, blending physics, economics, and information systems. Hidalgo’s interdisciplinary approach also appeals to technologists exploring how networks and trust shape economic ecosystems.

Is *Why Information Grows* worth reading?

Yes—it offers a groundbreaking framework for understanding growth through information accumulation, surpassing conventional capital/labor models. Hidalgo’s synthesis of entropy, computation, and economic complexity provides actionable insights for policymakers and business leaders. However, readers preferring purely quantitative economics may find its physics metaphors challenging.

What is "economic complexity" in *Why Information Grows*?

Economic complexity refers to a nation’s capacity to produce diverse, knowledge-intensive goods, which Hidalgo argues predicts long-term growth better than traditional metrics. Countries with robust networks of people and firms excel at embedding information into products, fostering resilience and innovation. This concept underpins the Atlas of Economic Complexity, a tool co-developed by Hidalgo.

How does *Why Information Grows* explain the role of trust in economies?

Trust enables collaboration, allowing societies to scale information production by pooling specialized know-how. Hidalgo frames economies as "personbyte" systems—networks where trust reduces transaction costs, letting individuals focus on niche expertise while relying on others’ crystallized knowledge. Low-trust societies struggle to achieve complex production chains.

What does "crystallized imagination" mean in the book?

This term describes human knowledge physically encoded into objects, like microchips or infrastructure. These artifacts allow societies to bypass individual cognitive limits by externalizing and sharing expertise. For example, toothpaste packaging encodes manufacturing, chemistry, and logistics knowledge users don’t need to possess personally.

How does *Why Information Grows* critique traditional economics?

Hidalgo challenges growth models focused solely on capital, labor, or institutions. He argues they overlook how information embedded in objects and networks drives innovation. Traditional metrics like GDP fail to capture economic complexity, which better predicts future prosperity.

What physics concepts does Hidalgo apply to economics?

The book uses entropy (disorder) and "out-of-equilibrium" systems to explain Earth’s information growth. Just as whirlpools form in draining bathtubs, human societies leverage energy surpluses to create ordered structures—from cities to microprocessors—defying universal entropy.

Why Information Grows Summary

The Evolution of Order, from Atoms to Economies

César Hidalgo

3.97(1480 Reviews)

Why Information Grows Summary Overview

Hidalgo's groundbreaking exploration reveals how information shapes economies through physics and networks. Praised by Steven Pinker as "thoroughly original," it redefines growth beyond capital and labor. What if knowledge networks - not resources - determine which nations truly prosper?

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Chapter 1

The Universe's Rare Information Pocket: Where Order Defies Entropy

In a universe relentlessly marching toward disorder, Earth stands as a remarkable anomaly - a place where information not only persists but grows. Cesar Hidalgo's "Why Information Grows" has captivated readers across disciplines, from economists to physicists, by bridging the seemingly disparate worlds of thermodynamics and global economics. The book has gained particular acclaim among tech entrepreneurs and complexity theorists, with Bill Gates naming it one of his top reads of 2015. What makes this work so compelling is Hidalgo's ability to explain why some regions of our world become innovation powerhouses while others remain trapped in economic stagnation - all through the lens of information theory and physics. As we navigate an increasingly knowledge-based global economy, Hidalgo's framework offers a fresh perspective on why prosperity remains so unevenly distributed across our planet.

Chapter 2

Information's Physical Nature: The Building Blocks of Complexity

Information isn't some abstract concept floating in the digital ether - it's fundamentally physical. When a $2.5 million Bugatti crashes, its atoms remain intact, but the arrangement of those atoms - the information - is destroyed. This distinction between matter and its arrangement explains why the car's value plummets despite no loss of material. Shannon's information theory defined information as the minimum communication volume needed to specify a message. Yet this created a paradox: random data technically contains more "information" than organized documents. To reconcile this with our intuition, we must understand Boltzmann's entropy concept. Imagine a half-full stadium. Entropy measures how many ways people can sit to achieve the same average state. When fans sit in specific patterns (all close to the field), entropy is low. When they sit randomly, entropy is high. While entropy often suggests disorder, it technically measures multiplicity - how many equivalent arrangements produce the same average state. Information-rich states are extraordinarily rare. A perfectly arranged Bugatti represents one specific configuration among countless possible arrangements of those atoms - similar to solving a Rubik's cube, which has 43 quintillion possible states but only one ordered solution. These information-rich states feature both short-range and long-range correlations, like DNA sequences showing patterns beyond random distribution. Finding these rare, ordered states - whether a baby fitting shapes into holes or solving a Rubik's cube - represents computation and intelligence. This physical understanding of information connects directly to economic value: the most valuable products aren't those with the most atoms but those with the most precisely arranged atoms - the most information.

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Chapter 3

The Paradox of Growing Order in an Entropic Universe

The universe presents us with a profound paradox: while thermodynamic laws predict increasing disorder, our planet demonstrates the opposite trend with growing complexity and information. This contradiction deeply troubled 19th-century physicists who couldn't reconcile Boltzmann's statistical mechanics with the observable growth of order in biological systems and human civilization. The apparent violation of entropy's inexorable increase seemed to challenge fundamental physical laws. Time flows irreversibly from past to future, yet this directionality wasn't explained by Newton's or Einstein's time-reversible theories of motion. Classical mechanics treated time as symmetrical - equations worked equally well running forward or backward. The arrow of time remained mysterious until scientists connected it to entropy's increase. But this only deepened the paradox: if entropy always increases, how does complexity arise? How do we explain the emergence of life, consciousness, and technological civilization in an universe apparently dominated by decay? Ilya Prigogine revolutionized our understanding by showing that information emerges naturally in steady states of physical systems that exist out of equilibrium. Earth functions as an information-rich pocket in an otherwise entropy-increasing universe, driven by constant energy input from solar radiation and planetary nuclear decay. In out-of-equilibrium systems like whirlpools, hurricanes, or living organisms, order emerges spontaneously after periods of chaos. These systems exhibit self-organization - the spontaneous emergence of coherent patterns from random initial conditions. Prigogine demonstrated that such systems minimize entropy production in their steady states, allowing information to become "sticky" enough to be preserved and recombined. This explains how our planet can host increasingly complex structures despite the universe's entropic trend. Complex adaptive systems like ecosystems and economies can maintain and increase their internal order by exporting entropy to their surroundings. Earth isn't violating thermodynamic laws; it's a special case where continuous energy flows create the conditions for information to grow and accumulate over time. This understanding bridges physics and economics: both involve systems that accumulate information through energy-driven processes that temporarily resist entropy's march toward disorder. Markets, like living systems, can spontaneously generate order when supplied with energy flows. The emergence of complex economic structures mirrors the self-organization seen in physical systems, suggesting deep connections between thermodynamics, information theory, and economic behavior. This framework helps explain how local pockets of increasing complexity can exist within the larger context of universal entropy increase. These insights have profound implications for understanding the origin of life, the development of intelligence, and the long-term fate of civilization. While the universe as a whole tends toward heat death, local regions can sustain and increase complexity through energy-driven processes that create islands of order in a sea of increasing entropy.

Chapter 4

Crystallized Imagination: How Humans Externalize Information

Unlike other species, humans possess the extraordinary ability to encode vast amounts of information outside our bodies - not just in books and recordings, but in physical objects from stone axes to computers. This ability to create physical instantiations of objects we imagine is uniquely human. Products embody not just information but imagination - information generated through mental computations that we externalize by creating objects. The key distinction lies in the source of physical order: edible apples existed in the world before entering our minds, while Apple products existed in someone's mind before materializing in the world. Both contain information, but only the latter are "crystals of imagination." Hugh Herr exemplifies this concept perfectly. After losing his legs to frostbite, he built his own robotic replacements. He literally walks on solidified pieces of his own imagination, expanding human capabilities through objects that embody information. Similarly, Ed Boyden's work in optogenetics is developing interfaces between humans and machines - essentially "a USB port for the brain" - that will open countless future possibilities. This perspective reframes international trade as exchanges of embodied imagination. Countries can be net importers or exporters of imagination, regardless of their monetary trade balance. Chile's trade with Korea illustrates this: Chile exports mostly copper and maintains a positive trade balance, but imports vehicles and parts that embody far more imagination. Similarly, Brazil exports iron ore and soybeans to China while importing electronics and chemicals - a positive trade balance but negative imagination balance. Products give us access to knowledge we don't personally possess. When using toothpaste, we benefit from the practical knowledge of its inventors and manufacturers without knowing how to synthesize sodium fluoride ourselves. Products are magical because they distribute the practical applications of knowledge residing in other people's minds and because they augment our natural capabilities beyond individual limitations.

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Chapter 5

The Personbyte Limit: Why Knowledge Has Boundaries

Our ability to crystallize imagination has dramatically improved our standard of living through complex products like refrigerators, jet engines, and digital devices. Yet this capacity is unevenly distributed globally - many countries can make shoes, but few can produce helicopters. This geographical disparity exists because developing the ability to create each "crystal of imagination" requires significant knowledge and knowhow. Knowledge and knowhow are "heavier" than the products that embody them - trapped in human bodies and networks rather than easily transferable like information in books or objects. Learning is both experiential and social, requiring practice and interaction with experts. This creates geographical bias in knowledge accumulation, as people learn primarily from those around them with relevant experience. The finite capacity of individuals to accumulate knowledge introduces the concept of a "personbyte" - the maximum knowledge and knowhow a human can hold. Products requiring more than one personbyte necessitate teams working in harmonious networks. Like the difference between individual musicians and a cohesive band like the Beatles, the network effect multiplies capabilities but introduces coordination challenges. The division of labor and economies of scale explain why Ford built the massive River Rouge complex, but they don't explain why industrial facilities differ so dramatically in size between products like cars versus pins. This difference stems from the quantization of knowledge and knowhow - cars require larger networks to hold the necessary expertise than pins do. While Ford divided Model T production into 7,882 tasks, this represents an upper bound on required personbytes since many tasks share overlapping knowledge. Despite increasing product complexity since the Model T era, megafactories haven't proliferated endlessly, suggesting a second quantization limit called the "firmbyte" - where production must be distributed across networks of firms rather than contained within single entities.

Chapter 6

Transaction Costs and Network Boundaries

Ronald Coase's groundbreaking 1937 paper "The Nature of the Firm" revolutionized our understanding of organizational economics by explaining why firms have natural size limits. He identified that economic transactions aren't the frictionless exchanges depicted in classical economics, but rather involve substantial costs in negotiating terms, drafting and enforcing contracts, monitoring performance, and resolving disputes. Firms emerge as "islands of conscious power" where employees follow hierarchical directives rather than responding to market price signals, creating internal economies that bypass these transaction costs. The boundary of a firm occurs at the precise point where the costs of internal coordination (bureaucracy, communication overhead, management complexity) equal the transaction costs of external market exchanges. This equilibrium explains why even the largest corporations don't simply keep expanding indefinitely. For instance, when General Motors attempted to vertically integrate most of its supply chain in the 1950s, it eventually discovered that managing such complexity internally was less efficient than maintaining networks of specialized suppliers. This dynamic explains the prevalence of industrial networks rather than monolithic corporations in complex manufacturing. Modern computers exemplify this, combining specialized components from a vast ecosystem: processors from Intel or AMD, memory from Samsung or Micron, displays from LG or Sharp, storage from Western Digital or Seagate, and software from thousands of developers. Each firm focuses on its core competency while relying on market mechanisms to coordinate with others. Standards play a crucial role in reducing inter-firm transaction costs, coevolving with markets in a reinforcing cycle. Historical examples abound: medieval European trade fairs standardized weights and measures that varied between towns, while the U.S. railroad industry's standardization of track gauges in the 1860s enabled continental-scale commerce. Language itself represents the ultimate standard - linguistic evolution has seen a consolidation from approximately 12,000 languages 12,000 years ago to today's 6,000, with English emerging as a global lingua franca for business and technology. These standardizations have enabled increasingly sophisticated networks of firms, particularly in manufacturing. Modern supply chains can span dozens of countries - the classic example of Barbie doll production across 20 nations demonstrates this complexity, with materials and components crossing multiple borders before final assembly. However, these networks aren't frictionless - complex collaborations often require extensive contractual frameworks, intellectual property agreements, quality assurance protocols, and regulatory compliance measures that can significantly impact innovation cycles and resource allocation. The healthcare sector provides a stark illustration of transaction costs in modern service industries. Administrative interactions between healthcare providers and insurance companies cost approximately $68,000 per physician annually in the United States. The proportion of healthcare workers in administrative roles grew from 18.2% to 27.3% between 1969-1999, reflecting the growing complexity of healthcare networks. This demonstrates how knowledge-intensive industries require extensive networks for information sharing and coordination, but these networks must be "quantized" into manageable units (personbytes at the individual level and firmbytes at the organizational level) due to the cognitive and organizational limits of humans and institutions.

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Chapter 7

Trust as the Foundation of Economic Networks

Trust forms the foundation for economic networks, challenging the purely economic view of network formation. Consider apartment hunting in Boston, where the best apartments circulate through social networks rather than hitting the open market - demonstrating how markets are embedded in social structures. Mark Granovetter's research showed that nearly 56% of professional workers found jobs through personal contacts, with these socially-connected jobs offering better pay and satisfaction. This pattern extends across blue and white-collar workers, with studies showing 34-70% of people finding employment through personal connections across different demographics and countries. Francis Fukuyama distinguishes between "familial" societies (southern Europe, Latin America) where trust is limited to family, and "high-trust" societies (Germany, US, Japan) where people trust beyond kin. This cultural difference profoundly affects economic structures - familial societies develop numerous small family businesses and a few large family-controlled conglomerates, while high-trust societies create professionally-run organizations of all sizes. Network size matters critically for economic complexity. High-trust societies can form larger networks capable of producing more complex products, leading to greater prosperity. The industrial structure of a country reveals its cultural trust levels - societies with robust non-family organizations develop stronger private economic institutions. The contrast between Silicon Valley and Boston's Route 128 demonstrates how social institutions affect network performance. Silicon Valley thrived with dense social networks, open labor markets, and porous boundaries between firms and institutions. Companies competed intensely while learning from each other through informal communication and collaboration. Route 128, conversely, operated with autarkic corporations that internalized activities and maintained secrecy. Their hierarchical structures kept authority centralized with vertical information flow, creating distinct boundaries between firms. This lack of adaptability ultimately caused Route 128 to shrink compared to Silicon Valley.

Chapter 8

Economic Complexity and the Nestedness Pattern

To understand why knowledge and knowhow remain geographically circumscribed, we must examine how they manifest through industries. By analyzing industry-location matrices, we discover a striking pattern called "nestedness" - less diversified locations possess subsets of industries found in more diverse locations, while rare industries appear almost exclusively in the most diverse locations. Data on international trade and tax residency of firms reveals this triangular pattern. For example, of Honduras' 50 exported products, Argentina exported 25 and the Netherlands 48. Of Argentina's 227 exports, the Netherlands exported 213. This subset structure is statistically greater than what would be expected from population or industrial diversity differences alone. Products exported by most countries include simple items like garments, while products exported by few countries include sophisticated items like optical instruments and medical imaging devices (along with some rare natural resources like uranium). By combining information on product ubiquity with the industrial diversity of exporting countries, we can identify truly complex products. The most complex products tend to be produced in a few highly diverse countries, while simpler products are produced everywhere - consistent with the idea that widely available industries require less knowledge and knowhow. Moving a complex industry resembles moving a jigsaw puzzle - the more pieces involved, the harder it becomes to transfer all components simultaneously. Industries are more likely to succeed in places that already possess much of the required knowledge and knowhow through related industries. This "diversification toward related varieties" explains why places producing curtains are pre-adapted to produce tablecloths but not espresso machines. The product space visualization helps illustrate these economic diversification patterns. In this network representation, nodes represent products, with links connecting products likely to be exported by the same countries. Malaysia's case (1980-1990) shows how economies diversify toward related industries rather than randomly - confirming the personbyte theory that diversification follows paths requiring similar knowledge and knowhow.

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Chapter 9

Reinterpreting Economic Growth Through Information

There are multiple ways to describe the economy - through traditional factors of production (physical capital, human capital, labor) or through natural science components (energy, matter, information). These approaches aren't incompatible but complementary. Economic theory has evolved from Adam Smith's decomposition of the economy into land, labor, and machinery through Robert Solow's mathematical growth models in the 1950s. However, these models revealed gaps between predicted and actual economic output, what Simon Kuznets called "a measure of our ignorance" (technically known as total factor productivity). I reinterpret the five traditional factors of economic growth - physical capital, human capital, social capital, land, and labor - through the lens of matter, energy, knowhow, knowledge, and information. Physical capital represents "crystals of imagination" - the physical embodiment of information carrying practical uses of knowledge. Human capital is society's stock of knowledge and knowhow embodied in individuals, while social capital is the ability to form networks needed to accumulate personbytes of knowledge. What's missing is the knowledge and knowhow accumulated collectively in firms and networks, which significantly contributes to economic output and growth prediction. Traditional economic models focus on stocks rather than diversity, measuring human capital through standardized tests that fail to capture the variety of knowledge in a population. Similarly, physical capital is typically aggregated by price, ignoring the critical distinctions between different types of capital. To characterize economies more accurately, we must consider both the diversity of products they export and the ubiquity of these products. When comparing countries like Singapore, Chile, and Pakistan, which export the same number of products but differ in GDP per capita, economic complexity helps identify Singapore's economy as more complex by incorporating information about the identity of exported products. What makes this measure truly important is its ability to predict economic growth over long periods. Countries with economic complexity levels higher than their GDP per capita (like China and India in 1985) tend to grow faster over time. This predictive power works best over 10-15 year periods rather than shorter timeframes, which are dominated by crises and commodity price fluctuations. The relationship suggests that products a country makes determine its equilibrium income level.

Chapter 10

The Fundamental Difference Between Biological and Economic Information

Seeds demonstrate the elegant marriage between knowhow and information in biology. A seed isn't merely DNA but contains organelles without which genetic information would remain inaccessible. DNA alone planted in soil cannot grow because it lacks the knowhow to unpack itself - it requires the machinery of cellular networks, including ribosomes, mitochondria, and other complex cellular structures that have evolved over billions of years. These biological networks use genetic templates to manufacture proteins and organelles on demand, constructing the structures that transform a seed into a tree. The process is remarkably sophisticated - a single seed contains not just the blueprint but also the complete factory needed to execute it. This includes energy-producing mechanisms, protein-building machinery, and cellular repair systems. The intimate connection between coded information and embodied knowhow allows biological organisms to reproduce and diffuse knowhow with remarkable efficiency, explaining how a few seeds can grow into forests or how rabbits could colonize Australia in less than a century. Unlike biology's elegant integration of information and knowhow, economies lack this intimate connection. While larger networks embody greater volumes of knowhow in both domains, economies cannot pack knowhow as efficiently as biological organisms. Consider a factory - its blueprints alone cannot produce products without skilled workers, specialized machinery, and established supply chains. Even with complete technical documentation, rebuilding Toyota's production system in a new location requires years of training and ecosystem development. This explains why knowhow remains geographically fixed while products that embody knowhow (like cars, smartphones, or pharmaceuticals) diffuse more effectively. A smartphone can be shipped worldwide, but the knowledge required to manufacture it remains concentrated in specific regions. This fundamental constraint shapes the structure of the global economy, requiring entire ecosystems to be reproduced for knowhow transfer to occur. Silicon Valley, Shenzhen's electronics manufacturing hub, and Germany's industrial corridors demonstrate how complex knowhow clusters in specific locations, resisting simple transfer despite globalization and digital connectivity. The contrast becomes even starker when considering how biological systems can regenerate from minimal starting points - a cutting from a plant can grow into a complete organism - while economic systems require massive coordination of people, processes, and infrastructure to replicate their knowhow in new locations.

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Chapter 11

The Dance of Information and Computation in Our Rebellion Against Entropy

The universe comprises energy, matter, and information, with information uniquely requiring mechanisms to emerge. Three fundamental concepts drive information growth: spontaneous emergence in out-of-equilibrium systems, accumulation in solids, and matter's ability to compute. Energy flows allow matter to self-organize, creating information naturally. Solids provide the stability information needs to endure against entropy, allowing recombination and growth. Matter's computational capacity enables selective information accumulation. Humans uniquely deposit information in objects, making our world fundamentally different from our ancestors' through atomic arrangements. We "crystallize imagination" by creating objects that began as mental fiction - from spears to jetliners. This ability to imagine and then physically manifest sets us apart. But crystallizing complex imagination exceeds individual capacity, requiring networks of humans functioning as distributed computers to accumulate necessary knowledge and knowhow. The "personbyte theory" explains the relationship between economic activity complexity and the size of networks needed to execute it. Activities requiring more personbytes of knowledge and knowhow need larger networks. This theory predicts that: simpler economic activities will be more widespread; only diversified economies can execute complex activities; countries diversify toward related products; and a region's income will approach its economy's complexity over time. In the world of atoms and economies, information growth depends on the eternal dance between information and computation, powered by energy flow, solids, and matter's computational abilities. Energy drives self-organization and fuels computation, while solids help order endure by minimizing energy needs and shielding information from entropy. Most crucial are collective forms of computation - from protein networks in cells to human society itself - that compute new forms of information. As entropy increases universally, our planet rebels with information-rich pockets where we form relationships, make alliances, and create families, often losing sight of the beauty in this godless creation that grew from modest physical principles.

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Key Themes in the Why Information Grows Summary

physicality of information
economic complexity
nonequilibrium thermodynamics
entropy and order
knowledge accumulation

Best Quotes from the Why Information Grows Summary

Information isn't some abstract concept...it's fundamentally physical.
Information-rich states are extraordinarily rare.
Markets, like living systems, can spontaneously generate order.
Products embody not just information but imagination.
This perspective reframes international trade as exchanges of embodied imagination.

Characters in the Why Information Grows Summary

César HidalgoAuthor and physicist who developed the framework
Claude ShannonMathematician who defined information theory
Ludwig BoltzmannPhysicist who developed the concept of entropy
Ilya PrigogineScientist who studied out-of-equilibrium systems

About the Author

César A. Hidalgo is the Chilean-Spanish-American physicist and bestselling author of Why Information Grows: The Evolution of Order, from Atoms to Economies, renowned for his groundbreaking work in economic complexity and data visualization.

A tenured professor at the Toulouse School of Economics and former MIT faculty member, Hidalgo bridges physics, economics, and artificial intelligence to explore how information shapes economic systems—a theme central to his book. He co-created influential platforms like the Observatory of Economic Complexity and DataUSA, which have redefined public data accessibility through award-winning visualizations.

Hidalgo’s expertise is further showcased in The Atlas of Economic Complexity (a foundational text on growth strategies) and How Humans Judge Machines, which analyzes human-AI interactions. His research has earned accolades including the Lagrange Prize and three Webby Awards. Recognized as one of the “20 Most Influential Latinos in Technology” (CNET), Hidalgo advises governments and institutions worldwide on data-driven development.

Why Information Grows has been translated into 12 languages and praised by Nobel laureates for its innovative perspective on information as the cornerstone of economic evolution. His forthcoming book, The Infinite Alphabet, is anticipated in late 2025.

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I love the fact that I can get useful, condensed, information and ideas in a 8 - 15 minute podcast style audio. I'm not a general fan of podcasts because of all the fluff, but this cuts through all that.

@BeFreed user

I am finishing up my doctorate, and have to read a lot of unfamiliar material... With BeFreed, you simply enter a prompt, and the app finds source material for you and generates an audio podcast. I find the process in BeFreed to be more streamlined than NotebookLM.

@Brad

I often search YouTube for something to listen to whilst making breakfast, when I'm out walking, commuting, etc, and BeFreed has provided an even more targeted approach, without the adverts and the fluff!

@BeFreed user

The absolute best part about this platform is its versatility. There is literally no subject that is off-topic. It handles whatever you throw at it... It is rare to find an learning tool with zero limitations that actually delivers on its promises.

@jayallen

BeFreed is fantastic. The user-friendly design means I spend less time navigating and more time learning. The mix of audiobooks, podcasts, and learning plans is a genius combo that has completely changed my daily routine.

@BeFreed user

At the start I needed a while to understand how to create podcasts in italian language and boom! It is so great! I can ask to explain every argument and it does so well and so smartly!

@matteo77

BeFreed has become my daily app for audio books tools... What I like the most is the way you put your text and come with an audio that you can listen on the go.

@kotanzu1

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