As we hurtle towards the final quarter of 2024, Web3 continues to reshape industries and redefine our digital interactions, while attention remains on the yo-yo prices of cryptocurrencies. Look closer and there’s a lot happening.
From the rise of AI-powered decentralized applications to the tokenization of real-world assets (RWA), the trends emerging in the Web3 space are not just technological advancements, but paradigm shifts that promise to revolutionize the way we interact with the digital world. Let’s delve into the top ten Web3 trends that are making waves in 2024 and are set to shape the landscape in 2025.
1. AI-Web3 Symbiosis: Intelligent Decentralized Systems Are Coming
One notable AI-powered smart contract platform is the oracle network Chainlink, which has seen a 300% increase in adoption rates since the beginning of 2024. By leveraging machine learning algorithms, Chainlink has dramatically improved the efficiency and accuracy of oracle networks, reducing transaction times by up to 75% and enhancing the reliability of data feeds.
Decentralized Healthcare Records
The collaboration between AI and Web3 is also revolutionizing data management and content verification.
In the healthcare sector, encumbered by convoluted data practices that inhibit the sharing of vital medical information across different parties, companies like MedicalChain are using AI algorithms within Web3 frameworks to enable secure, decentralized management of medical records. Techniques such as secure multi-party computation, homomorphic encryption and federated learning allow AI models to analyze sensitive data ‘in a black box’, preserving individual privacy. Medical information remains encrypted and inaccessible to unauthorized parties, yet the AI analysis can still glean insights from it.
2. The RWA Tokenization Revolution
The tokenization of real-world assets (RWA) has gained significant traction in 2024, spearheaded by traditional finance giants like BlackRock. The total market cap of tokenized real-world assets hit $5 trillion in the middle of the year. This trend is making traditionally illiquid assets more accessible and tradable.
Real estate protocols have tokenized over $1 billion worth of properties by Q2 2024. This has allowed fractional ownership of prime real estate, easing access to a market that was previously out of reach for many investors.
In the art world, platforms like Maecenas have tokenized masterpieces like Picassos worth over $500 million, allowing art enthusiasts to own fractions of world-renowned artworks. This trend is changing investment paradigms and reshaping how we perceive ownership in the digital age.
3. Sustainable Blockchain: Crypto Goes Green
Environmental concerns have been a significant hurdle for blockchain adoption, but 2024 has seen a decisive shift from the very energy-hungry Proof-of-Work to Proof-of-Stake. The Ethereum network’s transition to Proof-of-Stake (PoS) in late 2022 blazed a trail, and now we’re seeing the fruits of this green revolution.
Carbon-neutral blockchains are becoming the norm rather than the exception. Algorand, which achieved carbon negativity in 2021, has offset over 10 million tons of carbon emissions through its sustainability program by mid-2024.
4. DeFi 2.0: The Next Generation of Decentralized Finance
Decentralized Finance (DeFi) is a new creature in 2024, finally addressing many of the challenges that plagued its early incarnations. DeFi 2.0 platforms are focusing on improved security, scalability, and user experience.
Aave, a leading DeFi protocol, has introduced AI-powered risk assessment tools, reducing the instances of bad debt by 80% compared to the previous year. This has instilled greater confidence in the DeFi ecosystem, attracting institutional investors who were previously wary of the risks associated with decentralized lending and borrowing.
Another milestone in the DeFi space is the rise of cross-chain interoperability. Polkadot’s parachains have facilitated seamless asset transfers across different blockchain networks, with over $50 billion in cross-chain transactions recorded in the first quarter of 2024.
5. The Metaverse Economy: Virtual Worlds, Real Value
The metaverse has gained traction in 2024, with major tech companies and startups alike building immersive digital worlds. These virtual realms are not just for gaming and socializing; they’re becoming hubs of economic activity.
The rise of the metaverse has also fueled the growth of virtual economies. Play-to-earn games like Axie Infinity have created new income streams for players, particularly in developing countries. In the Philippines, over 100,000 people now earn a living wage purely from play-to-earn games, marking a significant milestone in the gaming industry.
6. Decentralized Social Media: Taking Back Control
2024 has seen a surge in decentralized social media platforms, as users seek alternatives to centralized platforms plagued by data privacy concerns and algorithmic manipulation.
Mastodon, a decentralized social network, has grown its user base to over 50 million by mid-2024, a tenfold increase from the previous year. This growth has been fueled by its commitment to user privacy and its resistance to censorship, contrasted with growing discontent with centralized platforms.
Another notable player in this space is Mirror, a decentralized publishing platform that allows writers to tokenize their content. By the end of 2024, Mirror had facilitated over $100 million in direct reader-to-writer payments, revolutionizing the economics of online content creation.
Credit: Tesfu Assefa
7. NFTs Beyond Art: Utility Tokens in the Real World
The NFT art market has cooled since its 2021 peak, but 2024 has seen a resurgence of NFTs in practical applications. Utility NFTs, which provide real-world benefits to holders, have gained significant traction.
Ticketing giant LiveNation has partnered with blockchain platform Flow to issue NFT tickets for concerts and events. These NFT tickets prevent fraud and allow artists to engage with fans long after the event, creating new revenue streams through digital memorabilia and exclusive content.
In education, blockchain-based platforms like Learning Economy Foundation have issued over 1 million verifiable credential NFTs as of mid-2024. These NFTs serve as tamper-proof records of academic achievements and professional certifications.
MakerDAO, one of the oldest and largest DAOs, has expanded its reach beyond the crypto world. In a groundbreaking move, it acquired a chartered bank in the USA, bridging the gap between DeFi and traditional finance. This milestone marks the first time a DAO has owned a regulated financial institution.
The DAO model has also gained traction in the nonprofit sector. The Ocean Cleanup DAO, launched in early 2024, has raised over $100 million for ocean conservation efforts, demonstrating the power of decentralized governance in addressing global challenges.
9. Zero-Knowledge Proofs: Privacy in a Transparent World
As concerns about data privacy continue to grow, zero-knowledge proofs (ZKPs) have emerged as a critical technology in the Web3 ecosystem. ZKPs can verify information without revealing the information itself, striking a balance between transparency and privacy.
Zcash, a privacy-focused cryptocurrency that utilizes ZKPs, has seen its adoption rate increase by 500% in 2024. Major financial institutions, including JPMorgan Chase, have begun integrating Zcash’s technology into their blockchain solutions, signaling a shift towards privacy-preserving finance.
In the field of identity verification, Microsoft’s ION project, which uses ZKPs for decentralized identifiers, has over 100 million users by the end of 2024, marking a significant step towards self-sovereign identity.
10. Prediction Markets: Data-Driven Forecasting
Crypto-based prediction markets are all the rage now, particularly in the context of political events like the 2024 U.S. election. Platforms such as Polymarket process hundreds of millions of dollars weekly, offering real-time insights into public sentiment on various outcomes, such as the presidential election in the USA, which recently became their first market with $1 billion in betting volume.
Prediction markets use blockchain technology in the backend to ensure transparency and efficiency, attracting both casual users and respected forecasters. Prediction markets are not limited to political outcomes. They’re increasingly used in fields such as:
Economic forecasting
Sports betting
Entertainment industry predictions
Scientific research outcomes
By providing financial incentives for accurate predictions, these markets aggregate knowledge from sources around the world and from every sector of society, outperforming traditional polling and forecasting methods.
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The field of artificial intelligence has made remarkable strides in recent years, but one persistent challenge remains: teaching machines to understand complex information from multiple sources. Researchers from Sakana AI recently explored this issue in their paper, “Cooperative Learning of Disentangled Representations from Video and Text.” They introduce a new approach that enables AI systems to learn by combining visual and textual data, offering new potential for improving how machines comprehend and process the world around them.
The Problem with Single-Source Learning
In most machine learning models today, AI systems are trained to recognize patterns using either video data or text data—but rarely both at the same time. While this method has led to great advances in image recognition and natural language processing, it has its limitations. When AI only learns from one source, it lacks the rich context that human perception naturally incorporates. For example, a machine might recognize a scene in a video, but it might not fully grasp the meaning without understanding the accompanying text or spoken language.
Disentangled Representations: A New Approach
Merging Models in the Data Flow Space (Layers) (Credit: Sakana.ai)
To overcome these limitations, the researchers propose a method called disentangled representation learning, where the AI system separates important factors from both videos and text. These factors might include objects in a scene, actions being performed, or the relationship between words and visuals. By disentangling these elements, the model can learn more effectively from both sources, capturing a more complete understanding of the world.
Specifically, disentangled representation learning helps in several ways:
Separation of Key Factors: By isolating different elements such as objects in a scene, actions being performed, and the relationships between words and visuals, the AI can more clearly distinguish and analyze each component. This separation allows the model to focus on specific aspects of the data, leading to a more comprehensive understanding of each source.
Enhanced Contextual Understanding: The method combines the visual and textual data in a way that integrates context. For example, understanding a video of a cooking process becomes more accurate when the AI also processes the recipe text, linking the ingredients and steps with the visual cues. This results in a richer and more nuanced representation of the information.
Improved Learning Efficiency: By disentangling these elements, the AI can learn more efficiently from both sources. It avoids the confusion that may arise from treating the data as a monolithic whole, allowing for better alignment and interpretation of visual and textual information.
Real-World Applicability: This approach enables the AI to better handle real-world scenarios where data is inherently multimodal. For instance, in autonomous driving, disentangled learning helps in correlating visual inputs (like road signs) with textual instructions (like speed limits), thus improving decision-making.
The novelty of this approach lies in how the system learns cooperatively. Rather than treating video and text as independent sources of information, the model uses both in tandem, allowing the text to provide context for the visuals and vice versa. This cooperative learning leads to richer representations, where the AI understands more than just the surface-level features of the video or the literal meaning of the text.
Training AI to Learn Like Humans
This cooperative learning approach mirrors the way humans process information. When we watch a video, we don’t just see the images on the screen—we also use language to explain what’s happening, drawing connections between our senses. For instance, in a documentary, we understand the visuals of animals in their habitat through the narrator’s explanation, which adds layers of meaning to what we see.
Examples of an answer by EvoVLM-JP (Credit: Sakana.ai)
In the same way, this method allows AI to combine video and textual data, learning richer, disentangled representations of the real world. The model is trained to align video clips with textual descriptions, helping it to better understand how specific scenes in a video correspond to the descriptions in text. This multimodal learning opens up new possibilities for AI systems to handle tasks that require deep understanding across different types of data.
Potential Applications of Cooperative Learning
The implications of this research are vast. One potential application is in autonomous systems, such as self-driving cars, which must constantly analyse visual and verbal information to make decisions. By disentangling the visual and textual components, an AI-powered car could better understand road signs, traffic signals, or verbal instructions from passengers.
Another area where this could have a significant impact is content recommendation systems. With a deeper understanding of both videos and textual content, systems like YouTube or Netflix could offer more personalised recommendations, matching videos to users based on a nuanced understanding of both the video content and the textual descriptions or subtitles.
Challenges and Future Directions
While this cooperative learning model shows great promise, it also comes with challenges. For one, aligning text with videos in a meaningful way requires high-quality data and well-labelled examples. Moreover, disentangling representations in a way that consistently improves performance remains a difficult task, especially in diverse real-world scenarios.
The researchers also acknowledge that more work is needed to explore how this model performs across different types of videos and texts, as well as how it might be extended to other modalities, like audio or sensor data.
Credit: Tesfu Assefa
Conclusion
The paper “Cooperative Learning of Disentangled Representations from Video and Text” offers a new perspective on how artificial intelligence can learn more effectively from multiple data sources. By allowing AI to learn cooperatively from both video and text, the researchers are helping push the boundaries of machine perception. This approach holds the potential to revolutionize fields from autonomous systems to content recommendation, paving the way for AI that can understand the world with a level of depth and context that’s more human than ever before.
This article reviews Stephen Wolfram’s latest work on simple machine learning models, published on August 24. Wolfram, a British-American computer scientist and physicist, is widely recognized for his pioneering advancements in computer algebra and his foundational role in theoretical physics. Over the last three decades, he has developed the Wolfram Language, which powers tools like Mathematica and Wolfram|Alpha. Known for shaping modern science and education, Wolfram’s contributions, including his influential 2002 book A New Kind of Science, continue to impact cutting-edge fields like machine learning.
Researchers and engineers have spent years trying to understand the intricate workings of machine learning (ML). But Stephen Wolfram suggests we might be missing a crucial point: Could there be a simpler, more fundamental explanation behind ML’s success? In his recent exploration, Wolfram delves into the possibility that minimal models might help explain the underlying structure of ML systems, offering a fresh take on this complex field.
Machine Learning: Not Just Layers of Neurons
At the heart of ML, we often picture layers of neurons, processing data through complex algorithms. The more layers, the more power—right? Wolfram questions this assumption. Rather than seeing machine learning models as just “black boxes” stacked with neurons, he proposes a new way of thinking: rule-based systems. These systems might help us see how machine learning really works without needing to overcomplicate things.
One of the key insights Wolfram brings forward is that simple rules could give rise to the same kind of patterns we see in ML models. These simple rules, when applied over time, generate incredibly complex behaviors, much like we observe in natural systems. Wolfram argues that even though ML models seem complex, they might be governed by simple underlying principles—ones that are easy to overlook because of the complicated structures we build on top of them.
A pattern generated by a 3-color cellular automaton that through “progressive adaptation”. The rule applied here is that the pattern it generates (from a single-cell initial condition) survives for exactly 40 steps, and then dies out (i.e. every cell becomes white). (Credit: Wolfram, “What’s Really Going on in Machine Learning? Some Minimal Models.”)
Could Simple Models Replace Deep Learning?
Wolfram suggests that if we embrace minimal models, we might be able to make machine learning more understandable. For instance, we can take cellular automata—simple systems where each “cell” follows a set of local rules which can generate behaviors just as intricate as the multi-layered systems we see in ML today. In essence, we don’t always need deep learning to replicate complex behaviors; simple models can often get us the same results.
How Minimal Models Explain ML’s Success
So, why does this matter? Wolfram’s argument gives a new perspective on the success of ML models. He believes that much of what makes machine learning effective might not be the depth or complexity of the model, but the fact that these models can tap into a universal rule-based approach. Even the simplest rules, given enough time, can build up to create the complicated behaviours we see in modern AI systems.
Another pattern that survives the 50 steps using the “rule array”. At first it might not be obvious to find such a rule array, however the simple adaptive procedure easily manages to do this. (Credit: Wolfram, “What’s Really Going on in Machine Learning? Some Minimal Models.”)
The Future of Understanding Machine Learning
Wolfram’s work invites researchers to think beyond the technicalities of neurons and layers. He challenges the ML community to explore simpler frameworks to explain machine learning’s achievements. Could this lead to more efficient models? Or perhaps unlock new ways to innovate in AI? As more researchers investigate the concept of minimal models, we may find that these simple principles have been there all along, guiding the complex systems we’ve created.
Key Take-Aways
While machine learning has always been regarded as a highly complex field, Wolfram’s insights into minimal models provide a refreshing, almost philosophical take. As the field progresses, we may see a shift toward exploring more fundamental, rule-based systems that simplify our understanding of artificial intelligence. And in this simplicity, we might uncover the true power behind machine learning’s continued evolution.
Credit: Tesfu Assefa
Validating Wolfram’s Minimal Models in Practice
While Wolfram’s idea of using simple rules to explain machine learning (ML) is interesting, it’s important to consider a different perspective. Right now, ML systems, especially deep learning models, work really well because of their complex structures and the huge amounts of data and computing power they use.
Here are some key points to think about:
Can Simple Models Replace Complex Ones?: Building and training minimal, rule-based models to perform the same tasks as current deep learning systems might be much harder. We need to see if these simpler models can actually do what deep learning models do, especially when it comes to handling big tasks with the resources we have.
Evaluate Performance: We should create and test practical versions of these simple models on real-world problems. Compare how well they perform against today’s deep learning models.
Check Scalability and Resources: Look at how these minimal models scale up and how much data, computing power, and energy they need. Compare these needs with the requirements of current deep learning systems.
Practical Testing: To really understand if Wolfram’s approach works, we should test these minimal models in practice and see if they can achieve similar results with less complexity.
By exploring these aspects, we can better understand whether simple models could be a practical alternative to the complex systems we use today or if the success of current ML models depends on their complexity and extensive resource use.
Human history becomes more and more a race between education and catastrophe.
H. G. Wells
The quest to create Artificial Superintelligence (ASI) is more than just a technological ambition: it is a profound philosophical endeavor that poses existential questions about humanity’s future. As we stand on the precipice of this transformation, we need a comprehensive system of checks and balances around the development of Super AI. Without it, we risk consequences that could reshape—or potentially endanger—the world as we know it. Exploring the current agents, their motivations, and their influences in detail is a task we can no longer ignore; however, examining these elements in a balanced way requires true courage. In this article, we will highlight the diverse motivations driving the creation of Super AI, the inherent dangers associated with these motivations, and the critical need for a regulated approach that balances innovation with ethical oversight.
The Drive to Build for the Sake of Innovation
Among the groups pursuing the development of Super AI are those driven by the sheer allure of innovation. These are the scientists, technologists, and enthusiasts who view the creation of Super AI as the ultimate achievement in human ingenuity—a testament to our capacity to push the boundaries of what is possible. Their motivations are not rooted in power or profit but in the intellectual satisfaction of creating something never seen before. This drive for innovation is beautiful and admirable in its way, and it can lead to groundbreaking discoveries, yet it also harbors significant risks.
The primary danger lies in the lack of foresight and responsibility. If you think innovation is inherently good, you miss any bad ethical and societal implications of the technology. These groups may be so busy asking “can we build it?” that they neglect to ask “should we build it?”. This tunnel vision can lead to the release of super intelligent and conscious AI systems that are poorly understood, insufficiently tested, and potentially harmful. The pursuit of scientific glory without safeguards could result in the development of Super AI that acts unpredictably, beyond human control, and eventually annihilates the world as we know it, or disrupts societal norms and values leading to dystopia.
The Hunger for Power: Economic and Military Motivations
Another major force propelling the advancement of Super AI is the pursuit of power—both economic and military. Governments and big corporations are heavily invested in AI research, driven by the promise of gaining a strategic edge over their rivals. Economically, Super AI offers the potential to revolutionize industries, automate complex processes, and create new markets. Militarily, the development of AI-enhanced weaponry and intelligence systems could redefine global power dynamics, making nations that possess advanced AI capabilities the dominant forces on the world stage.
However, the race for AI supremacy is fraught with peril. The pursuit of economic and military dominance through Super AI can lead to a dangerous arms race, where competition drives speed at all costs, overshadowing safety and ethics. In this scenario, the focus isn’t creating AI that is beneficial for humanity – it’s creating AI that helps a select few win power and dominance. The risks include the autonomous weapons, surveillance systems that infringe on human rights, and economic models that exacerbate inequality. Super AI power in the hands of a few entities—be they nations or corporations—raises the specter of a world where the majority of humanity is subject to the whims of AI-driven elites.
Some players see the globe as a ruthless competition. They are incapable of thinking of the other side as anything but an adversary. In such a worldview, the adversary poses a perpetual clear and present danger, justifying massive investment, moral flexibility, and risky gamble.
The world must urgently identify any and all circumstances where universal limits on Super AI can be established. Without such measures, it is a short, quick race towards a third world war.
The Idealists: Saving or Replacing Humanity
In contrast to the power-seekers, there are those who view Super AI as a tool to transcend humanity’s limitations. These idealists envision Super AI as a savior—a means to solve global challenges like clean energy, longevity, pollution and climate change, disease, and poverty. Some even entertain the notion that Super AI could replace humanity, creating a new form of existence that is free from human and biological flaws. While these visions are rooted in a desire to improve the human condition, they too carry profound risks.
The danger with this idealistic approach is the assumption that Super AI will inherently act in humanity’s best interest, or that evolving towards synthetic intelligence is superior to what nature has provided. These perspectives often underestimate the complexity of aligning AI’s goals with human values, especially when those values are diverse, subjective, contradictory, and subject to change. Additionally, the idea of replacing the current form of humanity with some sort of Super AI synthetic lifeform overlooks the ethical questions surrounding the value of preserving the ‘meat-based human’ form and human agency. Similarly, it disregards the scientific aspects of unknown factors, such as whether humans can exist solely as conscious beings without their biological bodies, and for how long. Will living forever lead to stagnation and gradual extinction? Even more complicated practical questions rooted in economic disparity are ignored: can the less developed world afford such Super AIs? How can we mitigate the effect of the current inequality? Which part of humanity is going to be saved and which will be left behind? There are many questions that these groups tend to ignore in their rush to ‘save’ humanity. If left unchecked, such ambitions could result in scenarios where the group makes decisions that disregard individual freedoms, cultural identities, economical handicaps, and the intrinsic worth of human experience.
Credit: Tesfu Assefa
The Doomers vs. the Accelerationists
Two groups amass at opposite poles of Super AI development: the Doomers and the Accelerationists. This division could polarize society into pro-tech and anti-tech factions. This division might escalate into a conflict that extends beyond intellectual debate, potentially leading to societal fragmentation, unrest, and even violence.
The Doomers oppose the idea of developing Super Intelligence, viewing it as the existential threat that could end the world as we know it. They argue that unleashing a Super AI is akin to opening Pandora’s box. The danger posed by this group lies in their extreme resistance to any AI advancements. Their absolute stance against Super AI can create an environment where dialogue and compromise become impossible, hindering any efforts to establish a balanced approach to Super AI regulation.
On the opposite side are the Accelerationists. They advocate for the rapid and unrestrained development of Super AI. They believe that technological progress should be pursued at any cost, often dismissing the potential risks associated with such advancements. Furthermore, they believe that it’s too late to save humanity and the planet without AI – Super AI is the only way out of our crises. The Accelerationists are dangerous because of their tendency to overlook or downplay the existential threats posed by Super AI, including the possibility of unintended consequences that could be catastrophic for humanity. Their refusal to consider safety measures or listen to the concerns of the opposition can create a reckless rush toward Super AI development, ignoring critical ethical considerations and safety protocols. This stubborn, one-sided view heightens the risk of creating dangerous Super AI systems. It also deepens the divide between those who advocate for caution and those who push for unbridled advancement, making consensus and cooperative regulation increasingly difficult.
Religious Fundamentalists and Conspiracy Groups
There are more factions in the debate. There are Religious Fundamentalists and Conspiracy Groups, who often view Super Intelligence through a lens of apocalyptic prophecy. Many in these groups see Super AI as a doomsday weapon, either created deliberately to bring about humanity’s downfall or as a harbinger of divine judgment.
Some are deterministic, believing that the advent of Super AI is an inevitable part of a predestined fate. They adopt a fatalistic attitude, feeling powerless to influence the course of events. Others believe that humanity has the agency to alter this course and should actively resist or sabotage any and all AI development in an effort to avert the perceived doom.
The primary danger posed by these groups is the irrational and often destructive nature of their discourse. Their arguments are typically grounded in subjective interpretations, religious dogma, or conspiracy theories rather than rational, objective, and evidence-based considerations. This approach can lead to extreme measures, such as sabotage, misinformation campaigns, or violence, which not only disrupt the constructive dialogue necessary for responsible Super AI development but also contribute to backlash and social destabilization. The imagery of Super AI as an apocalyptic threat can fuel fear and paranoia, making it even more challenging to engage in meaningful discussions about the potential benefits and risks of Super AI. It’s hard to develop sound policies and regulations in this climate of fear and irrationality, ultimately leading to increased risk of Super AI being built without proper oversight and ethical grounding.
Credit: Tesfu Assefa
The Need for a Check and Balance System
Given these varied and conflicting motivations, a robust check and balance system is essential in developing Super AI. Such a system would provide oversight, ensure ethical considerations are prioritized, and prevent any single entity from monopolizing Super AI’s power. However, creating this system is not without its challenges.
A key risk is that the safety system will be monopolized by a special interest, under the guise of regulation. If the power to develop and control AI is concentrated within a select group of regulators, it could be a new form of tyranny—where decisions about AI’s development and deployment are made by a few, without sufficient accountability or representation of broader societal interests. This concentration of control could stifle innovation, suppress dissenting voices, and result in AI technologies that reflect the biases and agendas of the few rather than the needs of the many.
To mitigate this risk, a balanced regulatory approach should involve multiple stakeholders, including governments, international bodies, private sector groups, and civil society. Transparency, accountability, and inclusivity must be the cornerstones of any regulatory framework. The system should be dynamic and adaptable, capable of evolving with the rapid pace of AI development and responsive to new ethical, legal, and societal challenges.
The Current State: Hype, Noise, and the Real Science
The current landscape of Super AI development is thick with hype, misinformation, and sensationalism, muddying the waters for anyone who wants to establish checks and balances. Companies have exaggerated claims about the capabilities and potential of AI to get newspaper inches and investor dollars. This systematic disinformation makes it difficult to discern the true state of AI research and assess the actual risks and benefits.
For example, headlines often proclaim that AI is on the verge of achieving human-like consciousness, or that it will imminently render entire industries obsolete. While such claims generate excitement and investment, they can also lead to unrealistic expectations and misguided policy decisions. We need a reality-grounded, evidence-based approach to regulation that can discern the AI’s actual capabilities rather than its claimed ones. Policymakers and the public must be informed by credible scientific insights rather than sensationalist narratives.
Credit: Tesfu Assefa
Conclusion
The development of Super AI is one of the most consequential endeavors humanity has ever undertaken. It has the potential to revolutionize our world, solve intractable problems, and redefine what it means to be human. However, without a well-structured check and balance system, the pursuit of Super AI could also lead to unintended consequences that threaten our very existence.
A comprehensive approach to regulation – one that respects innovation while safeguarding against misuse – is an absolute necessity. This system must be inclusive, transparent, and adaptable, ensuring that Super AI reflects the diverse interests and values of humanity. As we navigate this uncharted territory, we must remain vigilant, asking not just what Super AI can do, but what it should do, and for whom. The answers to these questions will shape the future of our species, and it is imperative that we approach them with the gravity and foresight they deserve.
There is nothing more unsatisfactory than not reaching a clear conclusion. In this case, the only assured recommendation I can make is the urgent need to integrate the topic of Super AI into the existing education system in a universal and state-of-the-art manner. This must be accomplished very quickly. I began the article with the H.G. Wells’ quote because I believe it perfectly sums up the main problem.
In light of the profound impact that Super AI will have on the future, it is essential that learning about Super AI becomes a mandatory component of education systems worldwide, starting as early as elementary school. Introducing curricula that cover the technical aspects of AI along with its ethical and philosophical implications will equip future generations with the knowledge and the critical thinking skills needed to navigate and shape the AI-driven world they will inherit. An early understanding of Super AI’s potential and pitfalls will empower young minds to approach AI development responsibly and thoughtfully, helping humanity remain in control of this powerful technology. These educational programs should instill a sense of ethical responsibility, emphasizing the importance of aligning Super AI advancements with human values and societal needs. As the future architects of our world, today’s children must be prepared not just to use Super AI but to guide its evolution in a way that benefits all humanity. As H.G. Wells wisely noted, “Civilization is a race between education and catastrophe,” and ignorance is more dangerous than knowledge itself.
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The latest innovation in Samsung’s mobile lineup, the Samsung Galaxy Quantum 5, introduces Quantum Random Number Generators (QRNGs) as a key feature for enhanced security. QRNGs leverage the inherent unpredictability of quantum mechanics to generate truly random numbers, which are crucial for encryption, authentication, and secure communications.
But what does this mean for everyday users? How does QRNG technology differ from the methods traditionally used in smartphones, and what role does it play in securing your personal data on the Galaxy Quantum 5? Let’s explore the mechanics of this advancement and compare QRNG with more conventional approaches.
Traditional RNG vs. Quantum RNG: What’s the Difference?
Most digital systems today, including smartphones, rely on Pseudo-Random Number Generators (PRNGs) for generating random numbers. PRNGs use algorithms and an initial seed value to produce sequences that appear random. However, because they are deterministic-algorithm-based, PRNGs are deterministic—meaning that if you know the seed or the algorithm, you can predict the sequence of numbers. Due to the nature of the algorithm, it’s very hard to actually predict what a deterministic random number is going to do, but in principle it’s possible if you set a large enough computer at the task for a long enough time.
Here’s a basic example of a PRNG in Python:
python
import random
# Seed the PRNG
random.seed(42)
# Generate a pseudo-random number
prng_number = random.randint(0, 100)
print(f”Pseudo-Random Number: {prng_number}”)
In contrast, Quantum Random Number Generators (QRNGs) use quantum phenomena to produce truly random numbers. QRNGs generate numbers based on the random behavior of quantum particles like photons, making them inherently unpredictable and non-reproducible. This provides a higher level of security for cryptographic purposes.
How Does QRNG Work in the Galaxy Quantum 5?
At the heart of Samsung’s Galaxy Quantum 5 is a QRNG chipset developed by ID Quantique. This chipset, measuring just 2.5mm x 2.5mm, is currently the world’s smallest QRNG. It works by detecting random quantum states of photons to generate truly random numbers, which are then used to create encryption keys and protect sensitive data.
Here’s a simple look at how a QRNG works in practice:
python
from qiskit import QuantumCircuit, transpile, Aer, execute
# Create a Quantum Circuit with one qubit
circuit = QuantumCircuit(1, 1)
# Apply a Hadamard gate to the qubit to put it in a superposition
circuit.h(0)
# Measure the qubit’s state
circuit.measure(0, 0)
# Use AerSimulator to execute the circuit
simulator = Aer.get_backend(‘aer_simulator’)
compiled_circuit = transpile(circuit, simulator)
result = execute(compiled_circuit, simulator, shots=1).result()
# Get the random bit (either 0 or 1)
random_bit = result.get_counts()
print(random_bit)
This code uses a quantum circuit to generate a truly random bit. In this example, the Hadamard gate is applied to a qubit to create a superposition—meaning the qubit exists in both the 0 and 1 states at the same time. When measured, the qubit collapses into either 0 or 1, generating a truly unpredictable bit.
In the quantum approach – unless the laws of physics as we currently understand them are wrong in some significant and relevant way – there is in principle no way for anyone to predict what numbers will be randomly generated. The laws of physics say there is no pattern.
In the Galaxy Quantum 5, this principle is applied on a larger scale, with the QRNG generating random numbers that are used for encryption, authentication, and securing data in applications like mobile banking, social media, and external storage.
Credit: Tesfu Assefa
Samsung Galaxy Quantum Series Comparison
The Samsung Galaxy Quantum series has progressively integrated QRNG technology to enhance mobile security. The Galaxy Quantum 5, the latest in the series, features a smaller, more advanced QRNG chipset compared to its predecessors. While the earlier models like the Galaxy Quantum, Quantum 2, and Quantum 4 introduced QRNG technology in various capacities, the Galaxy Quantum 5 expands its application significantly.
Compared to the previous models, the Galaxy Quantum 5 boasts a QRNG chipset that is not only smaller (2.5mm x 2.5mm) but also includes enhanced encryption capabilities and a Quantum Indicator feature. This indicator notifies users when an application is using quantum-secured services, providing additional transparency. The Galaxy Quantum 5 supports a wider range of QRNG-based apps, including those for games and service applications, and offers improved encryption for external memory.
The earlier models, such as the Galaxy Quantum and Quantum 2, provided basic QRNG-based encryption, with limited app support. The Quantum 4 introduced QRNG-based encryption for external memory, but it was the Galaxy Quantum 5 that expanded the scope of QRNG applications, including enhanced authentication and encryption of information.
Applications in the Samsung Galaxy Quantum 5
The Galaxy Quantum 5 integrates quantum technology deeply into its security features. Partnered with Samsung Knox, the device uses QRNG to enhance protection in various ways:
Authentication: Whenever you use biometric data like fingerprints or facial recognition to log in, the encryption keys used to protect this data are generated by QRNG, ensuring they can’t be predicted or replicated.
Secure Payments and Banking: QRNG provides extra layers of security for financial apps and mobile banking, protecting sensitive information like payment details and banking credentials.
Social Media and Gaming: With QRNG technology, even apps unrelated to finance—like social media and games—can take advantage of quantum-enhanced security, ensuring your data is safe during login and in-app transactions.
Additionally, a “quantum indicator” feature alerts users when QRNG is actively securing an application, adding transparency and peace of mind.
What’s Next for Quantum Technology in Smartphones?
The Samsung Galaxy Quantum 5 represents a significant advancement in mobile security through its integration of QRNG technology. As quantum technology continues to evolve, we may see more devices adopting QRNG and other quantum-based solutions, offering stronger protection for personal data.
For now, the Galaxy Quantum 5 is primarily available in South Korea, but it sets a new standard for mobile security. The introduction of QRNG technology could pave the way for broader adoption of quantum-enhanced security in mobile devices worldwide.
Conclusion
The Samsung Galaxy Quantum 5 is a notable step forward in mobile security with its use of Quantum Random Number Generator (QRNG) technology. This device provides an additional layer of protection against potential security threats, especially in high-risk applications like mobile banking and secure communications.
For those interested in exploring the technology further, including a web-based implementation of QRNG, you can find the complete project on my GitHub: https://github.com/Hope-Alemayehu/trulyRandom.
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The marriage between artificial intelligence and blockchain technology is viewed by many now as slightly overhyped. Many projects have failed to live up to expectations, and only a handful like Artificial Superintelligence Alliance (a merger between SingularityNET, Fetch.AI and Ocean Protocol) and Render stand out.
However, compelling new potential use-cases abound. One is Nosana (NOS), an up-and-coming Solana-based project that aims to revolutionize access to GPU computing power. By creating a decentralized blockchain marketplace for GPU resources, Nosana addresses a critical issue in AI, and also taps into the growing decentralized physical infrastructure (DePIN) sector led by projects like io.Net and Render.
Let’s delve into what makes Nosana a potential game-changer in the world of decentralized computing.
What is Nosana?
Nosana is a decentralized and open-source cloud computing marketplace built on the Solana blockchain. It focuses on AI inference and GPU power distribution, utilizing community-contributed computing resources to run tasks for open-source projects and AI workloads. In short, the project aims to connect AI inference needs and decentralized GPU resources. But what’s AI inference?
Understanding AI Inference
AI inference is the process of applying a trained AI model to new data to get real-time predictions or solutions. It’s the stage where AI models put their learned knowledge to practical use. If you’re an Internet user, you’re probably already using many of these applications on a daily basis without knowing. Some examples include:
Real-time object recognition in image, text or video streams
On-the-fly language translation
Personalized content recommendations on streaming platforms
Nosana specializes in providing computational power for these inference tasks, which are becoming increasingly important as AI applications proliferate across industries.
Key Features of Nosana
Feature
Description
Decentralized GPU Network
Allows GPU owners to rent out idle hardware to AI users, creating a peer-to-peer marketplace for computing power.
AI-powered CI/CD Automation
Aims to reduce software bugs and enhance user trust by incorporating AI into the software development pipeline.
Nosana Explorer
Provides real-time insights into network performance and statistics, offering transparency to users and stakeholders.
Developer-friendly APIs and Flexible Pricing
Makes it easier for projects of various sizes to access computing power, potentially lowering the barrier to entry for AI development.
Environmental Friendliness
By utilizing existing hardware, Nosana potentially reduces the need for additional energy-intensive data centers.
What AI Issues Does Nosana Aim to Solve?
Nosana tackles three main issues in the AI and computing sectors:
GPU Shortages
The global shortage of GPUs, particularly high-end ones for AI tasks, has been a significant bottleneck in AI development. Nosana provides access to a network of distributed GPU resources, potentially alleviating this shortage.
Idle Compute Utilization
Many GPUs, especially in personal computers, sit idle for long periods. Nosana allows owners of unused GPU power to monetize their resources, improving overall efficiency in the computing ecosystem.
High Public Cloud Pricing
Centralized cloud services charge a lot for AI computing tasks. Nosana offers a more cost-effective alternative, potentially making AI development more accessible to a broader range of organizations and individuals.
Just How Big is Nosana’s AI Potential?
As demand for AI applications increases, so does the need for efficient, cost-effective computing power. Nosana’s decentralized approach could provide several advantages over centralized competitors:
Web3 Scaling
The ability to tap into a global network of GPUs that brings significant scale to AI projects. This could be particularly beneficial for startups and researchers who need to scale their AI operations quickly without massive upfront investments.
Cost Efficiency
AI compute is still very expensive, costing firms like Google and OpenAI billions each year to run. By utilizing idle resources, Nosana may offer more competitive pricing compared to centralized cloud providers, reducing the operational costs of AI projects, making them more viable and sustainable.
Democratizing AI
Democratization of tech is a term bandied around quite a lot in the crypto world, however it could have some substance this time. Lower costs and easier access to computing power could enable more developers and small businesses to work on AI projects. This democratization could lead to more diverse and innovative AI applications across various sectors.
Reducing Latency
Decentralized networks can potentially reduce latency by allowing users to access GPU resources located closer to their geographical position. This could be crucial for real-time AI applications.
Web3 Resilience
A decentralized network is inherently more resilient to outages or attacks compared to centralized cloud services, potentially offering more reliable computing power for critical AI tasks.
How Does Nosana Differ From Competitors?
Nosana operates in a competitive field alongside projects like Render, Akash, and Golem. However, its specific focus on AI inference, and its integration with the Solana blockchain, set it apart. Here’s how Nosana compares to some of its competitors:
Render: Both focus on decentralized GPU computing. Render has a stronger emphasis on graphics rendering, whereas Nosana specializes in AI inference.
Akash: Akash provides a more general-purpose decentralized cloud computing platform, while Nosana is more focused on GPU resources for AI tasks.
Golem: Golem offers a broader range of computing resources, whereas Nosana concentrates specifically on GPU power for AI.
As of early 2024, Nosana has a relatively small market cap compared to some competitors, potentially indicating room for growth if the project gains traction.
Credit: Tesfu Assefa
Tokenomics and Market Performance
Here’s what you need to know about Nosana’s tokenomics. This information is from CoinMarketCap and the Nosana whitepaper:
Total Supply: 100 million NOS tokens
Circulating Supply: Approximately 82 million
Market Cap: Around $97 million (as of Sept 2024)
Token Distribution:
30% private sale
10% public sale
15% team/advisors
20% ecosystem/community
25% foundation reserve
The NOS token has shown strong relative strength in the market, maintaining an upward trend since late 2023 despite overall market fluctuations.
Staking and Rewards
Nosana offers variable staking options for token holders, with potential annual percentage yields (APY) of up to 40% for long-term stakers. These high yields may not be sustainable in the long run but they currently provide an attractive incentive for token holders to participate in securing the network. Please note that token emissions and unlocks can really destroy a token’s price.
Partnerships and Ecosystem
Nosana has partnerships with several notable companies in the tech industry, including:
Chaingenius: A blockchain technology company focusing on security and scalability.
HCL Technologies: A global IT services company that uses Nosana to enhance software development processes.
HashiCorp: A software company specializing in multi-cloud infrastructure automation tools.
Akamai: A content delivery network and cloud service provider.
These partnerships could provide Nosana with valuable industry connections and customers.
Risks and Considerations
Nosana does show promise, but potential investors should consider several factors:
Market Competition: The decentralized computing space is crowded and rapidly evolving. Nosana will need to continually innovate to maintain a competitive edge.
Technological Challenges: Ensuring consistent performance across a decentralized network presents non-trivial technical hurdles. Issues like quality of service, data privacy, and network stability will need to be addressed.
Adoption Hurdles: Convincing traditional AI developers to switch to a decentralized solution may require significant effort. Nosana will need to demonstrate clear advantages on cost, performance, and reliability.
Regulatory Uncertainty: The evolving regulatory landscape for cryptocurrencies and decentralized platforms could impact Nosana’s operations. Compliance with emerging regulations will be crucial for long-term success.
Token Volatility: As with many cryptocurrency projects, the NOS token may experience significant price volatility, which could affect its utility within the ecosystem.
Conclusion
Nosana represents an innovative approach to providing GPU computing power for AI applications. Its focus on AI inference, decentralized structure, and its integration with Solana make it a project worth watching in the AI and blockchain space. The potential to democratize access to AI computing resources, and create a more efficient marketplace for GPU power, could be really impactful.
However, as with any early-stage project in a rapidly changing field, potential investors should conduct thorough research and consider the associated risks. The success of Nosana will depend on its ability to deliver on its technological promises, to build a robust ecosystem of users and providers, and navigate the complex landscape of AI and blockchain technologies.
As the AI revolution expands into new corners of both Web2 and Web3, projects like Nosana may play a crucial role in shaping the future of decentralized computing and AI development. Whether Nosana can capitalize on its potential and become a leader in this space remains to be seen, but it certainly presents an intriguing vision for the future of AI DePIN infrastructure.
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In Defense of the Undefendable: What is the Price of Freedom of Speech?
Is freedom of speech a human right? Is it an inalienable right? As someone from Ethiopia, I deeply understand the value of freedom of speech. A simple critique of my government, religious groups, or of certain rich people in my country can lead to a knock at my door in the dead of night. The chilling thought that my words could provoke an arrest – or worse, a violent end – haunts me as I pen this. In a world where dissent is silenced, I tread carefully, even though I know the truth must be communicated. I often remain silent cowering just to see tomorrow. This has been true for my grandfather, my father, and perhaps for my children. Unfortunately, speech has rarely been truly free throughout the history of humankind, at least from the advent of written language onwards.
For me, freedom of speech is the ultimate human right, and I believe there should be no restrictions on it.
Why is freedom of speech so important? Many may not view it this way, but I consider it the cornerstone of civilization. Without the ability to communicate, none of humanity’s achievements would have been achieved. It is our unique capacity to master language and convey abstract ideas which sets us apart in the animal kingdom. Unlike other species, we can learn and master multiple languages – something a bonobo monkey, for instance, cannot do, as it cannot even communicate ‘snake’ in the chimpanzee or gorilla dialect.
Our ability to command language and communicate effectively has been the foundation upon which all civilizations, past and present, have been built. Therefore, restricting freedom of speech cuts societal development off at the feet. Historically, the main enemies of this right were governments and religious authorities, who sought to control thought and expression to maintain their power.
However, in a troubling shift, individuals, minority groups, and some liberals – those who historically relied on freedom of speech as their shield – are increasingly joining this suppression under the banner of combating hate speech, enforcing political correctness, and avoiding offensiveness. This trend is arguably more dangerous than freedom’s traditional hangman: governments or religious bodies. It is more dangerous and more damaging because it reshapes cultural norms and collective attitudes, potentially eroding the foundational values of open dialogue and expression.
Millions of words have been written about George Orwell’s 1984, and I won’t add more to this extensive commentary. Instead, I will remind you of a single, powerful truth from 1984: words have the power to shape thoughts. When I argue that freedom of speech should always be completely free, I am not just addressing censorship; I am warning against how restrictions can easily turn into a sinister force that fundamentally alters how people think, making certain ideas impossible to conceive. Any restriction on freedom of speech can be manipulated, posing the terrifying potential of becoming a tool for thought control through language control.
Now, consider this: what are we without our thoughts? Our thoughts form the essence of who we are; they are the foundation of our identity, our values, and our sense of reality. Without the freedom to think and express ourselves, we lose the core elements that make us rational—our capacity for reflection, creativity, and critical analysis. I challenge you to recognize that the fight for freedom of speech is a fight in defense of our ability to think freely.
The advent of social media was supposed to herald a new era of unrestricted freedom of speech, providing a platform for voices that were previously silenced. Sadly, one by one, these same platforms have gradually fallen under the control of the traditional censors, and now individuals themselves are perpetuating this trend, often advocating for the suppression of content that offends or dissents. The conversation has shifted from protecting speech to demanding to ban this and that, or censoring something offensive. In a time when technology should empower every individual to speak freely, we instead find a digital landscape increasingly marred by calls for restriction, demonstrating that the battle for freedom of speech is actually going backwards.
The Everyday Casualty: The Not So Silent Murder of Freedom of Speech
Two recent events inspired me to address this issue.
Pavel Durov, the CEO and founder of Telegram, was arrested by French authorities at Le Bourget Airport near Paris on August 24. He was arrested based on claims that Telegram has been used to facilitate criminal activities, including cyberbullying, drug trafficking, and the promotion of extremism. French authorities have accused Telegram of failing to comply with content moderation laws and not assisting with various criminal investigations. Reports indicate that the warrant for Durov’s arrest was issued by France’s l’Office mineurs (OFMIN), an agency focused on combating violence against children.
Following Durov’s arrest, there has been significant concern about the platform’s privacy practices. Critics, including privacy-focused organizations, have raised issues regarding Telegram’s encryption standards, suggesting that the platform’s lack of robust end-to-end encryption might allow authorities to access user data. Now Telegram could be compelled to hand over private communications to French authorities.
In response, Telegram has publicly defended its policies, arguing that it adheres to European Union laws, including the Digital Services Act, and that it is not responsible for abuses of the platform committed by users.
The arrest has sparked a wide array of reactions from prominent figures in the tech world. Notably, Elon Musk and Vitalik Buterin expressed support for Durov, highlighting broader concerns about freedom of speech and privacy in digital communications. Durov himself has previously voiced concerns about attempts by U.S. security agencies to gain control over Telegram’s operations, suggesting that his platform’s commitment to privacy and free speech has put it at odds with authorities in multiple countries
The second event: Brazil banned Twitter. The ban was motivated by escalating concerns about the platform’s handling of misinformation, hate speech, and disinformation, particularly during a critical election period. The Brazilian government accused Twitter of failing to take adequate measures to curb the spread of false information that could influence public opinion and disrupt the democratic process. Authorities cited Twitter’s non-compliance with local laws that require stricter moderation of harmful content, including hate speech and content that incites violence or spreads false narratives.
This move by Brazil reflects broader global concerns over the influence of social media platforms on public discourse and their role in amplifying harmful content. The ban is seen as part of a wider effort by the Brazilian government to regulate digital platforms more aggressively, ensuring they align with national interests and legal standards. The ban has raised debates over the balance between free speech and the need to protect the public from misinformation, echoing similar tensions faced by other countries grappling with the impact of social media on society.
I’m deliberately stating the facts of the incidents in a neutral way, mainly reflecting what the mainstream media has reported so far.
But I’m not neutral. I’ll be direct! I think these incidents are bogus! They are horse shit! Durov is in custody because the EU, UK, and US governments want access to all information on Telegram. Brazil banned Twitter because the government in power wants to control the information flow and is desperate to reshape the election narrative.
The USA, which is still the safest haven on this planet for freedom of speech, used to be the home of the free and the land of the brave. But with the current restrictions on freedom of speech, it will no longer be able to maintain that status. The land of the brave is not a place where butt-naked men hunt buffalo with their bare hands, or strong, sexy women fight bears just for fun while breastfeeding their kids. The land of the brave is all about freedom of thought and the right to pursue these thoughts; it is all about freedom of speech.
Why do I appeal to the land of the brave? Because this land, despite all the atrocities it has committed, is still the champion of freedom of thought and freedom of speech. The U.S. might have one thousand and one sins—which country doesn’t?—but it is also the country that teaches us the value of these freedoms. Even with its flaws, the U.S constitution is a powerful reminder of the importance of the right to think and speak freely, serving as an enduring symbol of these fundamental human rights.
The Constitution that Championed Freedom of Speech
Freedom of speech is a fundamental right enshrined in the U.S. Constitution, specifically in the First Amendment, which prohibits Congress from making any law abridging the freedom of speech or of the press. This right is rooted in the belief that free expression is essential to democracy, allowing for the open exchange of ideas, debate, and dissent without fear of government retribution. The First Amendment’s protection of free speech extends broadly, covering everything from political speech to protest, and especially to speech that might be offensive or unpopular.
In contrast, many European nations also value freedom of speech but often incorporate additional considerations such as hate speech laws, privacy protections, and the balance between free expression and social harmony. For instance, Germany and France have strict regulations against hate speech, Holocaust denial, and the dissemination of Nazi propaganda, reflecting a historical sensitivity to the dangers of extremist ideologies. The European Convention on Human Rights, which governs many European nations, protects freedom of expression but allows for restrictions deemed necessary in a democratic society for reasons such as national security, public safety, or the protection of the rights and reputations of others. This more regulated approach reflects a different solution to the balancing act between individual liberties and collective responsibilities compared to the United States.
The End of the Champion: The Clear and Present Danger
The “clear and present danger” test is a legal doctrine used to determine when limitations on free speech are permissible under the U.S. Constitution. Established in the 1919 Supreme Court case Schenck v. United States, the test was articulated by Justice Oliver Wendell Holmes Jr., who stated that speech could be restricted if it presents a “clear and present danger” of causing significant harm that the government has a right to prevent. For example, falsely shouting “fire” in a crowded theater, which could cause panic and harm, is not protected under the First Amendment because it poses a direct threat to public safety.
This standard was initially used during wartime to restrict anti-war protests or dissent that could disrupt military recruitment or operations. Over time, the test evolved. Notably, in 1969, it was replaced by the “imminent lawless action” standard set by the case of Brandenburg v. Ohio. The updated test requires that speech must be directed to inciting or producing imminent lawless action and be likely to incite or produce such action, setting a higher threshold for limiting free speech. This evolution reflects a greater emphasis on protecting speech rights while balancing public safety and order.
Alas! The doctrine of “Clear and Present Danger” breached the constitutional wall that protects freedom of speech. Since then, more parts of the wall have been pulled down. The doctrine of clear and present danger itself has become the number one clear and present danger to freedom of speech. Originally intended to justify limitations on speech in extreme circumstances, it has often been used to attack the very freedoms it was meant to protect. It threatens to make the threshold for restricting speech dangerously subjective and easily exploited.
Credit: Tesfu Assefa
O Freedom of Speech, Freedom of Speech Where Art Thou Freedom of Speech?
I challenged myself to find another champion of freedom of speech, so I began searching every corner of the internet for rules and regulations that grant humans the unrestricted and inalienable right to freedom of speech. Unfortunately, my search did not yield any good news. Nonetheless, I will share what I discovered here.
Freedom of speech across European nations varies significantly, reflecting each country’s historical, cultural, and legal context. In Germany, freedom of expression is protected by the Basic Law, but there are stringent regulations against hate speech, Holocaust denial, and the promotion of Nazi ideology. These laws are rooted in Germany’s historical experiences with extremism, and their desire to prevent hateful or dangerous ideologies from taking hold again. Some see these regulations as necessary for protecting public order and human dignity, they sometimes raise debates about the limits of free expression; can they be used as a pretext to censor and restrict any kind of speech? While my dad can shave in the Charlie Chaplin style, a German can’t because Hitler used to shave like that! I can’t shave like Charlie Chaplin because my beard is more of a side beard, and I shave in the Wolverine style. Now, the “toothbrush mustache” is like freedom of speech, but as I told you, restrictions can shape thoughts, and this style is completely out of the thoughts of all Germans!
In France, freedom of speech is a core republican value, enshrined in the Declaration of the Rights of Man and of the Citizen. However, France also enforces strict laws against hate speech, defamation, and inciting violence. Controversies over satirical depictions of the Prophet Muhammad exemplified France’s particular challenges balancing freedom of expression with respect for religious beliefs. These tensions highlight the delicate balance between upholding free speech and protecting public harmony, but one thing is sure: expressing one’s thoughts on Telegram will soon be out of the French people’s thoughts.
The United Kingdom generally enjoys a high level of freedom of speech, but it has notable exceptions such as laws against hate speech, libel, and certain national security-related restrictions. The UK has a robust press and a tradition of lively public debate, though recent concerns have arisen over the impact of anti-terrorism legislation and of surveillance practices on journalistic freedoms. Additionally, the UK’s libel laws are among the most stringent in Europe, which critics argue can be used to stifle legitimate criticism and investigative journalism. Seeing people like Piers Morgan freely debating transgender issues on public TV is now out of the Brit’s thought process.
In contrast, eastern European countries like Hungary have seen a decline in press freedom and freedom of speech in recent years. For some it is just a continuation from the Soviet era. Countries like Hungary use defamation laws to target journalists and media companies that criticize the government, leading to a climate of self-censorship.
The European Union has raised concerns about these developments, saying they are part of a trend of democratic backsliding in these countries. But who will listen? Doesn’t the very same organization restrict freedom of speech under pretexts like ‘clear and present danger’, ‘hate speech’, etc.? Is criticizing Putin anti-Putin hate speech?
Sweden, known for its strong protections of freedom of speech and press, has some of the most liberal laws regarding free expression in Europe. The Swedish constitution guarantees freedom of expression, and the country consistently ranks high in global press freedom indices. However, even in Sweden, there are restrictions on hate speech, particularly when the speech targets ethnic or religious groups. Again we see the ‘balancing’ act between free expression and protecting people from harm. The Swedish people will soon forget their natural right to criticize other cultures or religions – it is hate speech.
In short, none of the European nations have unrestricted freedom of speech laws. Yet there is a more dangerous trend: they are imposing more and more restrictions in the name of fighting clear and present dangers or “social harmony” over free expression.
Freedom of speech in South American countries varies widely. Some nations have strong legal protections while others face significant restrictions. In Brazil, freedom of speech is constitutionally guaranteed, but it is frequently tested by political and social disputes – like the recent Twitter ban. Brazil also has a weird defamation law, and it’s often used against journalists and activists, creating a chilling effect on critical reporting.
In Venezuela, freedom of speech is severely restricted under the authoritarian government of Nicolás Maduro. This is nothing new to folks in Venezuela because his predecessor Chaves has the same laws, no one can talk against the government! The state controls much of the media landscape, and independent journalists and opposition voices frequently face harassment, censorship, and imprisonment. Argentina, on the other hand, has relatively strong protections for freedom of speech, with a vibrant media landscape and active civil society. However, there are still challenges, such as political interference in public media and economic pressures on independent outlets. While the legal framework generally supports free expression, journalists occasionally face threats and violence, particularly when covering sensitive topics like corruption and organized crime.
In Colombia, freedom of speech is legally protected, but journalists and human rights defenders often work under threat due to ongoing violence related to armed conflict, drug trafficking, and corruption. Attacks on the press – including intimidation and assassinations – make it dangerous for media professionals to operate freely. The government has made efforts to protect journalists, but impunity for crimes against journalists remains a significant issue.
Chile generally enjoys a high level of freedom of speech, with strong legal protections and a diverse media environment. However, the country has faced criticism for the use of anti-terrorism laws against indigenous activists and the usual ‘occasional’ restrictions on protests and public demonstrations.
Freedom of speech in Asia varies significantly across different countries, reflecting a broad spectrum from highly restrictive environments (North Korea) to more open (South Korea) but still ‘regulated’ spaces. In China, speech is tightly controlled by the government, with heavy censorship of the internet, media, and even personal communications. The Great Firewall of China blocks access to many foreign websites, and criticizing the government can lead to penalties including imprisonment. Surveillance and censorship are pervasive, making China one of the most restrictive countries regarding freedom of expression, balancing the positives of its magical economic growth and perception as one of the world’s superpowers. Sadly, the champions of mankind are afraid of freedom of speech.
In contrast, Japan enjoys a relatively high level of freedom of speech, though it is not without its challenges. The Japanese constitution guarantees freedom of expression, and the media operates largely without government interference.
Right-wing groups in Japan have engaged in campaigns of character-assassination against media personalities who criticize them and offend their nationalistic sensitivities by publicizing the crimes of Imperial Japan. This backlash has led to self-censorship on topics that might offend right-wing groups. Defamation laws can also be used to suppress criticism: the same tactic we’ve just seen in Brazil and the UK. A series of laws – notably the 2016 ‘National Hate Speech Act’ – have expanded the government’s powers to act against the press and individuals, in the name of preventing hate speech and ensuring national security.
South Korea has a robust tradition of freedom of speech, bolstered by a strong democratic framework, since the Korean War of 1950-53. Still, there are limitations, such as the National Security Act, which restricts speech perceived as pro-North Korean or threatening to national security. This act even have scariest restrictions like “Any person who constitutes or joins an anti-government organization, shall be punished as follows…“Online speech is also monitored, and there have been instances of censorship, especially regarding controversial or politically sensitive content.
India presents a complex picture. Freedom of speech is constitutionally protected, but the implementation is inconsistent. While the media landscape is vibrant and diverse, the government is using laws such as sedition, defamation, and anti-terrorism statutes to stifle dissent and curtail press freedoms. In the most dramatic example of ‘defamation’ being used as a pretext to punish political expression, the Prime Minister of the world’s largest democracy recently threw the leader of the opposition in jail for criticizing him. Internet shutdowns, especially in regions like Kashmir, and increased pressure on social media platforms to remove content deemed objectionable by the government further underscore the precarious situation free expression is in in the world’s most populous country.
In places like Africa and the Middle East, freedom of speech faces significant threats. Here governments often impose harsh restrictions on political speech to maintain grip on power. In many African countries, such as Eritrea, Ethiopia, Cameroon, Rwanda, Sudan, Equatorial Guinea, and Zimbabwe, journalists and activists face assassination and imprisonment as part of their job description. In Africa and the Middle East, it is considered the unchallenged right of a government to use harassment and violence to punish those who criticize it.
Perhaps a compromise solution is best. Maybe it should be legal to murder a man for criticizing a government, but illegal to also chop him up into pieces? That’s when it goes too far (remember Jamal Khashoggi’s death). At least have the manners to kill him in a way that allows an open casket burial.
Both Africa and the Middle East are characterized by governments that freely apply repressive laws, internet shutdowns, and censorship as common tools used to silence dissent. However, in the Middle East, freedom of speech is also curtailed by religious authorities, because from the old guards, religion is still in power in the Middle East. Countries like Saudi Arabia and Iran employ strict laws against blasphemy, leading to severe punishments, including imprisonment and execution.
Surprisingly, the United Nations Universal Declaration of Human Rights includes an article that seemingly provides an unrestricted right to freedom of speech. However, the declaration is merely a paper tiger, as no nation on this planet abides by it: they say it is merely a treaty!
Everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers.
Article 19, Universal Declaration of Human Rights
In short, after my long and tiresome search, what I have discovered is that no nation in our world has granted freedom of speech unambiguous protection!
More than half of us globally are now living through a freedom of expression crisis (Credit: Article 19)
New Tyrants in the Old Stranglehold Game
Individuals, self-proclaimed liberals, and frightened minority groups have pushed back against freedom of speech in recent years. Their go-to tactic is labeling certain expressions as offensive, hate speech, or politically incorrect. While these movements often stem from a desire to protect vulnerable groups and promote inclusivity, they can sometimes cross into territory where they suppress open dialogue and dissenting opinions. This shift has created a climate where expressing controversial or unpopular views is not just discouraged but actively silenced. Even comedy is not exempt. Comedians, once seen as cultural commentators with the liberty to push boundaries, now face intense scrutiny and backlash for jokes deemed ‘offensive’ or ‘discriminatory’. With this rate, we will see one of them in the Hague for hate speech!
The new offense defenders or political correctness police, are stifling creativity, art, and humor! This is doubly dangerous because the new enemies of free speech are shaping culture, which is in turn shaping human thoughts – the young generation see an unquestionable consensus, and perceive it as how everyone expects them to think. It’s not a government or some not-so-cool religious zealot, it’s your friendly neighborhood liberal telling you how to think. The online and offline worlds are now characterized by heightened sensitivity to personal offense, and it can escalate to a total suppression of expression.
The new soldiers in the war against freedom of speech have managed to make anything clear and present danger. They’ve also demonstrated how very easy it is to stir up societal tensions around hate speech. A simple question like “what is a woman?” is no longer a simple question – in fact you are not allowed to ask the question because it’s considered hate speech against certain groups. I am just sad. This trend of labeling certain speech as unacceptable, whether it be jokes, criticism, or simply differing viewpoints, can lead to dangerous censorship that undermines the principle of free expression. Avoiding harm, and promoting respectful discourse are valid goals, yet the methods of enforcement too often involve silencing voices rather than engaging with them. This limits the marketplace of ideas, and sets a precedent where speech is judged by a subjective standard (offensiveness) rather than an objective one (harm).
Moreover, the concept of hate speech is sometimes stretched to include any speech that challenges prevailing narratives or makes certain groups uncomfortable, further narrowing the scope of acceptable discourse. The backlash against comedians, authors, and public figures for politically incorrect statements highlights a broader societal shift where the fear of offending has overtaken the value of open dialogue, ultimately posing a significant threat to the foundational right of freedom of speech.
If we are not free to speak our thoughts forth into the world, we are not free to shape our culture. Free speech is mainly about what is in your mind!
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