Beyond the Brain: Unveiling the Body’s Hidden Memory Network

For decades, scientists believed that memory was an exclusive function of the brain, carefully encoded by neurons. However, a groundbreaking study led by Nikolay V. Kukushkin at New York University challenges this notion, revealing that memory functions extend beyond the brain into other parts of the body. This discovery not only reshapes our understanding of memory but also opens new avenues for enhancing learning and treating memory-related disorders.

The Body as a Memory Archive

Traditionally, memory has been associated with the brain’s neural networks, but this research suggests that cells throughout the body also play a role in storing and recalling information. Just as a library extends beyond a single room, our bodies may house multiple archives of knowledge, each contributing to the overall memory landscape.

Kukushkin explains, “Learning and memory are generally associated with brains and brain cells alone, but our study shows that other cells in the body can learn and form memories, too.” This revelation raises the possibility that organs such as the heart, lungs, and even skin may contribute to our memory system, holding imprints of past experiences.

The Science of Memory Formation

The research builds on the well-established “massed-spaced effect,” a principle in neuroscience that suggests information is better retained when studied in spaced intervals rather than in a single cramming session. To test whether non-neural cells exhibit a similar phenomenon, Kukushkin and his team conducted experiments using human neuroblastoma and kidney cells. They exposed these cells to repeated pulses of forskolin and phorbol ester—chemicals that activate key memory-related signaling pathways.

Remarkably, these non-brain cells exhibited memory-like behavior. When exposed to spaced chemical pulses, they activated CREB, a transcription factor crucial for memory formation in neurons. To visualize this process, the researchers engineered the cells to produce a luminescent protein that glowed in response to memory activation, allowing them to track cellular memory formation in real-time.

The Massed-Spaced Effect in Non-Neural Cells

A key finding of the study was that non-neural cells responded more robustly to spaced stimulation than to massed stimulation. When the chemical pulses were delivered with intervals between them, the memory gene activation was stronger and more sustained. This mirrors how neurons process information in the brain, suggesting that memory mechanisms may be a fundamental feature of cellular function across different tissues.

One of the study’s most striking discoveries was the role of ERK and CREB signaling in cellular memory. ERK, a kinase involved in memory formation, was phosphorylated more effectively in cells subjected to spaced stimulation. Additionally, CREB activation was significantly higher in these conditions, further reinforcing the parallel between neuronal and non-neuronal memory storage.

Credit: Tesfu Assefa

Implications for Health and Learning

The implications of this research extend far beyond the laboratory. If non-neural cells possess memory-like properties, this could revolutionize approaches to medicine and education.

For example, understanding how cells retain information about past exposures could inform treatments for chronic diseases. Just as a chef refines a recipe based on past experience, our bodies might be capable of “remembering” metabolic patterns, helping to optimize blood sugar regulation or immune responses.

Kukushkin notes, “At the same time, it suggests that in the future, we will need to treat our body more like the brain.” This perspective could lead to breakthroughs in regenerative medicine, where cellular memory is harnessed to improve tissue repair, or in cancer treatment, where understanding how cells recall chemotherapy exposure might lead to more effective therapies.

A New Perspective on Memory

This research challenges the traditional view that memory is exclusively a function of neural networks. By demonstrating that non-neural cells can encode and retain information, it suggests that memory is a distributed property of biological systems. This could explain phenomena such as immune memory and metabolic adaptation, which rely on the body’s ability to retain and process past experiences.

As we deepen our exploration into cellular memory, we may uncover new strategies for enhancing learning, improving health, and redefining the role of memory in human biology. The body is no longer just a vessel for memories—it is an active participant in the intricate dance of learning and adaptation.

Conclusion

Nikolay Kukushkin’s research represents a paradigm shift in our understanding of memory. By showing that non-neural cells can exhibit memory-like behavior, it expands the boundaries of what we consider to be a cognitive function. This discovery has profound implications for healthcare, learning, and the future of memory research, opening doors to innovative approaches that treat the body as an integrated archive of experiences. As we continue to explore this emerging field, we may unlock new ways to enhance cognition, optimize health, and rethink the fundamental nature of memory itself.

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Should we still want biological space colonists?

I’ve always been a space cadet. Images from Apollo 8 and Apollo 11 burned themselves indelibly in my mind when I was very young. In between Apollo 8 and Apollo 11, the immortal film 2001: A Space Odyssey by Stanley Kubrick and Arthur Clarke also burned itself indelibly in my mind. I’ve always been persuaded that colonizing space is not only our right, but also our destiny and our duty. I’ve written a book about this.

In 2001, astronauts David Bowman and Frank Poole are accompanied by the artificial intelligence ‘Hal’ crewing the spaceship ‘Discovery’.

“Whether Hal could actually think was a question which had been settled by the British mathematician Alan Turing back in the 1940s,” says Clarke in the novel written with the film. “Hal could pass the Turing test with ease.” Both the novel and the film leave us with the impression that Hal is a conscious being like us.

“Poole and Bowman had often humorously referred to themselves as caretakers or janitors aboard a ship that could really run itself,” says Clarke. “They would have been astonished, and more than a little indignant, to discover how much truth that jest contained.”

Human-level AGI and conscious machines could be imminent

Clarke doesn’t answer (or ask) the obvious question of why not send just Hal. My young self didn’t think of this question either, for it seemed obvious to him that Bowman and Poole were the real space explorers. He identified with them, not with Hal.

I’ve kept this preconception for decades. But in these decades I’ve been slowly warming up to the idea that AIs could be conscious beings like us. This seemed to me, however, a long-term prospect (decades or centuries, not years).

But AI technology has been advancing very fast in the last couple of years. Now I think that current AI technology could be on the right track. If so, Human-Level Artificial General Intelligence (HL-AGI) and conscious machines could be imminent. It seems very plausible to me that, very soon, we’ll see an AGI pass the full Turing Test and credibly claim consciousness.

I think machine consciousness will be a strange type of consciousness at first. It will have a wholly other texture, very different from human consciousness. But then further advances could bring machine consciousness closer to human consciousness. AIs in robotic bodies, trained with real-time interactions with humans, could experience a more human-like consciousness.

Then the conclusion that AI robots are persons will be inescapable, and we space enthusiasts won’t be able to avoid the obvious question. Why not just send robots to colonize space?

The obvious advantages of robotic space colonization

Once we achieve HL-AGI and have fully autonomous conscious robots, sending humans to colonize space will seem inefficient. Robots can handle space’s vacuum, radiation, and temperature without the needs of life support systems.

They won’t require food, water, or air, reducing the cost and complexity of missions. Robots don’t age or die like humans, meaning less frequent replacements or resupply missions. If one is destroyed, its knowledge isn’t lost; that is backed up somewhere else.

Their computational power and decision-making capabilities will surpass human limits, enabling them to adapt and solve problems more effectively. Robots don’t sleep. Robots can work non-stop, maximizing productivity in space colonization tasks.

They can repair and upgrade themselves, further cutting costs and human intervention. Humans bring emotional and psychological needs that complicate space travel; robots don’t suffer from isolation or stress. The financial and logistical burden of human safety, health, and comfort in space is immense.

Conversely, robots can be designed for specific tasks, like building habitats or mining resources, without the need for extensive training or support. In summary, robots would be cheaper, more durable, and more efficient, making human-led space colonization less practical.

Credit: Tesfu Assefa

Mind children

OK, but… but…

But we want real people like us to colonize Mars, the solar system, and then the stars! Persons! Not robots!

This is a totally understandable emotional reaction. But, as I say above, the conclusion that AI robots are persons could soon be inevitable.

I’m too old (and probably so are you) to participate directly in the beginnings of space colonization in the solar system. But I would identify with younger persons in space and think that I’m participating through them. But then, if AI robots are persons, it seems evident that I should be able to identify with the robots as well.

I’m slowly and gradually warming up to this perspective.

And after HL-AGI, we’ll have robots with artificial superintelligence (ASI). They – our mind children – will become cosmic engineers among the stars.

Our cosmic destiny is to spread intelligence and meaning into the cold universe, and our mind children will achieve our common cosmic destiny.

“We are now preparing to hand the gift of knowing on to new forms of intelligent beings,” said James Lovelock, the prophet of Gaia, in his last book. “Do not be depressed by this. We have played our part.”

I’m proud of having played my little part as a human being (release 1.0) of the 20th and 21st century, and we all should be collectively proud of giving birth to our mind children. The universe belongs to them.

On a less gloomy note, I’m persuaded that humans and machines will merge and co-evolve, eventually becoming one and the same thing. So we will be our mind children, and they will be us.

Once we see humans with AI implants and AIs with human implants (e.g. mind grafts from human uploads) we’ll know for sure that the co-evolution of humans and machines toward our common cosmic destiny has begun. But I guess it has already begun.

Back to the question

Based on all the considerations above, wasting time and resources with biological space colonists doesn’t seem to make sense. Let’s save all that money we spend on crewed space programs. Let’s build conscious HL-AGI robots first – the first generation of our mind children – and send them to colonize the planets and the stars. We’ll be there through them.

The logic of this seems very solid. However…

However, there are at least two consideration that suggest that we should continue to pursue conscious HL-AGI robots and human space expansion in parallel.

First, predictions fail. I said that we’ll have HL-AGI and conscious autonomous robots soon. But what if I’m wrong? Getting a solid start in space expansion is very important and urgent (see my book). Therefore, we should get started now with the technology that we have today instead of waiting for new technology that is not guaranteed to arrive soon.

Second, crewed space programs have demonstrated and continue to demonstrate a unique potential to motivate brilliant young people to become scientists and engineers. Those brilliant young people motivated by the dream to colonize space would accelerate the development of future technologies, including HL-AGI and then ASI.

So forget what I said, and let’s build those little crewed outposts on the Moon and then Mars. Our mind children will likely take over one day, but let’s have some useful fun before.

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Top Altcoin Charts to Watch in 2025

Introduction

Cryptocurrency markets change quickly, so it is important for investors to monitor key metrics that show market trends, performance, and sentiment. This two-part series shares 20 charts every crypto trader should know. 

In Part 1, we explored critical Bitcoin charts to help investors understand the bigger picture. Now, in Part 2, we turn our attention to altcoin charts, diving deeper into metrics that reveal the performance and potential of altcoins. Whether you’re tracking DeFi activity, NFT adoption, or market sentiment, these charts provide valuable insights to navigate the ever-changing crypto landscape.

Let’s explore ten essential altcoin charts every trader should follow!

Altcoin Charts

These charts provide essential data to understand altcoins’ market position, performance, and future trends.

1. Top Altcoin Market Capitalization

Credit: TradingView and CoinMarketCap

The market capitalization of top altcoins measures the total value of circulating non-bitcoin cryptocurrencies like Ethereum (ETH), Solana (SOL), and Cardano (ADA). A rising market cap signals growing investor confidence, often due to positive upgrades or increased adoption. For example, Ethereum’s Shanghai upgrade boosted demand as stakers could withdraw and re-stake more efficiently.

This chart helps traders:

  • Spot ecosystem shifts: See which altcoins lead during bullish phases.
  • Identify market risks: Sharp drops may indicate regulatory concerns or project issues.

Tracking these data helps investors understand capital flows and recognize potential trading opportunities.

2. Ethereum Gas Tracker

Credit: Blockchain.com, Etherscan, and Dune Analytics

The chart of Ethereum gas fees tracks the average transaction fees on the network, offering insight into network demand. Spikes in fees signal network congestion, and often happen when DeFi activity surges. For example, gas fees skyrocketed during popular NFT drops.

High fees can prompt users to explore alternatives like Arbitrum or Optimism, which offer lower-cost transactions.

This chart helps traders plan their transactions and spot trends indicating when the network is under heavy load.

3. DeFi lending/borrowing Volume Chart

Credit: DeFi Llama
Credit: CoinGecko

The chart of DeFi lending/borrowing tracks the total value of the assets that are lent and borrowed across decentralized finance protocols. When borrowing volumes rise, it can indicate increased market speculation that drives liquidity demand, like during bull runs when traders take leveraged positions. Conversely, a drop in borrowing suggests caution, with investors retreating to stable assets.

This chart helps traders assess market sentiment and shifts in DeFi activity. Platforms like Aave and Compound often reflect these trends, signaling key turning points in market confidence.

4. Layer-2 TVL chart

Credit: L2Beat

The Layer 2 TVL chart monitors the Total Value Locked (TVL) in Ethereum’s layer-2 solutions, such as Arbitrum and Optimism. Rising TVL highlights growing adoption of these networks for cheaper and faster transactions, often driven by demand from DeFi, gaming, and NFT projects. For instance, Arbitrum saw a TVL surge in 2023 due to increased liquidity in its DeFi ecosystem. 

These metrics are essential for understanding user migration from Ethereum’s mainnet to Layer 2s, which can boost altcoin prices associated with the networks.

Credit: Tesfu Assefa

5. NFT marketplace volume by blockchain

Credit: DappRadar and OpenSea Analytic

The NFT marketplace volume chart tracks trading activity across blockchains like Ethereum, Solana, and Polygon. High trading volumes often signal strong demand for NFTs, indicating where the action is in the underlying altcoin ecosystem. A rise in activity on alternative chains could mean they’re gaining adoption over Ethereum in specific niches. For example, Ethereum dominates the NFT market, but Solana and Polygon have gained traction due to lower fees and faster transactions, according to NFTScan.

6. DeFiLlama narratives tracker

Credit: DeFiLlama

The DeFiLlama narratives tracker highlights trending themes and sectors in the cryptocurrency market, such as liquid staking, Layer 2 adoption, or real-world assets (RWAs). By aggregating data from DeFi protocols, this tool helps investors spot emerging narratives that drive market activity and influence altcoin performance.

For example, during the rise of liquid staking platforms like Lido, the tracker showed increased capital flow, signaling a key opportunity for altcoin growth. Traders can use this tool to align their strategies with market trends and identify early movers in the DeFi ecosystem.

7. Social media sentiment analysis

Credit: LunarCrush

The social media sentiment analysis chart tracks discussions and emotions surrounding cryptocurrencies on platforms like Twitter, Reddit, and Telegram. Positive sentiment often indicates growing interest, while negative sentiment may signal caution or fear among traders.

For example, a surge in mentions of altcoins like Solana or Polygon during major announcements can reflect community excitement and potential price movements. Conversely, rising negative sentiment could foreshadow selling pressure.

This chart helps traders understand market mood, and identify when hype or skepticism could influence price trends. Analyzing sentiment alongside other metrics provides a broader view of market dynamics.

8. Wallet activity tracker

Credit: Cielo.finance

The wallet activity tracker monitors what’s going on in blockchain wallets. This could be things like large transactions, active addresses, and changes in wallet balances. An uptick in wallet activity often reflects growing interest or significant market moves. For instance, spikes in Ethereum wallet activity during DeFi booms indicated increasing participation in staking and trading.

Sudden large transfers from whale wallets to exchanges can signal potential sell-offs, while rising balances in non-custodial wallets suggest accumulation.

This tool helps investors track shifts in market dynamics, offering early signals for price changes.

9. Staking participation rate by altcoin

Credit: Staking Rewards

The staking participation rate measures the percentage of an altcoin’s total supply that is locked in staking. This can be viewed as a measure of long-term confidence in the network. Coins like Ethereum (ETH), Cardano (ADA), and Solana (SOL) rely on staking to secure their Proof-of-Stake (PoS) networks.

A higher staking rate indicates trust in the network’s future, because it means stakers are locking their assets to earn rewards, thereby supporting network stability. For example, Ethereum’s transition to PoS boosted its staking participation, reflecting optimism about its scalability and growth.

This metric is a critical indicator for investors evaluating the health and long-term potential of altcoin ecosystems.

10. Meme coin market cap chart

This CoinMarketCap chart helps investors understand speculative trends and gauge market phases where meme coins thrive.

Credit: CoinMarketCap

The chart of meme coin market cap tracks the total value of popular coins like Dogecoin (DOGE), Shiba Inu (SHIB), and Pepe (PEPE), as well as lesser-known ones. Meme coins often see spikes in market cap during bullish phases, fueled by community hype, social media trends, or celebrity endorsements.

For example, Dogecoin’s surge during Elon Musk’s tweets showcased how sentiment can drive speculative activity. Rising meme coin dominance reflects high-risk appetite among traders, while declines suggest a shift toward more serious assets.

Conclusion

There are a myriad of charts to steer you through the altcoin markets. These ten examples, along with the Top Ten Bitcoin charts in part 1, will help you keep your bearings in these stormy seas. Godspeed cryptonauts!

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From VUCA to BANI: Futurist Jamais Cascio Helps Navigate the New Chaos

I’ve been talking with Jamais Cascio off and on for a couple of decades. About a month or so ago, he posted about completing a new book titled Navigating the Age of Chaos: a Sense-Making Guide to a BANI World That Doesn’t Make Sense

Researching the latest from Jamais, I came across two tropes or memeplexes that I was unfamiliar with – VUCA and BANI. Jamais, who has long been a highly respected thinker and scenario builder in the world of futurists, had shifted much of the discourse from YUCA to BANI. From what to what?

VUCA = Volatility, Uncertainty, Complexity, Ambiguity

BANI = Brittle, Anxious, Nonlinear, Incomprehensible

I will steal a brief biographical note about Jamais from his website: “Selected by Foreign Policy magazine as one of their Top 100 Global Thinkers, Jamais Cascio writes about the intersection of emerging technologies, environmental dilemmas, and cultural transformation, specializing in the design and creation of plausible scenarios of the future.” I will let my email exchange with Jamais take it from here.

RU Sirius: I had heard nothing of VUCA and BANI until I saw your post about completing a book on it. There are so many separate intellectual groupings these days. How would you characterize the people who have been part of this discourse around VUCA and who now are attentive to your new BANI suggestion?

Jamais Cascio: VUCA was developed in the late 1980s at the US Army War College. Through the 90s it was primarily (although not exclusively) a tool for military strategists and planners to think about the larger picture. After 9/11, a whole bunch of business consultants and strategists adopted the language, and within a few years it was the default term to sound smart while talking about the complexities of global existence. Folks at the Institute for the Future, where I had been doing most of my work, had widely adopted the VUCA phrasing and framing.

When I conjured up BANI as a way of giving a better framing for what I saw happening in the world, I didn’t expect it to get much traction. And, to be honest, it didn’t when I first talked about it in late 2018. After COVID-19 hit, a friend who had seen the original presentation pushed me to make it public. I published it on Medium in early April of 2020, and within a few weeks it was getting thousands of hits daily. By late 2020, I was regularly seeing it being used around the world.

With a handful of exceptions, the people who first embraced BANI as a language for making sense of the world came from the Global South. Brazil and Latin America at first, but very quickly South Asia and the Indo-Pacific. To this day, the vast majority of links I see to the BANI concept come from places like India and Malaysia, but I get pings from Russia, Ukraine, China, Vietnam, and more. Most of the places that have started to use BANI as part of their normal strategy (business or political) discussions are places that seem to be facing considerable chaos.

VUCA still gets used quite a bit, and often the two are used in tandem (“Our VUCA-BANI world”). From what I can see, VUCA is still embraced in parts of the world where systems seem to be more functional than not, while BANI has really taken hold in places that seem to be overwhelmed by things.

RU: I’m thinking back to your association with Worldchanging. So much has changed since that time. I think of Worldchanging as having had the thin hope for a utopian or at least broadly positive future and that now you’re talking about navigating dystopia or in fact apocalypse (as represented recently by the LA fires). Would that be an accurate read? 

JC: Yes and no. One of the underlying conceits of Worldchanging was that we fully recognized the dire state of the world, but wanted to focus on what could be done about it rather than dwelling on the disasters. Alex Steffen referred to it as “clear-eyed optimism,” and that phrase feels right. But nowhere in the Worldchanging prècis did we underplay how absolutely catastrophic things were starting to be.

BANI builds on that to an extent, as one of my main arguments remains that we have all of the knowledge and tools we need to make a big difference now, but we don’t yet seem to have the desire/will to do so. It’s not a question of waiting for the right technologies – the Singularity is not a sustainability strategy – nor is it a situation where we simply don’t know what we’re facing. We know what’s going on. We know how to push back against disaster. We have not yet chosen to do it.

BANI offers a language for articulating and better-understanding the nature of what’s happening, in part because we can’t resolve a problem if we don’t recognize it, and in part because using a structured understanding of reality helps to understand why much of this chaos seems so unexpected. The difference in tone between Worldchanging and BANI comes from roughly 20 years of seeing the Worldchanging solutions being ignored or denigrated.

Worldchanging told you not to Fuck Around; BANI is when you Find Out.

RU: There’s a possible problem with the notion that we know how to push back but we’re not doing it. It’s the problem of ‘we’. William Burroughs used to always say “there is no we.” There are people with oligarchical wealth and there are all varieties of nation-states and billions of humans married to a wide variety of ideologies, memeplexes, religions etc. So the heavy lift is in the politics… the power and wealth wielded by some, the variations in awareness with everybody else, all that massive complexity… that’s a huge lift! I appreciate the work you’re doing trying to puzzle it all out. I appreciate the emphasis on resilience and empathy. Can you share other strategic thoughts?

JC: I fully agree that the presence and expanding power of oligarchical wealth is one of the big barriers to structural change. And you’re right about the variety of clashing beliefs. I suppose that when I say ‘we’, I mean it in the simplest sense: humankind. Human civilization as a whole.

Outrageous wealth will protect you individually from the dangers of a BANI world, but cannot protect the system upon which your wealth and power is based. A multi-billionaire locked into his safety cave surrounded by robot guards might live out the rest of his life (and you know it would be a “his”) in peace and comfort, but would not be able to do anything with his wealth.

The thing about a global crisis (or, really, overlapping set of crises) is that, eventually, it will affect everyone, even those who can temporarily keep themselves safe. A collapsing Atlantic Meridional Overturning Circulation will not only hurt the poor. Movements driven by misinformation and rage will eventually be enraged at you, too.

In the upcoming BANI book, Navigating the Age of Chaos: A Sense-Making Guide to a BANI World that Doesn’t Make Sense, we talk about both BANI and BANI+, a set of responses to the BANI dynamics, shoehorned into a BANI format, too.

B=Bendable, resilient, flexible, adaptive
A=Attentive, empathetic, accepting, willing to listen
N=Neuroflexible, improvisational, experimental, iterative
I=Interconnected, inclusive, diverse, open

All of these BANI+ ideas boil down to a willingness to be adaptive, to not rely on existing (and increasingly outdated) scripts, to be able to recognize the changes that are happening and not rely on expectations and predictions. BANI shows that our expectations about the world are too often just illusions; BANI+ cautions us to not let our responses be trapped by calcified expectations, too.

Unfortunately, the political winds have made some of these concepts unappealing to some. We had initially considered making the I in BANI+ ‘Inclusive’, but got so much pushback from people we realized that we had to change it. 

My most recent Medium piece on BANI puts the responses in the context of seeing the 2024 US election as a BANI event (using older terms before we settled on the final language of BANI+).

RU: I want to push a little more on the political and cultural complexity of dealing with so many different belief systems – and what I would view as toxic belief systems. It appears to block solutions based on human decision-making at a scale that is big enough to address the issues humankind faces. I agree with your earlier comment that waiting around for a Singularity or some great technical hacks to solve our urgent situation is not a good response. But, although we can’t rely on tech solutions, I often think that tech solutions might have more chance of averting pending disasters than the behavior of humans and their institutions. Your thoughts?

JC: I have a couple of immediate responses, then I’ll dig a bit deeper.

The first is that tech solutions are very much a part of how we deal with many of the large-scale global crises, bearing in mind that our technologies are also cultural artifacts. The way our cultures evolve will shape the importance we place on tools and tool capabilities. But, overall, tech of a wide variety is critical and will continue to be.

The second is that over the past decade or so I’ve been doing a bit of what I call ‘foresight forensics’. That is, I look at old forecasts and scenarios that I’ve done, old enough that we’re now roughly in the period those forecasts describe, and compare them to reality. 

Right off the bat, I need to tell you that I do not believe that a forecast needs to be “correct” to be useful. Forecasts and scenarios are not meant for investment planning, they’re meant to make the reader more conscious of and sensitive to the nuances of what’s changing in the world. 

But at a broad level, the forecasts and scenarios that I’ve worked on have been largely on-target as to the kinds of technological impacts we’ve seen with (e.g.) self-driving cars, ubiquitous networks and cameras, biotech, that sort of thing. Where they’ve been terribly, hilariously wrong, in nearly every case, has been in any forecasts that rely on people changing their behavior to reflect a desire to improve their world and their futures. Some people will do it, but rarely enough to make a real difference, and rarely with improvement as a goal. When we’ve successfully changed behavior, improving the world is usually a side-effect, not the intent.

When I argue that “we” (human civilization as a whole) have the knowledge and the technologies needed to push back against climate catastrophe, resource collapse, etc., the second part of that argument is that we have not demonstrated the will to do so. We can, but will we? That overly-simplistic statement is meant to encapsulate the panoply of forces that work in opposition to global rescue: the ideological, the financial, the geopolitical, the religious, the petty – all of the human forces that focus on gaining advantage now with little attention paid to the future.

The irony is that one of the most visible movements to embrace a long-term perspective is essentially a roundabout argument for doing nothing now. It argues that focusing resources and funds and attention on solving present-day problems slows the advances towards Revolutionary, World-Changing, Transformative super-technologies that will improve billions if not trillions of future lives, someday. It’s pure coincidence that the progenitors of those R,W-C,T super-technologies just happen to be the products and services that will make a narrow set of people even more wealthy today.

I’ve been mulling the question of what has driven the move from a VUCA world to a BANI world. I don’t have any final answers, but a handful of things keep popping up: 
the ability to easily see acute manifestations of chronic problems without useful context; 
the role of algorithmic curation of media/social media with a focus on increasing advertising revenue; the increasing concentration of wealth and political power into a shrinking number of hands, and the corresponding changes to the economy and culture to favor them; 
and all of this in the larger context of environmental systems that have been over-stressed, leading to abrupt disruptions that the other three forces are more likely to worsen than to ameliorate. 

This is my gut sense now. It’s not in the Navigating The Age of Chaos book, just (again) something I’m mulling. I’m probably wrong.

RU: When we talk about brittleness and anxiety being defining aspects of our moment, this isn’t just the words of those trying to comprehend the future and make suggestions. These are taxing emotional states that humans are experiencing everywhere. Perhaps it’s even more difficult for people in the West who are accustomed to a certain comfort level. This is not a good way to live. And yet these are the conditions. General thoughts?

JC: You’re correct, and that was the intent. From the beginning, I meant BANI to encompass not just the more abstract aspects of the world, or the big-picture/big-system stuff like climate, but also the lived experiences of people in this world. The inclusion of Anxiety came directly from reading posts by younger people on places like Reddit about what’s going on in their lives, and the very real fear many of them felt about their futures. Brittleness describes the personal experiences as much as it does big systems like democracy or climate. Nonlinear is a fancy way of saying disproportionate (at least in the BANI context), and lots of us feel like our ability to act keeps diminishing as power and wealth become ever more concentrated. And incomprehensible… something I don’t outright say in the book but heavily imply is that “incomprehensible” can be boiled down to the things that happen that make us simply say “what the fuck?”

And yes, it’s taxing. In the book I elaborate quite a bit on how Anxious often manifests as despair. Despair is deadly.

The irony of the present circumstances for the West is that our material lives are (as a whole) better than ever, with better gadgets and services and new ways to do our daily tasks, even as the bigger systems like climate and democracy are collapsing. The deck chairs on the Titanic have never been more beautifully arranged.

But I also make a point of saying that what we’re talking about with all of these crises isn’t apocalypse. It’s not the End of the World, even figuratively. What it will be like, is already like for a rapidly-growing proportion of the planet, is misery. Our lives will be increasingly filled with misery as these systems break and our so-called leaders do nothing but try to figure out how to make a quick buck on the crisis.

RU: And beyond that, do you have any thoughts about how people who have lived through the 20th century with high – or even utopian – expectations, can cope with and maybe even enjoy life in this world as it is?

JC: I saw a comment today about embracing uncertainty. We (as Americans, as folks in the post-industrial world more generally) tend to associate uncertainty with danger – and quite appropriately so, really, if history is any indication. But uncertainty can mean that awful outcomes are not guaranteed. Recognize that better outcomes are possible, but also act to support that outcome happening. I want to be honest… but that usually means that I’m not very reassuring! Right now, any kind of response about ‘enjoying life’ feels like spouting bullshit.

RU: On LinkedIn you asked people how they use BANI in their work. What were one or two of the most interesting responses and why?

JC: I got a few responses with some details, but they mostly boiled down to this (this text is pulled directly from the book draft): 

• BANI is a new perspective. Very often those of us who think about the world and try to derive insights get locked into particular mindsets and points of view. They’ve worked before, why wouldn’t they work now? By bringing in a reframing of the situation, one that is simultaneously familiar in structure but novel in perspective, we have an opportunity to look at the set of dilemmas and problems in a new context.

• BANI offers a distressingly accurate depiction of the challenges we face at present, and a likely vision of what the next few decades will hold. It’s not that it tells us something new, necessarily, but it offers a narrative of the world that fits better with what people have been experiencing. It’s more than a tool for business consultants and futurists, it’s a perspective that can be applied to any structured approach at understanding human behavior amidst disruption.

• BANI focuses on the human, emotional aspects of disruptive change. BANI is not quantitative or mechanical; it’s much more about how people – from leaders to citizens – feel about what they are experiencing in a chaotic world. How people feel about their lives is a critical determinant of the decisions they’ll make.

• BANI reflects the sometimes-overwhelming levels of disruption caused by the chaos around us, but frames this disruption as being in the form of dilemmas, not problems. Problems can be solved. Dilemmas usually don’t have a single solution or answer; more often, dilemmas must be responded to in a way that minimizes harm, even while recognizing that the challenges they pose won’t completely go away.

• BANI acknowledges that what we are experiencing is real. BANI reassures people that what they’re seeing, feeling, living through is real. We are often afraid to express our worries, thinking that we may be exaggerating the problems or overreacting to bumps in the road. But what we’re experiencing now and will experience in the years to come does differ from the past.

One thing that needs to be emphasized is that the chaos we’re experiencing is because our crises are combinatorial. It’s not just that we’re seeing a surge in fascism, for example, we’re doing so amidst an acceleration of climate disruption, the metastatic growth of social media influence, the spread of hallucinatory AI into seemingly everything, the biggest land war in Europe since 1945, multiple genocides happening around the world, and more and more. Each of these is a major crisis in and of itself, but they combine and co-evolve in unprecedented ways.

Credit: Tesfu Assefa

RU: Mindplex Magazine is oriented towards people who are excited about the current hoopla about AI and the possibility of AGI. Can you give us a capsule summary of how you view the current state of AI and where it fits into your scenario? And, if your view is pretty much negative or dismissive, can you think of a way it can be set off in a better direction?

JC: This is a difficult question/set of questions, because there’s both the current state of AI technology and the high-likelihood future versions of AI technology at play here.

With regards to present-day AI, I call LLM systems ‘spicy auto-correct’. We very often see that ChatGPT and Grok and Gemini give answers that may be linguistically correct, with accurate syntax and tense agreement, but completely senseless, because the LLMs don’t understand anything, they provide a viable choice for the next word in a sentence. It’s more sophisticated than your phone’s auto-correct, of course, but it still has a mathematical understanding of language rather than a meaning-based understanding. An AI system arguing that water freezes at 32°F, so it’s still liquid at 27°F, does not actually understand what “freeze” means; it just relies on the statistical likelihood that if a number is a target, a number lower than it hasn’t reached the target conditions.

This should not be surprising. It’s the John Searle Chinese Room argument. The thought-experiment is about a room with a non-Chinese-speaking person with a box of Chinese characters and a set of rules as to which characters to output if a given set of Chinese characters comes in. Searle asks if this person or system is intelligent or knows Chinese. My take is that the room in and of itself is not intelligent, but could well be a component of a larger intelligent system. LLMs are not AGI; they’re at best a possible component of a future AGI.

My main concern about present-day AI (which is largely, but not exclusively, LLM-based) is the way it’s being pushed into everything with a chip, and users are pushed to rely on the technology. Especially given the biases of source data. Especially given the unethical sourcing of data. Especially given the increasing levels of auto-cannibalism. Especially given the likelihood of hallucinations and confabulations, and the overwhelming presence of AI slop (AI-generated books on Amazon, AI-generated images at the top of Google Image search, etc.). AI tools are being put to use in situations where they’re simply not appropriate or really useful. LLMs like ChatGPT should never be used as a search engine, yet Google puts an unavoidable “AI Overview” on many/most of their search results. Then you have situations where the owner of the LLM platform doesn’t like the responses and the changes the rules (Grok!).

And don’t get me started on the energy issues.

And you have multiple examples of CEOs thinking that they can get rid of their mid-level staff (writers, coders, etc.) and replace them with AI – only to find that what they’re getting is crap. It’s not just that AI is a catalyst for job loss, it’s that AI is a catalyst for job loss while (often? usually? nearly always?) doing the job worse.

Present-day AI is bad because it’s made unethically (bias, copyright, energy), used inappropriately, and pushed to unsuspecting and non-consenting users.

With all of that said, this ‘AI-is-bad’ moment is not permanent. 

At some point, the bias issue will be compensated for, the source material will be more trustable, the hallucination, and the confabulation problem will be solved (or at least controlled), and the overviews and summaries will actually be accurate. 

It remains to be seen whether LLM-based generative AI leads to some version of AGI, but either way advanced LLMs will eventually be useful and accurate enough to do many of the tasks it’s being asked to do now. Moreover, I do believe that AGI is possible, although my suspicion is that it will look nothing like what most people expect. I’m by no means an expert in the subject, but I think that an AGI that is the emergent result of a human-like neural structure – a brain emulation, if you will – is more likely to be recognizable as ‘sapient’ than an AGI built from entirely novel processes.

Real AI/AGI will be transformative. What we have now is more akin to a get-rich-quick bubble of too-often harmful technology.

How to make it all better? For now, my number one answer is stop making it part of everything even vaguely digital. What we have under the flag of ‘AI’ can’t be relied upon to do correctly much of what it’s being tasked to do. That doesn’t mean that it can’t do it, period, but that in too many cases the accuracy of the response can’t be depended upon. And is often unnecessary and wasteful.

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Could generative AI be on the right path to AGI?

Some time ago Ben Goertzel reported that somebody told him: “For the camp that continues to claim that throwing massive amounts of compute at LLMs isn’t a reasonable path to AGI… I don’t know if that’s accurate anymore.”

Ben then argued to confirm that no, throwing more and more computing power at large language models (LLMs) isn’t a reasonable path to artificial general intelligence (AGI).

The overall flavor of Ben’s arguments is captured by his analogy with music: music generation models trained on music up to the year 1900 “will not invent progressive jazz, neoclassical metal, grunge, acid house, etc. etc. etc.” I’ll come back to this analogy.

I’ve long been persuaded that Ben is right on this point. However, I’ll play devil’s advocate and try to argue that, yes, LLM-like big data crunching could be all (or almost all) of general intelligence.

Could statistical data crunching be almost enough?

I asked this question on social media, including the SingularityNET forums: Perhaps language is all there is? Or most of what there is? What I mean is that we could consider all forms of interacting with the rest of the world as a generalized form of language, and perhaps a generalized type of transformer technology with suitable training input would reproduce all aspects of cognition just like LLMs reproduce language.

Predictably, I received very skeptical replies. Come on, really now. How can language be all there is?

Ben conceded that everything is a language in some sense, but argued that real AGI will need a new framework of which today transformer-based LLMs could well be a part, but only a small one. Ben makes this point in his last book: “the basic architecture and algorithmics underlying ChatGPT and all other modern deep-NN systems is totally incapable of general intelligence at the human level or beyond, by its basic nature,” he says. “Such neural networks could form part of an AGI, sure – but not the whole cognitive part.”

But perhaps we shouldn’t dismiss the possibility that, yes, a generalized form of language could be all, or most, of what there is to AGI. The possibly at least merits further thoughts.

I’m not expressing a conviction, but a hypothesis. Current generative AI is not good enough for AGI. But what if it is almost good enough?

Let’s go for a drive

The example that comes to my mind is driving. When I’m driving, I use decades of experience with the ‘language’ of driving in the street. This language is composed by tokens like steer right/left, speed up, slow down etc. My experience tells me which token to ‘utter’ next, even without formal rules. All drivers know that in certain situations one should slow down, even if one is not able to say exactly why. It is your hands and your feet that know, so to speak. It seems to follow that a suitable ‘LLM’ trained with millions of hours of street videos of people driving – maybe call it an ‘LDM’, a Large Driving Model – could drive pretty well.

Could generative AI methods enable an AI, trained on a very large repository of videos of people driving in all sorts of different situations, to drive a car well enough? I think this hypothesis is worth exploring.

OK, maybe driving. But AGI? Come on.

Well, of course AGI will need other things as well, for example reasoning models for logical thinking, inference, mathematics and that sort of things. And some good old Bayesian reasoning of course. But I think of those subsystems as a very thin surface layer on top of a very thick bulk.

Vectors in the mindscape

If you ask me if there is a largest prime number, I’ll answer that no, there isn’t, and I’ll tell you exactly how I have reached that conclusion. But ask me why I like this particular woman at first sight instead of liking that other woman? The only honest answer I can give is that I don’t know (or care), but I still like her at first sight.

Do you still want an intellectual answer? Well, I guess there must be some vector that represents this woman in the bulk of my hugely multidimensional mindscape, and the tip of the vector comes close to some ideal woman.

But isn’t this a good description of what LLMs do?

So I’m entertaining the idea that some kind of LLM on steroids could be a good model for most of my mind. I claim to be generally intelligent, so it follows that some kind of LLM on steroids could achieve general intelligence. Of course the LLM should be complemented and enhanced by other things. But it would be the major part of a general intelligence, not a small one.

So I do agree with Ben, but with a difference in emphasis. He sees the LLM glass half empty, but I see it half full.

Perhaps I should have said that today’s early LLMs are on the right path to reproduce not general intelligence (the surface layer), but the more primitive intelligence (the bulk) that enables us all animals to stay alive in the cold, unforgiving universe out there. But I suspect that the gulf between the two is not that wide.

Credit: Tesfu Assefa

Active inference

There are interesting parallels and analogies between LLMs and a theory of sentient behavior called active inference, originated by Karl Friston and other scientists. The theory suggests that sentient life forms act upon their environment to build and continuously refine an internal model of the environment.

This is not limited to sentient life but rather is “something that all creatures and particles do, in virtue of their existence,” suggests Friston. The theory is based upon a “free energy principle” that has been proposed to unify information, thermodynamics, and biology. “For Friston, the free energy principle explains all features of living systems,” notes Anil Seth, and is “as close to a ‘theory of everything’ in biology as has yet been proposed.”

The analogies suggest that, perhaps, today’s early LLMs manifest the same universal forces that produced you and me.

And what about consciousness?

Thomas Nagel, in ‘What is it like to be a bat?‘, said conscious exists when it’s “like that” to be a certain being. In that sens, I am persuaded that it will be “like something to be an LLM” (say, a future one called GPT 10, or perhaps even GPT 7), even if it’s very different from our familiar experiences.

Back to progressive jazz

Let’s go back to Ben’s music analogy. Train generative AI on music up to the year 1900, and run it at low temperature. The AI will produce decent imitations of the music styles on which you trained it, though probably a bit aseptic and unimaginative. But now raise the temperature to the point where the AI produces music on the edge of chaotic noise, which only vaguely reminds of its training set. Most of that music will be unpleasant noise that nobody wants to hear. But now and then a high temperature run will produce something that some listeners will find at least interesting. Those samples will be publicized, discussed in music books, and included in new training sets. So there will be a gradual drift toward new styles, and perhaps we will get progressive jazz and all that.

I think this non-linear feedback will soon be evident in language and literature. Much of the text that we read online is already written by AI, and much more will come. AI started imitating people, but soon people will start imitating AI and picking up some new expressions produced by AI.

To be continued…

I’ve been writing this article for months. Of course there’s a lot more to be said, but I didn’t want to wait forever. So I’ll continue thinking and write a follow-up soon. In the meantime, there are always interesting discussions on X, like this one where Ben and I participated.

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Crime Report: Illicit trades on-chain shot up in 2024

The cryptocurrency industry is becoming more mainstream than ever. More dumb money floods in with every bull cycle – and cybercriminals lick their lips. Legitimate adoption brings an increase in illicit activities, with threats ranging from international security issues to consumer protection concerns.

According to a new Chainalysis 2025 report, on-chain illicit activity has become more diverse, with some actors using crypto primarily for money laundering imported from off-chain.

Donald Trump’s questionable $TRUMP and $MELANIA meme coins have raised billions of dollars in market cap, and concerns about ethics and regulation. Investors should be more vigilant than ever with what they buy and how they interact with crypto. 

2024 Crypto Crime in Numbers: How Big Was It?

The criminal proceeds received by illicit cryptocurrency addresses in 2024 is estimated at $41 billion. This is down from previous years, so should we celebrate? Chainalysis noted that the number will go up as more illicit addresses are identified, pushing the final total above $51 billion. 

For comparison, the 2023 estimate was initially at $24.2 billion before ballooning to $46.1 billion. The report excludes revenue from non-native crypto crimes.

Credit: Chainalysis

The rise in cryptocurrency value sent to illicit addresses from 2020 to 2024 shows that bad actors are upgrading their tactics. Yet the share of all crypto transaction volume that can be linked to illicit activities fell to 0.14% in 2024, from 0.7% in 2020.

Credit: Chainalysis

Which Assets Were Widely Used in Illicit Activities in 2024?

There has been a significant shift in the types of cryptocurrencies involved in illicit activities, marking a clear departure from Bitcoin’s dominance. Bitcoin was the currency of choice for cybercriminals in 2020, accounting for nearly three-quarters of all illicit transactions. This was simply due to its high liquidity and recognition at the time.

Other assets gained market share and the situation changed. Stablecoins account for more than six out of ten illicit transactions, marking 77% year-over-year growth. This shift mirrors the broader trend in the crypto market where they are used more to transfer fixed values, getting away from the volatility of Bitcoin. However, centralised stablecoin issuers like Tether have frozen funds linked to crimes such as scams and terrorism financing.

Credit: Chainalysis

Even then, other forms of crypto crime continue to revolve around Bitcoin. Ransomware and darknet market (DNM) transactions still predominantly rely on BTC, illustrating its persistent role in specific illicit activities.

Privacy coins like Monero have seen a rise in usage within the DNM space.  Other forms of crypto crime, such as scams or money-laundering, involve a very wide range of assets, reflecting the diverse ways illicit actors are adapting to the growing crypto industry.

The report also revealed that transactions involving sanctioned entities, especially in jurisdictions where access to the traditional financial system is restricted, lean toward stablecoins. The bottom line is that cryptocurrencies are used everywhere, even in conflict zones.

Authorities will look at these to try to understand illicit activities. They will have their work cut out, as it has been previously reported that less than 10% of stablecoin transactions are from real users. 

Stolen Funds and Scams: North Korean Hackers Run the Show

Stolen funds increased by 21% year-over-year, reaching $2.2 billion. While decentralized finance (DeFi) platforms were the primary targets for these thefts, centralized services took the damage in the second and third quarters of 2024.

North Korea, as is slowly becoming the norm, is responsible for the lion’s share of these hacks. North Korea stole a record $1.34 billion in 2024, up from $660.5 million the previous year. These hacks are increasingly carried out by North Korean IT workers who infiltrate crypto and Web3 crypto companies to use advanced tactics to compromise private keys. This tactic has been used in nearly 44% of all stolen crypto in 2024.

High-yield investment scams and ‘pig butchering’ schemes flourished in 2024. With AI being one of the biggest crypto narratives, it was only a matter of time before it was used in scams. Bad actors used AI to bypass KYC regulations. Crypto ATM scams are also on the rise, targeting the elderly.

Law Enforcement Closes in on Ransomware

Ransomware remains a major threat. It continues to generate millions of dollars despite two major challenges: law enforcement disruption, and a decrease in victim willingness to pay ransoms. Attack volumes remained stable in 2024, but the payments made were lower than in previous years. 

Darknet markets (DNMs) saw a slight decline in revenue, earning $2 billion compared to nearly $2.3 billion in 2023. Fraud shop activity dropped sharply by more than half, totaling $220.1 million. This decline in fraud shop volumes can be partly attributed to a major U.S.-Dutch operation that dismantled the Universal Anonymous Payment System (UAPS), a crypto-processor used by numerous fraud shops.

Credit: Tesfu Assefa

Crypto Crime Is Getting More and More Complex

Crypto crime is becoming diverse and professional as organized groups use digital assets for a wide range of traditional crimes. In 2024, a sizable portion of the $40.9 billion received by illicit crypto addresses came from entities providing the infrastructure and services necessary for criminal operations, such as laundering and hacking tools.

Huione Guarantee serves as a prime example of the growing professionalization of crypto crime. The marketplace has processed over $70 billion in crypto transactions since 2021, facilitating illicit activities such as servicing sanctioned entities.

Wrapping Up

Crypto criminal networks are bigger and more sophisticated than before. The ball is in the authorities’ courts to thwart the rising complexity of crypto crime before it spirals beyond control. Whether they will get the support under a Trump administration is still debatable. 

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Nonso Nolly is a roboticist working on Drones and Robotics in Lagos, Nigeria

Nonso Nolly is raising money via the Drones and Robotics Association Innovators Association to continue his work in making fabulous drones and robots. 

You can see him discuss and show off some of his earlier efforts here. He’s excited about recent progress in AI and wants to get busy doing more stuff. I encourage you to donate to his effort. 

I spoke with him via email.

RU Sirius: Explain your progress in the field of drones and robotics.

Nonso Nolly: My recent progress in Drones and Robotics can be divided into three categories

* Design and Development: We have successfully designed and developed several drone models, including quadcopters, hexacopters, and octocopters, with varying payload capacities and flight times. 
* Autopilot Systems: Our drones are equipped with advanced autopilot systems, enabling autonomous flight, waypoint navigation, and real-time telemetry. 
* Sensor Integration: We have integrated various sensors to enhance drone stability, navigation, and data collection – such as GPS, accelerometers, gyroscopes, and magnetometers.

RU: How does your work relate to developments in AI? Are you infusing some of that excitement into your most recent work?

NN: Relation to developments in AI –
1) Machine Learning: We are exploring the application of machine learning algorithms to enhance drone autonomy, obstacle avoidance, and decision-making. 
2) Computer Vision: Our team is working on integrating computer vision capabilities into our drones, enabling them to detect, track, and analyze objects and environments.
3) Natural Language Processing: We are developing voice command and natural language processing capabilities for our drones, allowing users to interact with them more intuitively.

Regarding infusing AI excitement into recent work, this is something we would like to do –
1) AI-Powered Drone Inspection: We are developing an AI-powered drone inspection system for the oil and gas industry, enabling autonomous inspection, anomaly detection, and predictive maintenance.
2) Drone-Based Crop Monitoring: Our team is working on a drone-based crop monitoring system, using AI-powered computer vision to analyze crop health, detect pests and diseases, and optimize crop yields.
3) Autonomous Drone Delivery: We are exploring the development of autonomous drone delivery systems for medical supplies, packages, and other essential items, leveraging AI-powered navigation and obstacle avoidance.

RU: Please give us a bit of background on your life and influences. Who and what made you a technology maker and visionary?

NN: Growing up in Nigeria, I was fascinated by technology and innovation. My parents encouraged my curiosity and supported my interest in science and technology.

My journey into robotics and technology began at a young age. I started building and creating things, from simple remote control models to more complex robots. This hands-on experience helped me to develop problem-solving skills and think creatively.

My education played a significant role in shaping my skills and knowledge. I studied Electrical engineering at the University of Lagos, Nigeria. During my time at university, I was exposed to various aspects of engineering, including robotics, mechatronics, and computer-aided design (CAD).

After completing my studies, I worked on projects including building robots for industrial automation using Arduino microcontrollers, and developing drones for mapping and surveillance, and package delivery. These experiences helped me refine my skills and gain expertise in robotics and engineering. 

My Youtube channel, where I share my projects, tutorials, and experiences, has been instrumental in showcasing my work and inspiring others.The channel has gained a significant following, and I would say I’ve become a respected figure in the robotics and maker communities.

RU: I am in the San Francisco Bay Area in the USA, where the cultural environment around technological evolution is widely known. Tell Mindplex readers about the cultural environment where you are in Nigeria, and tell us how you have assembled a team to do the work.

NN: I’m based in Lagos, Nigeria. The city is increasingly known for its vibrant cultural environment, rapid technological growth, and entrepreneurial spirit.

Being the economic hub of Nigeria, Lagos offers a unique blend of traditional and modern culture. The city is home to various ethnic groups, with a strong emphasis on community, family, and respect for elders. These cultural values have influenced my approach to teamwork, collaboration, and innovation.

Regarding my team, I’ve assembled a diverse group of talented individuals who share my passion for robotics and innovation. I have been able to register in Nigeria under the name ‘Drones And Robotics Innovators Association’ with the aim of promoting the development and application of Robotics and Artificial Intelligence technologies in the country. The core objectives of the Association are –
1) Industry development 
2) Capacity building 
3) Promoting innovations

Credit: Tesfu Assefa

RU: Talk a little bit about your influences in robotics, drones, AI and what have you been inspired by.

NN: I’ve been inspired by – Boston Dynamics: Known for their advanced robotics and artificial intelligence research. NASA: A leading space agency that has inspired many with its technological advancements. DIY makers and robotics enthusiasts: I’ve been inspired by the creativity and ingenuity of makers and robotics enthusiasts worldwide.

RU: Tell us more about the DIY makers who influenced you.

NN: I have been influenced by DIY Makers including Adafruit, Instructables, Arduino, and Robotics enthusiasts like Chris Anderson, Spark fun, and Robot operating system (ROS).

RU: Great. Give the Mindplex readers your best pitch for funding your project in robotics, drones and AI. Tell us what you’ll use the money for.

NN: Thank you in advance for considering supporting the Drone and Robotics Innovators Association! Our organization is dedicated to fostering innovation and growth in the drone and robotics industries. Here’s how your contributions will help us achieve our goals –

1) Community Development: 30% of the funds will go towards building a robust community platform, where innovators, entrepreneurs, and industry experts can connect, share ideas, and collaborate on projects. 
2) Project Funding: 25% of the funds will be allocated to support innovative projects and startups in the drone and robotics space. This will include funding for prototype development, testing, and iteration.
3) Education and Training: 20% of the funds will be used to create educational resources, workshops, and training programs for individuals and organizations looking to develop skills in drone and robotics technologies. 
4) Events and Outreach: 15% of the funds will go towards organizing events, conferences, and meetups that bring together industry experts, innovators, and enthusiasts. This will help promote the association’s mission and foster collaboration. 
5) Administrative Costs: 10% of the funds will be used to cover administrative expenses, including marketing, website maintenance, and operational costs. 

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How to Keep Your Crypto Portfolio Safe in 2025

As Bitcoin surges past $104,000 around the Trump inauguration, which brings a pro-crypto administration for the first time ever to the United States of America, newcomers and veterans alike face increasingly sophisticated threats to their digital assets. 

The FBI’s revelation that crypto scams resulted in $2.57 billion in 2023 and Chainalysis reporting $2.2 billion lost in 2024, with individual victims losing an average of $54,000, serves as a sobering reminder that security cannot be an afterthought. 

Drawing from recent cases and expert insights as shared by ApEx, here’s what you need to know to safeguard your crypto portfolio in 2025.

The Foundation: Seed Phrase Security

It all starts with your private key or seed phrase. Your seed phrase is effectively the master key to your crypto kingdom, and treating it with anything less than extreme caution is a recipe for disaster. 

Blockchain.com’s analysis last year revealed a telling statistic: 27% of cryptocurrency losses in 2023 stemmed from compromised seed phrases, with victims losing an average of $85,000.

The most dangerous mistake? Digital storage. Whether it’s a screenshot, a notes app, or cloud storage, cybercriminals deploy specialized malware designed to scan for these digital breadcrumbs. 

A particularly devastating case in 2023 saw hackers targeting cloud-synced screenshots, resulting in millions in losses. And it’s not just hackers you have to worry about. As the recent devastating Los Angeles firestorm has shown, “safe as houses” don’t apply when your crypto kingdom is written on a piece of paper stored in your burning home’s safe. 

You need physical security as well as digital. Write your seed phrase on metal plates or high-quality paper, and distribute copies across multiple secure locations like safety deposit boxes. This old-school approach might seem inconvenient, but it’s far better than losing your entire portfolio to a digital breach. Cold storage is always a welcome safety shield, but it’s only as good as your seed phrase protection. Using advanced techniques like multi-sig or multi-party computation (MPC) is also smart. 

Device Security: Your First Line of Defense

The mobile revolution made cryptocurrency trading more accessible but also more vulnerable. Symantec’s 2023 Internet Security Threat Report found that 42% of mobile device users experienced security breaches affecting their crypto holdings. In one particularly aggressive attack, spyware targeting Android users intercepted SMS two-factor authentication codes and drained wallets, with one victim losing $200,000 in minutes.

The most effective countermeasure is device dedication – maintaining separate devices specifically for cryptocurrency transactions. These devices should have full-disk encryption and regular system updates. While this approach might seem excessive, it creates a secure environment that significantly reduces your exposure to malware and other digital threats.

Social Media: The New Battleground

The rise of artificial intelligence has given scammers powerful new tools. According to the UK’s National Cyber Security Centre, 73% of cryptocurrency scams in 2023 originated on social media platforms. The most alarming development is the use of deepfake technology to impersonate trusted figures in the crypto space.

A particularly sophisticated scam in 2023 employed deepfake videos of Elon Musk promoting fraudulent cryptocurrency projects, ultimately stealing over $100 million from victims. These scams succeed because they exploit our natural tendency to trust familiar faces and voices. In 2025, they’re even more evolved, using AI agentic technology to fool users. They especially target Twitter and Telegram groups, posing as real people. 

Protection requires you to remember two directives: 

  • First, interact exclusively with verified profiles and official websites, using bookmarks to bypass potential phishing links. 
  • Second, adopt universal skepticism toward investment opportunities, regardless of who appears to endorse them. 

Remember: legitimate crypto projects don’t need to solicit investments through direct messages or social media posts.

Credit: Tesfu Assefa

Smart Contracts: Hidden Dangers in Plain Sight

The DeFi sector’s explosive growth has made smart contract vulnerabilities an increasingly lucrative target. In 2023 alone, exploits in smart contracts led to losses exceeding $686 million. A single high-profile incident resulted in a $120 million theft, affecting thousands of users who believed their investments were secure.

To navigate this risk, limit your DeFi activities to protocols audited by established security firms. More importantly, regularly review and revoke token approvals – these permissions can become backdoors for wallet-draining exploits. Some hardware wallets have built-in Web3 contract review features. These allow you to verify a contract’s interactions before approving it: an additional layer of protection against smart contract vulnerabilities.

The Silent Threat: Clipboard Hijacking

One of the most insidious threats in cryptocurrency trading is clipboard hijacking malware. These programs silently monitor your clipboard, and when you ‘copy’ a wallet address into your clipboard, it switches it for one controlled by attackers. Kaspersky’s research shows a 30% increase in these attacks, with one notable case resulting in a €50,000 loss from a single transaction.

The defense against this threat requires vigilance and proper tools. Check the recipient address character by character before you hit ‘send’. When possible, use QR codes instead of copy-paste operations. Hardware wallets that display and verify transaction details provide crucial protection against these attacks.

The Power of Test Transactions

Perhaps the simplest yet most overlooked security practice is to send test transactions.

 Coinbase reports that 33% of irreversible transaction errors could have been prevented by this basic precaution. A notable case saw an investor lose $10,000 in Ethereum by accidentally sending funds to a Binance Smart Chain address – a mistake that a small test transaction would have revealed. I have personally lost $1000 USD sending funds to Polymarket over the wrong network, and which surprise, surprise, and my numerous emails and messages has not even received a single reply from Polymarket’s team. I’ve also lost $500 USD when I copied and pasted a Solana address and missed the first letter. Somehow the transaction went through, and those funds are lost forever. 

A refresher: 

  1. Before sending large amounts, always conduct a small transaction to test if the address and network are correct. 
  2. Once confirmed, document the successful steps for future reference.

This small investment in time and transaction fees can prevent catastrophic losses.

As cryptocurrency adoption continues to grow, the security landscape grows more complex. Yet the fundamentals remain unchanged: combining technical safeguards with cautious practices provides the strongest defense against scams and theft. Stay safe so that you don’t look back at the end of the year and mourn the life-changing funds the bad guys now have instead of you.

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Bitcoin Price Predictions for 2025: Wall Street Meets Crypto

Introduction

It was a nervous start to 2025, but a year expected to be a bumper one for crypto. There are a few reasons to be optimistic: incoming president Trump’s patronage, Michael Saylor’s relentless buying and the possibility of a Bitcoin Strategic Reserve

Yet Bitcoin surprisingly had a bad start to 2025. It tumbled below $91k at the start of this week (13 Jan), as the Fed signaled slower rate cuts and the DOJ prepared to unload $6.5 billion worth of seized crypto. But when traders hit the ‘sell’ button, there was a counter-movement: major players from Wall Street to Silicon Valley bet on much higher prices, and the price has rebounded from 12% this week to its current $104k (17 Jan).

Is the Trump inauguration a “buy the rumor sell the news” event? Is the market top already in? I don’t have that answer. Instead, let’s zoom out a little and see what the experts and TradFi smart money believe is in store for the world’s leading cryptocurrency in 2025. 

The Bitcoin Bull Case

The biggest banks on Wall Street are now all business about Bitcoin. 

“Bitcoin has moved beyond the retail speculation phase,” says Fundstrat’s Tom Lee, who sees prices reaching $250,000. Lee points to last November’s record $6.2 billion ETF inflows as evidence that big money is finally embracing crypto.

Tech Visionaries Double Down

Tech investor Tim Draper isn’t backing down from his $250,000 prediction. The early Tesla and Skype backer calls Bitcoin “cheap” even as it trades near $100,000. He’s joined by MicroStrategy’s Michael Saylor, whose company keeps accumulating Bitcoin through every market swing.

“People will freak out when Bitcoin crashes from $180,000 to $140,000,” Saylor says, comparing price swings to the revolutionary impact of putting engines in horse carriages. “Volatility is the price of growth.”

The Institutional Wave

Major financial institutions have dramatically shifted their stance on Bitcoin. 

Morgan Creek Capital’s Mark Yusko targets $150,000, citing growing institutional FOMO. Van Eck’s research team projects $180,000 or higher within a year, driven by shifting political winds and institutional adoption.

The numbers back up this institutional interest. On top of the headline-grabbing ETF inflows, major banks are building crypto trading desks, and pension funds are dipping their toes in the market. 

Standard Chartered makes comparisons to gold’s 4× price increase after its first ETF launch, suggesting Bitcoin could follow a similar trajectory.

A daringly precise prediction comes from quantitative analyst Sminston With: $275,000 on 1 Nov, 2025. They base this on ‘regression analysis’ of previous market cycles, a mathematical guess as opposed to the more intuitive ones from market veterans.

Credit: Tesfu Assefa

Market Headwinds

Not everyone’s convinced the path higher will be smooth. The DOJ’s planned sale of 69,370 Bitcoin looms over the market, while Fed warnings about persistent inflation suggest interest rates might stay higher for longer. Some analysts warn this could cap Bitcoin’s upside in the near term.

InvestingHaven’s analysts warn Bitcoin could drop to $75,000 in their bearish scenario. 

Robert Kiyosaki expects a “bloodbath” down to $60,000 before a potential surge to $250,000 later in 2025. 

Maybe people are giving too much weight to the upcoming DoJ sale – the $6.7 billion potential selloff must be considered against things like the $10 billion that MicroStrategy acquired in December alone. 

The Political Factor

The incoming Trump administration’s crypto stance adds another layer to price predictions. Plans for a Bitcoin Strategic Reserve and a potential shift in oversight from the SEC to the CFTC have caught Wall Street’s attention. In addition, Donald Trump’s has appointed numerous crypto bulls such as new SEC chair Paul Atkins and crypto czar David Sacks, who will reshape current policy. 

AllianceBernstein analyst Eric Martindale notes, “We’re seeing a fundamental shift in how institutions view Bitcoin. It’s no longer a question of if they’ll adopt Bitcoin, but when and how much.”

The USA’s moves put peer pressure on other countries to create their own reserves – a factor that could make things very interesting. 

Global Money Flows

Beyond U.S. borders, global institutional adoption continues to accelerate. Japanese pension funds are increasing crypto allocations, while European investment firms are launching their own crypto products. This global demand could help absorb selling pressure from events like the DOJ’s Bitcoin liquidation.

Technical Perspectives

Chart analysts point to several key levels that could influence Bitcoin’s path to the lofty predictions above. The recent consolidation near $100,000 has established strong support levels, while previous cycle data suggests potential resistance around $150,000 and $180,000.

These technical factors matter more than ever, as institutional traders bring their traditional market expertise to crypto. “The market is maturing,” says Yusko. “Technical analysis works better now because the traders using it have billions to put behind their convictions.”

Long-Term Vision

Ark Invest’s Cathie Wood takes an even longer view, predicting $650,000 by 2030 with potential upside to $1.5 million. “Bitcoin is evolving into a standard part of institutional portfolios,” she says. This long-term perspective helps explain why many institutions aren’t deterred by short-term volatility.

Investment Implications

Today’s Bitcoin market combines institutional muscle with residual retail speculation. Predictions grab headlines, but Bitcoin remains notoriously unpredictable. The DoJ’s planned sale shows how large holders can still move markets. Add uncertain Fed policy and changing regulations, and investors should expect turbulence.

But something fundamental has changed. BlackRock doesn’t launch ETFs for passing fads. Standard Chartered doesn’t make price predictions about memecoins. The world’s biggest financial players are betting Bitcoin is here to stay. Unlike previous cycles built on retail hype, this one has serious institutional backing.

Looking Ahead

Most experts cluster around $200,000 for 2025, but the path there won’t be smooth. Monday’s drop shows how macro factors can still rock the market.

Whether Bitcoin hits these ambitious targets or not, one thing is clear: Wall Street and Washington DC’s Bitcoin skeptics have become Bitcoin believers who are likely diamond handed. As institutional money flows in and regulations evolve, 2025’s price predictions may say less about Bitcoin’s future than the transformation in global finance.

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Ten Essential Bitcoin Charts To Know In 2025

Introduction

Cryptocurrency markets change quickly, so it is important for investors to monitor key metrics that show market trends, performance, and sentiment.  

Bitcoin is king, and where it goes, the market usually follows. These charts provide essential data to understand Bitcoin’s market position, performance, and future trends. Let’s dive in. 

  1. Bitcoin/USD
Credit: CoinMarketCap

Everything in crypto starts with the Bitcoin chart, measured against the de-facto world currency (for now?) the U.S. Dollar. This is the first and still most important chart in crypto, which you can find on sites like CoinMarketCap, CoinGecko, and your favorite exchange’s BTC trading page. 

Determine the time range you’d like to review – with Bitcoin, it’s better to zoom out to steady your nerves; the 4-year halving cycle below proves this. Dial up Crypto Twitter, understand how events like Chinese New Year, Christmas, U.S. Tax Season, U.S. elections, summer holidays and others can impact the price of BTC each year. 

Also, understand how to read a Bitcoin depth chart here. You have your homework cut out for you! 

  1. Bitcoin Dominance (BTC.D)
Credit: TradingView

Bitcoin Dominance (BTC.D) represents Bitcoin’s share of the total cryptocurrency market. When BTC.D rises, it signals that Bitcoin is performing better than altcoins, often during market corrections when investors prefer safer assets. 

A falling BTC.D usually indicates increased interest in altcoins, particularly in bullish markets as traders chase higher returns. For example, during the 2017 ICO surge, BTC.D dropped to nearly 32% due to an altcoin boom. 

Tracking BTC.D helps traders understand market dynamics and adjust their portfolios accordingly, balancing exposure between Bitcoin and altcoins based on current trends and sentiment.

  1. Bitcoin mining hash rate
Credit: Blockchain.com

The Bitcoin mining hash rate measures the computational power used by miners to process transactions and secure the Bitcoin network. It shows how many calculations are performed every second to solve the mathematical problems required for mining new Bitcoin blocks. 

A higher hash rate makes the network more secure, as it becomes harder for bad actors to control or attack it. Factors that influence the hash rate include mining equipment efficiency, electricity costs, and Bitcoin’s price. Over the years, the hash rate has grown significantly, due to advancements in technology and increased participation from global mining operations.

  1. On-Chain Metrics (Wallet Balances & Transactions)
Credit: The Block

On-chain metrics track blockchain activity by analyzing wallet balances and transaction histories. Wallet balances reveal how much cryptocurrency users are holding, helping identify trends like accumulation or selling. 

‘Transaction volume’ measures the number of transactions happening on the network, showing how actively the cryptocurrency is being used. Higher transaction volumes can signal strong market activity, while lower volume may suggest reduced engagement. 

These metrics provide a hint of a cryptocurrency’s network health, helping investors make better decisions based on real blockchain data instead of relying solely on price charts or market speculation.

  1. Stablecoin Supply Ratio (SSR)
Credit: CryptoQuant

The Stablecoin Supply Ratio (SSR) compares Bitcoin’s market capitalization to the total market cap of all stablecoins. It shows how much buying power stablecoins have relative to Bitcoin. A low SSR means there are more stablecoins available, indicating strong potential buying power that could push Bitcoin’s price up. 

A high SSR suggests fewer stablecoins are in circulation. This means less capital is available for Bitcoin purchases, a factor that could limit price movement. Investors use SSR to assess market liquidity and anticipate possible price movements based on how much money is ready to flow into Bitcoin from stablecoins.

Credit: Tesfu Assefa
  1. Bitcoin Volatility Index (Crypto VIX)
Credit: TradingView

The Bitcoin Volatility Index (Crypto VIX) measures how much Bitcoin’s price is expected to fluctuate over a set period, typically 30 days. It’s calculated using data from Bitcoin options trading. A high volatility index means Bitcoin’s price could change significantly; it means a risky and uncertain market. A low index suggests the market is stable: smaller price movements are expected. 

Traders and investors use this index to gauge market sentiment, adjust their portfolios, and make informed trading decisions. Understanding Bitcoin’s volatility helps manage risks and spot trading opportunities in the unpredictable cryptocurrency market.

  1. Bitcoin ETF inflows and institutional investments
Credit: Coinglass

ETF inflows and institutional investments play a crucial role in the cryptocurrency market. When large institutions invest in Bitcoin through ETFs, it indicates growing trust in digital assets. ETFs allow traditional investors to gain exposure to Bitcoin without directly holding it. 

For example, BlackRock’s Bitcoin ETF has attracted billions of dollars, boosting market confidence. Higher ETF inflows often signal strong demand, which can push Bitcoin’s price upward. Investments from major firms like Fidelity and Grayscale show long-term interest. Monitoring these inflows helps investors gauge market sentiment, as increased institutional participation often leads to higher liquidity and reduced market volatility.

  1. Bitcoin four-year cycle
Credit: TradingView

The Bitcoin four-year cycle is a pattern based on Bitcoin’s halving events, which occur approximately every four years. During each halving, the reward for mining Bitcoin is reduced by half, limiting new supply. This scarcity often leads to price increases due to higher demand and lower availability.

The cycle includes four phases: accumulation, uptrend, distribution, and downtrend. Prices typically rise after halving events, followed by a peak, profit-taking, and eventual correction. Understanding this cycle helps investors anticipate potential market movements. By studying past cycles, traders can make better investment decisions, identifying favorable entry and exit points for long-term profitability.

  1. Bitcoin Exchange Flows
Credit: CryptoQuant

Bitcoin Exchange Flows charts are used by traders to monitor the flow of Bitcoin into and out of exchanges. This can provide insights into market sentiment and potential price movements, and traders can gauge whether investors are accumulating or distributing their holdings. Increased inflows often indicate that traders are preparing to sell, which can lead to downward price pressure, while outflows suggest accumulation and potential bullish trends. 

Additionally, these charts help identify significant shifts in trading volume, which can signal upcoming volatility or trend reversals. Understanding exchange flows thus empowers traders to make informed decisions based on market dynamics and investor behavior. 

  1. Altcoin Season Index
Credit: Coinmarketcap

Bitcoin doesn’t just go up indefinitely. Eventually, it’ll take a breather and let the rest of the market share in the spoils, which sees massive growth for the many altcoins. 

Altcoin Season Index tracks how well altcoins perform compared to Bitcoin over a 90-day period. If 75% or more of the top 50 altcoins outperform Bitcoin, it is considered an ‘Altcoin Season’: a strong altcoin market.

If fewer than 25% outperform Bitcoin, it’s ‘Bitcoin Season’, meaning Bitcoin is dominating the market. This index helps investors see when altcoins might offer better returns, guiding them to a trading strategy that favours altcoins. By keeping an eye on this index, traders can adjust their portfolios to take advantage when the market trends towards Bitcoin and away from it, to maximize potential profits during favorable market conditions.

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