The Dawn of AI and Crypto Civilization

The day after superintelligence won’t look like science fiction. It will look like software updates shipping at the speed of thought and entire industries quietly reorganizing themselves before lunch. The popular image of a single “big bang” event misses the truth: superintelligence will arrive as an overwhelming accumulation of competence—systems that design better systems, diagnose with inhuman accuracy, and coordinate decisions at a scale no human institution can rival. When optimization becomes recursive, progress compresses. What once took decades will happen in weeks.

We already have hints of this future hiding in plain sight. In 2023, DeepMind’s AlphaFold revolutionized biology by predicting the structures of more than 200 million proteins—essentially mapping the building blocks of life in a few years, a task that traditional methods could not complete in centuries. Large language models now write code, draft contracts, and discover novel materials by searching possibility spaces no human team could fully explore. Training compute has historically doubled roughly every 6–10 months during the early 2020s, far faster than Moore’s Law, and algorithmic efficiency gains have compounded that advantage. When intelligence accelerates itself, linear expectations break.

The economy the morning after will belong to organizations that treat intelligence as infrastructure. Productivity will spike not because workers become obsolete, but because one person will wield the leverage of a thousand. Software-defined everything—factories, finance, healthcare—will default to machine-led orchestration. Diagnosis rates will climb, downtime will shrink, and supply chains will become predictive rather than reactive. The center of gravity will move from labor scarcity to insight abundance.

Crypto will not be a side story in this world; it will be a native layer. Superintelligent systems require neutral, programmable money to transact at machine speed, settle globally, and audit without trust. Blockchains offer something legacy rails cannot: cryptographic finality, censorship resistance, and automated enforcement via smart contracts. When AI agents negotiate compute, data, and energy on our behalf, they will do it over open networks with tokens as executable incentives. Expect on-chain markets for model weights, verifiable data provenance, and compute futures. Expect decentralized identity to matter when bots and humans share the same platforms. Expect treasuries to diversify into scarce digital assets when algorithmic trading dwarfs traditional flows and fiat systems face real-time stress tests from machines that never sleep.

The energy footprint will surge first—and then collapse per unit of intelligence. Today’s data centers already rival small nations in power draw, yet the same optimization engines driving AI are slashing watts-per-operation each year. History is clear: as engines get smarter, they get leaner. From vacuum tubes to smartphones, efficiency rises faster than demand—until entirely new use cases layer on top. Superintelligence will do both: it will squeeze inefficiency out of the system while unlocking categories we’ve never priced before, like automated science as a service and personalized medicine at population scale.

The political impact will be just as real. States that master compute, data governance, and talent will compound their advantage. Those that don’t will import intelligence as a service and awaken to strategic dependence. Regulation will matter—but velocity will matter more. The nations that win will be the ones that regulate with a scalpel, not a hammer, pairing safety with speed. Meanwhile, crypto networks will function as jurisdiction-agnostic commons where innovation keeps moving even when borders slow.

Critics will warn about control, and rightly so. Power concentrated in any form demands constraints. Yet the greater risk is paralysis. Every previous leap—from electricity to the internet—created winners who leaned in and losers who hesitated. Superintelligence will be no different, except the spread between the two will widen overnight. The answer is not fear; it’s instrumentation. Align objectives, audit outputs, and decentralize critical infrastructure. Do not shut down the engine of abundance—build guardrails and drive.

The day after superintelligence, markets will open, packages will ship, and most people will go to work. But the substrate of reality will have changed. Intelligence will no longer be the bottleneck; courage will be. The bold will build economies where machines and humans create together, settle on-chain, and optimize in real time. The timid will debate yesterday’s problems in tomorrow’s world.

This is not a warning. It’s an invitation.

Superintelligence doesn’t replace humanity—it multiplies it. Crypto doesn’t disrupt finance—it finally makes it global, programmable, and impartial. And the future doesn’t arrive with fireworks. It arrives with results.

How hackers steal millions from bank accounts

The latest information from IBM Security Trusteer’s mobile security research team indicatesthat hackers have been using ‘mobile emulators’ to steal millions from financial institutions in Europe and the USA.

How they did it?

They set up a network of mobile device emulators that were behind thousands of spoof devices able to access thousands of compromised accounts. A set of set of mobile device identifiers was used to spoof an actual account holder’s device, and in each case it is likely that these accounts had been infected by malware, or collected via phishing.

The hackers have the victim’s username and password, and using an automatic process are able to “script the assessment of account balances.” They can then automate large numbers of fraudulent transfers. These are never large enough to trigger bank scrutiny at the time.

How does an emulator work?

It mimics the characteristics of several mobile devices. They are often used by developers to test applications, but in the wrong hands they are a crime tool.

According to Finextra: “IBM Trusteer says that the scale of the operation is one that has never been seen before, in some cases, over 20 emulators were used in the spoofing of well over 16,000 compromised devices.”

IBM added, “”The attackers use these emulators to repeatedly access thousands of customer accounts and end up stealing millions of dollars in a matter of just a few days in each case. After one spree, the attackers shut down the operation, wipe traces, and prepare for the next attack.”

IBM Trusteer’s intelligence team has also observed a trending fraud-as-a-service offer in underground venues, promising access to this type of operation to anyone willing to pay for it, with or without the required skill.

“This lowers the entry bar for would-be criminals or those who plan to transition into the mobile fraud realm,” says IBM, and is likely to become a growing trend amongst cybercriminals.

2020 Cybersecurity: Year Zero Trust

Prior to 2020, “the technology industry has long assumed that it would eventually get rid of the concept of implicit digital trust,” Emil Sayegh writes, pointing out that this got completely flipped this year as digital transformation was forced on a new route due to the surge in remote working. He calls it the year of ‘Zero trust’.

Why is this? Because organizations have had to rethink their security concerns with so many employees working from home. “Remote work IT capabilities changed the perimeters of traditional security, as well as its threat, Sayergh says, and adds that there is mounting evidence “that since this big shift, cybersecurity threats and threat vectors have increased 400% from pre-Covid times.”

Cybercriminals were quick to catch on to the fact that there were bound to be places that were easy to breach, plus they have updated their methods of attack to exploit fears by using more ransomware and targeted malware on organizations. What this tells us that there is a critical need to deal with their threats in a more efficient and intelligent way.

Every day is ‘Day Zero’

A ‘Day Zero’’ is the day that any cyber threat is unleashed, and in “a Zero Trust world, every day is assumed to be a potential ‘day zero’,” Sayergh says. The position to take from an IT perspective is one of overarching ‘mistrust’ and continuous vigilance over “who accesses what at every level possible.” As Sayergh remarks, every time a network is accessed it should be treated as ‘stranger danger’. Therefore all access should be “fully authenticated, authorized, and encrypted before any access can happen.” Ultimately, Zero Trust operates on the basis of a “hermetically sealed security” that also “empowers employees to work securely and efficiently, wherever they may be operating.”

As organizations now work on implementing Zero Trust, security capabilities are increasing. It also applies to cybersecurity strategies, and “leverages tools such as multi-factor authentication and active session-based risk detection to produce higher levels of security.”

In effect, Zero Trust has been akin to the cavalry riding into 2020. As Sayergh concludes: “By controlling access to specific applications, systems, and resources combined with an assumption of the continual breach, Zero Trust is positioned to enable a seamless move to greater security for all.”

Mastercard introduces AI-powered cybersecurity

Cybersecurity remains one of the hottest topics around. While browsing today’s media I noted one article said that cyber attacks rose by 250% during the pandemic. Apparently it was the perfect time for scammers and hackers to wield their weapons.

This may be one of the things that prompted Mastercard to launch Cyber Secure, “a first-of-its-kind, AI-powered suite of tools that allows banks to assess cyber risk across their ecosystem and prevent potential breaches.”

 

It all comes down to the fact that the digital economy is expanding rapidly and is more complex. Alongside this positive news, comes the less appealing revelation that the growth creates a vulnerability that some are delighted to take advantage of.  For example,it is estimated that one business will fall victim to a ransomware attack every 11 seconds by next year.

 

Ajay Bhalla, president, Cyber & Intelligence, Mastercard said:

“The world today faces a $5.2 trillion cyber breach problem. This is one of the biggest threats to consumer trust. At Mastercard, we aim to stay ahead of fraudsters and to continually evolve and enhance our protection of cyber environments for our bank and merchant customers. With Cyber Secure, we have a suite of AI-powered cyber capabilities that allows us to do just that, ensuring trust across every experience, for businesses and consumers.” 

 

Cyber Secure will enable banks “to continuously monitor and track their cyber posture,” writes Polly Harrison. It will allow banks to be more proactive in managing and preventing data compromise, as well as protecting the integrity of the payment ecosystem and consumer data. It should also, of course, prevent financial loss caused by attacks.

Mastercard has based its new product on the AI capapbilities of RickRecon, which it purchased in 2020. It uses advanced AI for risk assessment, which evaluates multiple public and proprietary data sources and checks it against 40 security and infrastructure criteria.

Harrison writes, “In 2019, Mastercard saved stakeholders $20bn of fraud through its AI-enabled cyber systems,” so it is to be hoped that Cyber Secure prevents even more theft in 2021 and beyond.