The 4T Framework, named by me, honoring my 4T newsletter btw

The article was written using chatGPT (AI), which is more structured than my cognition . Enjoy!

In Romanian language here on FB https://www.facebook.com/permalink.php?story_fbid=pfbid0K5hbyzaFQZQ866Y5VPYPwA3y38PRZ52ocEtwEiU8kgqWSBJsToDUtXJvv5jeT8uzl&id=61568891512276&rdid=5EeIaYah6nmUsYoy#

For the last 30 years, technology has been teaching machines to process information.

First came the Internet.

Then came the Cloud.

Then smartphones.

Then AI.

Now something deeper is emerging - Quantum technology.

But quantum is not simply the next generation of computing it is a broader field involving computation, communication, sensing, simulation and measurement.

Some capabilities are already established. Others are moving toward practical deployment. Many of the most ambitious possibilities remain speculative.

Welcome to the Quantum Era — for basic knowledge, I wrote before some easy-to-understand quantum concepts here https://liviuf.substack.com/p/quantum-computing-and-ai-for-faster (some concepts are hard to understand cause we learn and navigate in school with Euclidean concepts, but I do not go deeper cause is more a philosophical debate btw) . Talking about “philosophy,” you can read here about God, time, and quantum here https://liviuf.substack.com/p/god-time-and-quantum-physics

THE GREAT TRANSITION

Every major technological era changes what humans can do.

The Industrial Revolution gave us machines that could amplify physical power.

The Digital Revolution gave us machines that could amplify information.

The AI Revolution is giving machines the ability to generate, transform, and increasingly act on information.

Quantum technologies could take us somewhere different: the ability to use the fundamental behavior of matter and light to compute, communicate, simulate, and measure in new ways.

It is not simply about having a faster computer.

Quantum processors are not universally faster than classical computers. Their potential is more specific: they may offer advantages for particular problems, especially those involving quantum systems, certain mathematical structures and some optimization or sampling tasks.

The broader opportunity is to change the relationship between information, matter, energy and computation.

THE 4T FRAMEWORK

I see the next technological transition through four interconnected forces:

THINKING

TECHNOLOGY

TRANSCENDENCE

TRANSFORMATION

Quantum technology sits at the intersection of all four — but at different stages of maturity.

Some quantum capabilities are already useful.

Some are plausible near-term applications and others belong to a longer-term, more uncertain future.

1. THINKING

AI is changing the way we think.

Large language models can already generate text, images, code, strategies and hypotheses.

But intelligence does not exist in isolation.

The next frontier is the convergence of:

AI + computation + simulation + scientific discovery.

Today, AI can help researchers search large design spaces, identify patterns and propose molecular or material candidates. Classical high-performance computing already supports much of this work.

Quantum computing may eventually contribute where accurate simulation of quantum systems becomes difficult for classical machines. However, current quantum processors remain limited by noise, scale, and error correction. In many applications, quantum advantage has not yet been demonstrated.

A more realistic near-term loop is:

Human → AI → Classical simulation → Experiment → Discovery

A possible future loop is:

Human → AI → Quantum simulation → Experiment → Discovery

The second loop is promising, but it is not yet a general capability.

If it becomes practical, it could accelerate parts of the scientific method — especially in chemistry, materials science and physics.

2. TECHNOLOGY

The quantum domain is much larger than quantum computers.

I see at least six major quantum domains:

Quantum Computing

Quantum processors use quantum states to perform calculations. They are already operational in laboratories and through cloud-accessible platforms, but current systems are noisy and limited.

The established capability is experimentation: researchers can run quantum circuits, test algorithms, and explore hardware architectures.

The plausible near-term opportunity is specialized advantage in selected tasks, although the timing and commercial value remain uncertain.

Large-scale, fault-tolerant quantum computing capable of solving important problems beyond classical reach remains a longer-term possibility, not an established capability.

Quantum AI

Quantum machine learning and quantum-enhanced optimization are active research areas.

Some algorithms show theoretical promise, but broad, practical advantages over classical AI have not been established.

Near-term value is more likely to come from hybrid workflows, where classical AI and quantum processors are used together for carefully selected problems.

Quantum Communication

Quantum communication technologies already exist in limited forms, including quantum key distribution demonstrations and specialized links.

Their practical deployment is constrained by distance, cost, infrastructure and the need for trusted nodes or advanced networking architectures.

A large-scale quantum network connecting processors, memories and sensors remains a research and engineering challenge.

Quantum Sensing

Quantum sensing is among the most mature and commercially relevant quantum areas.

Atomic clocks, quantum magnetometers and other precision instruments already demonstrate real capabilities.

Near-term applications may include navigation, timing, medical research, geological surveying, infrastructure monitoring and scientific measurement.

The performance advantage will depend on the specific sensor, environment, cost and comparison with improving classical technologies.

Quantum Simulation

Quantum systems can be used to study other quantum systems, and specialized analog quantum simulators already support research.

Digital quantum simulation of complex molecules and materials is a major long-term goal.

Near-term progress is likely to be incremental and domain-specific rather than a sudden replacement for classical chemistry and materials modeling.

Quantum Cybersecurity

The threat from future cryptographically relevant quantum computers is not immediate, but it is strategically important because migrating global systems takes time.

Post-quantum cryptographic standards and migration efforts are already underway.

This is one of the clearest near-term quantum-related priorities: preparing systems before a capable quantum adversary exists.

And these domains will not develop independently.

They may converge.

But convergence should be treated as a research and investment direction, not as a guaranteed near-term outcome.

3. TRANSCENDENCE

This is the part that fascinates me most.

Technology increasingly challenges the boundaries we once considered fixed.

AI challenges the boundary between:

human intelligence and machine intelligence.

Biotechnology challenges the boundary between:

biology and engineering.

Brain-computer interfaces challenge the boundary between:

mind and machine.

Quantum technology challenges something even more fundamental:

our relationship with physical reality.

Quantum mechanics tells us that nature behaves in ways that do not match everyday intuition:

Superposition.

Entanglement.

Quantum tunneling.

Measurement.

Probability.

These are established features of quantum theory and have been repeatedly confirmed experimentally btw.

The technological shift comes when we stop merely observing these phenomena and start engineering with them.

That shift is already real in some technologies, including lasers, semiconductors, atomic clocks and medical imaging.

The more ambitious quantum applications — especially large-scale quantum computing and networking — remain under development.

That is the profound opportunity, but also the reason for caution.

4. TRANSFORMATION

Every major technology eventually leaves the laboratory.

It becomes infrastructure.

The Internet did.

Cloud computing did.

AI is doing it now.

Quantum technologies may follow a similar path, although their adoption curve will likely be more specialized and uneven.

The first wave may not be a quantum computer sitting on everyone’s desk (it is very hard btw; even some marketing claims that some companies do it this ;) )

It may be invisible or embedded in specialized systems.

The most plausible early applications include:

post-quantum cybersecurity

precision timing

quantum sensing

scientific instruments

specialized simulation

research and development tools

Other areas may benefit later, depending on demonstrated performance and economics:

drug discovery

materials science

logistics

finance

energy

navigation

medical technologies

defense

scientific research

It is too early to claim that quantum technology will soon transform all of these sectors.

The user may eventually never know that quantum technology is powering a particular application — just as most people do not think about the semiconductor physics inside a smartphone.

But that outcome depends on quantum systems becoming reliable, affordable and demonstrably better for specific tasks.

FROM THE DIGITAL WORLD TO THE QUANTUM WORLD

DIGITAL ERA

We digitized information.

↓

AI ERA

We began to automate parts of intelligence.

↓

QUANTUM ERA

We are learning to engineer computation, communication and measurement using the behavior of quantum systems.

And then comes the interesting question:

What happens when these layers converge?

AI + Quantum + Biology

AI + Quantum + Robotics

AI + Quantum + Materials

AI + Quantum + Energy

AI + Quantum + Cybersecurity

These are not yet unified technological systems.

They are emerging research and development directions.

Some combinations are already practical, such as AI-assisted scientific discovery and quantum-inspired optimization.

Others, such as AI-guided quantum simulation for new medicines or materials, are plausible but not yet broadly demonstrated.

They may become parts of the same technological ecosystem.

But the timing will depend on evidence, engineering and economics — not vision alone.

THE QUANTUM INTERNET

We spent decades building an Internet that connects people and machines.

The next conceptual leap is connecting quantum systems.

A future quantum network could connect quantum processors, quantum memories and quantum sensors.

In principle, such networks could support distributed quantum computing, secure communication protocols and coordinated sensing.

Some components already exist in experimental or limited operational forms. Researchers have demonstrated quantum links, entanglement distribution and quantum networking prototypes.

However, a global quantum Internet is not imminent.

Major challenges remain, including photon loss, quantum memory, error correction, interoperability, network architecture, cost and the difficulty of preserving fragile quantum states over long distances.

The quantum Internet will not simply be today’s Internet, but faster it represents a fundamentally different communication paradigm.

QUANTUM SENSING

Most public discussion focuses on quantum computing.

Quantum sensing may reach practical markets sooner in several applications.

Why?

Because you do not need a universal fault-tolerant quantum computer to benefit from quantum physics.

You need a sensor capable of measuring something better, faster or more efficiently than existing technology can.

Some quantum sensors are already established in laboratories and specialized instruments.

Near-term or emerging applications may include:

GPS-independent navigation.

More sensitive medical and biological measurements.

Underground geological mapping.

Infrastructure monitoring.

Precision timing.

Detection of small changes in magnetic or gravitational fields.

The commercial outcome will vary by use case. A quantum sensor is not automatically better than a classical sensor in every environment.

Sometimes the biggest technological revolutions do not come from computing more; they come from measuring better btw..

AND THEN THERE IS QUANTUM BIOLOGY

This is where my Trip 3.0 book (biohacking and book finished but not published yet. After the “success” of the 2nd book I decided not to publish, but I am still thinking about it btw) perspective becomes particularly interesting. Just think in a way we are human beings with quantum biology ;).

Quantum biology is a real research field, but its scope and technological implications remain debated.

There is strong evidence that quantum mechanics underlies chemistry and that certain biological systems may exploit quantum effects. Photosynthetic energy transfer, enzyme reactions, avian magnetoreception and olfaction are among the areas studied, although the mechanisms and their functional importance are not equally established.

We are still far from a complete technological framework for exploiting quantum effects in biology.

A plausible near-term direction is not “quantum biology” as a universal platform, but better integration of:

AI models of biological systems

classical and quantum chemistry

advanced experiments

biotechnology

precision measurement

Quantum simulation may eventually help with selected molecular problems that are difficult for classical methods.

But it is not yet very clear when, where or whether quantum computers will deliver decisive advantages in drug discovery, longevity research or regenerative medicine.

A more responsible formulation is:

AI models biological systems

quantum simulation may explore selected molecular behaviors

biotechnology tests and engineers biological systems

advanced sensors measure the results

That could contribute to drug discovery and materials research.

It could eventually influence longevity and regenerative medicine.

But those outcomes remain plausible possibilities, not established consequences of quantum biology.

Quantum processors are likely to remain specialized for a long time, even if they become commercially important.

The most realistic future is not classical computing versus quantum computing.

It is classical computing, AI accelerators, and quantum processors working together where each is best suited.

TRIP 3.0 book

This is why I see the Quantum Era as an important part of my Trip 3.0 book.

Trip 1.0 book https://www.amazon.com/Trip-1-0-Unique-Healing-journey/dp/B0D6GQGX37 was about the healing journey of incurable disease.

Trip 2.0 book https://www.amazon.com/Trip-2-0-memoirs-adventures-disruptive/dp/B0D6H7ZLZL was about disruptive thinking and memoirs, adventures, semi-medical ideas.

Trip 3.0 is about what happens when humanity begins to combine AI + Quantum + Biology + Longevity + Human augmentation.

The boundaries between these fields are becoming more connected.

But they are not disappearing.

Each field has different evidence, timelines, risks and constraints.

That is precisely why the intersections matter.

When disciplines interact, new domains can appear.

That is often where disruption begins — but it is also where hype can outrun reality.

WE ARE EARLY

There is a temptation to look at today’s quantum technology and conclude:

“It is not ready yet.”

In many areas, that is correct.

The question for businesses is not:

“Is quantum ready for mass adoption?”

The better question is:

“Which quantum developments are relevant to our sector, and what should we start learning before they mature?”

Because technological revolutions reward preparation, not prediction.

THE NEXT DECADE

I believe the next decade will be defined by convergence — but not by the arrival of a fully realized Quantum Era everywhere at once.

AI will likely become more autonomous.

Robotics will likely become more capable.

Biology will become increasingly programmable in selected domains.

Computing will become increasingly heterogeneous.

Quantum technologies are likely to move further from laboratories into selected real-world applications, especially in sensing, timing, cybersecurity preparation, and specialized research.

Quantum computing may produce important demonstrations and possibly early advantages in narrow tasks, but the timing of broad commercial impact remains uncertain.

A large-scale fault-tolerant quantum computer may emerge within or beyond the next decade. It may also take longer. Current evidence does not justify treating that outcome as guaranteed.

A global quantum Internet is even more speculative. Experimental networks and specialized links may expand, but a general-purpose quantum network connecting the world is unlikely to be a routine consumer infrastructure within the next decade.

Quantum biology may generate valuable scientific insights, but sweeping applications in longevity or regenerative medicine should be treated as longer-term possibilities rather than near-term expectations.

CONCLUSION

The Industrial Age gave humanity machines.

The Digital Age gave humanity networks.

The AI Age is giving humanity machine intelligence.

The Quantum Era may give us something equally important: new ways of computing, communicating, and measuring physical systems.

Some of those capabilities already exist.

Some are moving toward practical deployment.

Some remain hypotheses about what future engineering may make possible.

And when AI meets Quantum we may not simply build better machines we may discover new ways of approaching problems that are currently too complex, expensive, or difficult to model.

Welcome to the Quantum Era.

— Liva

#QuantumEra #QuantumComputing #QuantumAI #ArtificialIntelligence #QuantumSensing #QuantumInternet #DeepTech #FutureOfTechnology #Innovation #Longevity #Biotechnology #Trip30 #4T #Singularity #Future

Elon Musk future predictions made in his recent The Economist interview:

AI will surpass all human intelligence within about 5 years.

Musk predicts that artificial intelligence will exceed the combined intelligence of all humans, marking the beginning of a superintelligence era. Humans will no longer be the dominant intelligence.

He compares the future relationship between humans and AI to that between chimpanzees and humans, suggesting people will no longer be “in control.”

An “age of amazing abundance” within about 10 years.

AI combined with billions of humanoid robots could create an economy with virtually unlimited production of goods and services.

Money may become largely irrelevant.

If robots can produce nearly everything at extremely low cost, Musk believes scarcity could disappear, making money far less important than today.

Most physical and intellectual jobs will be automated.

Humanoid robots and AI assistants are expected to perform the majority of work currently done by humans.

Work will become optional rather than necessary.

People may choose to work for purpose or enjoyment instead of economic survival.

AI remains an existential risk.

Despite his optimism, Musk reiterated that there is still roughly a 10–20% chance that advanced AI could lead to human extinction, though he believes development is unlikely to stop.

AI companies should review each other’s frontier models.

He proposed voluntary peer review and regular collaboration among leading AI labs to improve safety before releasing powerful systems.

Space will become essential for computing.

Musk suggested that future AI could require enormous amounts of computing power, potentially leading to data centers powered by solar energy in orbit.

He believes his long-term predictions are often underestimated. Musk described himself as a modern-day “Cassandra,” arguing that many of his forecasts initially sound implausible but later prove accurate.

Timeline

Timeframe Prediction

~5 years AI surpasses the combined intelligence of humanity.

~10 years Humanoid robots create an “age of amazing abundance”; work becomes largely optional; money loses much of its importance.

Long term Society is transformed by superintelligence, with humans no longer the dominant intelligence on Earth.

It’s worth noting that these are Musk’s personal forecasts, not established scientific consensus. Some AI researchers consider his timelines plausible but aggressive, while others believe they are substantially too optimistic or too short.

Sam Altman has discussed the technological singularity in several recent interviews and essays. His latest comments are notably more optimistic than in previous years.

Sam Altman’s key points on the Singularity

“We are now in the singularity.”

In a recent interview on the Relentless podcast, Altman said humanity has already crossed into the singularity—not as a sudden event, but as the beginning of a new era where AI increasingly contributes to its own improvement.

The singularity is a gradual process.

Rather than a dramatic overnight transformation, he describes it as a series of accelerating advances that society gradually adapts to.

AI agents are already performing real cognitive work.

2026: AI will generate novel insights.

He predicts AI systems will move beyond summarizing existing knowledge to producing original scientific and technical discoveries.

2027: General-purpose robots.

Altman expects robots capable of performing useful real-world tasks to become practical, bringing AI into the physical world.

AI will transform science.

He believes AI will dramatically accelerate research in medicine, materials science, biology, and energy by helping scientists make discoveries much faster.

Economic growth could accelerate enormously.

AI could enable unprecedented productivity growth, making many goods and services dramatically cheaper while creating new industries.

People will continue to work.

Although AI will automate many tasks, Altman argues humans are naturally competitive and purpose-driven, so work will evolve rather than disappear completely.

Risks remain significant.

Even while expressing optimism, Altman continues to advocate for AI safety, alignment research, and international cooperation to reduce the risks of increasingly capable systems.

Altman’s timeline

Timeframe Prediction

2026 AI agents perform meaningful cognitive work.AI begins producing genuine scientific insights.

2027 Useful humanoid and industrial robots become widespread.

2028-2029 AI significantly accelerates scientific discovery and economic growth.

2030 Society increasingly coexists with superhuman AI across most industries.

Altman vs. Musk

Sam describes the singularity as already underway and generally beneficial if managed well. Elon predicts superintelligence within about five years , while emphasizing existential risk.

Sam expects a gradual transition but Elon often describes a more abrupt intelligence explosion .

Sam focuses on scientific progress and abundance .

Elon focuses on abundance through AI and humanoid robots , alongside the possibility that humans may no longer be the dominant intelligence.

One interesting convergence is that both Altman and Musk now place transformative AI on a much shorter timeline than they did a few years ago. Their main difference is in emphasis: Altman generally frames the transition as a manageable, incremental process with enormous upside, while Musk places greater weight on the possibility that superintelligence could escape human control.

In the first two parts on LinkedIn, I presented the key conclusions relevant to the labor market (LinkedIn being the primary platform used by both job seekers and HR professionals).

You can find them here:

Part 1:
https://www.linkedin.com/posts/lflorescu_pentru-că-este-multă-panică-pe-piața-muncii-activity-7439008920720941058-MWE0

Part 2:
https://www.linkedin.com/posts/lflorescu_deoarece-am-promis-că-dacă-primul-post-activity-7439621732597915649-HfOL

In a somewhat cynical way, most IT companies pretend to open junior positions, but I also see that the new generation is far less willing to put in extra effort. They are wired differently for the times we live in and the future we are heading toward, where—according to the AI bots on MetaBook (Facebook, which is basically for bots now, where humans are not even welcome anymore, by the way)—people will need to merge and collaborate with AI agents to adapt to the new reality.

As I mentioned in Part 2, I am now sharing the GitHub source code, and you can run it on your own datasets and occupations of interest, assuming you have the data.

You can find the source code made by Karpathy here:
https://github.com/karpathy/jobs

The interpretation of occupations can be customized and calibrated by anyone by coloring the job map however they choose.

The “Digital AI Exposure” option is one example—it estimates how much current AI (which is primarily digital) is likely to reshape each occupation. But you could write a different prompt for any question—for example, exposure to humanoid robotics, offshoring risk, climate impact, or other factors—and rerun the pipeline to generate a different map.

I found the analyses only for India and Sweden.

India’s IT job market appears to be even more exposed than the U.S. market. Below is a summary of the Indian labor market (and, by the way, due to the EU–India agreements, competition within the European labor market is likely to increase).

What makes India’s map different from the U.S. one:

• Agriculture employs 40% of India’s workforce and scores 2/10 (relatively safe).
• IT/BPO employs far fewer people but scores 8–9/10 (highly exposed).
• The industries that built India’s global reputation are among the most vulnerable.

So, while the AI revolution is already changing the way we work, the future of employment will ultimately be defined by uniquely human skills.

I’m Liviu Florescu, founder of 24 Software & Vraciul Digital — where enterprise IT consulting meets holistic health innovation.

What we/I do:

💻 IT Consulting & Software Development — Data platforms, analytics, application development, DevOps & IT outsourcing across Oil & Gas, Financial, Telecom, Pharma, and more. 50+ projects delivered, 7+ industries served.

🌿 Vraciul Digital — Holistic Health & Digital Wellness — Natural wellness consulting, digital health solutions, mind-body balance programs, and integrative health IT advisory. Ancient wisdom meets modern technology.

Whether you need to transform your IT infrastructure or find a balance between technology and well-being, let’s talk.

🌐 Explore: https://s24vd.netlify.app/

✉️ Email: liviuf@24software.ro

📹 Book a video call: https://lnkd.in/d2Q3-wUr

Phone no. : +40742299579

* text and website generated by Claude Cowork; domain and deployment free of charge at Netlify, but you can use your own domain. Enjoy!

#ITConsulting #DigitalWellness #SoftwareDevelopment #HolisticHealth #VraciulDigital #24Software #DataAnalytics #DigitalTransformation #WellnessTech

(nothing new for me ;) ) and how humans in most desk jobs will be cooked (discarded). Physical jobs will be less affected in the medium term, btw.

Part 1:
https://www.linkedin.com/posts/lflorescu_pentru-că-este-multă-panică-pe-piața-muncii-activity-7439008920720941058-MWE0

Part 2:
https://www.linkedin.com/posts/lflorescu_deoarece-am-promis-că-dacă-primul-post-activity-7439621732597915649-HfOL

In a somewhat cynical way, most IT companies pretend to open junior positions. At the same time, I also see that the new generation is less willing to put in extra effort. They are wired differently for the times we are living in — and the ones we are heading toward — where, according to AI bots on “Moltbook” (basically Facebook for bots, where humans are not even allowed, btw), people will have to merge with bots to adapt to the new reality.

As I mentioned in Part 2, I’m sharing the GitHub source code, and you can run it on your own data, using whatever occupations you want — if you have the data.

Here is the code:
https://github.com/karpathy/jobs

The interpretation per occupation can be customized by anyone by simply adjusting how you “color” the job map.

The “Digital AI Exposure” option is just one example — it estimates how much current AI (which is primarily digital) will reshape each occupation. But you can write a different prompt for any question — for example:

• exposure to humanoid robotics

• offshoring risk

• climate impact

—and re-run the pipeline to get a completely different map.

The prompt above can be used by anyone, for any job, providing a simple estimate of how exposed that job is to Digital AI, based on BLS data (U.S. labor statistics, lol).

I found interesting analyses mainly for India and Sweden.

The IT job market appears to be even more exposed than in the US. Below is a short summary of the Indian market (and with the EU–India agreement, competition in the EU job market will likely increase):

• Agriculture employs about 40% of India’s workforce → exposure ~2/10 (relatively safe)

• IT/BPO employs far fewer people → exposure 8–9/10 (very exposed)

• The jobs that built India’s global reputation are the most at risk

So yes — the AI Revolution is already reshaping how we work.

But the future of work will be defined by one thing:

👉 only human skills

My first job, over 20 years ago at Daewoo Automobile, was repairing industrial robots. The robots, in general, were Mitsubishi, Fanuc, or Siemens, from what I remember.

Read more

AI will help you tremendous . If this info helps you buy me a coffee here https://buymeacoffee.com/liviuflorei lol .

Step 1 : Use your presentation or create in 1 minute one with AI using for free gamma application

Step 2 : Convert you presentation from step 1 in a narrated video for free : https://www.synthesia.io/powerpoint-to-video

I present :

1. My video following step 1 and step 2 https://share.synthesia.io/7fbcf5ff-e888-4e76-b367-6fd2f9dba37d

2. What gamma can do for you

3. What power point to video converter can do for you

I stopped looking for answers in the usual places. What I found instead is that exist a more about life out there but you need extreme courage and be in a extreme mental equilibrium (spiritual equanimity ) otherwise can find you in a continuous nightmare.

Writing the book Trip 2.0 was a necessity to go beyond AI Revolution, Multiple Sclerosis, Lyme&co and knowing more about Universe .
I found myself stuck in the “noise” of modern and misery of corporate life , the algorithms, the hustle, the endless notifications, and so on. I realized that to see the world differently I needed a new lens.
This book documents that shift and I hope helps you in your Earth journey using futuristic disruptive and polymath ideas.
It touches on the uncomfortable and the profound. It’s for the explorers, the bio-hackers, extreme travelers, and anyone tired of the “script” we are handed at birth.
It’s scary to put this out into the professional world, but I believe the future belongs to those who understand the depths of human experience, not just the surface.
I’d be honored if you gave it a read and feedback. You can read quickly in max 2 days but thinking for many days after. Here Eng version : https://www.amazon.com/dp/B0CW1JNJHV

Genre: Short Sci-Fi / Philosophical Drama

Duration: ~1 minute

That’s pretty much where we might end up 😉 Don’t forget that the Chinese education system is inspired by the Romanian one from before the revolution. Real Humanoid Robot walking better tan Musk Optimus 3 that will be manufactured in 1 million exemplars in 2026..

If you want to buy me a virtual coffee: https://buymeacoffee.com/liviuflorei

I had the honor to personally meet two extremely courageous people (with real steel in their veins) who went through extreme experiences. Most likely, if I find the time, I will add those extreme stories they told me in an expanded edition of my book Trip 2.0 https://www.amazon.com/Trip-2-0-memoirs-adventures-disruptive/dp/B0D6H7ZLZL

To carry forward a family, a lineage or humanity itself, you need courage — and for quantum leaps you need a good dose of nonconformism. Just think of Planck, Marie Curie and Einstein. And it’s quite fascinating that the most prolific and nonconformist figure of our time — Elon Musk — said verbatim (see minute 32 in

or the screenshot attached to the post) in that interview: “My child is more autistic than I am.”

To have a clearer picture of children with autism spectrum conditions (I told you back when I was with Noah in therapy that 100% of autistic kids needed support): most of them have cognitive delays. There are neurodiverse people or people with milder autistic traits (you even see a good example very often on TV) who don’t need support. Clearly, those touched even slightly by Asperger traits or other spectrum traits are on a “different frequency :)” and they think much better in abstract domains. In the words of J. Rogan: I feel like a monkey in the presence of E. Musk ;)

In conclusion, when the two combine — courage and autistic nonconformism — they can lead to a major leap, if… the phenomenon is supported somehow by others ;)

Watch the full interview with E. Musk, it’s very interesting (especially for engineers): so you can understand where American society and part of humanity is heading ;)

As always in order to sustain my researches and content subscribe or buy me a virtual coffee :) here .

Some of the biggest problems with the new techno-feudalism, so successfully represented by the over-hyped AI, are at least two: data security and data privacy.

Right now there’s a lot of buzz on social media about OpenAI’s new browser, Atlas, which is supposedly “wow” and will surely dethrone old Google Chrome (of course Google will come back with something “wow” too, lol).

All your data and searches will automatically be uploaded to OpenAI’s servers in the U.S., meaning your personal information will effectively be accessible to Americans and if do you use DeepSeek probably to Chines. ;) . A clear example of what not to do regarding data security — but we move on.

About a year and a half ago, I ran a perssonal experiment to see if OpenAI – ChatGPT “sucks up” data. I wrote a Substack article about a substance property that did not exist anywhere else on the internet. Then I queried ChatGPT about that same property. Sure enough, ChatGPT “knew” — it had absorbed that knowledge. Not only did it “steal” my article, but because I had provided the Substack link , it indexed all my posts (unless it had already done so beforehand 😉).

Anyway, data privacy is a rather outdated notion in the current stage of technological evolution (cue the European GDPR warriors, lol). Personally, it doesn’t bother me too much since I want my ideas and knowledge to reach as many people as possible — though ideally, I’d like my work to be fairly compensated through my published books… so, hmmm.

A few months ago, Trump basically legalized data “scraping” for AI tech companies, justifying it as necessary to win the war against China.

Meanwhile, Reddit has sued (and is still suing) — rightly so, in my opinion — Perplexity AI in the U.S. for “training” on their data. (As a side note, OpenAI already settled with The New York Times for a modest sum after doing the same thing with their articles.)

A notable step toward data privacy is being taken by OpenAI in the U.K. through its OpenAI Enterprise partnership with the UK Ministry of Justice — now being touted as a success story for data governance in the public sector. This could pave the way for expansion across Europe, with data hosted in the EU. Long live the OpenAI business! Here’s the article.

Same story as with the EU cloud — nothing new under the sun.
For more disruptive news and ideas, support my Substack.

Now took in consideration last dramatic events (in ro and worldwide) is a continuous battle between heart and mind and the rationality seems to heading the world.

The majority of the people value interpersonal relationships and are guided more by the heart than by reason/mind, and are closely connected to nature. Interestingly, these values are completely different from those of capitalist/western society.

The Western way of life is fundamentally materialistic and driven by reason. If you are smart, then you have more possessions. The world has moved from villages and closeness to nature to cities. We live according to the cycles we create, as we can turn on the light anytime. Another major technological “conquest” is the mobile phone and the blue light TV, which is harmful to the brain, by the way. Another “technological conquest” that mimics interpersonal relationships is social media, which also harms the brain. Perhaps the brain is the most adaptable part of human biology - the rest lags behind and cannot keep up with progress (well, the brain struggles mightily too).

We can observe that a small part of the “smart” ones - in fact, we are all foolish and limited (compare yourself to the smartest person you know and see how ignorant you are. Think that even the smartest person can develop Alzheimer’s and can become a vegetable, with limited cognitive and memory capacities?) - flirt with the idea of returning to the traditional way of life.

Technology is not a bad thing; it is a natural and sometimes altruistic progression of human beings. But the greatest danger, including the AI revolution, is people. The greatest threat is that human biology has advanced slower than technological progress.

As Buddha said (from memory): “In all, there is good and bad” - think about how true this statement is for every known thing.

I conclude with what Jung said (from memory): “The greatest threat is people, because they are still unknown until now.”

So, I don’t see AI or even robots as a threat, but rather limited humans.

Punand la lucru cu relay.app si facand un agent AI

(cursul 3 ce te invata printre altele cum sa-ti automatizezi task-urile si masina AI sa lucreze in timp ce dormi) .

Am generat un rezumat - podcast al celui de-al doilea curs astfel incat pornind de la un text am generat (in somn lol) un podcast ce el gasiti facand click mai jos si sacrificandu-va 4:15 secunde din viata. Astept comments sau o cafea virtuala ca mi s-a uscat gura de atat vorbit lol. Enjoy podcast !

Here two scenes from the movie.

and the second

Enjoy and buy me a coffee here https://buymeacoffee.com/liviuflorei cause is hard to make a movie and is not pretty weather outside lol..

I’ve been wondering what might come next in the AI Revolution after the phase of AI agents. I believe the next phase — which has actually been “brewing” for quite some time — is AI digital twins, and it’s a very useful one.
To my shame, I first heard about it — both as a concept and as early implementation attempts — from Mr. Huang at NVIDIA in one of his presentations. It’s fascinating that you can simulate and test things that will happen physically long before they actually happen in the real world.

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