InnoLixir

China can't catch TSMC — the West keeps saying

That statement is true, narrowly — yet, dangerously misleading in every dimension that actually matters for national security.

Here is what's missing:

→ China produces chips at mature nodes (14–28nm) with genuine, growing self-sufficiency
→ The avionics, missile guidance, and communication electronics in the next generation of Chinese military hardware may run entirely on chips manufactured on those nodes
→ SMIC reached 7nm without a single EUV machine. The yield is low. The volume is low. The cost is high. But it exists — and is improving

30× volume gap with TSMC.
50% cost premium at 5nm.
And ten-year gap at the cutting edge.

But "China can't compete at the frontier" is not the same as "China can't manufacture the chips it actually needs."

We published a full engineering breakdown of what the gap actually is, where it is closing faster than analysts acknowledge, and what it means for nations, institutions, and engineers making decisions right now.

What is your read on this?
Are we overestimating China's chip capability — or underestimating it where it counts?

Technology is the new colonialism.

Empires once conquered with armies.

Alexander came with his organized legions.
The Mongols ruled with cavalry.
Britain had fleets.

Modern empires?

They dominate through:
• Chips
• Software
• Cloud platforms
• AI systems
• Export controls

Now, any country can have a flag, a military, and elections —

…and still not be truly sovereign if its digital backbone depends on foreign algorithms.

The old colonialism extracted:

Gold. Oil. Labor.

And modern technological dominance extracts:

Data. Dependence. Leverage.

The nations controlling semiconductors, cloud infrastructure, and AI may shape the future much more than those who are just controlling their territories.

A bitter truth:

Technology didn’t end colonialism.
It simply evolved it.

Read the full article: https://innolixir.blogspot.com/2026/05/technology-new-colonialism.html

“Soft skills” aren’t soft.

They can decide who gets trusted, promoted, and listened to — amongst equally competent professionals.

This article cuts through the fluff and focuses on the few human skills that actually drive business outcomes:

• Composure under pressure

• Clear ownership

• Productive disagreements

• Outcome-aligned communication

These aren’t personality traits.
These are actually trainable skills.

👉 How to Build Soft Skills That Actually Drive Success
https://www.linkedin.com/pulse/how-build-soft-skills-actually-drive-success-fluffy-kind-innolixir-vfvwf

Which soft skills do you think have the biggest impact on your career?
Or which skills have the biggest toll when missing?

Follow us: InnoLixir

How to Build Soft Skills That Actually Drive Success — Not the Fluffy Kind “Soft skills” — the tag itself is one of the most misleading labels in modern work environments. There is nothing soft that it has to deal with: Influencing decisions Managing conflicts Earning trust Being taken seriously — especially under pressure In reality — soft skills act as force mu...

THE TOP 10 FUTURE-PROOF SKILLS
FOR 2026 AND BEYOND
(BASED ON MARKET DATA)

The job market in 2026 isn’t just expected to change.
It’s showing signs for being braced to rewiring itself for good.

Therein —

AI isn’t replacing jobs... not yet.
But —
It’s readily redefining what humans must be great at.

Therefore —

Here is our pick of the top 10 skills...
backed by the real demand data...
that indicates,
will separate future-proof earners from the crowd:

1. AI & Data Literacy

Therein, an understanding of what AI can and can’t do is mandatory.
It requires, interpreting data, and making decisions based on it.
Thus, the skill is defining the new baseline — as email literacy once did.

2. Critical Thinking & Judgment

Machines can generate tremendous outputs.
And humans need to verify and decide on trusting and executing further.
Here, the premise is: AI can’t replace responsible human judgment.

3. Adaptability & Continuous Learning

Industry's leaders call adaptability the “new job security.”
So, those who learn, unlearn, and pivot fast can lead the longer-run.

4. Emotional Intelligence & Human Skills

AI can automate — but can't empathize, build trust, or resolve conflicts.
That’s where uniquely human characteristics come as most valued.

5. Problem-Solving & Strategic Framing

In modern working, AI can quickly answer questions you may ask.
But... those who can frame the right sets of problems can truly unlock its potential and create a disproportionately high value for businesses.

6. Cybersecurity & Resilience Awareness

As connectivity grows, so do threats associated with it.
Hence — security is no longer left for specialists only.
It’s becoming a core employability skill.

7. Cloud & Digital Platform Fluency

Cloud skills have rapidly become the backbone of digital teams.
From Amazon Web Services (AWS) to Microsoft Azure — knowing how systems scale is becoming a quiet must.

8. Creative & Innovative Thinking

When tools can automate ex*****on, the valued core shifts to original thinking and coming up with ideas that can differentiate marketable solutions.
Hence — the purely human skill is yet the most sought after.

9. Communication & Collaboration

AI writes — humans deliver impact through messaging.
So, strong communicators get faster and better opportunities.

10. Leadership & Influence

Teams and projects are still bound to succeed with human effort.
Thus, the leaders who inspire get paid premium.

SO —
THE REAL SHIFT —
ISN’T JUST ABOUT TECH

It’s all about human skills that AI can augment, not replace.

AI can handle volumes.
And humans can handle context, judgment, ethics, creativity, and leadership.

The future won’t belong to the smartest.
It's for those who can adapt complexity and create clarity around.

——

Which of these skills do you think will matter most in your field?

DEGREES or SKILLS?
WHAT THE JOB MARKET DATA SAYS ABOUT 2025

Let's begin with a bare truth:

Degrees... are no longer being seen as the guarantees of staying current with modern demands, as they once used to indicate.

But —

Skills are much more relevant now, than they used to be.

The essential market data shows:

📌 73% of employers use skills-based hiring — what they're truly looking is: what you can do — practically — not what’s printed on a piece of paper, a diploma, or a certificate issued from a respected institution.

📌 70% hirers prioritize skills over degrees — obviously, while evaluating candidates.

📌 Demand for reskilling will only increase with time — positively, consistently. It'll even require more than half the existing workforce to get adept at new skills by 2027... to remain relevant for the job market. The shift is due to ever increasing automation and AI adoption at rapid scale.

That means —

This isn’t a short-term trend.
This is indicating a paradigm shift.

WHAT THIS MEANS?

AS OF NOW —

Degrees still do matter… at least, not like before.

Because...

• Fields like medicine, law and other regulated professions still require degrees.

• Degrees are still signifying baseline commitments and learn-ability of any candidate.

However —

A degree alone is no longer guaranteeing employability.

Many graduates have been struggling to find relevant jobs. But employers are actively dropping degrees-based-gatekeeping for roles that can be best served by the skilled workforce only.

Thus —
SKILLS ARE WINNING THE MODERN WORLD

Why?

✔ Faster adaptation with new tech — where degrees often lag behind the race

✔ Real-world working proof beats anything on paper — portfolios, projects, and certifications can win any interviews

✔ Higher demand in tech, AI, cloud, and cybersecurity — skills there are outperforming any degree-based artifacts

Now —
In some markets:

Nearly "half" of job postings are no longer requiring any degrees.
There, skills are serving as filters for being good fit.

But... let's be fair —

Here, we are not being anti-degrees.

All we are talking about is being pro-performance, polishing skills.

The transition that we're facing right now is:
""" Degrees + Skills > Degrees alone """

The future seems to belong to those who combine the best from both the worlds, continuously:

🔹 Foundational knowledge — DEGREES
🔹 Practical, demonstrable abilities — SKILLS
🔹 Continuous learning mindset — UPSKILLING

Just consider —
Degrees are providing foundations, not ceiling.
And —
Skills are the structure that you can keep building on solid foundations.

If your résumé only boasts a degree... with no real-life projects to display, no portfolio to present, no skills that solve practical needs…
then you REALLY need to THINK and CALIBRATE.

———

What’s skills do you think are opening more doors than degrees alone?

AI IS QUIETLY DAMAGING THE WAY PEOPLE THINK

Don't think that this post is meant to malign AI...
The purpose here is to promote educated use.

Let's begin with a simple reality —
AI isn’t making people less intelligent.

Though —

It’s doing something far more subtle,
far more dangerous — than you think...

It’s quietly removing cognitive friction.

Why?

The answer is simple... and backed by various academic studies.

Here it goes —

When answers arrive instantly:
• We stop struggling
• We stop forming hypotheses
• We stop holding uncertainty for long enough to struggle

And the brain adapts far more quickly.

Hence —

What’s quietly changing:

1. Reduced problem endurance

People abandon thinking and using brain-power sooner,
because “the answer is just one prompt away.”

2. Shallow pattern recognition

With longer and frequent usage,
people adapt to recognizing only outputs —
and underlying structures that bring to those conclusions
get faded away from sight, memory and vision.

3. Outsourced judgment

Instead of deciding what’s correct, what's wrong,
people are getting more prone to deciding on
what sounds plausible — relying mostly on AI.

4. Lower tolerance for ambiguity

Discomfort, once used to drive insights.
Now, for heavy users of AI,
it only triggers yet another query — then, another query.

5. Confidence without comprehension

The most dangerous state in comprehension:
Knowing "what" without understanding "why."
Although AI didn’t cause this problem in the first place.
But... it tends to amplify a weakness that already exists,
by removing barriers that used to be in-place
for conventional means of learning.

However —

If — Used well, AI accelerates learning.
But if — Used lazily, it atrophies thinking.

Hence —

The difference doesn't lie in the tool, neither the tool is bad itself.
It's up-to the users themselves whether they force their brains to wrestle with tasks at-hand before they delegate them to ChatGPT or another tool.

Just —
Keep in mind —

If AI replaces your thinking, you lose depth — and with it, your leverage, too.
And if it follows you and your thinking, you'll enjoy your power over it.

Unfortunately... many people have already reversed the order.

Now —

What mental skills do you think people are losing fastest because of AI?

FIVE Things that Beginners
in EMBEDDED DEVELOPMENT Should Learn Early
— Though, They RARELY DO

Most beginners in the embedded development field, focus highly on tools.

And that’s understandable to some extent.

However —
that's also WHY many get stuck.

——

Here we have five tips — just 5 tips,
that shorten the learning curve dramatically,
if learned early:

1. Think that Hardware is Not a Stable Platform

Always assume that —
* Your sensors lie
* Clocks keep drifting
* Power fluctuates frequently
* Peripherals keep misbehaving

But —
if your code is designed to only work
when hardware behaves perfectly,
you can safely assume that it doesn’t work at all.

2. Learn to Think in Failure Modes — Not Just Features

You should ask early:
“What would happen if something fails in operation?”

Watchdogs, resets, corrupted states — these aren’t edge cases.
They’re normal.
They keep happening — especially in field deployments.

3. Timing has to be a Shared Resource

Interrupts, DMA, and background tasks —
they all compete for processing time.

So —
measure, measure, and measure.

If you don’t measure timing,
you’re relying on guessing.
And,
guesswork often fails at times
when you're least expecting it to.

Guessing only works…
until it doesn’t.

4. Simple Code Beats Clever One

Readable,
boring,
but predictable code survives —
much longer than “SMART” tricks.

In embedded systems,
clarity can be regarded as a performance booster.

5. Tools Keep Changing — Fundamentals Don’t

Your IDEs, frameworks, and libraries...
will come and go.

Keep your focus on —
understanding memory,
managing states,
and handling ex*****on order...
they stay relevant for decades.

Next time you work
on any embedded project,
keep in mind —
IF you practice
and internalize these,
as early as possible,
everything else will become easier to deal with.

——

SAVE THIS if you’re starting out,
or wish...
someone had told you sooner.

——

Which of these,
or any other tips did you learn the hard way...
or are still learning right now?

Windows 10 is fading — but the interesting part isn’t the OS.
It’s how people are responding.

— Some are moving to Windows 11, keeping continuity
— Some switching to Linux distros, gaining more control
— Some staying put, because change costs more than gives back

But —

None of these choices are purely technical.
They are reflecting how people think about:
– Risks
– Ownership
– Stability
– Responsibility

This article explores on what OS choices really say about us — beyond fanboy arguments.

👉 Goodbye Windows 10: What People’s OS Choices Reveal About How They Think
👉 https://www.linkedin.com/pulse/goodbye-windows-10-what-peoples-os-choices-reveal-how-think-mw0sf

Tell us honestly —

Which camp are you from — and what actually drove your decision?

Goodbye Windows 10: What People’s OS Choices Reveal About How They Think The end of Windows 10 isn’t just a technical milestone, or a journey to something better. It’s a psychological crossing of a barrier.

Object-Oriented Design (OOD) tailored specifically for embedded systems.

In this course, you can learn to design reliable and maintainable systems through the core thinking of OOP. That can make you a more productive developer. Additionally, opening new perspectives in embedded software design.

Leveraging OOP can help you write clean, efficient, and maintainable code, essential for the complexities of modern embedded applications.

Object-Oriented Design for Embedded Apps: SOLID Fundamentals Master Object-Oriented Design Patterns and Programming for Embedded Systems with Practical Patterns and SOLID Principles