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I am a business developer, sales professional, and FinTech strategist who strives to make an impact and change the world. For the better.

Although I have a bachelor's degree in Economics (with a major in Economics and Politics), I have been actively following and/or working in the Financial Services field since the very first year at university.

Because of the early start of my career and given opportunities to try myself out in different roles and different players in the world of finance (I worked at Western Union, Danske Bank, Norne Securities), quite quickly and easily I found myself being the most passionate about Financial Technology and its enormous potential to reinvent conventional finance and change the world for the better.

Now I am working in FinTech for more than 6 years, and every day I try to be a bit better and learn something new (and there are lots to learn!).

Currently, I am a part of Flutterwave, where I am scaling the business and leading company's expansion into Europe. Flutterwave is a Mastercard, VISA, Greycroft, Y Combinator, and Worldpay FIS-backed payments technology company headquartered in San Francisco. We're simplifying payments for endless possibilities. Flutterwave is trusted by leading companies like Uber, Facebook, TransferWise, Netflix, Jumia, Azimo, Binance, among other 90,000+ businesses. We were recognized as the #2 Most Innovative Company in Africa in 2019, according to Fast Company. We're part of 50 Future Unicorns🦄 according to CB Insights & Fast Company. Also, CNBC has included us in the Upstart 100, which lists the brightest, most intriguing, young startups promising to become the great companies of tomorrow. I am super excited to play an important part in the Financial Technology revolution, and having the ability to move the financial disruption forward.

I am highly interested in FinTech/TechFin, digital innovation (especially in banking, payments, and finance per see), and emerging technologies.

P.S. If you're passionate about FinTech as well as Blockchain & Cryptocurrency and always want to stay up-to-date, make sure to subscribe to my newsletter 🔔linas.substack.com🔔 and join over 111,000+ professionals globally who follow my work.

Linas Beliūnas

All the biggest people in AI and tech… united in one tiny dorm room… plotting the future of the world 😳

That would be incredible.

Except none of this is real.

This picture is 100% AI generated using Google’s newest model: Nano Banana Pro.

A model so good it can recreate a $10T “strategy summit”…
with a $12 IKEA lamp, tangled chargers, and a pizza box on the floor.

Masterpiece.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

All the biggest people in AI and tech… united in one tiny dorm room… plotting the future of the world 😳  That would be incredible.  Except none of this is real.  This picture is 100% AI generated using Google’s newest model: Nano Banana Pro.  A model so good it can recreate a $10T “strategy summit”… with a $12 IKEA lamp, tangled chargers, and a pizza box on the floor.  Masterpiece.

Brilliant: This is the actual tech stack holding up the global economy 👏😂

The middle couldn’t be more accurate:

↳ Unpaid open-source devs holding everything together with duct tape.
↳ AWS + Cloudflare doing 95% of the heavy lifting.
↳ AI bolted on like an afterthought.
↳ Microsoft, just… vibing aggressively.

But the bottom is where the entire plot twists.

ASML.

One Dutch company.
One machine.
One supply chain.

→ The foundation of ALL modern computing.

If ASML stumbles…

Nvidia breaks.
AI stalls.
Cloud collapses.
Finance panics.
Civilization reboots.

The funniest part?

This isn’t a meme.

It’s the closest thing we have to a global single point of failure.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

HSBC just dropped the most brutal AI report: OpenAI needs to raise at least $207 billion by 2030 so it can continue to lose money 😳

HSBC just published a 33-page analysis on OpenAI, and the takeaway is savage:

Even in their most optimistic scenario, OpenAI ends up with a $207 billion funding hole by 2030 🤯

Not because the business is collapsing.

But because the cost of intelligence is colliding with the laws of physics.

In essence, OpenAI isn’t a software company. It’s an industrial-scale energy and infrastructure project masquerading as one.

According to the HSBC model:

→ $250 billion committed to Microsoft
→ $38 billion committed to Amazon
→ 36 gigawatts of contracted compute (yes, gigawatts)

That’s enough power for a mid-sized country.

And the bill is up to $620 billion per year in data-center costs once everything goes online.

But here comes the wildest part.

HSBC assumes nearly everything goes right.

↳ 3 billion users
↳ 10% conversion to paid plans
↳ Massive enterprise adoption
↳ AI Ads
↳ AI Agents
↳ Jony Ive’s hardware moonshot
↳ 2% of the global ad market
↳ Zero competitive erosion

Even then… it’s not enough.

OpenAI still comes up short by $207B, and that’s even before adding the $10B safety buffer.

The report even hints that OpenAI may eventually need to “walk away” from parts of its cloud commitments because “less capacity is better than a liquidity crisis.”

But this isn’t just about OpenAI. This is about the entire AI economy.

If the leading company in the world - backed by Microsoft, NVIDIA, and Silicon Valley’s deepest VC pockets - can’t make the math work under ideal conditions, what does that say about everyone else? 🤔

It says the AI boom isn’t a software revolution.

→ It’s an infrastructure arms race.
→ It’s GPUs, power plants, cooling towers, land, water rights, grid upgrades, transformer stations, and supply chains.
→ It’s the biggest capex cycle since the industrial revolution - disguised behind a chat interface.

And suddenly the industry’s real bottlenecks become obvious:

Not talent.
Not models.
Not data.

Energy. Efficiency. Economics.

This is why the next breakthroughs won’t just be better models - they’ll be cheaper models.

Sparse architectures. TPU-scale alternatives. 20–60× efficiency gains.

AI that uses less, not more.

Because unless costs collapse, the race to AGI won’t be won by the smartest lab.

It will be won by the AI lab that can pay its power bill the longest.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

HSBC just dropped the most brutal AI report: OpenAI needs to raise at least $207 billion by 2030 so it can continue to lose money 😳  HSBC just published a 33-page analysis on OpenAI, and the takeaway is savage:  Even in their most optimistic scenario, OpenAI ends up with a $207 billion funding hole by 2030 🤯  Not because the business is collapsing.  But because the cost of intelligence is colliding with the laws of physics.  In essence, OpenAI isn’t a software company. It’s an industrial-scale energy and infrastructure project masquerading as one.  According to the HSBC model:  → $250 billion committed to Microsoft → $38 billion committed to Amazon → 36 gigawatts of contracted compute (yes, gigawatts)  That’s enough power for a mid-sized country.  And the bill is up to $620 billion per year in data-center costs once everything goes online.  But here comes the wildest part.  HSBC assumes nearly everything goes right.  ↳ 3 billion users ↳ 10% conversion to paid plans ↳ Massive enterpri

AI is about to change forever: Google may have just revealed the biggest shift in AI since the Transformer, and almost nobody is paying attention 😳

Google researchers just dropped something called Nested Learning, and if it works the way early results suggest, it might be the biggest shift in AI since the famous “Attention Is All You Need.”

- Not another bigger model.
- Not another trillion-parameter arms race.
- A completely new learning paradigm.

The core idea is beautifully simple yet mind-bending:

What if AI didn’t learn once but learned continuously? 🤔

- Not just updating a few temporary attention states.
- Not forgetting everything outside a 1M-token window.
- Not freezing after pre-training like it’s stuck in amnesia.

Nested Learning reframes an AI model as multiple learning systems stacked inside each other, each operating at its own speed - some adapting instantly, some slowly consolidating long-term memory.

Exactly like the human brain does.
Fast for experience.
Slow for wisdom.

And Google didn’t just theorize it. They built it 🤖

The proof-of-concept model - HOPE - already beats Transformers and modern RNNs across language modeling, reasoning, and long-context tasks at only 1.3B parameters.

- It retrieves information from massive sequences with ease.
- It resists catastrophic forgetting.
- It evolves during use.

This is not a bigger hammer. It’s a different physics.

→ Instead of stacking more layers, it stacks optimization loops.
→ Instead of making context windows larger, it makes memory smarter.
→ Instead of freezing intelligence, it lets intelligence grow.

If this trajectory holds, Nested Learning could push us closer to something that actually resembles AGI:

↳ Systems that don’t just perform but improve.
↳ Systems that don’t just store knowledge but develop it.
↳ Systems that don’t just follow rules but learn new ways to learn.

And that’s the part people aren’t ready for.

Because once AI models can rewrite their own learning processes, the frontier stops being about scale and starts being about self-improvement.

And that changes everything.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

AI is about to change forever: Google may have just revealed the biggest shift in AI since the Transformer, and almost nobody is paying attention 😳  Google researchers just dropped something called Nested Learning, and if it works the way early results suggest, it might be the biggest shift in AI since the famous “Attention Is All You Need.”  - Not another bigger model. - Not another trillion-parameter arms race. - A completely new learning paradigm.  The core idea is beautifully simple yet mind-bending:  What if AI didn’t learn once but learned continuously? 🤔  - Not just updating a few temporary attention states. - Not forgetting everything outside a 1M-token window. - Not freezing after pre-training like it’s stuck in amnesia.  Nested Learning reframes an AI model as multiple learning systems stacked inside each other, each operating at its own speed - some adapting instantly, some slowly consolidating long-term memory.  Exactly like the human brain does. Fast for experience. Slow

Incredible: Google may have just pulled off the quietest power move in AI, and almost nobody seems to grasp its significance 😳

Google’s latest AI model Gemini 3 Pro is now sitting at the top of the major leaderboards.

Not by a little, but clearly ahead on LMArena, WebDev Arena, and Vision Arena - in a year where the frontier is brutally competitive.

But here’s the part that actually matters:

Google trained it entirely on TPUs.

No NVIDIA.
No GPUs.
No external silicon.

Sure, that’s not new, as Google has used TPUs since Gemini 1.0…

But this marks the first time a TPU-trained model has matched and, in some areas, surpassed the strongest GPU-trained systems from OpenAI, Anthropic, and xAI in the same generation 🤯

Most importantly, it validates something Google has been quietly betting billions on:

Custom silicon + mature software + vertically integrated infrastructure can compete at the absolute frontier.

In other words, you don’t need Nvidia to build a world-class frontier AI model anymore.

Turns out, the next Google is Google.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Incredible: Google may have just pulled off the quietest power move in AI, and almost nobody seems to grasp its significance 😳  Google’s latest AI model Gemini 3 Pro is now sitting at the top of the major leaderboards.  Not by a little, but clearly ahead on LMArena, WebDev Arena, and Vision Arena - in a year where the frontier is brutally competitive.  But here’s the part that actually matters:  Google trained it entirely on TPUs.  No NVIDIA. No GPUs. No external silicon.  Sure, that’s not new, as Google has used TPUs since Gemini 1.0…  But this marks the first time a TPU-trained model has matched and, in some areas, surpassed the strongest GPU-trained systems from OpenAI, Anthropic, and xAI in the same generation 🤯  Most importantly, it validates something Google has been quietly betting billions on:  Custom silicon + mature software + vertically integrated infrastructure can compete at the absolute frontier.  In other words, you don’t need Nvidia to build a world-class frontier AI

End of an Era: "The Big Short" Michael Burry, the man who called the 2008 crisis, just placed a bet against AI… and then disappeared from public markets 😳

Michael Burry just made the most controversial move of the AI decade.

He spent $9.2M buying 50,000 Palantir put options expiring in 2027 - a bet that could pay up to $240M if AI hype cracks.

And right after placing it, he liquidated Scion, deregistered with the SEC, and went completely dark.

Exactly like he did before the 2008 crash.

Why is he doing this? 🤔

Burry believes the AI boom is being held up by a structural accounting illusion.

Hyperscalers are extending the “useful life” of GPUs and servers - from 2–3 years to 6-10 years - making earnings look far stronger than reality.

He estimates this inflates profits by $176 billion through 2028 🤯

Lower depreciation.
Higher EPS.
Sky-high valuations built on sand.

Palantir? Trading at a 287× forward P/E - nearly 10× the sector norm.

To Burry, that’s not innovation. That’s 2007 energy in GPU form.

The stakes are super high here.

→ Big Tech’s 2025 AI capex: $200B+
→ Key segment growth rates: <20%
→ Data center power demand: 1% of global electricity by 2027

Something doesn’t add up unless AI delivers massive productivity gains - fast.

Burry’s question: What if it doesn’t? 🤷‍♂️

There are 2 possible futures ahead.

1️⃣ The Bubble Burst

→ AI stocks drop 20–50%
→ Nasdaq loses trillions
→ Hyperscalers take massive write-downs
→ GPU supply chains buckle
→ Startups that rely on subsidized compute collapse

Burry wins big.
AI survives - but leaner, focused, forced to produce real value.

2️⃣ The AI Super-Boom

→ Productivity spikes
→ Enterprise adoption explodes
→ Capex compounds
→ AI becomes the next electricity

Burry’s puts expire worthless.

But most importantly, we need to understand what Burry is actually betting against.

Not AI itself.
Not the technology.
Not the future.

He’s betting against the story.
He’s betting against inflated earnings, manufactured EPS, and infinite-growth narratives built on depreciating silicon.

It’s the same pattern he saw in 2007: Everyone believes until the math breaks.

My takeaway is this:

Love him or hate him, Burry is doing what he always does:

He exits the stage right before everyone else sees the smoke.

The AI era is definitely not ending, but Burry thinks the first chapter is.

Buckle up.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

End of an Era: "The Big Short" Michael Burry, the man who called the 2008 crisis, just placed a bet against AI… and then disappeared from public markets 😳  Michael Burry just made the most controversial move of the AI decade.  He spent $9.2M buying 50,000 Palantir put options expiring in 2027 - a bet that could pay up to $240M if AI hype cracks.  And right after placing it, he liquidated Scion, deregistered with the SEC, and went completely dark.  Exactly like he did before the 2008 crash.  Why is he doing this? 🤔  Burry believes the AI boom is being held up by a structural accounting illusion.  Hyperscalers are extending the “useful life” of GPUs and servers - from 2–3 years to 6-10 years - making earnings look far stronger than reality.  He estimates this inflates profits by $176 billion through 2028 🤯  Lower depreciation. Higher EPS. Sky-high valuations built on sand.  Palantir? Trading at a 287× forward P/E - nearly 10× the sector norm.  To Burry, that’s not innovation. That’s 2

You don’t need a co-founder anymore - you need an AI stack. These are the exact tools solo founders are using to hit $1 million ARR in 2025:

🧠 Cursor → Code like a dev
🔍 Perplexity / Gemini → Market research
✍️ ChatGPT / Claude / Grok → Write & plan
🎨 Midjourney / Figma / Canva → Design & brand
⚙️ Zapier / Calendly / Tidio → Automate operations

That’s an entire startup.

No team. No office. No funding.
Just one person and ten tools.

And it’s working:

→ 78% of solopreneurs say AI has transformed their business
→ Generative AI spend is up 76% YoY to $644B
→ Dozens of $1M+ solo startups already proving it

But here’s the truth nobody tells you:

AI replaces tasks, not taste.
Automation builds speed, not belief.

The tools are your leverage. But You are the edge.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

You don’t need a co-founder anymore - you need an AI stack. These are the exact tools solo founders are using to hit $1 million ARR in 2025:  🧠 Cursor → Code like a dev 🔍 Perplexity / Gemini → Market research ✍️ ChatGPT / Claude / Grok → Write & plan 🎨 Midjourney / Figma / Canva → Design & brand ⚙️ Zapier / Calendly / Tidio → Automate operations  That’s an entire startup.  No team. No office. No funding. Just one person and ten tools.  And it’s working:  → 78% of solopreneurs say AI has transformed their business → Generative AI spend is up 76% YoY to $644B → Dozens of $1M+ solo startups already proving it  But here’s the truth nobody tells you:  AI replaces tasks, not taste. Automation builds speed, not belief.  The tools are your leverage. But You are the edge.

Epic: an AI detector just flagged the 1776 Declaration of Independence as 99.99% AI-written 👏😂

Either the AI detector doesn’t work, or the Founding Fathers were time-travelling prompt engineers...

And the wildest part?

These same tools are still used to expel students, flag employees, and trigger academic investigations - all based on vibes masquerading as science.

Meanwhile, millions of people are trusting software that can’t tell Jefferson from AI with life-changing decisions.

Peak 2025 risk management.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Epic: an AI detector just flagged the 1776 Declaration of Independence as 99.99% AI-written 👏😂  Either the AI detector doesn’t work, or the Founding Fathers were time-travelling prompt engineers...  And the wildest part?  These same tools are still used to expel students, flag employees, and trigger academic investigations - all based on vibes masquerading as science.  Meanwhile, millions of people are trusting software that can’t tell Jefferson from AI with life-changing decisions.  Peak 2025 risk management.

Insane: GeoSpy AI can locate an image using just a few pixels from a reflection. No metadata is needed 😳

The craziest part?

Everything you see here is run in real time and not sped up at all.

RIP privacy.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Jeff Bezos just made his biggest move since Amazon, and almost no one is ready for what it means 😳

He’s co-running a new AI startup, Project Prometheus, backed with $6.2 billion on day one.

Not for chatbots.
Not for apps.
For computers, cars, and spacecraft - the physical world.

In other words, he’s going after Tesla, NVIDIA, and SpaceX at the same time 🤯

Prometheus has already hired nearly 100 researchers from OpenAI, DeepMind, and Meta - people who actually know how to build robots, materials systems, and real-world AI.

Bezos is not chasing the “AI that talks.” He’s chasing the AI that builds 🤖

The one that can design, test, manufacture, and improve machines at superhuman speed.

That’s the real prize. The trillion-dollar one.

And when you zoom out, the picture becomes clear:

→ Musk has xAI + Tesla Optimus Bot.
→ Zuckerberg is building embodied Llamas.
→ Google is rebooting robotics.
→ And now Bezos steps in with a war chest the size of a sovereign fund.

That’s beyond just a rivalry. This is the final boss round of tech:

AI that runs factories, ships products, builds infrastructure, and eventually… builds itself.

Whoever gets there first doesn’t just win a market. They win the physical world.

And that’s exactly why Bezos came back from retirement.

He’s not here to compete. He’s here to end the game.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Wild: The Reverse Turing Test just happened in China 😳

XPENG just unveiled a humanoid robot so realistic that people thought it was a human in a suit.

Seriously, the CEO had to go on stage, grab a knife, and cut open its leg live to prove it wasn’t human.

Metal. Wires. Actuators. Not flesh 🤖

Welcome to the Reverse Turing Test Era, where machines are now so lifelike, we doubt they’re machines.

In case you missed it, XPENG’s Iron has:

→ 82 active joints
→ Synthetic muscles for fluid motion
→ 3 custom AI chips handling vision, language & action
→ Can walk, gesture, and even dance like a human

XPENG plans mass production by 2026, focusing on factories, malls, and homes.

Once, we built machines to imitate humans.

Now, we’re building humans who make us question if we’re still real.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

“Your startup is just an OpenAI wrapper”.

But everything is a wrapper…

→ Startups are venture capital wrappers.
→ VCs are rich people's wrappers.
→ Rich people are wrappers of wealth.

Zoom out far enough, and everything you build - from startups to AI - is basically just sand, reimagined.

Innovation was never about creating from nothing.
It’s about wrapping what already exists in ways no one else dared to.

That’s how every revolution begins - not from zero, but from a better wrapper.

So next time you think you need a new idea, remember: the world doesn’t need new atoms - just new wrappers for old ones.

Everything is a wrapper.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

“Your startup is just an OpenAI wrapper”.  But everything is a wrapper…  → Startups are venture capital wrappers. → VCs are rich people's wrappers. → Rich people are wrappers of wealth.  Zoom out far enough, and everything you build - from startups to AI - is basically just sand, reimagined.  Innovation was never about creating from nothing. It’s about wrapping what already exists in ways no one else dared to.  That’s how every revolution begins - not from zero, but from a better wrapper.  So next time you think you need a new idea, remember: the world doesn’t need new atoms - just new wrappers for old ones.  Everything is a wrapper.

Historic: Jeff Bezos’ Blue Origin has just successfully landed its New Glenn rocket booster, becoming only the second company in history to land a rocket booster after SpaceX 😳

Yesterday, Blue Origin finally did the thing nobody thought they’d pull off:

New Glenn landed its booster on a droneship.
First flight.
First try.
Clean landing.

And with that SpaceX’s 10-year monopoly on reusable heavy-lift rockets is over.

For a decade, SpaceX was the only company on Earth that could launch something big… land the booster… and fly it again.

That meant cheaper launches, higher cadence, and total dominance.

Blue Origin just broke that dominance.

This is the moment competition returned to space.

The space race is officially back 🚀🌎

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

West’s WeChat Moment: OpenAI may have just launched the single most important feature for the future of FinTech, & almost no one seems to realize it 😳

OpenAI just added group chats functionality, and with that, unlocked a new distribution layer.

Up to 20 people.
Planning, building, debating - all with AI inside the room.

A small feature on paper, but a paradigm shift in practice.

Because once you add social coordination to an AI interface, you’re no longer a chatbot.

You’re a platform. And platforms change everything.

For 18 months, OpenAI has been quietly assembling the components of an Everything App:

↳ Apps SDK → native apps inside ChatGPT
↳ Atlas browser → conversational navigation
↳ Sora → video + creator ecosystem
↳ Stripe integration → agentic commerce rails
↳ Now: group chats → social layer + collaboration

One interface.
One identity.
One behavioral loop.

This is the Western equivalent of WeChat’s expansion but built on intelligence, not messaging.

And the timing is perfect as ChatGPT already commands ~800M weekly users.

But here’s where it gets interesting for finance.

AI agents inside a social environment fundamentally change how people:

→ discover financial products
→ compare options
→ ask questions
→ make decisions
→ transact
→ and coordinate with others

When discovery → recommendation → decision → transaction
all happen inside ChatGPT…

Why would users jump to 12 different fintech apps?
Why would banks spend millions on customer acquisition?
Why would comparison tools survive?

That’s why OpenAI is constructing a world where the interface becomes the aggregator, and everyone else becomes a plugin.

Just like WeChat.
Just like iOS.
Just like Android.

Winner-take-most dynamics. Except this time, the OS is intelligence.

My takeaway is this:

FinTech spent a decade unbundling finance.

OpenAI is about to re-bundle all of it - inside one conversational layer.

We’re witnessing the birth of a new financial OS in real time.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

West’s WeChat Moment: OpenAI may have just launched the single most important feature for the future of FinTech, & almost no one seems to realize it 😳  OpenAI just added group chats functionality, and with that, unlocked a new distribution layer.  Up to 20 people. Planning, building, debating - all with AI inside the room.  A small feature on paper, but a paradigm shift in practice.  Because once you add social coordination to an AI interface, you’re no longer a chatbot.  You’re a platform. And platforms change everything.  For 18 months, OpenAI has been quietly assembling the components of an Everything App:  ↳ Apps SDK → native apps inside ChatGPT ↳ Atlas browser → conversational navigation ↳ Sora → video + creator ecosystem ↳ Stripe integration → agentic commerce rails ↳ Now: group chats → social layer + collaboration  One interface. One identity. One behavioral loop.  This is the Western equivalent of WeChat’s expansion but built on intelligence, not messaging.  And the timing is

Buffett is officially buying into the AI Revolution: Berkshire Hathaway acquired 17.9 million shares of Google parent Alphabet for $4.3 billion 😳

The man who sat out the entire dot-com boom.
The man who said “tech is outside my circle of competence.”

The man who built his entire career on avoiding hype, and he’s now making Alphabet one of his biggest holdings at age 95.

After the stock is already +90% since April 🤯

Warren Buffett finally said the quiet part out loud:

Google isn’t getting disrupted by AI.
Google is the disruption.

The world spent two years yelling “ChatGPT will kill Search.”
Buffett looked at the data, the distribution, the cash flow, the moat, and said:

“Actually, this might be the Coca-Cola of the AI era.”

→ Google touches billions of people every day.
→ It trains on the richest dataset in existence.
→ It embeds AI into Search, YouTube, Android, Workspace, Cloud. At the planetary scale.

Because in AI, Data + Distribution is everything.

And Google has both at an absurd scale.

Most importantly, Buffett doesn’t chase trends. He buys inevitabilities.

And today he told the world something very simple:

If the biggest tech skeptic of our time is buying Google now, maybe the AI revolution is just getting started.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Buffett is officially buying into the AI Revolution: Berkshire Hathaway acquired 17.9 million shares of Google parent Alphabet for $4.3 billion 😳  The man who sat out the entire dot-com boom. The man who said “tech is outside my circle of competence.”  The man who built his entire career on avoiding hype, and he’s now making Alphabet one of his biggest holdings at age 95.  After the stock is already +90% since April 🤯  Warren Buffett finally said the quiet part out loud:  Google isn’t getting disrupted by AI. Google is the disruption.  The world spent two years yelling “ChatGPT will kill Search.” Buffett looked at the data, the distribution, the cash flow, the moat, and said:  “Actually, this might be the Coca-Cola of the AI era.”  → Google touches billions of people every day. → It trains on the richest dataset in existence. → It embeds AI into Search, YouTube, Android, Workspace, Cloud. At the planetary scale.  Because in AI, Data + Distribution is everything.  And Google has both

Nailed it! This has to be the best illustration about Enterprise AI 👏😂

Everyone wants AI Agents, but nobody wants to admit their data looks like a crime scene.

What execs think AI Agents will do:

→ Fix workflows
→ Boost margins
→ Turn the company into a machine that prints EBITDA

What actually happens:

→ 37 data sources, none agreeing with each other
→ Compliance sweating harder than the GPUs
→ Agents hallucinating because they’re feasting on chaos

And the uncomfortable truth is this:

AI agents aren’t failing. Your data strategy is.

You can’t expect intelligence from an ecosystem held together by CSVs, legacy systems, and hope.

That’s not innovation. That’s an expensive science fair project.

Fix the data first, and only then implement AI.

That’s when AI Agents stop being a demo and start becoming your competitive advantage.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Nailed it! This has to be the best illustration about Enterprise AI 👏😂    Everyone wants AI Agents, but nobody wants to admit their data looks like a crime scene.    What execs think AI Agents will do:    → Fix workflows  → Boost margins  → Turn the company into a machine that prints EBITDA    What actually happens:    → 37 data sources, none agreeing with each other  → Compliance sweating harder than the GPUs  → Agents hallucinating because they’re feasting on chaos    And the uncomfortable truth is this:    AI agents aren’t failing. Your data strategy is.    You can’t expect intelligence from an ecosystem held together by CSVs, legacy systems, and hope.    That’s not innovation. That’s an expensive science fair project.    Fix the data first, and only then implement AI.    That’s when AI Agents stop being a demo and start becoming your competitive advantage.

AI is going back to the basics: ChatGPT’s Android beta app code just confirmed that OpenAI is launching Ads 😳

Not rumors.
Not speculation.
Hidden strings in the Android beta: “search ads carousel”, “bazaar content”.

This was only a matter of time because OpenAI is burning cash at a rate no startup in history has ever survived.

HSBC’s recent model showed the brutal truth:

→ Up to $792B in cloud + compute costs by 2030
→ $620-702B in annual data-center bills
→ $207B funding shortfall even under optimistic assumptions
→ Only 5-10% of users pay today
→ Growth = more usage = more loss

In other words, the free tier is a money pit.

So ads were never optional. They were inevitable.

The recent leak simply shows the moment the company stops pretending otherwise.

But here comes the interesting part.

OpenAI thinks ads could be a multi-billion-dollar revenue line.

↳ 2% of the global ad market.
↳ Integrated into shopping assistants.
↳ Invisible to paid users.

A Google-style engine inside ChatGPT.

And that’s the real shift.

AI isn’t just becoming the new interface. It’s becoming the new advertising surface.

The ironic part?

OpenAI is quietly turning into Google while Google is turning into OpenAI.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

AI is going back to the basics: ChatGPT’s Android beta app code just confirmed that OpenAI is launching Ads 😳  Not rumors. Not speculation. Hidden strings in the Android beta: “search ads carousel”, “bazaar content”.  This was only a matter of time because OpenAI is burning cash at a rate no startup in history has ever survived.  HSBC’s recent model showed the brutal truth:  → Up to $792B in cloud + compute costs by 2030 → $620-702B in annual data-center bills → $207B funding shortfall even under optimistic assumptions → Only 5-10% of users pay today → Growth = more usage = more loss  In other words, the free tier is a money pit.  So ads were never optional. They were inevitable.  The recent leak simply shows the moment the company stops pretending otherwise.  But here comes the interesting part.  OpenAI thinks ads could be a multi-billion-dollar revenue line.  ↳ 2% of the global ad market. ↳ Integrated into shopping assistants. ↳ Invisible to paid users.  A Google-style engine inside

Wild: Google just launched Gemini 3, and it might be the first AI that actually feels smarter than you 😳

It’s no longer just a “better chatbot.” It’s more like a thought partner.

A model that doesn’t just answer - it understands, reasons, builds, and creates.

Here’s why everyone’s freaking out:

↳ 1. It sees the world like a human.

Gemini 3 can watch a full-length video (hours of it) and understand plot, style, intent, and emotion.
Then remix it into something new.

Nothing else can do this.

↳ 2. It codes like a senior engineer.

Record-breaking performance on coding benchmarks.
Long refactors, messy codebases, multi-step planning - no sweat.

We’re finally moving from autocomplete to competence.

↳ 3. “Vibe coding” is the cheat code.

Say: “Make an app that feels like rainy Tokyo nights.”
Gemini 3:
→ designs it
→ animates it
→ scores it
→ builds it.

No specs.
Just vibes → product 🤯

↳ 4. The context window finally works.

Drop in a full codebase, a giant doc dump, or a 3-hour meeting.
Gemini 3 stays coherent.

Most importantly, it stays smart & useful.

My takeaway is this:

Gemini 3 probably marks a line in the sand.

The models before it feel old, while the models after it will feel dangerous.

And somewhere in between, the future of AI just arrived early.

P.S. check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Jeff Bezos just said the quiet part out loud: “Human progress will demand moving heavy industry off Earth.” 😳

Factories.
Data centers.
All of it - in space.

Using endless solar energy.
Mining asteroids for raw materials.
Leaving Earth as the home we protect.

“There’s no Plan B. This is the good one” - Jeff Bezos

It sounds wild. But it’s also… inevitable.

AI’s energy demands are exploding.
Data centers could soon eat 8% of global electricity.
Grids are cracking. Cities are overheating.

So what if the next data center isn’t in Texas but in orbit? 🤔

Projects like Google’s Suncatcher, Starcloud, and Blue Origin are already testing it.

→ Solar power with no night or weather.
→ Cooling powered by the vacuum of space.
→ Asteroid resources worth quadrillions.

Bezos’ speech just connected the dots:

AI → Energy → Space → Civilization shift.

If it works, we unlock a future of abundance:

↳ Infinite clean power
↳ Restored ecosystems
↳ Trillions in new industries
↳ Jobs no one’s imagined yet

If it fails, well, we’ve just wasted decades chasing stars while Earth suffers.

Either way, the question isn’t IF anymore.

It’s WHEN energy becomes too scarce, and who moves first.

Brilliant: This is exactly what it’s like to watch AI fixing a bug 👏😂

AI won’t take your job but it might rewrite it, refactor it, and break it before lunch.

P.S. for more great stuff, check out 🔔linas.substack.com🔔, it's the only newsletter you need for all things when Finance meets Technology. For founders, builders, and leaders.

Air Products

Project Manager

Cosette Pharmaceuticals, Inc.

Project Engineer

Allied Engineering and Design

•	Directly managed a multitude of petrochemical projects with CAPEX up to $15 MM USD, utilizing stage-gate methodology. Scope of responsibilities ranged from risk evaluation, definitive planning, FEED and execution planning, Engineering / Procurement / Construction Execution and supervision, and project completion handoff. 
•	Ensured all projects remained on-budget and on-schedule by maintaining key metrics. Supervised and troubleshoot mechanical, piping, civil, electrical, instrumental/control, PHA and HAZOP designs. Provided technical analysis, risk assessment, and compiled data/information to resolve and troubleshoot system process problems. Issued PR/PO through SAP for any required equipment/resource. 
•	Managed IFC fabrication/procurement, fieldwork operations, and led Pre-Startup Safety Reviews (PSSR) to ensure HSE/SHE compliance. 
•	Experienced emergency response PE who safely handled several business-critical projects while working with 250+ employees, vendors, and subcontractors.

Project Engineer at Infineum USA L.P.

Petron Scientech Inc / BioChem USA

•	Project management and engineering in a lean-team environment working on 8 to 12 concurrent multidisciplinary international projects through every phase of the project execution process, from conceptualized design to plant startup.
•	SME in processes such as; lignocellulosic bioethanol, Ethanol to Ethylene catalytic dehydration (ETE), Maleic Anhydride, High-Density Polyethylene (HDPE), bio-Glycols, and High-Purity Ethylene Oxide (HPEO). 
•	Assisted in preparation of BEDP and FEED package development, managed greenfield projects with the site and market feasibility, traveled to meet and negotiate with key Fortune 100 Chemical Process Industry (CPI) partners to ensure supplier, logistics, technology packages, EPC, and off-taker agreements. Furthermore, written and co-signed all appropriate NDAs, LOI, MOU, RFQs, and proposals. Business Development liaison for pre-commissioning phase projects and client negotiations. 
•	Developed new and updated PFDs and P&IDs using AutoCAD, calculated heat and material balances through CHEMCAD simulation, and equipment sizing/selection. Supervised and troubleshooted mechanical, piping, civil, electrical, instrumental/control, PHA and HAZOP designs and construction. Provided technical analysis, risk assessment, and compiled data/information to resolve and troubleshoot system process problems. Developed financial models that assessed various metrics (e.g. CAPEX/OPEX, IRR, EBITDA) for new projects.
•	Secondary position as the Systems Manager. Provided Systems/IT management and installation of new framework services, cloud operations, website maintenance, server setup, digital design, CRM and CMS administration, and general technology support.

Project Development Engineer

AustarPharma

•	Operated a multitude of well-calibrated manufacturing devices such as the high-shear granulator, fluid bed drying, dry and wet milling, blending, single and double layer tablet compression, capsule filling, and tablets/beads coating within an FDA and DEA (CII-CV) registered state-of-the-art cGMP commercial facility. 
•	Worked in a team-orientated environment where extensive sample data was recorded and validated during each process to ensure proper scale-up conditions and parameters were met.
• During R&D formulation development stage, various pharmaceutical drugs were reverse engineered and tested using an array of analytical and laboratory methods such as in-vito dissolution experiments. 
• Trained and supervised new staff. Demonstrated operational techniques and strategies within the production division. 
• Written and edited Standard Operation Procedures (SOP), Validation Protocols, and Root Cause Deviation reports based on regulation standards.
• Formulated and produced various pharmaceutical products including, but not limited to; Methocarbamol, Alendronate. and many others within the R&D development stages.

R&D Formulation Scientist and Production Technician

New Jersey Institute of Technology

•  Assisted the Vision and Neuro-Engineering Laboratory of the Biomedical Engineering Department in attaining concise data on human visual reaction to stimuli 
•  Wrote a research paper on the extended effects of virtual reality on the human psyche.

Virtual Reality Research Assistant

• Worked with Professor Boris Khusid on the development of electro-microfluidics for the control and manipulation of fine particles through a reverse osmosis separation membrane. 
• The fundamentals of micro-scale electro-hydrodynamics to the level where it will become useful in the design and operation of novel sensor

NASA Research Assistant

Mr. Sergey Tsvetkov is an experienced PMP-certified bilingual Project Manager with a proven record of successful execution of international projects, technical management, scheduling, supervision, and gated project completion with industrial processes including, but not limited to; batch pharmaceutical tablet process and ointment production, lignocellulosic bioethanol, Ethanol to Ethylene catalytic dehydration (ETE), Ethylene Oxide and Glycols, Air Separation technologies (ASU, PSA, and VSA), mechanical lubricants and oil additives, various R&D experience in electro-microfluidics, and reverse-engineering pharmaceuticals. 

Multidisciplinary skillset in Program Portfolio Management, Construction Supervision, Project Engineering, Process Engineering, Business Development, Financial Modeling, Computer Science, and Research & Development.

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