Still holding on to that 1% of hope

Nothing is real. We live in an illusion.

Figure AI humanoids completed a logistics challenge running continuously for 200 hours without a single failure

The future is starting to feel very real

Three exponential curves are driving robotics forward:

- AI getting better
- Chips and compute getting cheaper and more powerful
- Robot hardware and dexterity getting better

Any one of these trends would be significant. What about all three trends at the same time?

Kind of trust you develop with your trading bros who saw the highs and lows

Goldman Sachs Research: AI data centers are no longer being financed mainly by traditional corporate balance sheets.

They are increasingly funded through alternative assets like infrastructure, private equity, real estate, and private credit.

i.e. AI is increasingly becoming a real-assets infrastructure story, not just a software or semiconductor story, data centers are now being financed like pipelines, toll roads, utilities, and warehouses.

Morgan Stanley estimates about $2.9 trillion capital expenditure of global data-center construction through 2028.

With funding sources including $1.4T from hyperscaler cash flows, $200B corporate debt, $150B securitized credit, $800B private credit / asset-based finance / JV debt, and $350B other capital.

i.e. AI capex is increasingly credit-funded, so losses could spill beyond shareholders.

dot-com bubble vs. a possible AI bubble.

From the famous "Dean of Valuation", Professor Aswath Damodaran, of NYU Stern School of Business,

“And that’s the real big difference between the dot-com boom and bust and the AI boom. We don’t know whether there’ll be a bust. History suggests there will be a bust.

The dot-com boom and bust had no huge capital expenditure in that cycle. In fact, there was very little traditional CapEx, or even R&D, driving it. People started apps. They basically started going on it.

This has been the biggest infrastructure run-up I think I’ve ever seen in business. You can go back and compare it to the automobile business 100 years ago. The amount of money that’s being put into AI CapEx is immense, which means that when the correction comes, the pain will be more intense.

And herein lies the second problem. The dot-com boom and bust was almost entirely equity-funded. You think, so what? Well, when the bust came, those shareholders lost 60%, 70%, 80%, or 90% of their money. You felt sorry for them, but the loss was restricted to the shareholders.

The problem with the AI CapEx boom is that not only is it immense, but a big chunk of it is funded with debt, and the debt is coming from private capital rather than banks. There’s a very real chance that if there’s a correction and companies start having problems, that problem is going to show up as distress and default, and that really doesn’t stay restricted. It spills over into the rest of society.

I’m not saying it’s going to be 2008, but 2008 is an example of what happens when lenders overreach, when they lend money at too low a rate, and the correction comes. The pain spills over.

So that is my concern with this big market illusion: the potential societal cost of having to deal with debt coming due that you’re unable to pay. It’s much more painful than your share price dropping 90% and you feeling the pain."

Classic Bezos-style wisdom

"When you're under 40, never hire your friends. When you're over 40, only hire your friends"

- Jeff Bezos at a panel interview in Paris alongside Blue Origin CEO David Limp

For some context, Bezos founded Blue Origin in 2000 and personally hired longtime Amazon senior exec David Limp as its CEO in December 2023

Perfect immunity from jailbreak is not possible even for the strongest of LLMs.

New study shows that frontier models are getting harder to jailbreak, but not impossible to jailbreak.

The study attacks Anthropic’s Fable 5 and Opus 4.8 with automated red-team tools that keep rewriting harmful prompts until the model either refuses or gives a bad answer.

Fable 5 was more robust than Opus 4.8, with its worst attack success rate at 6.1%, while Opus 4.8 reached 11.5% under the strongest attack.

The hard truth is that avoiding absolutely every jailbreak is practically impossible, because even a tiny failure rate can produce many harmful completions when attacks are automated and repeated at scale.

The most crucial point is, that the old cartoon version of jailbreaks, weird encodings and theatrical role-play, is no longer the main problem.

The surviving weakness is contextual, because adaptive attackers rewrite the request after refusals, searching for a frame the model treats as legitimate rather than dangerous.

That is why perfect immunity is probably the wrong target; language models do not inspect intent from a clean moral altitude, they infer meaning through phrasing, context, and precedent.

In any system this flexible, there will always be boundary cases where a harmful request looks enough like education, safety research, fiction, troubleshooting, or policy analysis to slip through.

Bill Gates thinks some of the companies spending the most on AI are going to regret it (Save this).

His argument is that the current investment frenzy is going to produce a wide range of outcomes:

1. Some companies will be glad they spent every dollar.

2. Some will will have committed to data centers with electricity costs that are too expensive.

3. Some bought a generation of chips before capturing their full value.

You do not get to opt out of the race if you want to be a tech company but entering the race does not guarantee you win it.

The constraint he keeps returning to is power.

His solution:

Nuclear reactors placed specifically in locations where the economics and political acceptance are already strong.

This is because no data center buildout has permission to raise residents' electricity bills.

Jeff Bezos just compressed the entire AI race into one sentence. It has nothing to do with technology.

Bezos: “Think about the things that are not going to change over 10 years and those are probably the big things.”

Not a word about models. Not a word about compute. Just the oldest truth in commerce, dressed in the quietest language possible.

The whole industry is sprinting to predict the next disruption. Bezos is pointing at what has never been disrupted.

Bezos: “10 years from now customers are still gonna want low prices. I know they’re still gonna want fast delivery, and I just know they’re still gonna want big selection.”

Cheaper. Faster. More.

Those are not preferences. Those are instincts. Hardwired before we had fire, let alone software.

Bezos: “It’s impossible to imagine a scenario where 10 years from now a customer says, ‘I love Amazon, I just wish the prices were a little higher.’”

That sentence has never been spoken in the entire history of human commerce.

Now pull every headline and every hype cycle out of AI. Look at what remains.

Intelligence approaching free. Labor approaching free. Delivery approaching instant.

The most advanced technology in human history is not chasing the future. It is chasing the oldest demands the species has ever had.

Bezos: “When you identify the big things, you can tell they’re worth putting energy into because they’re stable in time.”

You do not need to outrun the market. You do not need to outpredict it. You need to see the thing it has always wanted and build into it until nothing on earth can move you.

The future was never a mystery. It was always just the past, moving faster.

Elon Musk just laid out why the probability you’re living in base reality is mathematically indistinguishable from zero.

Not as philosophy.

As arithmetic.

Any civilization that survives long enough builds the computing power to simulate a reality as real as its own.

That simulated reality produces conscious beings with no mechanism to know they aren’t original.

Those beings build their own simulations. The chain never breaks.

One original reality. Billions of simulated ones stacked inside each other.

No floor. No ceiling. No edge you could ever reach to find out.

Now tell yourself you’re in the original.

Musk: “If you apply Darwin to simulation theory, then only the most interesting simulations will continue. Therefore, the most interesting outcome is the most likely, because it’s either that or annihilation.”

Natural selection doesn’t just govern biology.

It governs which realities survive.

Boring simulations get terminated. Stagnant timelines get deleted. The only realities that persist are the ones worth the compute.

Musk: “We could be an alien Netflix series. And that series is only going to get continued if our ratings are good.”

The rise of artificial intelligence. The race to Mars. A species merging with its own technology.

This isn’t chaos.

This is a civilization that can’t afford to be boring.

And the man building the AI, the rockets, and the robots might understand something the rest of the species hasn’t processed yet.

Innovation isn’t ambition.

It’s how you keep a simulation from getting cancelled.

Musk: “Really we have one goal: keep it interesting.”

The question was never whether any of this is real.

It’s how many layers deep you are.

And that number might not even be finite.

Oracle Co-Founder and Chairman Larry Ellison explains why the leap from inferencing to reasoning is the most important evolution in AI:

Most people still think of AI as a prediction engine.

They're already behind.

Ellison draws a clear line between what AI used to do and what it does now, and the gap between the two is larger than most people appreciate.

"Not long ago, what we called reasoning was called inferencing. People would talk about — we got to train the model, and then we're using the model — and when the model was reasoning, we reduced that to just inferencing, a type of reasoning. That's no longer true."

Early AI models did one thing well: they inferred.

They took an input, matched it against patterns, and produced an output. Fast and useful, but fundamentally limited. The model wasn't thinking, it was retrieving.

That era is over.

"They reason like we reason. They do deductions. They do inference. They do calculations. They have strategy. They have rules. All the reasoning techniques that we use, they simulate and use."

This is a meaningful shift. Reasoning is a different cognitive process altogether.

One that works through a problem step by step, weighs options, applies strategy, and arrives at conclusions through logic rather than pattern recognition.

And this shift has real-world consequences for how AI gets deployed.

Ellison points out that not every AI application has the luxury of time to reason.

Autonomous vehicles and robots require local, on-device compute because a delayed decision in the physical world carries real consequences.

"You need a very very low latency response time," he explains. "That's why all the Tesla cars, all the Tesla robots have to have local compute in the car, local compute in the robot to make an immediate decision."

But for tasks where time is available, writing code, solving complex problems, working through multi-step challenges, the model can do something closer to what we do when we sit down to think hard about something.

"If you're writing code, I can tell you what code to write and you can take a moment to think about it and then give an answer."

Two categories. Two different demands. But both powered by the same underlying evolution, from systems that infer to systems that reason.

And the ceiling on that reasoning? Still being discovered.

"They think a lot faster than we do and solve problems a lot faster than we do. Or they solve really complicated problems that we can't solve at all."

Jonathan Ross, Founder and CEO of AI chip company Groq, offers a contrarian view: AI won't destroy jobs, it will create a labour shortage.

He outlines three things that will happen because of AI:

First, massive deflationary pressure.

"This cup of coffee is going to cost less. Your housing is going to cost less. Everything is going to cost less."

He explains this will happen through robots farming coffee more efficiently and better supply chain management, meaning people will need less money.

Second, people will opt out of the economy.

"They're going to work fewer hours. They're going to work fewer days a week, and they're going to work fewer years. They're going to retire earlier because they're going to be able to support their lifestyle working less."

Third, entirely new jobs and industries will emerge.

Jonathan points to history as evidence:

"Think about 100 years ago. 98% of the workforce in the United States was in agriculture. When we were able to reduce that to 2%, we found things for those other 98% of the population to do."

He continues:

"The jobs that are going to exist 100 years from now, we can't even contemplate."

Software developers didn't exist a century ago. In another century, they won't exist either, "because everyone's going to be vibe coding."

The same applies to influencers, a career that would have been unthinkable 100 years ago but now earns people millions.

His conclusion: deflationary pressure, workforce opt-outs, and new industries we can't yet imagine will combine to create one outcome...

"We're not going to have enough people."

🚨Iran’s negotiating team arrived in Zurich, Switzerland

"I love the smell of napalm in the morning "

55% of the KOSPI index is composed of two memory manufacturers: SK Hynix and Samsung.

Basically if the KOSPI falls, so do $MU, $SNDK, etc.

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