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President Trump responds to reports that Iran is preparing to impose tolls on vessels transiting the Strait of Hormuz in 60 days.

“There will be no tolls in the Hormuz Strait for 60 days during the cease fire period, and there will be no tolls after the 60 day period has expired, unless they are imposed by and for the US,” he says.

The funniest thing about a lot of socialists is that they finally got a technology that could make their utopia slightly less delusional, and their first instinct is to regulate it into a coma.

AI and robots are literally the only realistic path to abundance, cheaper goods, less forced labor, and public ownership of automated production.

Without that, socialism is just people arguing over who gets the smaller slice.

They saw the one machine that could actually weaken wage slavery and went:

“ew, scary, ban it”

Perplexity CEO on China catching up in AI:

“Whatever you did to not let them catch up didn’t even matter. They ended up catching up anyway.

What’s more dangerous is they have the best open-source model. And all the American developers are building on that.”

That was DeepSeek.

Now Z.ai just dropped GLM-5.2:

• MIT open weights
• 1M context
• 81.0 on Terminal-Bench 2.1
• within a few points of Claude Opus 4.8

The open-source AI race is not theory anymore.

That moment when everything turns around

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.