JD Vance on Iran: "The basic deal that we cut was, we'll lift our blockade if you stop shooting at ships, but if you shoot at ships, we are going to punch back, and we're going to punch back harder than ever before."

The framework: blockade lifted in exchange for no attacks on commercial shipping

Iran allegedly broke that condition, with strikes on 3 commercial vessels transiting Hormuz

The US response described as "a series of powerful strikes"

This is the mechanism behind the latest escalation. The moment tankers got hit, the truce was voided by design.

Apparently Iran called Trump and "They want to make a deal so badly..." 🤪

"We've already won"

Nasdaq futures are holding. Almost as if it's magic... 😉

Futures are green. Is the crisis already over? 😜

Well... Trump did say you would get tired of winning...

The U.S. 3 month treasury yield has begun breaking upward this week.

$KOSPI/USD H2 #Indicator #Signal #Trading #GlobalOneAI

South Korea's KOSPI margin debt hits $19 billion, as analysts warn of possible forced-selling if the market rout continues.

U.S. military flights to Europe and the Middle East are ramping up.

Looks like the U.S. is going to war again on behalf of Israel.

Goldman Sachs: "Token use by AI agents is expected to multiply 24 times by 2030"

AI agents are now creating the first serious cost test for the AI boom. As was reported this week, Uber and Microsoft are already rethinking expensive agent usage.

A chatbot may answer once, but an agent plans, calls tools, checks results, edits mistakes, and repeats the loop.

That loop can make one user request consume 10x, 50x, or even far more tokens than a normal answer.

Goldman’s bullish case is that monthly token use could reach 120 quadrillion by 2030, while inference cost per token keeps falling 60%-70% per year.

The fight is now between agent productivity and token waste.

"Every 10 seconds, global token demand is around 31.7 billion in 2026. By 2030 its 1.27 trillion, a 40x increase."

~ Qualcomm CEO Cristiano Amon:

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The token explosion is not mainly about smarter answers; it is about AI moving from human-paced interaction to Agent-paced activity.

Once agents become persistent, the economy of AI stops will be the background infrastructure.

Every useful action has a hidden bill: context must be carried, memory must be updated, sensors may need to be interpreted, and mistakes must be caught before they become expensive.

The middle east right after Iran feels unhappy with the U.S

Goldman Sachs new report "An AI Job Apocalypse?"

Says AI could displace 15mn workers, but not cause mass unemployment.

Estimates AI could lift productivity and GDP by 15% after full adoption.

The clearest pressure sits in customer support, back-office work, claims, billing, and entry-level tasks.

Goldman’s own labor model finds a small current drag of 16K jobs monthly.
Younger workers look more exposed because AI can absorb the basic tasks that teach judgment.

College graduates are not collapsing yet, but their industries adopt AI faster than others.

Joseph Briggs, GS global economists still expects more than 9% of workers to face displacement across 10 years.

MIT professor Daron Acemoglu is more cautious, expecting 2-4% job losses across 5 years. His concern is that current AI replaces routine office tasks more often than it supports workers.

Neil Thompson of MIT adds a missing filter: capability does not mean reliability, access, or cheap deployment. A chatbot can answer broadly, but businesses need accuracy, private data, and repeatable workflows.

The xAI team really cooked with Grok 4.5.

The price to performance ratio is honestly kind of insane. Getting frontier-level performance this close to open source hosted pricing is a huge deal. AI inference just got a lot more accessible. 🔥

Both Elon Musk and Demis Hassabis has said robotics is bottlenecked by hands and robots will not become useful until hands improve massively.

And now 1X Technologies is preparing to reveal a robotic hand that may surpass human finger control.

The big deal here is the controllable force across the small joints that make dexterity possible. A 10-20DoF hand would sit near the hard boundary between compact hardware and humanlike control.

The design appears built around Bowden tubes, which route force through cable-like tendon paths.
Real intelligence may be hiding in the routing, not the fingers.

That architecture lets actuators sit away from the fingers, keeping the hand lighter.

A human hand uses the same broad trick, with muscles pulling tendons across joints.

1X is applying that idea to humanoid robotics, where compact hands must handle real objects.

The visible side reportedly shows 20 tendons, suggesting 10 paired actuator paths.

A matching hidden side could raise the system to 40 tendons and 20 actuators.

The lower estimate points to coupled finger joints, where one tendon path drives several links.

The higher estimate points to independent IP control, where each finger segment can move separately.

That difference separates a strong gripper from a hand that can shape contact precisely.

The catch is calibration, because tendon friction, stretch, and backlash can erase beautiful mechanics.

If 1X has solved that reliably, the hand could become a serious advantage for NEO.

39 gold miners sit in the world's top 100 mining companies.

Just 22 copper miners out earn all of them.

By share of $730B in combined 2025 mining revenue:

1️⃣ Copper: 22 companies, 28.1% of revenue, the single largest share of any commodity

2️⃣ Gold: 39 companies, more producers than any other metal, but only 21.3% of revenue

3️⃣ Iron ore: just 5 companies, still out-earning gold at 22.4%

4️⃣ Glencore alone earned $63B, more than the entire coal sector combined

Volume isn't value. The revenue crown belongs to copper and iron ore, not gold.