Sebastian

Believe in the dream. Don’t give up. 🇪🇺EU/Acc

[Sebastian @is_ober]

Tja.

[German Simply 🇩🇪 @GermanSimply_]

"Tja."
The ultimate German reaction to everything.

[Sebastian @is_ober]

SOTA frontier models now only lead by small margins. With Fable from Anthropic having approx a 10-12% lead. Amazing how dynamic this field still is at this level.

[Z.ai @Zai_org]

Introducing GLM-5.2: Frontier Intelligence, Open Weights

- Significant improvements in coding and agentic tasks
- Strong long-horizon capabilities with a 1M context window
- Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong balance between performance and token efficiency
- MIT-licensed open weights
- Same API pricing as GLM-5.1

Tech Blog: https://t.co/LAsxUdN0JZ
Weights: https://t.co/g0A1C4UWx4
API: https://t.co/Kc3E22cbN7
Coding Plan: https://t.co/Nk8Y98HNhU
Chat: https://t.co/WCqWT0qCQb

[Sebastian @is_ober]

This is bad. I am sincerely sorry for the people impacted. But it’s seems this or worse has to happen before German society and government (politicians / bureaucrats) understand that the party is over (long) - we need real change. No incremental BS. Afraid this is still warmup.

[Holger Zschaepitz @Schuldensuehner]

Hello from Germany, where the auto crisis just deepened. BMW has issued a major profit warning, implying a profit drop of >60%. Its EBIT margin is now expected at just 1–3%; a shocking level for a premium automaker that once stood for double-digit profitability. This comes only a day after VW executives reportedly described their own company as facing an existential threat, according to Manager Magazin. BMW is now worth less <€40bn.

[Sebastian @is_ober]

Orchestration as post SOTA model optimization frontier. Game on.

[OpenRouter @OpenRouter]

Introducing the Fusion API, the smartest compound model in the market.

Fusion achieves Fable-level intelligence at half the price.

How it works 👇

[Sebastian @is_ober]

Stoically not giving up yet, on this hope.

[DHH @dhh]

May Europe one day wake up and start striving for this level of capitalistic homerun. Dump the degrowth nonsense, celebrate progress, and once again reach for the stars.

[Sebastian @is_ober]

The consumer harness entered the chat.

[Mark Gurman @markgurman]

It’s easier than ever to use ChatGPT - and in the future other third-party AI models installed via the App Store - inside of Siri and the Siri app. All the prep work is in there for Siri to be a platform for both Apple’s own AI and rival options.

[Sebastian @is_ober]

Powerplay is on.

[SightBringer @_The_Prophet__]

⚡️This is a monster signal.

This is the moment frontier AI stops being treated like software and starts being treated like controlled strategic capability.

The key phrase is not “customers.”

The key phrase is “foreign national Anthropic employees.”

That means the state is no longer only controlling chips, model weights, or overseas access. It is moving into cognition access by nationality. That is the real threshold. The U.S. government is saying the highest models are sensitive enough that even people physically inside the United States, working inside the company, may be barred from touching them if their nationality creates deemed-export risk.

That is weapons-control logic.

This is ITAR logic for intelligence.

The corporate language about a “misunderstanding” is probably diplomacy.

Companies say that when they need to preserve customer trust, employee morale, and regulatory room. But national security authorities do not force emergency suspension of top model access because someone made a minor paperwork mistake.

Something about Fable 5 and Mythos 5 crossed the line: cyber capability, autonomous R&D acceleration, AI-improving-AI utility, bio/security planning, code exploitation, or some blend of all of it.

The U.S. state just showed that Anthropic does not fully control Anthropic’s frontier layer.

That is the phase change.

Labs can brand themselves as public-benefit AI companies. They can talk about safety. They can sell enterprise plans. They can publish model cards. But once the models become national capability, the sovereign arrives. The state does not need to own the company to control the access surface. It only needs legal authority over export, security, procurement, and liability.

This confirms the arc we’ve been tracking:

Frontier AI becomes state-supervised strategic infrastructure.

Public AI splits from strategic AI.

Foreign access gets restricted.

Labs become quasi-defense contractors.

Model access becomes a national security perimeter.

Enterprise customers learn that API access is not property. It is revocable permission inside a sovereign-controlled stack.

The most important implication is organizational.

If foreign national employees can be cut off from frontier systems, AI labs now have to reorganize internally around citizenship, clearance, compartmentalization, and controlled access. That breaks the old Silicon Valley assumption that global talent can freely collaborate around the frontier. The next AI lab structure looks less like Google in 2015 and more like a defense prime crossed with a classified research facility.

For markets, the winners are the national champions with U.S.-aligned infrastructure, cleared customer channels, government relationships, compliance capacity, and domestic compute. The losers are open access, foreign-dependent AI wrappers, offshore model distributors, and any enterprise whose moat depends on unrestricted access to frontier APIs.

For geopolitics, this is escalation. China will read this correctly. Allies will read this correctly. Every serious state will understand that frontier models are now part of national power.

The AI race just moved from “who has the best chatbot” to “who controls cognition as a strategic asset.”

[Holger Zschaepitz @Schuldensuehner]

Good Morning from Germany, where corporate insolvencies keep climbing: Courts registered 2,308 business bankruptcies in March 2026, up 15.8% YoY, and highest since 2013. Consumer insolvencies jumped even more sharply, by 18.9%. The squeeze on Germany’s economy is far from over.

[Sebastian @is_ober]

And when the tide comes in, some will be washed out. Insane.

[Chubby♨️ @kimmonismus]

Subscription plans are massively subsidized.

And by massively, I mean absurdly:

Claude Max 20x: $200/month, with usage reportedly worth around $8,000

ChatGPT Pro 20x: $200/month, with usage reportedly worth around $14,000

[Sebastian @is_ober]

First movers addressing this will be also the winning firms coming out on the other side. Courage playbooks are en vogue again.

[Chubby♨️ @kimmonismus]

Interestingly, banks are the sector where AI will first cause significant job losses.

Banks are openly preparing for AI-driven job cuts, with executives at JPMorgan, Citigroup, Goldman Sachs, and Standard Chartered acknowledging that roles will be eliminated as the technology takes hold.

Junior analyst classes are being cut by as much as two-thirds, leaving students struggling to break into finance, even as banks still source most of their AI talent from those same entry-level cohorts.

Meanwhile, banks are rolling out targeted AI use cases like Citigroup's wealth-management avatar and Revolut's in-app assistant, though some doubt that all the announced cuts are truly AI-driven rather than cover for prior overhiring.

[Sebastian @is_ober]

@gabor would love, if you guys could fix Google Tasks, that’s a sub par tool forever by now. Real pain not having Trello style tooling in workspace. Also great destination to consolidate tasks for me, team and agents. Not asking for more. (Ähhhm, maybe Google Voice API) 😅

[Aaron Levie @levie]

As we enter the era of AI agents, one of the defining questions is how you develop competitive advantage when your competitor has access to the same AI models and intelligence as you.

The companies that are able to best harness their internal institutional knowledge, existing data assets, and domain-specific workflows -- connected with AI -- will be those that are able to stay ahead in the future.

Whether a company decides to build out the tech stacks themselves, or leverage a variety of best-in-class tools is certainly one core variable. But the key is to find the way that the enterprise can capture and protect the value created by their unique data, processes, and expertise over the long run. Each industry will have their own version of this, and the competitive advantage will vary by vertical.

We’re increasingly seeing this at Box, where customers want to ensure that they can take advantage of their institutional knowledge and have the flexibility of bringing any AI model and intelligence to their data at any time. This is a pattern that will increasingly become a core principle of strategy in the future.

[Sebastian @is_ober]

@KDHabibi Aber ganz ehrlich, Rotwein Kubiki braucht jetzt auch keiner mehr in Deutschland.

[Sebastian @is_ober]

Euphoria +🌷 valuation + humanity changing technology. These times in we live.

[Yoshik @AskYoshik]

The AI numbers are starting to look very ugly.

Even under "best case" assumptions, FT's own data shows Microsoft AI ROI at -9%, Google at -15%, Meta at -28%, Oracle at -35%. Only Amazon barely comes out positive.

This is exactly why I keep comparing this to the dot-com era. Incredible technology does not automatically mean sustainable economics. The internet survived. Most internet companies didn't.

Right now hyperscalers are spending trillions hoping future demand catches up to present capex. That's not certainty. That's a leveraged bet.

[Sebastian @is_ober]

😂

[Ethan Brooks @alt_w_v_g]

My wife mentioned a nice private school over dinner this week
She said the campus was beautiful
I asked what's the tuition
She said we should look at it as an investment in him not a cost
I made a note
She said don't make a note
I said I always make notes
She said this isn't a deal
I said everything is a deal
She closed her eyes

She said we'd discuss it Saturday
I agreed

Saturday 7:02am
She came downstairs in her Saturday robe
Coffee in hand
I had my cargo shorts on

The dining room had been cleared
The projector was on
The analyst was at the head of the table
Quarter zip on, three iced coffees, a legal pad, and two laptops
He had been there since 6:44am

I texted him at 11:14pm Friday
The text said dining room 6:45am bring the model
He sent a thumbs up

My wife stopped in the doorway
She said what is this
I said you said you wanted to discuss it
She said this is not a discussion
I did not respond
She sat down anyway

The analyst stood
He said good morning ma'am
She did not respond
He sat back down
A printed deck in front of each seat
A fourth copy in case

Slide 1 Tuition Schedule
$38,500 per year
Thirteen years
$500,500 nominal
Before escalators
The school has raised tuition 4.2% per year for a decade
With escalators $648,000
My wife said okay
I said I'm not done

Slide 2 Opportunity Cost
Even before escalators
$38,500 invested annually
10% nominal return
S&P long-run average since 1928
By his eighteenth birthday $944,000
My wife said we can afford it
I said I know that's not the slide

Slide 3 Terminal Value at Age 65
$83 million
She was quiet

The analyst slid the sensitivity tables across the table
8% return $31 million
10% return $83 million
12% return $222 million
She did not look

She said this isn't about money
I said it's always about money
She said no it isn't
I said then what is it about
She did not answer

She said you can't put a dollar value on his teachers his classmates his environment
I said I can the analyst already did slide 6
He flipped to slide 6
She did not look

She said the school is the best in the city
I said best is a feeling
She said it produces the best students
I said the students were already the best before they got there

She said our son deserves it
I said our son deserves $83 million

My son walked in
He is five
Dinosaur pajamas
He looked at the projector
He looked at the open deck on the table
He looked at slide 3
He said are we modeling pre-tax or after-tax
The analyst opened a new tab
My wife looked at the ceiling

He said what's the discount rate
The analyst set down his pen
She closed her eyes

He said is this the same return assumption from the 529 conversation
The analyst stopped typing
He looked at me
I did not say anything

She stood up
Sat back down

He said dad can I help
I said yes
He pulled up a chair
The analyst handed him a printout
He started reading

My wife watched him read
She watched him for a long time

She said his name
He looked up
She said do you like school
He said the work is too easy and the kids don't ask questions

She did not respond
She looked at the ceiling
She walked out of the room

The analyst started packing up
He said should I follow up Monday sir
I said no follow up needed

He'll be fine

Sent from my iPhone

[Holger Zschaepitz @Schuldensuehner]

Good Morning from Germany, where the road to socialism is paved with ever-rising govt consumption. Since 1999, state consumption is up 63%, while GDP has risen only 31% and capital investment a meagre 16%. The public sector keeps expanding, but the investment base is stagnating. Germany is becoming less of a market economy and more of a state-led redistribution machine.

[Statistisches Bundesamt @destatis]

Die Produktion der energieintensiven Industriezweige in Deutschland ist von Februar 2022 bis März 2026 saison- und kalenderbereinigt um 15,2 % gesunken. In der gesamten Industrie ging sie im selben Zeitraum um 9,5 % zurück. Mehr dazu: https://t.co/7qwv7iBLQX

[Sebastian @is_ober]

Are you ready?

[Brett Adcock @adcock_brett]

Watch a team of humanoid robots running a full 8-hr shift at human performance levels. This is fully autonomous running Helix-02 https://t.co/IdZR0T1F5I

[Mario Nawfal @MarioNawfal]

🇩🇪🇮🇷 Germany's Vice Chancellor just said the Iran war is "temporarily slowing our positive economic momentum."

Brother.

Germany has been in and out of recession for two years. Volkswagen was closing factories. Energy costs cratered the industrial base before a single Iranian mine hit the water.

The momentum he is referring to is currently undetected by all known measuring instruments.

The Iran war found it anyway. Somehow.

[Sebastian @is_ober]

Ready for some non-scaling surprises in the next months? There has been too much consensus in genAI.👇

[Robin Delta @heyrobinai]

THE ENTIRE AI INDUSTRY JUST GOT HUMILIATED

a tiny model trained in just a few hours on a single graphics card is planning 48x faster than billion-dollar supercomputers.

It actually understands physics instead of just memorizing patterns.

yann lecun was right the whole time

for three years every major lab told you the same story. scale is all you need. just throw more GPUs at it. just train on more tokens. eventually the model will "wake up" and understand the world.

it was a lie. or at minimum, a very expensive bet that just lost.

LeCun kept saying generative AI is a dead end. predicting the next pixel or the next token is fundamentally wasteful, the model burns trillions of parameters memorizing surface details instead of learning how reality actually works.

he proposed JEPA instead. predict abstract concepts in a compressed thought space. don't paint the world pixel by pixel, understand it.

the problem was JEPA kept collapsing. left to its own devices the model would cheat, mapping a dog, a car, and a human to the same point in latent space. technically minimizes the loss. learns absolutely nothing.

every fix was ugly. seven loss terms. frozen encoders. EMA tricks. stop-gradients. the kind of duct-tape engineering that should have been a red flag.

then LeCun's team dropped LeWorldModel.

they replaced all the hacks with one regularizer that forces the latent space into a gaussian distribution. the model can no longer cheat. to make accurate predictions it has to actually encode physics.

15 million parameters. single GPU. trains in hours.
plans 48x faster than foundation world models.
detects physically impossible events on its own.

meanwhile OpenAI is raising another $40B to train GPT-6 on a data center the size of manhattan.

the entire scaling thesis just got embarrassed by a model that fits on a gaming PC.