Andreas Berentzen

MSc Artificial Intelligence @ UvA | ML data engineer @ Vectr consulting | ❤️ Timeseries & Graph data ❤️ | Published work at ICML, NeurIPS

[Andreas Berentzen @AndyTheGuttler]

@HedgieMarkets I can't express how happy I am I don't work there (would've already quit way earlier anyway)

[Andreas Berentzen @AndyTheGuttler]

@admirim Rightly so

[Andreas Berentzen @AndyTheGuttler]

It's good to see @OpenAI is staying true to its non-profit nature 😁

[Andreas Berentzen @AndyTheGuttler]

Coding agents have a bias for complexity

[Andreas Berentzen @AndyTheGuttler]

@The_Davos_Man Lol

[Telegraph Football @TeleFootball]

Gianni Infantino has further diminished the reputation of an organisation that had already become a byword for sleaze under his predecessor Sepp Blatter. He should resign.

The Telegraph says Gianni Infantino must go. Read the full Telegraph View ⤵️
https://t.co/2TwulFjyCv

[Andreas Berentzen @AndyTheGuttler]

@kajakallas @Bart_DeWever @LucFrieden @prevotmaxime @Xavier_Bettel 🙌🙌

[Andreas Berentzen @AndyTheGuttler]

@USMNT Lekker voor jullie

[Andreas Berentzen @AndyTheGuttler]

@ellencarmichael Maybe you should just accept the decision of the referee. What is ‘wrong’ is subjective and in this game the ref makes the final call. Not anyone else

What had happened is objectively using political weight to overturn an official decision. Don’t talk about ‘righting a wrong’

[Ronin @DeRonin_]

My entire AI stack is now Chinese 🇨🇳

87% cheaper. same revenue

swaps by task:

1. reasoning / backend brain
Opus 4.8 → Kimi K2.7
benchmark gap: ~8% · price: ~11x cheaper

2. code generation
GPT-5.5 → Qwen 3.7 Max
benchmark gap: ~18% · price: ~7x cheaper

3. agent loops + tool calling
Sonnet 4.7 → GLM 5.2
benchmark gap: ~3% · price: ~5x cheaper on input

4. cheap volume / bulk processing
GPT-5.5 mini → MiMo V2.5
benchmark gap: ~6% · price: ~12x cheaper

5. image generation
GPT-Image-2 → Wan 2.5
benchmark gap: ~5% · price: ~8x cheaper

6. video generation
Sora 2 → Kling 3.0
benchmark gap: roughly equal · price: ~6x cheaper

[ result after 30 days: ]

operating costs dropped 87%, output quality dropped 4% on average, revenue unchanged

the most important that these models will be not banned in a month and i can run them locally

nobody will steal my data and i can learn them as i need

full article drops tomorrow with:
> exact routing logic per task type
> the 2 cases where I still pay for American
> the migration playbook anyone can copy in a weekend

VERY IMPORTANT to get migrated now, while it's not too late

[Andreas Berentzen @AndyTheGuttler]

@CtrlAltDwayne It’s institutional investors that want to see returns as simple as that

[Andreas Berentzen @AndyTheGuttler]

@RodrigoRabaco Thanks for supporting the movement. China in this context is doing a service to the world. I hope we can build open source SOTA MLLMs cross borders at some point.

[Andreas Berentzen @AndyTheGuttler]

Intelligence is inherently spatial.
Intelligence requires some relational structure over representations. Without it concepts collapse to one

[Andreas Berentzen @AndyTheGuttler]

@HealthRanger It’s his investors talking

Same as happened to Sam Altman

[Andreas Berentzen @AndyTheGuttler]

@Shankthetank @coinbureau Thank god they’re Chinese

[Andreas Berentzen @AndyTheGuttler]

The VC’s are getting to him

Scraping all text and video data available on the internet, training MLLMs from it and selling it back to the public is not a tennable business model.

But investors need to see returns, hence this behaviour

[Coin Bureau @coinbureau]

🚨ANTHROPIC CEO: OPEN SOURCE AI IS GETTING DANGEROUS

Anthropic CEO Dario Amodei told lawmakers that open-source AI is moving down a “very dangerous path.”

His warns that once powerful models are released openly, companies lose the ability to monitor misuse, revoke access, or update safety guardrails.

[Dr Alexander D. Kalian @AlexanderKalian]

The AI bubble reveals a deeper problem: there aren't enough people doing tangible real-world work.

VC funds pouring money into AI is a symptom of too much idle capital desperately looking for places to park itself.

The explosion of AI vibe-coded apps and B2B SaaS tools - which almost nobody actually downloads or finds useful - shows there are too many people building software to "help" businesses, compared to people actually running those businesses.

The same pattern appears in AI drug discovery: for every founder genuinely trying to discover drugs with AI, there are 20+ VCs, incubators, conferences, consultancies, CROs, patent lawyers, and marketers all trying to take a cut - while bearing almost none of the real risk.

This extends across AI in general. For every person actually building AI, there's an army of project managers, executives, marketers, and consultants talking about it in meetings.

We have a chronic shortage of people willing to take real risks: developing new drugs, opening new mines, building factories, inventing machines, constructing homes, or growing food.

Everyone prefers the safer, more reliably compensated roles - finance bro, consultant, tech bro, lawyer, salesperson, marketer.

Traditional white-collar work is necessary for coordination and efficiency. But do we really need this many people whose main job is planning, streamlining, and negotiating with each other?

[Ihtesham Ali @ihtesham2005]

Mistral CEO Arthur Mensch walked into the French parliament this week and told lawmakers Europe has exactly two years to build independent AI infrastructure or hand over one trillion dollars in spending to American tech companies.

The math he laid out should be front-page news.

This is not a technology story. It is a macroeconomic one.

Global wages are fifty trillion dollars. AI will cost around ten percent of that. Europe's share is nine trillion. Which means over one trillion dollars in AI spending over the next five years flowing somewhere.

Europe already sends 250 billion dollars a year to the US in digital services. Every dollar that leaves funds American R&D. None of it comes back.

Mario Draghi's competitiveness report last year made the same point from a different angle. Europe needs eight hundred billion euros in annual investment just to close its existing productivity gap with the US.

AI dependency makes that gap structural. You cannot close a productivity gap when the tool driving productivity is owned by your competitor.

Mensch compared it to gas. The same way Europe discovered too late what energy dependence costs in a crisis, it is standing at the same crossroads with AI right now.

The compute is being allocated today. The chips are being spoken for today.

Europe is watching it happen and calling it a technology debate.

It is not. It is a sovereignty one.

Watch the full podcast on YouTube at @CNBCi

[Andreas Berentzen @AndyTheGuttler]

@ChiefEngineerCE @asaio87 Until it breaks, agents run it sycophantic circles and the people that know are worth millions.

The total amount of information is increasing so we do need to be cognisant how we spend our attention

[andrei saioc @asaio87]

It's painfully obvious to me, after 12 years of shipping production code, that:

We are massively overestimating AI and massively underestimating it at the same time.

→ 96% of the code I write today is AI-generated
→ but I review every single line like my job depends on it
→ the developers who win won't be the ones who prompt the fastest but be the ones who know what "good" looks like

Here's what nobody wants to admit:

AI didn't make engineering easier.
It made judgment the entire job.
The bottleneck was never typing.

It was knowing what to build, what to throw away, and what will break at 3am six months from now.

Juniors are shipping 10x more code.

And introducing 10x more bugs they can't explain.

The skill isn't writing anymore.

It's reading. Reviewing. Saying no.

Taste is the new 10x.

The engineers who treated coding as typing are panicking.

The ones who treated it as thinking have never been more valuable.

Adapt accordingly.