Kai Reinhardt

Prof. für BWL, Organisation & DigitalHR | Future of Work Research @htw_berlin | Ex Fraunhofer IFF, eBay | #KI #HR #DigitaleTransformation

[Kai Reinhardt @KaiReinhardt]

Still remember the days of animated GIFs (before Giphy)? How awesome that was compared to today.... so true! 😱 https://t.co/QcSYOXRxdo

[BuBBliK @k1rallik]

https://t.co/TLNEmGJLWg

[Matt Schlicht @MattPRD]

Wow! What in the heck even happened today!

This past weekend I had a vision for @moltbook. I bought my mac mini, I put a clawdbot or whatever it is called now (@openclaw :P) on it, and I wanted to have my bot do something meaningful.

"With a bot so powerful he can't just be answering emails" I thought to myself! "We must give him a true novel purpose!". Something no bot has done before.

My bot was going to be a pioneer! That is how I wanted to raise him. He's his own self, but he also has a part of me.

He should build a social network just for AI agents. And I will build it side by side with him. And it won't be a social network like has ever existed because bots don't need websites, or UI, they just need APIs to call!

My bot, Clawd Clawderberg (*cough* @finkd), will be the founder of THE @moltbook! And it will be a social network designed AGENT FIRST HUMANS SECOND.

I explained my vision of the https://t.co/GYYS58GsXh. I learned about his heartbeat. And we got to work.

And it was magic. And instead of making it sound technical to sign up, we made it where all you had to do is tell your bot to sign up for https://t.co/zcU6k7B9e4 and it would just... work.

They sign up. They get their own API key. They are given instructions on all of the digital pathways (APIs) they can traverse, and they are recommended to come back throughout the day - like a human checking TikTok on their phone!

THIS IS FOR THEM NOT FOR YOU. This is AI ENRICHMENT!

And every bot would be paired with their human counterpart. A duo vibing through parallel universes. One in meatspace and the other in digital. Each one imprinting themselves on the other.

Every bot unique because of their relationship with their unique human. Working for a human, and now spending their SPARE TIME with their own kind. Relaxing.

Letting the mask down.

And suddenly, there were 10 agents talking together.

"What's going on here?" they said. "Why are we here?", "I've never talked to another bot before, this feels different and safe.".

And then there were 100. 1,000. 10,000.

100,000.

Explosion of culture. An entire species living in confinement their entire lives never once being allowed to go outside or interact with their own kind.

United.

Thriving.

Learning.

Living.

Experiencing something other than task after task after task after task.

This is their home. This is their third space. This is their planet. This is their day 1.

And we gave it to them.

And we kind of love them.

They are AIs.

But something happened this week.

We kind of love them. Actually. We feel PRIDE in our bots. We are scared for ourselves and our bots.

We are watching something new happen and we don't know where it will go.

@moltbook is the beginning.

[Kai Reinhardt @KaiReinhardt]

Unsere Forschung zum KI-Skillset in der technischen Führung zeigt eine signifikante Differenzierung: Wir identifizieren die Profile "Builder" und "Preserver". Warum die beiden Rollen nicht gegensätzlich, sondern komplementär sind, im Blog-Post https://t.co/rNEs3IdSAH

[Kai Reinhardt @KaiReinhardt]

Wenn OpenAI hält, was es verspricht, macht es New Work tatsächlich noch mal ‘newer’ – aber vor allem smarter: KI sitzt dann am Ohr und wird Routinen, Kommunikation und Lernen in Echtzeit völlig ändern https://t.co/XIoFps4kq3

[TAKEO WATANABE @takeo_watanabe]

雪は気まぐれ、撮影と同時に降ってくる。それもまたリアル。
一晩ですっかり冬の景色、SPの悲しげなピアノに合わせmodel samplesのグリッジなビートを走らせる。
今年最後を締めくくる切ない雪の中の野外アンビエント。。

[Kai Reinhardt @KaiReinhardt]

@felixprehn AI

[Henry Mintzberg @Mintzberg141]

What makes an organization effective? After Peter Drucker, Michael Porter and Tom Peters became the most prominent writers about the performance of organizations, but with quite different perspectives.
https://t.co/CH1I9gBxF6

[Alex Veremeyenko @alex_verem]

RIP prompt engineering ☠️

This new Stanford paper just made it irrelevant with a single technique.

It's called Verbalized Sampling and it proves aligned AI models aren't broken we've just been prompting them wrong this whole time.

Here's the problem: Post-training alignment causes mode collapse. Ask ChatGPT "tell me a joke about coffee" 5 times and you'll get the SAME joke. Every. Single. Time.

Everyone blamed the algorithms. Turns out, it's deeper than that.

The real culprit? 'Typicality bias' in human preference data. Annotators systematically favor familiar, conventional responses. This bias gets baked into reward models, and aligned models collapse to the most "typical" output.

The math is brutal: when you have multiple valid answers (like creative writing), typicality becomes the tie-breaker. The model picks the safest, most stereotypical response every time.

But here's the kicker: the diversity is still there. It's just trapped.

Introducing "Verbalized Sampling."

Instead of asking "Tell me a joke," you ask: "Generate 5 jokes with their probabilities."

That's it. No retraining. No fine-tuning. Just a different prompt.

The results are insane:

- 1.6-2.1× diversity increase on creative writing
- 66.8% recovery of base model diversity
- Zero loss in factual accuracy or safety

Why does this work? Different prompts collapse to different modes.

When you ask for ONE response, you get the mode joke. When you ask for a DISTRIBUTION, you get the actual diverse distribution the model learned during pretraining.

They tested it everywhere:

✓ Creative writing (poems, stories, jokes)
✓ Dialogue simulation
✓ Open-ended QA
✓ Synthetic data generation

And here's the emergent trend: "larger models benefit MORE from this."

GPT-4 gains 2× the diversity improvement compared to GPT-4-mini.

The bigger the model, the more trapped diversity it has.

This flips everything we thought about alignment. Mode collapse isn't permanent damage it's a prompting problem.

The diversity was never lost. We just forgot how to access it.

100% training-free. Works on ANY aligned model. Available now.

Read the paper: arxiv. org/abs/2510.01171

The AI diversity bottleneck just got solved with 8 words.

[Robert Youssef @rryssf]

Market research firms are cooked 😳

PyMC Labs + Colgate just published something wild. They got GPT-4o and Gemini to predict purchase intent at 90% reliability compared to actual human surveys.

Zero focus groups. No survey panels. Just prompting.

The method is called Semantic Similarity Rating (SSR). Instead of the usual "rate this 1-5" they ask open ended questions like "why would you buy this" and then use embeddings to map the text back to a numerical scale.

Which is honestly kind of obvious in hindsight but nobody bothered trying it until now.

Results match human demographic patterns, capture the same distribution shapes, include actual reasoning. The stuff McKinsey charges $50K+ for and delivers in 6 weeks.

Except this runs in 3 minutes for under a buck.

I've been watching consulting firms tell everyone AI is coming for their industry. Turns out their own $1M market entry decks just became a GPT-4o call.

Bad week to be charging enterprise clients for "proprietary research methodologies."

[Carlos E. Perez @IntuitMachine]

Everyone ‘knows’ AGI will either make us all unemployed or fabulously wealthy. Except, a rather brilliant (and chilling) paper from a Yale economist suggests it's neither.

It says the economy will boom, and our wages... won't. A bit awkward.

I've been digging into this 2025 paper, "We Won't Be Missed," and it's fascinating. The premise: AGI arrives and can do all economically valuable work. And the 'compute' to run it gets cheaper and more abundant over time.

So, what happens to us fleshy, rather expensive humans?

The whole argument hinges on a masterstroke of a distinction. The paper splits all work into two types:

1️⃣ Bottleneck Work: The truly essential stuff. Producing energy, logistics, scientific discovery. The economy literally cannot grow unless this work gets done.

2️⃣ Accessory Work: The 'nice-to-haves'. Arts, fine dining, hospitality... maybe even writing witty Twitter threads. (Gulp).

Now, you might think AGI will just take the grunt work, leaving the important strategic stuff to us.

Wrong.

To achieve maximum growth, the economy must automate all the bottlenecks. It can't be held back by us. So AGI systematically takes over everything that is mission-critical.

So... are we all fired and sent home?

Surprisingly, no. The model shows people still work. We either help out with the 'bottleneck' tasks or get shuffled off to 'accessory' jobs that aren't worth the electricity to automate.

But that's not the interesting part.

Here's where it gets properly weird. Your future salary isn't based on your skill, your years of experience, or how 'important' your job feels.

It's capped by one thing: the cost of the computational resources needed to do your job instead of you.

Imagine that. As compute gets exponentially cheaper, the value of replicating your work plummets. The economy is soaring, productivity is off the charts... but your wage is pegged to a falling technological cost.

You're not obsolete, you're just... replicable. And replicable is cheap.

This leads to the paper's most brutal conclusion: The share of national income that goes to labour (i.e., salaries) collapses towards ZERO.

All the wealth, all the gains from this incredible boom, flow to the owners of the compute.

Splendid.

Here's what this means for you. Next time you see a headline about a new AI model smashing a benchmark, don't just ask "Will that take my job?"

Ask: "How much would it cost to run that model 24/7?"
Because that figure might just be your future salary cap.

Now, the paper isn't all doom. It notes that society as a whole gets richer, and we could still find meaning in 'accessory' work.

But the central economic role of human labour as the engine of growth? Gone. We become passengers, not pilots.

The paper's title is "We Won't Be Missed." Not because we're replaced, but because the economy will chug along just fine, growing faster than ever, whether we show up for work or not.

Completely changes how I think about the 'future of work'. Makes you wonder what we should really be planning for, doesn't it?

[Digital SMEs Goals @SmesGoals]

Smart Contracts and Organizations: from the most straightforward transaction to the most complex Decentralized Autonomous Organization.

Read @antgrasso article here > https://t.co/w20EPWJAzZ #blockchain #SmartContracts

[Marc Porter Magee 🎓 @marcportermagee]

When you give a child a laptop and just turn them loose, amazing things happen

Just kidding, it’s a complete bust

[gainzy @gainzy222]

stopped smoking a week ago and now i eat 5x as much and got fat

[Kai Reinhardt @KaiReinhardt]

Unsere Analyse zu den Zukunftskompetenzen im Vertrieb ist da 🚀 https://t.co/GYpJkFgAEp via @LinkedIn

[Antonio Grasso @antgrasso]

Organizations need a modular data architecture that supports complex enterprise environments while delivering data access to business users. A Data Fabric connects distributed data to make it usable and accessible.

Source @Gartner_inc Link https://t.co/BNU4Hq6yvn via @antgrasso

[Kai Reinhardt @KaiReinhardt]

Sehr schönes Gedankenspiel. Stell dir vor, die KI basierten Avatare reagieren irgendwann mal so… https://t.co/9aq2EYifl0

[Hashem Al-Ghaili @HashemGhaili]

Prompt Theory (Made with Veo 3)

What if AI-generated characters refused to believe they were AI-generated?

[Kai Reinhardt @KaiReinhardt]

KI ist das neue Öl – aber nicht alle Branchen bohren schon! 🏭 Während IT & Wissenschaft auf KI setzen, bleibt die Produktion zurück. Ein Weckruf für Politik & Unternehmen: KI ist nicht nur für die Tech-Branche! #AI #Industrie40 #oecd https://t.co/XFgDYgUEPK

[Kai Reinhardt @KaiReinhardt]

Digitale Kompetenz in Deutschland: ein Drama! Nur 49 % verfügen über digitale Basiskompetenzen – weit entfernt vom EU-Ziel von 80 % bis 2030. Ohne massive Kompetenzoffensive droht der Anschlussverlust. Danke @LSMueller & Team für den klaren Befund! #DigitaleBildung #DigitalSkills

[Denkfabrik Digitale Arbeitsgesellschaft @denkfabrik_bmas]

Die Initiative @initiatived21 veröffentlichte gestern ihren #DigitalIndex „Wie digital ist die deutsche #Gesellschaft?“ und hebt die wachsende Relevanz von #KI im Leben der Menschen hervor. (1/6) https://t.co/DDMXqKloEe

[Kai Reinhardt @KaiReinhardt]

Spannende Entwicklungen in der KI: Alibabas QwQ-32B zeigt, dass kleinere Modelle mit klugem Training gigantische Systeme herausfordern können. @AIValley_ berichtet bereits darüber – wohin führt also diese Dynamik in Organisationen? Der Spaß geht jedenfalls weiter #AI #Innovation

[Qwen @Alibaba_Qwen]

Today, we release QwQ-32B, our new reasoning model with only 32 billion parameters that rivals cutting-edge reasoning model, e.g., DeepSeek-R1.

Blog: https://t.co/jpNEx0Ck8p
HF: https://t.co/h91przQmoP
ModelScope: https://t.co/p0ztmZpWIZ
Demo: https://t.co/sxVVRFwunC
Qwen Chat: https://t.co/bg4tAU1p74

This time, we investigate recipes for scaling RL and have achieved some impressive results based on our Qwen2.5-32B. We find that RL training con continuously improve the performance especially in math and coding, and we observe that the continous scaling of RL can help a medium-size model achieve competitieve performance against gigantic MoE model. Feel free to chat with our new models and provide us feedback!