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Dear Readers,
Sometimes it happens quietly: a single breakthrough changes the perspective on an entire discipline. This is exactly what is happening now in fluid dynamics, where DeepMind is using AI to solve decades-old theoretical puzzles and reveal new singularities. Instead of simply calculating simulations faster, knowledge itself is being recreated here – and the question arises: what other hidden structures could we soon discover through AI?
This issue is all about such turning points. You'll read about profound model updates such as GLM 4.5 and Qwen3-Coder, which are rethinking creativity and programming. We shed light on the race between OpenAI and Anthropic, take a look at Meta Connect's big announcements, and assess how AI is increasingly becoming a geopolitical power factor between the US and China. We also cover the debates from the AI+ DC Summit and new UN initiatives on global governance. In other words, a complete panorama that shows you how AI is changing our present and reshaping our future.
In Today’s Issue:
⚡ Fred Krueger warns: “Get ready to lose your job”
✨ And more AI goodness…
All the best,
Suno teases v5 release
Suno announced that v5 is “coming soon” and hinted it will “change everything.” No details yet, but expectations are high after v4 reshaped AI music generation.
Humanoid shares robot-building documentary
Humanoid released a 22-minute film showing the 7-month process behind its HMND 01 Alpha robot. The team promises an unfiltered look at the challenges and progress.
DeepMind advances AI fluid dynamics research
Google DeepMind, with Brown, NYU, and Stanford, published new work on using AI to model fluid dynamics. The study points to faster, more accurate simulations for science and engineering.
Get ready to lose your job.
— #Fred Krueger (#@dotkrueger)
5:01 PM • Sep 18, 2025
It is clear that AI will completely transform the job market. But now it is slowly becoming apparent just how much.
Everything announced at Meta Connect 2025 in 20 minutes
Next version insanely better is the plan
— #Sholto Douglas (#@_sholtodouglas)
12:03 AM • Sep 18, 2025
Anthropic feels the pressure from OpenAI's Codex. The next Claude is supposed to be “insanely better.”
AI wins gold at programming Olympics
The Takeaway
👉 AI-supported PINNs can find unstable singularities that were overlooked using conventional methods.
👉 There is a pattern: the λ parameter (blow-up speed) correlates with the order of instability – this opens up possibilities for predicting new solutions.
👉 Applications: better mathematical and physical models, e.g., in fluid mechanics, aerodynamics, and climate, where precise boundaries are important.
👉 Consequence: AI can play a concrete role in discovering new knowledge in areas that have previously been more theoretical - not just simulating, but helping to understand.
A blink of an eye is all it takes to gain a new understanding of the world of fluid dynamics: DeepMind has used AI to discover a new type of “singularity” – problems that have existed in theory for decades, but which no one has been able to systematically identify until now.
What exactly is this about? Singularities are cases in which variables such as pressure or velocity run to infinity or become undefined in mathematical equations – for example, when very small changes have huge effects. DeepMind used Physics-Informed Neural Networks (PINNs), i.e., neural networks that already know what physical equations look like during training, and forced them to satisfy these equations exactly.
Why is this exciting for the AI community? Because here, AI is not just a computing aid, but a tool for gaining insight. This system makes it possible to detect theoretical limits, classify instabilities, and recognize patterns that were previously hidden – e.g., how quickly such singularities “inflate” (blow-up speed, λ) in relation to the complexity of the instability.
This method could open doors—toward rigorous computer-aided mathematical proofs, more reliable simulations for climate models, aerodynamics, or even more general differential equations. How much can AI close the gap between experimental physics, pure mathematics, and practical application in the future?
Why it matters: This work shows that AI can not only solve existing equations but also discover new phenomena—even in fields where theory has long stalled. It could help systematically address fundamental questions such as the existence of stable singularities in the Navier-Stokes equations.
Sources:
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US-China AI & Trade: Technology as Gunpowder in the Trade War
A recent report shows how AI technology is increasingly being used as a geopolitical lever in the trade conflicts between the US and China. While the US wants to force ByteDance to sell off part of its US operations, China is tightening its stance on chip exports and targeting Nvidia. Behind this is a global race for control of key technologies, which in the long term could transform trade agreements into power-political technology deals and place a considerable strain on international cooperation.
AI+ DC Summit: Regulation & Job Risks in the Global Race
At the AI+ DC Summit in Washington, it became clear that AI has long been at the center of geopolitical and economic power issues. Discussions focused on Western countries' dependence on chips, competition with China, and the social consequences of massive automation. While industry representatives called for safety standards and government frameworks, politicians warned of a looming division in the labor market. The debate highlighted the challenge democracies face in combining technological innovation with social stability.
UN governance & global policy framework: Symbolism vs. substance
A new UN resolution aims to pave the way for an independent scientific body and a global governance dialogue on AI. On paper, this looks like an important step toward internationally coordinated rules. However, experts warn that the initiatives lack clear enforcement mechanisms and run the risk of becoming purely symbolic gestures. Without binding standards, there is a threat of dominance by the leading AI nations, while poorer countries could remain excluded from the regulatory framework.
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