One Market to Rule Them All
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Exotic: a highly in-demand, scarce, and inaccessible financial asset.
The best performing assets of 2026.
Launching soon.
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Moore Threads led this week’s winners with a 23.67% gain.
The S5000’s integration with RLinf puts a domestic GPU inside an embodied-AI workflow spanning training, simulation and robotic control.
China’s GPU race is moving from substitution to deployment.
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Pay attention.
Access the inaccessible @poddotnetwork
Humanoid brands are still fighting for the market, but their suppliers are already getting paid.
Since being featured in our thesis, ROBOTIS' Q2 revenue nearly doubled, China demand accelerated, and shares gained 31% as actuator demand showed up in revenue and profit.
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Humanoid brands are still fighting for the market, but their suppliers are already getting paid.
Since being featured in our thesis, ROBOTIS' Q2 revenue nearly doubled, China demand accelerated, and shares gained 31% as actuator demand showed up in revenue and profit.
Exotic.
Humanoid brands are headed for a war of attrition, but the suppliers underneath them get paid for every robot built, no matter who wins.
Joints, actuators, and sensors are the trade.
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Xi’s three day U.S. visit begins today.
Trump and Xi meet tomorrow with trade, AI and critical minerals on the table.
A longer truce could lower the risk of another supply shock. The race to build independent AI, chip and rare-earth supply chains will continue.
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Humanoid robotics is becoming commercially credible faster than it is becoming broadly investable.
In one week, @Figure_robot took its latest robot into 30 homes it had never seen, @BostonDynamics opened a Hyundai factory center to train Atlas for manufacturing work, and @UnitreeRobotics launched a robotic hand the size of a human hand with 22 degrees of freedom for $6,500.
Yet the companies pushing the category forward are private, buried inside much larger companies, or listed in markets many investors cannot easily reach.
The opportunity is global, but access is fragmented.
Soon that will change.
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Qwen Law sounds very exotic.
Correct. People often say open models are six months behind the frontier. But “open” is too broad, - a model that needs a cluster is downloadable, not but not local to the everyday person.
I want a scaling law for the best model that fits on one 24GB GPU.
On Artificial Analysis’ current index, GPT-5 scored 23 in August 2025. Qwen3.5-27B reached 23 roughly 6.6 months later. GPT-5.3 Codex scored 33 in February 2026; Qwen3.8-27B reached 34 about 6.3 months later.
A composite score is not task by task equivalence of course. But the pattern has now repeated across two Qwen generations.
im seeing people post about 'Qwen Law' - basically matching frontier capabilities about two quarters later. Now will this hold for Astra and Fable 5.1? Thats yet to be seen.
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Just in: Qwen introduces Qwen-Image 2.1, an open-weight model with a 7B visual generator that handles image creation and editing in one pipeline.
Smaller, downloadable models broaden the AI investment case from hosted platforms to local compute and deployment software.
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Quantum computing is accelerating, making post-quantum readiness increasingly urgent.
The opportunity lies in the trusted hardware, identity systems, and network infrastructure needed to replace vulnerable encryption without disrupting critical services.
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Dell stock rose 341% in a year.
AI server orders flooded in as customers replaced aging hardware. Those servers have thinner margins, but the volume gave Dell scale, and storage helped.
For the rally to hold, the server refresh has to outlast the rush to secure memory supply.
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For decades, quantum computers have been too error-prone to trust. Logical qubits are starting to change that.
Today’s encryption is now on the clock.
The picks and shovels: crypto-agile PKI, HSMs, secure elements, and hybrid encryption.
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Quantum computers rely on fragile qubits that make too many errors to run complex calculations reliably.
Microsoft and Quantinuum used error correction to cut those errors 800x in a peer-reviewed Nature paper.
Fewer errors enable longer, more useful calculations.
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A July @digicert survey of 1,000 IT and cybersecurity decision makers revealed major institutions are behind on quantum-readiness plans.
Expect an increase in global demand for post-quantum hardware, identity, and network infrastructure.
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