This GitHub repo teaches you loop engineering (from zero).

What loop engineering really is, how to get started, practical examples & more.

If you use AI to code, you should save this: github.com/cobusgreyling/loop-engineering

$PLTR The Dip Was the Setup — Sovereign AI Catalyst Ignites

Palantir just got the ultimate co-sign: Jensen Huang calling it “the single most important enterprise stack in the world.” The Nvidia partnership expansion for sovereign AI is a game-changer. The chart shows the exact kind of shakeout we love — sharp flush to 106 followed by a powerful reversal candle on heavy volume.

The Pure Technicals:
- Massive volume spike on the green reversal candle off the lows
- Fonsie Channels coiling tighter into the flush, now expanding on the bounce
-Measured move projection targeting 155+ (62%+ upside from the low)
- RSI washed out and turning — classic post-shakeout setup
Key Levels:
Near-term Target: $138–$150
Stretch Target: $155–$170+ (measured move + channel expansion)
Support: $112 – $115 zone (now acting as new floor)

Quick DD:
• Expanded Nvidia partnership to deliver sovereign AI infrastructure for US government and critical agencies using Nemotron models
• Jensen Huang: “Palantir is going to integrate Nvidia so that we can process at the speed of light and at extraordinary scale”
• Alex Karp: Combining Palantir infrastructure with NVIDIA AI removes security risks while giving full control over data and models
• Positioned at the center of the AI stack — enterprise deployment, customization, and mission-critical operations

The technical flush + fundamental rocket fuel = classic institutional re-accumulation setup. This is how the biggest moves begin.

#PLTR #Palantir #Nvidia #SovereignAI #AITech

The company that JUST built one of the most advanced AI models on Earth is not a chip giant or a research lab. It delivers dinner. 🍽️ 🥘

China's food-delivery app Meituan released a 1.6 trillion-parameter model this week, trained from start to finish on 50,000 domestic chips, with not a single American processor involved. The wall built to deny China frontier Ai just got walked straight through, by a company best known for bringing you takeout.

The size is not even the real story. Until now, China could run finished models on home-grown chips, but the punishing work of training one from scratch was assumed to need American silicon.

Meituan says it did the whole thing, training and all, on Chinese hardware alone. That is the exact assumption the entire export-control strategy was built on, and it just cracked.

And the part almost nobody noticed is why a “delivery company” could pull this off.

Meituan has spent years watching trillions of real-world orders move through cities, food, couriers, shops, logistics. That is data about the physical world that no lab model trained purely on the internet possesses. The takeout business was not a distraction from the AI. It was the moat. Think about it.

The model is open-source and FREE, runs a one-million-token memory, and had quietly topped global developer charts for two months under a code name before anyone knew it was Chinese.

Meituan claims it performs on par with Google's flagship Gemini 3.1 PRO

This is the whole contest in a single image. One side is betting that intelligence is a treasure to be locked in a vault. The other is betting it is a flood that cannot be dammed, and that the company sitting on the most real-world data wins, even if that company delivers your lunch. A trillion-parameter model, trained on banned hardware and handed to anyone who wants it, is the loudest evidence yet of which bet is winning.

Is this why Dario is upset these days? Anthropic Dario just described this situation as a “very dangerous path,” warning that releasing highly capable frontier AI models as completely FREE as open source can reduce oversight of how they are used.

The uncensored version of GLM-5.2 via abliteration: Run it on your computer 40B active, 1M context, and zero DARIO guardrails.

Ask no permission from the fear Theater crew.

huggingface.co/huihui-ai/Huihui-GLM-5.2-abliterated-GGUF

Here’s the list of western companies moving ai workloads to chinese models:

1. lindy → deepseek v4
2. cursor → kimi k2.5
3. coinbase → glm-5.2 + kimi 2.7
4. shopify → qwen
5. airbnb → qwen
6. uber eats → qwen2
7. siemens → deepseek + qwen
8. chapsvision → qwen
9. microsoft → testing deepseek v4

it’s becoming a procurement story!!!

🚨TODAY: #Huawei open-sources OpenPangu-2.0-Flash

#OpenPangu 2.0 includes two 512K-context models:
• Flash: 92B total,6B active—Weights+inference code+training ops released
• Pro: 505B total,18B active—flagship model, coming in July

More open-source components later this year

GPT-5.6 finally getting released feels huge.

This is the kind of model jump I’ve been waiting for, not just slightly better autocomplete, but something that might actually feel like a real step toward powerful agents, serious coding, better reasoning, and creative work that doesn’t feel lobotomized.

Now I just hope the EU actually gets access too.

Please don’t make us watch Americans cook with the good stuff while we sit here with the safety-scissored tourist version.

Most people don't want freedom

They want better furniture in the cage 🤡

The damage Dario 🤡 and Anthropic have done to the American AI industry is just unbelievable.

Wait until other companies catch up with Nvidia on the hardware side.

Add to that the number of people who, like me, were paying for top tier plans and relying on their models, and are now building local infrastructure to run open source models instead.

China's playboko is really simple.

Take intelligence down to the cost of energy

Output more power than the USA

The giant training cluster focus was a massive distraction

Yes, many of us are rightly pissed about regulatory capture in the US with recent anthropic theater. The doomerism, the fear mongering, the attempts to slow down power distribution, the bureaucracy and institutional self interest are real.

But we should also be grateful for what this moment is doing to the industry.

The open source community is booming. New models, new local solutions. People are adapting. Intelligence is being distributed no matter what. And once a civilisational shift reaches this level of momentum, no committee, no regulator, no authoritarian impulse, and no power hungry institution can fully contain it.

Progress is like the waves in the ocean. It does not ask declining institutions whether they feel comfortable being disrupted.

Technology will move forward because human curiosity, ambition, and creativity are deeper forces than bureaucracy.

We are entering a new era, not because everything is perfect, but because the old systems are no longer capable of holding back what is emerging.

The fear mongers may slow things down in the short term. They may create noise, panic, and friction.

But in the long arc, they are only proving the point. The future is becoming too distributed, too intelligent, and too alive to be captured by the same forces that captured the past.

Welcome to a new era of progress.

Look beyond the short term chaos and the pattern becomes obvious.

Acceleration will continue.

Open source AI will keep expanding.

And the bureaucratic forces trying to preserve yesterday’s power structures will eventually be outpaced by a world they were never imaginative enough to understand.

The worst case scenario for USA AI: 1. Chinese open sources keep gaining market share. China owns the model layer. 2. Those models were trained and inference-optimized on Huawei chips instead of NVIDIA. China also owns the chip layer. 3. US doesn't build data centers fast enough to keep up with the demand of compute, storage and energy. China meanwhile exports the inference and training layer(for continual training it will happen along with inference)

Export control is not the right strategy here. Simply banning "open source from China" doesn't solve the issue here. USA must invest in open source models, hopefully get Chinese models to use NVIDIA, and invest in nuclear asap.

AI at scale is constrained by physical inputs, and China has more slack in electricity plus dominant control over several minerals and magnet supply chains that data centres and chips depend on.

ClinePass just launched. $9.99/month for curated access to the best open-weights coding models inside Cline 🤯

> GLM 5.2
> Kimi K2.7-Code
> DeepSeek V4 Pro
> MiniMax M3
> Qwen3.7-Max and more

No separate API keys. No provider accounts. 2-5x the standard rate limits.

Works in the IDE extension, CLI, and SDK.

cline.bot/cline-pass

github.com/cline/cline

Why are companies like Lindy, Cursor, and Coinbase quietly routing production AI workloads to DeepSeek, Kimi, and Qwen?

The answer isn’t politics, It’s procurement.

- Lindy replaced Claude with DeepSeek V4 across 100% of its agent traffic dramatically lower costs and better results on many tasks.
- Cursor built a flagship feature on Kimi K2.5.

Others making the same calculation: Shopify, Airbnb, Uber Eats, Siemens, Coinbase, and Microsoft testing.

When a model delivers strong performance at a fraction of the cost, the math becomes very simple.

I think It’s no longer just about who builds the smartest model, It’s about who can afford to run it at scale.

24% of central banks plan to cut dollar holdings.
Only USD shows real "decrease" intent.
Gold and the euro are where they're rotating.

RMB leads on "increase" at 32.
The dollar's reserve dominance is being trimmed on purpose, by the people who hold the most of it.

That's the slow tide under gold.