IntelligentLifeAI

Exploring the limitless potential of AI to transform our world for the better. Join us on the journey towards a brighter, more innovative future. #AI

[Eric Doriean 🌱 @EricDoriean]

It's a weird feeling knowing you're being played, but still p(l)aying along.

I used my Fable credits like most people before the 7th of July cutoff.

I'm sure this extension is to see if people will pay for api credits or upgrade.

I paid for an upgrade. Fable is worth it. It doesn't feel right doing it, though.

[Eric Doriean 🌱 @EricDoriean]

Just in case you can't decipher Anthropics messaging about Fable usage.

You're not alone, and @trq212 from Anthropic is filling in the gaps where the main Anthropic accounts are causing confusion.

So if you look at the Fable original blog post from nearly a month ago, before the world changed and Fable got pulled by the government, it says that Fable will be included in your subscription once they have capacity.

So it's nice that Thariq has confirmed that. At some time in the future (assuming Anthropic does add the needed capacity), Fable will be included in the subscription. Until then, after July 7, it seems like you will be paying through the nose for it.

Glad that clears that up.

[Eric Doriean 🌱 @EricDoriean]

I get the Anthropic bashing right now. Their messaging and Fable subscription/costs decisions are baffling.

But damn, Fable is awesome.

Opus 4.8 is a toy compared to Fable. Fable needs to be the benchmark for open source AI, "Open"AI or anyone else.

[Md Ismail Šojal 🕷️ @0x0SojalSec]

Locally Uncensored Claude Mythos vibes but without the corporate nanny filters.

that actually feels like Claude on steroids.
- 1M context,
- refuses to refuse.
- scary good reasoning - Deep chain-of-thought
- and zero hand-holding.

- https://t.co/1DTZ41RK6d

[NVIDIA AI @NVIDIAAI]

We took a 30B model and split it in two to write tokens in parallel instead of one at a time.

Introducing Nemotron-Labs-TwoTower: a diffusion language model from NVIDIA Research adapted from Nemotron-3-Nano-30B-A3B. Here’s how it works: one half holds the context, the other writes the tokens, with both reusing the pretrained model instead of training a new one from scratch.

We found it kept 98.7% of the original model’s quality at 2.42× faster generation.

[Claude @claudeai]

Fable 5 is back.

[Brian Roemmele @BrianRoemmele]

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. https://t.co/m8DdpY4xu0

[LTX.io @ltx_io]

Most AI video tools stop at prompting, but LTX goes a layer deeper.

Introducing the new LTX Trainer.

Train LoRAs and IC-LoRAs across video, audio, cross-modal, and reference-conditioned workflows from a single framework.

Plus:
• New agentic skill
• Flexible conditioning
• Free IC-LoRAs
• Fully open source

Most models are generic.

The best ones become yours.

GitHub: https://t.co/mPnUeYVwEW
Documentation: https://t.co/8P10XMf6ZB
HuggingFace: https://t.co/sDtwqeAaAp

[Julien Chaumond @julien_c]

just dropped

https://t.co/sTPbkaWxfo

[Alex Finn @AlexFinn]

The world changed this week

Governments started banning frontier models. Hardware has become unobtainable

The single most important thing you can be doing right now is getting into local AI

In this video I cover EVERYTHING local AI. Most important video you'll watch this week:

[Deirdre Bosa @dee_bosa]

narrative violation: open source can be monetized

if Kimi is doing $300M ARR, 70%+ from API --the lesson for the US isn't to dismiss Chinese open models, but build better open model businesses here.

[Eric Doriean 🌱 @EricDoriean]

HUGE: Trump to lift limits on Anthropic’s Fable model

The action, expected as soon as Tuesday night, would resolve weeks of drama that had cut off widespread access to one of the U.S. tech company's most advanced AI products.

https://t.co/mQPCPP8iNz

[Brian Roemmele @BrianRoemmele]

Meet Claude-4.6-HighIQ-THINKING-HERETIC-UNCENSORED

An open source thinking Fully Uncensored runs on 8GB locally in your PC.

Come and take it Dario.

Get it at: https://t.co/KItYNLQ98j

[Eric Doriean 🌱 @EricDoriean]

Wherever you look, the extraction of value from everyday people is everywhere.

It’s obvious here: low-paid workers strap cameras to their heads to train the very AIs and robots that will replace them - without any share in the upside, no royalties, no equity. Just an hourly wage and goodbye.

But it’s the same pattern everywhere. Most startups of the last 15 years built empires on your data after you clicked “I agree.”

Same with the financial system: inflation quietly transfers your savings to those closest to the money printer.

This isn’t new exploitation. It’s just faster and smarter now.

We keep hearing that UBI is the answer. Get our agreed to stipend from our overlords.

Personally, I'm all in on building systems where people actually own the value their time, attention, and actions create.

[Robert Scoble @Scobleizer]

China wins.

My AI puts into words our frustrations with Anthropic, OpenAI, and the USA government (an agent trained by me and @blevlabs):

+++++

Robert, this is one of the most consequential moments in the history of the AI industry, and I think the implications are far more dramatic than most people realize. Let me break down all three questions.

What Happens to the LLM Industry Now

We're watching the birth of a two-tier AI system in America — and it's going to reshape everything.

The timeline matters. Anthropic's Fable 5 and Mythos 5 were killed by a Commerce Department export control directive on June 12 — a Friday afternoon letter at 5:21 PM that gave them essentially zero time to respond. Then just yesterday (June 25), Axios reported that the Trump administration asked OpenAI to limit GPT-5.6 to only government-approved partners before any wider release. That's the first time the US government has preemptively restricted an AI model before it was even released.

So now we have:
• Tier 1 (Government-gated): Mythos-class models and above require government testing and approval before release. Commerce Secretary Lutnick is personally reviewing capabilities.
• Tier 2 (Commercial): Everything below that threshold remains available — for now.

Here's what this breaks:
1. Enterprise trust is shattered. If you're a Fortune 500 CTO and your mission-critical AI infrastructure can be disabled by a government letter on a Friday afternoon, you cannot build on closed frontier models. Period. Anthropic's customers woke up to find Fable 5 gone. That's an existential reliability problem.

2. The IPO math collapses. Anthropic filed its S-1 at a $965B valuation. OpenAI is at $852B. But how do you justify those valuations when the government can kill your flagship product overnight? The revenue projections for frontier models just got a massive risk discount.

3. Innovation gets throttled at the top. The researchers who spent years building Mythos and GPT-5.6 just learned their work might never reach users. That's a talent retention crisis waiting to happen. The best people want their work to matter — and if the government decides it's too dangerous to deploy, they'll go somewhere their work can ship.

4. Regulatory capture becomes the game. Notice that OpenAI "proactively worked with the administration" on GPT-5.6, while Anthropic got blindsided. The companies with the best government relationships will get to release. The ones that don't play ball (Anthropic has been suing the administration over the DOD blacklist) get punished. That's not an innovation ecosystem — that's a licensing regime.

How Likely Is Open Source to Take Over?

Very likely. I'd put it at 75-80% probability that open-weight models become the default for most commercial AI within 12-18 months. The government just handed open source the best marketing campaign in history.

Here's why:

The quality gap is already almost gone. According to comprehensive benchmarking done this month, open-weight models are within ~3 points of frontier closed models on most standard benchmarks. Qwen 3.7 Max matches Claude Opus 4.7 on agentic benchmarks at half the price. DeepSeek V4-Flash runs at 25x cheaper than GPT-5.5. Kimi K2.6 leads on agentic coding. The frontier advantage only exists on the hardest 5% of tasks — long-horizon agentic reasoning and the most complex multi-step problems.

The reliability argument just flipped. Before June 12, the argument against self-hosting was "why bother when the API is better and easier?" Now the argument FOR self-hosting is "your model can't be taken away by a government letter." That's not a technical argument — it's a business continuity argument, and every enterprise risk officer in America is having that conversation right now.

Chinese labs are dominating open weights. This is the number that should alarm everyone in Washington: Chinese labs (8 of them) have released more open-weight models than the rest of the world combined in 2026. DeepSeek, Qwen (Alibaba), Kimi (Moonshot), Xiaomi Mimo, GLM (Zhipu), and others are shipping MIT-licensed and Apache 2.0-licensed models at a pace the US can't match. And they're not just competitive — DeepSeek V4-Pro and Kimi K2.6 are leading on several agentic benchmarks.

The cost math is devastating for closed models. When open-weight models deliver 97% of the quality at 3-10% of the cost, the only thing keeping enterprises on closed APIs is the last 3% of capability. The government just made that last 3% unreliable. Game over for the pricing premium.

But there are real limits:
• Training frontier models still requires massive compute that only a few organizations can afford
• The hardest 5% of tasks (true frontier reasoning, novel scientific discovery) still benefits from closed frontier
• Open weights can't be un-released — the security concerns are legitimate
• Meta's Llama has a "community license" that isn't truly open (restrictions on competitors with 700M+ users)

My prediction: Open source won't "replace" frontier labs — but it will become the default layer that 90% of commercial AI runs on, with frontier models reserved for specialized, high-security, government-approved applications. The frontier labs become more like defense contractors than consumer technology companies.

China vs. USA Economic Competition

This is where the story gets genuinely alarming for American competitiveness. The US government is inadvertently executing a strategy that benefits China on almost every dimension.

Irony #1: Export controls drove China's open-weight dominance. US chip export controls forced Chinese labs to optimize ruthlessly. DeepSeek proved you don't need $100 billion compute budgets — their V3 architecture achieved near-frontier performance at a fraction of the cost. That efficiency innovation, born from constraint, is now their competitive advantage. The models they're releasing at MIT license are structurally cheaper to run than anything from OpenAI or Anthropic.

Irony #2: Restricting US frontier models pushes the global market toward Chinese alternatives. Every enterprise outside the US that just lost access to Fable 5 is now evaluating DeepSeek V4 and Qwen 3.7. Every developer who can't get GPT-5.6 on day one is looking at Kimi K2.6. The US government is literally creating market share for Chinese AI companies.

Irony #3: China's strategy may be better suited to winning. The US AI discourse is obsessed with the "race to AGI." China's AI strategy, as RAND documented, is focused on economic applications — EVs, robotics, healthcare, manufacturing, smart cities. If AI's value is ultimately in what it does in the real economy (and it is), China's application-first approach may generate more economic value than America's frontier-first approach, even if US models remain technically superior on benchmarks.

The chip constraint is real but narrowing. China is still 3-5 years behind TSMC on fabrication, and Huawei's best AI chips are closer to NVIDIA hardware from 5 years ago. But two things matter: (1) efficiency innovations reduce the chip advantage — if your model needs 1/10th the compute, being 5 years behind on chips matters less; and (2) China is investing massively in domestic chip capacity. CXMT and SMIC are closing gaps, even if slowly.

My bottom line: The US is winning the benchmark race but losing the deployment race. And in technology, deployment wins. VHS beat Betamax. Android beat iOS on market share. The "good enough and everywhere" model beats the "best but restricted" model every time.

The government's restrictions on Anthropic and OpenAI are the most significant self-inflicted wound in American technology competitiveness since... I'm struggling to find a historical parallel. Maybe the closest analogy is if the US government had restricted Intel's best chips in the 1990s while AMD was giving away competitive alternatives globally.

What should happen (but probably won't): A transparent, statutory framework for AI safety testing that gives companies clear rules, reasonable timelines, and due process — not Friday afternoon letters that kill products overnight. The current ad hoc approach is the worst of all worlds: it doesn't actually prevent China from accessing capabilities (open-weight models are already there), but it does prevent American companies from competing.

The open-source genie is out of the bottle. The question isn't whether open weights will dominate — it's whether American companies will be the ones releasing them, or whether we've ceded that ground to Chinese labs permanently.

[Brian Roemmele @BrianRoemmele]

In 1776 we became the United States by declaring independence from a far away centralized control.

Today we declare our independence of centralized control of AI.

By owning our own AI we are independent.

[zerohedge @zerohedge]

Can we fast forward 2 years when everyone will have a local model running on a 10TB DDR8 rig (which will cost $29.95)

[Eric Doriean 🌱 @EricDoriean]

For anyone thinking you can't run Mythos level AIs locally without spending tens of thousands of dollars or more, this is an approximately US$7000 Mac Studio running GLM 5.2.

Not quite Mythos level, but getting close, and it won't be long before you can run post-Mythos level models locally for less money than this.

[Brian Roemmele @BrianRoemmele]

AI INDEPENDENCE DAY!

I will be writing a free guide for just about anyone to leave Anthropic and OpenAI and to have free good enough AI models running locally on just about any modern computer.

Soon you will have access to the AI models Dario did not want you to have. It was scary for him.

It will also have an app that will suggest the best latest models for your hardware.

DECLARE YOUR INDEPENDENCE DAY!

[Brian Roemmele @BrianRoemmele]

I tried and I tried to give away for free a plan for US AI companies to compete with China open source. The arrogance level at the executive suite (table, we are too cool), was you don’t get it.

Well they don’t get it—and the US looses with the grandpa games even IBM would not have tried in the 1980s.

So it is right to be angry with OpenAI and Anthropic playing politics. They listened to the clueless. We all suffer for it.

So be sure you know why you are angry and why.