This is Seedance 2.5, and it is Hollywood level stuff.

Robots & Art 🌈

🇪🇺 Mistral CEO Arthur Mensch just gave Europe a stark warning:

Build your own AI infrastructure within two years or send over $1 trillion to American tech companies.

His argument is simple. Global wages are about $50 trillion, and AI could absorb roughly 10% of that value. Europe’s share is around $9 trillion, meaning more than $1 trillion in AI spending is up for grabs over the next five years.

The question is: who gets paid?

Europe already spends hundreds of billions on US digital services every year, helping fund American R&D while falling further behind in the technologies driving future productivity.

Mensch compared AI to energy dependence. By the time a crisis exposes the risk, it’s already too late.

The chips are being allocated. The data centers are being built. The AI economy is being carved up now.

This isn’t really a technology debate anymore. It’s a sovereignty debate.

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❗️AI data centers may be using far less water than most people think.

According to the Manhattan Institute, data centers account for just 0.2% of daily U.S. water consumption and that figure is falling as the industry shifts to liquid cooling.

The big change is 45°C liquid cooling, which allows many AI facilities to use dry coolers instead of water-intensive cooling towers.

The result? Cooling water usage can drop from roughly 2.6 million gallons per MW per year to nearly zero.

And the benefits go beyond water savings. Liquid cooling is also more energy efficient and makes it easier to capture and reuse waste heat, turning AI factories into potential assets for local communities and power grids.

The future AI data center may consume less water than critics expect and provide more value than just compute.

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The intelligence alliance known as Five Eyes has issued a rare public alert, warning that powerful AI models able to carry out damaging cyberattacks may become available within the next few months.

This coalition, which includes Australia, the United States, the United Kingdom, Canada, and New Zealand, expressed concern that advanced AI systems could simplify the execution of major cyberattacks against both government and business targets.

According to the statement, such models have the capacity to automate specialized cyber functions. They can analyze code, identify vulnerabilities, propose exploits, and coordinate actions across networks—all tasks previously requiring expert human intervention.

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A Texas-based company, Minicircle, is preparing to offer an injectable gene therapy focused on increasing longevity. This new treatment aims to stimulate the production of klotho, a protein linked to anti-aging processes.

Minicircle plans to launch the therapy outside the U.S. regulatory framework, specifically in regions such as Honduras, the Bahamas, and Panama. The intention is to bypass comprehensive trials typically required by the FDA and instead operate in locations with less stringent oversight.

The company’s approach reflects a trend where biomedical innovation may shift to countries with more flexible regulatory environments if others choose a slower or more cautious path.

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🗣️ Recursive self-improvement: Anthropic co-founder Jack Clark says it could arrive by 2028.

AI systems could help invent their own successors with Claude 10 building Claude 11, and so on potentially “without any researchers involved.”

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👓 Meta is rolling out a new line of AI glasses called the “Muse Spark” glasses, which come in three styles.

The glasses can play music, capture images to translate languages and answer questions about a person’s surroundings. CBS News’ Maya Blackstone tried them out.

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The Trump administration is urging Meta to submit its artificial intelligence models for federal review before releasing them to the public.

Meta remains the only major U.S. AI company not participating in the voluntary government review program.

According to recent reports, OpenAI, Anthropic, Google, xAI, and Microsoft have already agreed to share their models with a government AI safety group.

The review process is designed to evaluate whether advanced AI models can be used for sensitive cybersecurity tasks, identify potential security risks, or present national security concerns before they reach widespread use.

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🤖 Anthropic just turned Claude into a slack teammate

Anthropic introduced Claude Tag, a new system that lets teams tag Claude directly in Slack and assign it real work.

Mention Claude in a thread, and it can break tasks into steps, analyze data, write code, merge pull requests, investigate incidents, and report back with results.

Unlike a personal AI assistant, there’s one shared Claude per channel, allowing teammates to jump into projects without losing context. Claude also learns from ongoing conversations, reducing the need to repeatedly explain the same work.

With its new “ambient” mode, Claude can even act proactively, following up on stalled discussions and surfacing important updates on its own.

Anthropic says the concept evolved from Claude Code, and internally, 65% of its product team’s code is now generated by Claude-powered tools.

Source.

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🔥This new feature is like managing a legit employee now.

One that already knows your full company context, sits in every channel, remembers every conversation, and does the work alongside you. it becomes especially powerful when you connect it to all your tools, too.

Here's a bunch of ideas for ways to use it:

1. Content pipeline. Tag Claude in the channel where your team dumps hooks, ideas, screenshots all week. It keeps a running list of what's actually usable, sorts them by theme, then every friday posts next week's content plan ready to go.

2. Client account manager. Let Claude sit in the shared client channel. It remembers every promise, deadline, request buried in the chat. so when the client asks "where are we on the homepage?", it answers from the real history and flags anything your team agreed to but hasn't done yet.

3. Catch the dropped balls. People say "i'll send that tonight" or "let's circle back monday," then it slips. Claude quietly tracks every loose end like that and pings whoever owns it when the deadline passes. It’s the teammate who actually remembers what everyone promised.

4. Campaign control room. Drop Claude in the channel where marketing posts the landing page copy, the emails, the ad scripts. It reads all of it and flags when they don't match, like an ad promising a discount the landing page never mentions. An extra set of eyes on the whole campaign.

5. Community listening. Point Claude at your member or Discord channel and ask "what does everyone keep asking for?" It reads the whole conversation and tells you the top requests, the most common complaints, who keeps volunteering to help. like a researcher who never stops listening to your audience.

6. Sales handoff. The person who books the call drops everything they learned in the channel. Before the next call, the closer asks Claude "catch me up on this lead." It pulls the full history: the budget, the objections, what got promised. No "let me forward you my notes."

7. Sponsor tracker. Sponsor deals get discussed across dozens of scattered messages. Claude keeps a clean list: who's booked, which dates, what they paid, what's been delivered.

8. Recurring reports. Set it once: "every monday at 9am, read last week's channel and post a summary of what got done." It runs on its own and drops the recap in. You review it instead of writing it, every week, no reminders.

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🤖 Over 1 Million ChatGPT Users Show Signs of Suicide Risk Each Week

OpenAI revealed that about 0.15% of ChatGPT’s 800 million weekly users show signs of suicidal planning, while another 0.15% show emotional dependence and 0.07% show signs of psychosis or mania.

Those percentages sound small, but they translate to roughly 1.2 million users discussing suicide-related concerns, 1.2 million showing unhealthy attachment, and 560,000 experiencing possible mental health crises every week.

The disclosure comes as AI companies face growing scrutiny over how chatbots handle vulnerable users, highlighting the massive mental-health challenges that emerge at ChatGPT’s scale.

Here is the 5-minute rule that can save you or a relative:

1. If you or someone you know is using ChatGPT as a therapist, the US suicide line is 988. Call or text. Free. 24 hours.

2. If you have a teen, open ChatGPT, Settings, Parental Controls. Link your account to theirs. Turn on quiet hours and distress alerts. 4 minutes.

3. Check their phone for Character AI, Replika, and Nomi. Character AI banned under-18s on November 25, 2025. The other two officially ban minors but teens still get in with fake birthdays.

4. Replace one AI chat a day with one text to a real person.

The bot will never call 988 for you. A friend will. Save this for someone who needs it.

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❗️How Andrew Ng organizes his engineering team to move faster in the era of AI.

"1 to 10 engineers in a team, often made up of generalists: high-context, highly empowered generalists."

When code gets generated much faster, organizations become the slow part.

Once a feature can move from idea to working prototype in a day, every surrounding function is suddenly exposed.

Product has to decide faster, design has to clarify faster, marketing has to understand faster, and legal has to review faster.

So his way is 1-10 high-context generalists who can move much faster because they do not need every decision translated across departments before anything happens.

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🗣️SoftBank’s Masayoshi Son:

“The AI revolution has only just begun. For an industry that is still at such an early stage, calling it a bubble is an insult.”

“One of the main themes of our new vision is physical AI, robots equipped with super intelligence... Artificial super intelligence won’t be replacing humans. But it will help humans evolve. It’s a tool for human advancement, a colleague and a partner.”

"We are going to pursue ASI all the way through, without holding anything back. And if I’m to take on something like that, I won’t be content unless we’re the best. That’s simply the kind of person I am.”

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🇨🇳 The DR02 by DEEP Robotics is the world's first IP66-rated humanoid robot, meaning it's completely dustproof and water-resistant.

This humanoid from Hangzhou also does pushups like it’s nothing.

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🔥10 free resources that teach you more about AI in 30 days

1. 3Blue1Brown. Grant Sanderson's neural network visualizations. The math inside ChatGPT, made visible.

Watch: https://www.youtube.com/c/3blue1brown

2. Andrej Karpathy's Zero to Hero. The OpenAI founding member walks you through building GPT from scratch in raw Python.

Watch: https://karpathy.ai/zero-to-hero.html


3. The Batch by Andrew Ng. A free weekly newsletter from the Stanford professor who taught most of Silicon Valley how machine learning works.

Subscribe: https://www.deeplearning.ai/the-batch

4. Import AI by Jack Clark. The Anthropic co-founder's free newsletter. The favorite read of researchers at OpenAI, Google DeepMind, and Anthropic itself.

Subscribe: https://importai.substack.com/

5. The Dwarkesh Podcast. Long-form interviews with the most important people in AI. His Karpathy episode is the best free AI podcast ever published.

Listen: http://dwarkesh.com/

6. Latent Space podcast. Run by swyx and Alessio Fanelli. The single best podcast for building AI products in production.

Listen: https://www.latent.space/

7. Kaggle. Free signup, free notebooks, free GPUs for learning, and over 1,000 free interactive courses. Owned by Google.

Site: https://www.kaggle.com/

8. Hugging Face. Free to download any open-source model. Free interactive notebooks. 1 million AI builders inside.

Site: https://huggingface.co/

9. Speech and Language Processing. The Stanford NLP textbook used at every top university. Authors release the full draft online, free, every year.

Book: https://web.stanford.edu/~jurafsky/slp3

10. Dive into Deep Learning. A free interactive book with code, math, and discussions for every chapter. Used at 500+ universities including Stanford, MIT, and Berkeley.

Book: https://d2l.ai/

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❗️Mistral CEO reveals the biggest risk in the AI boom

Mistral CEO Arthur Mensch says the entire AI spending frenzy comes down to one simple equation: If a company spends €1 on AI and doesn’t get €2 back, the party ends.

That’s a problem when tech giants are collectively spending more than $100 billion a year building AI infrastructure.

Right now, the strongest ROI story is coding. Developers are saving time, shipping faster, and companies can measure the gains.

But coding is only a tiny slice of the economy.

The real money is in manufacturing, industrial operations, logistics, and engineering. And AI hasn’t yet proven it can deliver massive returns there.

That’s why this matters: Data centers, GPUs, and power plants are being built today for demand that may not exist tomorrow.

The AI boom isn’t just a technology bet anymore. It’s a bet that businesses will find enough real-world value to justify all the infrastructure being built.

If they do, today’s spending will look genius. If they don’t, it could become one of the most expensive assumptions in tech history.

@aipost 🏴

❗️Claude Fable 5 approved for return

Currently invokeable on AWS but not for everyone

You need :

• US identity verification
• Upload simple use case to Anthropic
• Wait for account review
• Only approved accounts can call it

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🤖 Anthropic says it has uncovered what may be the largest AI model extraction campaign ever detected.

In a confidential letter to U.S. lawmakers and White House officials, the company alleges that operators linked to Alibaba and its Qwen AI division created nearly 25,000 fake accounts and generated more than 28.8 million interactions with Claude between April 22 and June 5, 2026.

According to Anthropic, the goal was “distillation” using Claude’s responses to help train a competing AI system. The company claims the operation specifically targeted Claude’s most advanced capabilities, including coding, complex reasoning, autonomous agents, and long-range planning.

Anthropic argues that large-scale extraction efforts like this could allow rivals to accelerate AI development without bearing the full cost of training frontier models from scratch. The company is now urging Washington to strengthen protections for AI intellectual property, allow AI firms to share extraction data, and tighten enforcement around unauthorized model copying.

@aipost 🏴

📈 AI agents are becoming the first real economic test of the AI boom.

Goldman Sachs predicts AI token usage will explode 24x by 2030 as agents replace simple chatbots. The reason? Agents don’t just answer questions, they think, plan, use tools, check their work, fix mistakes, and repeat the process, burning through far more compute along the way.

The industry’s hope is that AI gets cheaper fast enough to keep up. But companies are already feeling the pressure. Uber and Microsoft have reportedly started scrutinizing costly agent deployments, and Microsoft is moving developers away from Anthropic’s Claude Code toward its own tools.

@aipost 🏴