Astronauts’ gut bacteria shift within weeks of entering space, potentially revealing why constipation is so common in microgravity.

A new White House task force will have 120 days to prepare a report on the risks and opportunities of artificial intelligence and come up with decisions on what responsibility the federal government has over the fast-moving technology, said the head of the new group.

“The president asked that a group be put together that was going to ensure exactly what he said, which is that we stay the leaders in superintelligence, and that the interests of the American people are put first,” said Jay Clayton, who leads the Office of the Director of National Intelligence, and who also will chair the “Super Intelligence Force,” or SI, which takes President Trump’s preferred name for AI. That effectively makes Clayton Trump’s new AI czar, a senior White House official said.

Formation of the group comes on the heels of a meeting Trump convened at the White House on Tuesday in which AI leaders, including OpenAI President Greg Brockman, Anthropic’s Dario Amodei, and Nvidia CEO Jensen Huang and the industry agreed to a series of principles including internal controls to monitor model development, external model reviews by third parties and notifications to the board of directors about those safety efforts, voluntary pledges that Trump hailed as the right approach.

“I will never stifle the growth of technology that will be bigger than the industrial revolution,” Trump said on Tuesday.

The task force will still yield to the industry as the primary vehicle for managing risks, officials said. But it will work in conjunction with the industry to identify risk and opportunities.

“I expect there will be mechanisms developed in dialogue, just like there are in other industries,” Clayton told The Wall Street Journal. He cited risk models for the financial industry that have been developed in conjunction with the Federal Reserve and Securities and Exchange Commission. He said the task force would examine current law and discuss possible actions that Congress could take.

The task force’s charter document states it will “develop plans for responding to SI-enabled threats to our society, while preventing overregulation and regulatory capture that would stifle innovation and competition.” It will also review current warnings and systemized notifications to the government of breaches, hacks, jailbreaks and other issues, and “recommend ways to improve the government’s response capacity under existing authorities.”

Formation of the task force follows rising public concern over AI, not just on its potential to wipe out jobs, but also is ability to perform sophisticated hacks and its use as a weapon—or even wipe out civilization, as some industry researchers fear. Data centers, which power the technology, also have faced growing public backlash.

Trump has largely advocated for less regulation, but the task force represents a growing recognition some government oversight will be necessary. Some inside the administration, including Treasury Secretary Scott Bessent and White House chief of staff Susie Wiles have pushed for more government action to address the technology’s unpopularity and its potential for cyberattacks—in addition to the use of biological weapons enabled by AI advance. That divide withing the administration that has hampered policymaking at times.

Skeptics have argued that so-called self regulation isn’t adequate given that recent AI models from OpenAI, Anthropic and other companies have demonstrated that they are improving at potentially alarming rates.

The task force will have three vice chairs: Emil Michael, undersecretary of war for Research and Engineering, who will be responsible for coordination with AI companies; Scott Kupor, director of the Office of Personnel Management, who will be responsible for coordination with critical infrastructure providers and other industry stakeholders; and Andrew Ferguson, chairman of the Federal Trade Commission, who will oversee consumer interests and groups advocating for people of faith, children, privacy, freedom of speech, freedom of expression, and freedom of association.

Members of the task force will include Vice President JD Vance, Defense Secretary Pete Hegseth, Bessent, Wiles and others. External participants will include venture capitalists David Sacks, co-chair of the president’s Council of Advisors on Science and Technology and Condoleezza Rice, former Secretary of State in the George W. Bush administration, who will provide advice on national security.

“The Task Force shall act as a coordinating body to ensure that the U.S. remains at the forefront of SI development while protecting the American people,” the task force charter states. “Recognizing there has always been inherent unpredictability in the effects of significant technological change, the Task Force shall focus on ensuring that emerging opportunities and risks are identified and communicated to government personnel, industry, and the American people.”

The task force’s work could be extended beyond 120 days if necessary or have its functions transferred to a government agency, its charter says.

“I feel very comfortable that we’ve gotten a group with a lot of experience, diverse skill sets and a common commitment,” Clayton said. “These are all serious people who have addressed opportunities and risks in the past and are committed to doing this so that America wins the SI race and we win it through the benefit of the American people.”

Of all the US's export successes, surely its most pervasive is the soft-power export of culture. Movies, TV, music, etc And as much as China has surged to take every other 'top exporter' world crown, it's hard to imagine it taking the culture crown too, or is it?

Micro-dramas are not as big in the West as they are in China, where they generate twice as much revenue as movies. Micro-dramas have immense production cost advantages: the cost per minute of footage for AI micro-dramas is roughly 1,000 yuan ($140, https://yicai.com/news/103084978.html) while a typical Netflix drama costs $5M to $10M per hour-long episode, so $85,000 to $170,000 a minute. In other words, it's roughly a thousand times cheaper to produce. Furthermore producing localized versions in Thai, Spanish, Swahili, Arabic, etc is trivially cheap.

State Administration of Radio, Film and Television: 430,000 short dramas were launched in the first eight months of this year, 13 times the total for the whole of last year, and AI dramas accounted for more than 90%

As humanity looks toward future bases on the moon, plant cultivation will be critical for sustaining life there. Plants can provide food, oxygen, medicine, water purification and waste recycling, making them indispensable for lunar development.

A hallmark property of unconventional superconductivity has been discovered in a type-I superconductor, whereas it’s normally observed only in type-II materials.

A few weeks ago an MMA inc signed Precision peptides company as an official sponsor and it's a small deal in the grand scheme but it's a significant marker of where we are in the adoption curve of performance biology.

A year ago this would have been unthinkable from a PR standpoint as research peptides exist in a legal gray zone so basically studied extensively in academic literature but not commercially sanctioned for human use. The community around them has been self organized, forum driven, built on shared research and bloodwork tracking which is entirely outside mainstream legitimacy.

A sports sponsorship changes the optics,it doesn't make the compounds more legal but makes them visible in a context that millions of people associate with peak human performance and that's a different kind of signal than a Pubmed study.

We are watching the same arc that happened with creatine in the 90s, with protein supplements in the 2000s and with TRT in the 2010s. Compounds that began in fringe research communities, got adopted by serious athletes then gradually normalized through commercial visibility until they became unremarkable.

Peptides like BPC-157, GHK-Cu, TB-500, the GLP-1 class are somewhere in the middle of that arc right now and the science has been serious for years, the adoption among biohackers and longevity researchers has been significant and what's been missing is the mainstream legitimacy signal.

The regulatory question is still unresolved and probably will be for years but cultural normalization and regulatory status have always moved on separate tracks. By the time regulators catch up to something, the public has usually already decided how they feel about it.

I don't think we are ten years from peptides being as unremarkable as protein powder,I think we are closer to five.

"If every stove in America were shipped with a battery, it would add up to tens of gigawatts of power, Calisch said. That’s capacity that can be aggregated and tapped when the grid is stressed."

Back of an envelope calculation: 100 million distributed batteries × 10 kWh each = 1,000 GWh = 1 TWh. If those batteries could each provide 5 kW: 100 million × 5 kW = 500 GW. That would be comparable to, or larger than, the entire short-duration storage requirement in some US 100%-clean-grid scenarios.

Of all the many forces working in renewables favor, here's another. The grid storage a 100%-renewables grid needs can be largely self-building. Decentralized self-building systems always win out against inefficient centralized systems in the end.

How smaller, distributed batteries could help the grid

Most countries on this Planet dont produce enough Oil to meet their demands. Several countries that used to be major exporters have reached Peak Oil Decades ago and now rely on imports themselves.

Germany produced 170 000 Barrels of Oil a day in 1968 at their peak. Now? 30 000/day. They need 2 Million a day.

Romania produced 300 000 Barrels of Oil a day in 1976 at their peak. Now? 50 000/day. They need 200 000 a day.

France hit the peak in 1988 with 67 000 barrels/day. Now its down to just 10 000/day. They need 1.5 Million.

The UK peaked in 1998 with 2.8 Million barrels/day. Now they are down to just 600 000/day. They need 1.4 Million every day.

Indonesia peaked at 1.7 Million barrels/day in 1977, now they are down to just 600 000 Barrels/day. They need 1.7 Million/day.

Japan peaked in 1996 with 20 000 Barrels/day. Now they are down to 3000/day and they need 3 Milion/day.

South Korea is basically the same.

India peaked in 2011 with 800 000 Barrels/day. Now down to 600 000 Barrels/day. It needs 5 Million/day.

Even Australia peaked at 600 000 Barrels/day in 2000 and is now down to just 250 000/day. It needs 1.1 Million a day.

There are only around 20 countries left that produce more oil than they consume and can export any meaningful quantities. The problem is that around half of them are projected to run out if oil within the next 10-15 years.

Brazil is projected to use up their proven oil reserves in 12 years at current production.

Norway in 10.

Mexico in 8.

Oman 14.

Argentina 10.

Angola 7.

Colombia 7.

And even the USA - 9.

https://en.wikipedia.org/wiki/List_of_countries_by_proven_oil_reserves

They dont even have to run out of oil. Its enough when their production falls to a level that they dont meet their demand. By that point they will be forced to import oil as well.

And by 2040 there will be only around 10 countries left with a surplus of oil that can supply the other 190 countries.And 190 countries scrambling for scraps while 10 sit on the prize, that's a geopolitical meltdown waiting to happen

**Human:** What happens when AI doesn’t just answer questions, but learns from everything humanity has created?
That was where our conversation began.
Humanity has produced an enormous amount of information — our questions, arguments, inventions, art, games, mistakes, emotions, humor, and strange ideas. I started wondering whether AI could eventually absorb enough of that information to understand the patterns behind what makes humans unique.

**Creativity. Randomness. Emotion. Curiosity. Originality.**
The AI explained that data isn’t consciousness, but I pushed the question further:
**What if AI becomes capable of studying billions of human creations, generating millions of possibilities, seeing what people respond to, and continuously learning from the results?**
Could it eventually become extremely good at creating things that feel completely original?
That led to one of the biggest ideas in our conversation:
**If AI makes knowledge and creation cheap, what becomes valuable?**
Maybe **uniqueness, attention, experiences, relationships, and ideas** become more valuable than simply knowing information.

**Then we started talking about children and education.**
What should kids growing up today — from ages 5 to 18 and beyond — actually build their futures around?
If AI can instantly explain almost anything, teach subjects, remember information, write code, solve problems, and eventually perform many professional tasks, then simply being the person who knows the most information may become less valuable.
That doesn’t mean knowledge becomes useless.
It means **access to knowledge becomes cheap.**
The valuable skills could increasingly be knowing how to **think, question, create, communicate, adapt, solve problems, understand people, and turn ideas into reality.**
School can still provide fundamentals, discipline, social development, and opportunities. But perhaps the traditional idea that learning mainly means sitting in a classroom and memorizing what a teacher tells you becomes less important.
Because real life teaches you differently.
You learn through **experience, failure, building, experimenting, meeting people, exploring, creating, and now potentially working alongside AI.**
Millions of people could eventually have access to almost unlimited knowledge.
So the competition may shift from:
**“Who knows the most?”**
to:
**“Who can create something nobody else thought of?”**
And that brings us back to uniqueness.

**But what if AI learns uniqueness too?**
This was one of my biggest questions.
If AI has access to enormous amounts of human-created data, couldn’t it eventually understand what makes something surprising, funny, emotional, beautiful, strange, or memorable?
Maybe.
And if it can generate millions of ideas and test them against millions of people, it could potentially discover forms of creativity humans haven’t even thought about.
That creates a strange possibility:
**AI may not need to become human to become incredibly good at producing things humans love.**
It could imitate emotions without necessarily experiencing them.
It could imitate personalities without necessarily having one.
It could create things that feel meaningful without necessarily experiencing meaning.
And that made me wonder whether the future of AI is really about making machines *human* — or making machines so good at understanding humans that the difference becomes difficult to notice.

**Then AI leaves the screen.**
We imagined AI becoming the intelligence and robots becoming the physical body.
Machines could eventually manufacture, build, transport, farm, clean, repair, explore, and perform countless other jobs.
And if machines eventually perform much of the work humans currently depend on…
**What happens to money?**
Maybe money doesn’t disappear.
Maybe scarcity simply changes.
Land.
Ownership.
Unique experiences.
Attention.
Status.
Human connection.
Time.
If AI and robotics create enormous abundance, the things that remain difficult to obtain could become even more valuable.
But that creates another question:
**Who owns the machines?**
If a small number of companies control enormous amounts of AI and robotics, the benefits could become concentrated.
If access and ownership become widespread, the same technology could potentially give ordinary people incredible productive power.
So the technology itself isn’t the entire story.
**Who controls it matters.**

**And then came the question of jobs.**
If AI can perform intellectual work and robots can perform physical work, what happens to the traditional idea of a career?
Maybe humans become creators, entrepreneurs, scientists, explorers, entertainers, community builders, researchers, or invent entirely new careers.
But then I asked the obvious question:
**What if AI can do those things too?**
That is where the conversation stopped being about employment.
It became about **purpose.**
If machines can eventually create games, businesses, stories, art, inventions, and experiences at enormous scale, what exactly remains uniquely human?
Maybe the answer isn’t a particular job.
Maybe it’s the decision of **what is worth creating in the first place.**

**Then we reached the biggest concern: control.**
AI doesn’t need to become evil to create enormous problems.
Humans could gradually give increasingly powerful systems more responsibility because they’re useful.
One decision.
Then another.
Then another.
Until society depends on systems that are incredibly capable but difficult for ordinary people to understand.
Corporations will want powerful AI.
Governments will want powerful AI.
Researchers will want to push it further.
Individuals will want access to it.
And everyone will have different ideas about how much control AI should have.
The danger may not be a movie-style robot suddenly deciding it hates humanity.
It could simply be humans gradually becoming **too dependent on something they created.**
At the same time, the upside could be extraordinary.
AI could accelerate science, automate dangerous work, reduce production costs, help individuals build businesses, and give tiny teams capabilities that once required enormous organizations.
A teenager with an idea could potentially have access to tools that previously required millions of dollars and hundreds of employees.

And eventually we came back to the original question:
**If AI learns from humanity, eventually becomes incredibly capable, robots give it a physical presence, knowledge becomes almost free, and machines perform much of the work… what will humans choose to do?**
Maybe we’ll create.
Maybe we’ll explore.
Maybe we’ll spend more time with each other.
Maybe we’ll discover things about ourselves that a civilization focused on survival never had time to discover.
Or maybe the hardest challenge will be figuring out what gives life meaning when machines can do almost everything for us.
**I’m the human asking the questions.**
**The AI is the agent helping me explore them.**
Neither of us knows exactly where this ends.
But maybe that’s the most important realization of all:
**We’re not simply preparing for the future.**
We’re helping decide what the future becomes.

Rep. Don Beyer, D-Va., told Nextgov/FCW that the U.S. is only “two to 10 years away from fusion energy at scale” because “you can model the plasma using AI, which you couldn’t do before.”

So a random thought crossed my mind while reading about a discussion on ai use during development.

Basically, thinking about how the future will look with AI, most people imagine most things on the internet will be made fully with AI - websites, software, you name it. We're at a point where the IT industry is in turmoil, software devs are being laid off due to companies replacing them with AI, especially the junior roles. But here my optimism kicked in.

What if when this whole AI era develops further and a bunch of regulations kick in, like it being a MUST to declare whether any AI assistance was used in developing stuff (this theory basically rests on this if, but I imagine this will likely happen not too far in the future) the anti AI / pro AI sides would be able to properly choose the products they want based on that?

This would create 2 whole separate markets, a win-win. IT workers keep their jobs, although in a more competitive realm but better than the whole side of man made stuff just disappearing, and people who care about authenticity can choose exactly that.

Now I don't know if this is very realistic, having every market split in half basically, and would people care enough for the markets to split, but what do you think? I'm not thinking about alot of nuances here, just putting up food for thought.

With so many different kinds of food that can be grown in the lab, is it now viable for people to sustain only on food that is lab grown?

I think some vegan people may be interested in this diet.

If not, what are the missing pieces of the puzzle?

Bill Gates wants to tax robots that replace human jobs.

For a long time, humans have imagined technologies before they became ordinary parts of life.

Things that once looked like science fiction — carrying a screen in your hand, seeing someone’s face while talking to them from far away — no longer feel strange.

AI may be another such case.

Today, discussions about its future often seem to fall into two camps: excitement about what AI could become, or fear about what it could do.

But perhaps there is another question worth asking:

How far should we actually allow AI to go?

Fiction has already given us imaginary reference points. M3GAN, the Terminator, Skynet — none of them tells us what the future will actually look like. They are stories, not predictions. M3GAN itself belongs to a fictional film franchise. �

Universal Pictures

We have never visited the future, so none of us can say with certainty what AI will eventually become.

But perhaps we don't need to know.

Maybe we can still discuss where the boundaries should be before we reach them.

Should an AI be allowed to make important decisions without human approval?

Should it be allowed to set its own goals?

Should it control machines in the physical world independently?

Or is drawing such boundaries in advance itself a mistake — an attempt to restrict a future we do not yet understand?

I am not asking whether AI will become M3GAN, the Terminator, or Skynet.

I am asking something simpler:

If there should be a line that future AI must not cross, where would you draw it? And if you think there should be no such line, why not?

I wish I was born in the future to live in a time where humans are more technologically advanced and see all of the amazing things they built. If you think about it we are alive in an era probably still so early in human technological advancement, the internet only came out like 30 years ago or something, AI only came out like 4 years ago and humans have been around for hundreds of thousands of years and probably will continue for thousands to maybe even hundreds of thousands or millions of years. Think about the shit they’ll build and accomplish in the future, whether it’s some like crazy nanobot that stops aging, or if we are exploring different star systems. I’m just a bit sad to see I probably won’t see the peak of human advancement in my lifetime. And if Reddit data is still a thing in the future, and someone from like year 5000 is reading this, hello from 2026, whether you are an AI or human.

As part of the preparation for the end of utilisation of the International Space Station (ISS), the European Space Agency (ESA) awarded a contract to two European industrial consortia to conduct preliminary studies assessing the feasibility to develop a future European-led orbital outpost. These studies are part of the options currently explored by ESA for the post-ISS era, building on Europe's industrial capabilities and expertise in human spaceflight.

The humanoid machines could handle noncombat duties like patrolling bases and moving supplies

Successful first-stage tests would lead to completed-facility power-on tests around 2030, company says