Nathan Putnam retweeted
As of now, no fly can ever know for sure if it is living in a real world or a simulated one. Must be incredibly depressing
Nathan Putnam retweeted
US GOV "bans" DeepSeek?
They claim it's because the servers are in China, but they ban even US inference providers if they use DeepSeek.
They also ban anything "built with" or "based on" DeepSeek models.
🚨美国国土安全部公开了一份针对DeepSeek的禁令,禁止任何美国联邦民用政府机构采购@deepseek_ai 的模型(也包括基于DeepSeek开发的第三方产品)
刚看了《联邦公报》的文件。这份公告在当地时间10月19日预公开,计划10月20日正式刊登,所附命令标注的原始发布日期是7月24日。
要求里表示在采购端,要把DeepSeek及关联实体的相关产品和服务,从机构批准清单、采购平台等渠道移除;
而在使用端,要清理机构IT系统里已经使用的相关产品。
使用DeepSeek实现的第三方产品和服务,同样被纳入了范围。
这份命令适用于美国联邦民用行政机构,其中国家安全系统、隔离涉密信息系统另有管理边界,国防和情报体系也属于其他权限范围。
DHS给出的理由包括服务器位于中国、政府人员使用服务可能导致敏感数据外流,并援引安全研究,称DeepSeek的iOS应用存在严重漏洞。
命令也设置了豁免申请程序,申请期限按命令签发日期起算60天。
我更在意的是第三方产品这一条。
按文件写明的范围,给这些机构提供AI助手、Agent或业务系统的团队,即使交付的是自己品牌的产品,也会受到其采用DeepSeek所带来的采购限制。
文件里也没有给本地部署、第三方托管单列自动豁免。
这就把影响传到了做应用的团队身上。
模型由谁开发、产品由谁交付、服务部署在哪里,原本是几个可以分别选择的事情,现在底层模型的供应商,会直接影响整个产品能否进入这部分政府市场。
对准备做美国政府项目的AI团队来说,选模型又多了一个很现实的条件:能力、速度、价格都合适之后,还得看客户有没有资格采购和使用。
Nathan Putnam retweeted
Ukraine hits another Yandex data center in Russia and Cloudflare data shows Russian bot traffic dropping dramatically. Might have an impact right before the November elections.
Nathan Putnam retweeted
“I don’t think that in my entire life as a journalist, I’ve ever reported on a more heinous crime than this.”
Drop Site’s @jeremyscahill reflects on his reporting on the Feb. 28 U.S. strike on the Shajareh Tayyebeh Primary School in Minab, Iran, which killed 156 civilians, including 120 children and 26 teachers. All 26 teachers killed were women, including one who was six months pregnant.
“When it’s our bombs that are dropped on children across the world, we know almost nothing about who was killed in these strikes.”
Scahill spoke with doctors, parents, teachers, survivors, and people who lost loved ones in the attack.
“Part of what we set out to do was to approach this story and say: Let’s hear what happened that day through the lens and perspective of the people who survived it and those who lost their loved ones that day.”
For more than two months, I have been working on a truly horrific story about one of the gravest war crimes committed by the United States since Vietnam: The bombing of the Shajareh Tayyebeh school in Minab, Iran. It was one of the first targets struck in the opening hours of the war on February 28, 2026.
At least 156 people were killed in the U.S. cruise missile strikes—120 of them were children and 26 were teachers. We spoke to survivors, first responders, parents, doctors, teachers, psychologists, and other witnesses. Some of them had never before shared their experiences of that day.
It would be impossible to do justice to what happened in Minab that day with words alone. In more than 25 years in journalism and reporting on war, I do not believe I have reported on a more heinous single crime.
Massacre at Minab: The School That Became a Grave
dropsitenews.com/p/minab-sch…
Please share this story with as many people as you can.
"I don’t even know how to write what I’m thinking without sounding alarmist…but I don’t see how 90%+ of NVIDIA’s sales ever end up generating a single dollar of revenue..."
wheresyoured.at/wherere-all-…
Update those priors
ourworldindata.org/data-insi…
To me, that is the most salient and worrying trend: that people in positions of power and influence are now notably ignorant about history and the classics, comfortable only with referencing pop culture....The cultural elite has abandoned cultural elitism.
edwest.co.uk/p/doomscrolling…
Nathan Putnam retweeted
The future is open source. We need to embrace it and get on with it.
Imagine if America closed the door on open source.
We would explicitly be forcing American companies to pay $26-56 per 1MM tokens for the same intelligence their adversaries/competitors around the world would pay $0.50-1 for.
This is economically unsustainable unless AI is bullshit.
If it’s the supposed through line of all future economic activity that we’ve been told it is, we can’t handicap America at such a meaningful cost disadvantage.
This can also be viewed thru a military lens and not just a simple economic one as well.
Letting our adversaries attack us for $0.50 per 1MM tokens while we spend $26-56 per 1MM tokens to defend ourselves is equally ruinous.
It’s the Cold War Soviet collapse in reverse.
Nathan Putnam retweeted
Popper argued that the traditional academic disciplines and their arbitrary subject matters don't objectively exist in reality. Instead of studying a specific topic, he argued that thinkers should focus entirely on solving concrete, practical problems that cut across disciplinary boundaries.
Administrative Convenience vs. Real Problems
Administrators favor neat subject matters because divisions, departments, and specific course catalogs provide a clean bureaucratic structure. However, Popper noted that this structure forces students into arbitrary academic silos. Because real-world problems do not conform to artificial department lines, forcing students to specialize in a subject rather than a problem chokes true critical thinking and intellectual growth.
How It Fails Students
"Instead of encouraging the student to devote himself to his studies for the sake of studying, instead of encouraging in him a real love for his subject and for inquiry, he is encouraged to study for the sake of his personal career; he is led to acquire only such knowledge as is serviceable in getting him over the hurdles which he must clear for the sake of his advancement."
This structure favors passive, bucket-like memorization over the active trial-and-error necessary for learning. Consequently, students prioritize passing bureaucratic hurdles over developing the critical thinking skills needed to challenge dogmatic ideas.
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Yet, Popper's ideas above are completely unknown to over 99% of scientists at all levels. All incentives favor specialization. No one stops to think we are like ant castes with strict missions and methods.
Investigators are thus highly motivated to 'protect' their fields from outsiders. The more interdisciplinary one is, the more they risk being dismissed as a dilettante.
The proven way for Principal Investigators to get their first funding is to propose continuing their subject matter and methods they used as trainees. They must do this to 'pay the bills', since they are unlikely to be funded by any other fields' experts. This domino effect often continues for whole careers.
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When students seek guidance, I begin by asking what motivates them -- what question would they love to completely devote themselves to for an extended time? In almost every case, the student begins their answer with a scientific field and only then a biological or disease question. Often, my advice is to identify the top 3 investigators in the world working to solve their problem. Find out what they doing. Communicate with them. Prepare yourself to work in such a group and, if possible, join a top lab.
When students ask what elective classes they should take for a biomedical career, I generally encourage taking philosophy and statistics.
Nathan Putnam retweeted
Hamming's talk is so important that I reproduced it on my site. It's one of the only things on my site written by someone else.
paulgraham.com/hamming.html
A mathematician who shared an office with Claude Shannon at Bell Labs gave one lecture in 1986 that explains why some people win Nobel Prizes and other equally smart people spend their whole lives doing forgettable work.
His name was Richard Hamming. He won the Turing Award. He invented error-correcting codes that made modern computing possible. And he spent 30 years at Bell Labs sitting in a cafeteria at lunch watching which scientists became legendary and which ones faded into nothing.
In March 1986, he walked into a Bellcore auditorium in front of 200 researchers and told them exactly what he had seen.
Here's the framework that has been quoted by every serious scientist for the last 40 years.
His opening line landed like a punch. He said most scientists he worked with at Bell Labs were just as smart as the Nobel Prize winners. Just as hardworking. Just as credentialed. And yet at the end of a 40-year career, one group had changed entire fields and the other group was forgotten by the time they retired.
He wanted to know what the difference actually was. And he said it wasn't luck. It wasn't IQ. It was a specific set of habits that almost nobody is willing to follow.
The first habit was the one that hurts the most to hear. He said most scientists deliberately avoid the most important problem in their field because the odds of failure are too high. They pick a safe adjacent problem, solve it cleanly, publish it, and move on. And because they never swing at the hard problem, they never hit it. He said if you do not work on an important problem, it is unlikely you will do important work. That is not a motivational line. That is a logical one.
The second habit was about doors. Literal doors. He noticed that the scientists at Bell Labs who kept their office doors closed got more done in the short term because they had no interruptions. But the scientists who kept their doors open got more done over a career. The open-door scientists were interrupted constantly. They also absorbed every new idea passing through the hallway. Ten years in, they were working on problems the closed-door scientists did not even know existed.
The third habit was inversion. When Bell Labs refused to give him the team of programmers he wanted, Hamming sat with the rejection for weeks. Then he flipped the question. Instead of asking for programmers to write the programs, he asked why machines could not write the programs themselves. That single inversion pushed him into the frontier of computer science. He said the pattern repeats everywhere. What looks like a defect, if you flip it correctly, becomes the exact thing that pushes you ahead of everyone else.
The fourth habit was the one that hit me the hardest. He said knowledge and productivity compound like interest. Someone who works 10 percent harder than you does not produce 10 percent more over a career. They produce twice as much. The gap doesn't add. It multiplies. And it compounds silently for years before anyone notices.
He finished the lecture with a line I have never been able to shake.
He said Pasteur's famous quote is right. Luck favors the prepared mind. But he meant it literally. You don't hope for luck. You engineer the conditions where luck can land on you. Open doors. Important problems. Inverted questions. Compounded hours. Those are not traits. Those are choices you make every single day.
The transcript has been sitting on the University of Virginia's computer science website for almost 30 years. The video is free on YouTube. Stripe Press reprinted the full lectures as a book in 2020 and Bret Victor wrote the foreword.
Hamming died in 1998. He gave his final lecture a few weeks before. He was 82.
The lecture that explains why some careers become legendary and others disappear is still free. Most people who could benefit from it will never open it.
I fear that Ai will prove to be to America's tech sector what the Automobile was to our manufacturing. Large entrenched companies slow to innovate because they were allowed to become an oligopoly just so a foreign competitor could disrupt them.
dropsitenews.com/p/deepseek-…
Nathan Putnam retweeted
It’s a silent epidemic affecting nearly everyone:
The Meaning Crisis
We are drowning in bullshit—literally “meaninglessness”
We feel disconnected from ourselves (each other) and a viable future
Alienation without (anxiety within)
So how can you reclaim meaning in your life?
We're addicted to our phones.
We're disconnected from nature.
Jobs are at the threat of replacement.
Schools and religious ideologies are losing trust.
We're going through a meaning crisis.
Here's how you navigate it:
youtu.be/uy9_bfhfFvQ
Nathan Putnam retweeted
nothing more american than missing your target and mortar striking civilians 🇺🇸🇺🇸🇺🇸🇺🇸
Nathan Putnam retweeted
"The rate of profit is highest in those nations going fastest to ruin."
—Adam Smith, Wealth of Nations




























