田田 retweeted
End of a 40 year cycle of declining interest rates, the start of a 40 year rise.
Demographics and population decline are going to make the debt far harder to carry.
Hence rates must go up, and prices must come down.
田田 retweeted
No one tells you that once you find the right routine for your neurospicy brain, you'll cry.
Because life WAS harder.
You can finally focus and do things easily without getting overwhelmed.
If you're struggling, try The Fabulous.
田田 retweeted
My first piece for @NewYorker is out today!
As Xi Jinping lands in DC to start his state visit, you'll hear a lot about the US-China AI race. I'd like to tell a complementary AI story.
This past May, a few days after Trump visited Beijing, I went to the town people call China's vibe-coding capital, Liangzhu. There, you learn that China's AI scene is not monolithic. It's also full of contrarians, cool vibe coders, spiritual seekers, and people who love AI but refuse to join the 996 grind.
Liangzhu is on the edge of Hangzhou. I hung out with a group of anti-mainstream builders who use AI to make whimsical apps for fortune-telling, mental well-being, and creativity. Some of them run their lives entirely by bazi astrology (their founder almost became a Taoist monk). They meet on "Crazy Thursday" to vibe-code together. Rent is cheap, so they can get a bigger place with a living room to have friends over (unthinkable in Beijing or Shenzhen). In Liangzhu, they want to use AI to forge their own future.
It’s a ground-level story—less about model capabilities, hyperscalers, or AI policy, and more about how people in China are using AI, and the human stories behind it.
田田 retweeted
习近平希望用人工智能助中国赢得未来,引领国家迈向下一场经济革命。为了实现这一愿景,中国正在动用倾国之力。政府提供巨额资金支持,并利用开源策略帮助中国企业赢得全球用户。cn.nytimes.com/china/2026092…
田田 retweeted
EL EGOÍSMO ES LA FORMA MÁS EFICIENTE DE CARIDAD
Suena contraintuitivo, pero la economía nos enseña que una sociedad no necesita que todos sean altruistas para que las personas terminen ayudándose unas a otras.
De hecho, muchas veces ocurre lo contrario.
El individuo que busca mejorar su propia situación y ganar más dinero, es aquel que tiene un incentivo permanente en descubrir qué necesitan los demás.
Es simple: para prosperar, tienes que servir.
Esta es una de las grandes virtudes del Capitalismo.
No necesita que ames a tu prójimo para que puedas beneficiarlos.
No necesitas sentir una profunda preocupación por el bienestar del consumidor para producirle bienes.
Basta con que quieras obtener algo para ti y entiendas que, para conseguirlo, tienes que ofrecer algo que otros quieran.
El altruismo depende de la voluntad de ayudar. El mercado, en cambio, puede hacer que ayudar a otros sea parte del camino para ayudarse a uno mismo.
Por eso el egoísmo, entendido como búsqueda legítima del propio interés dentro de intercambios voluntarios, es la forma de apoyo al prójimo más eficiente que existe
Es una maravillosa alquimia: convertir intereses particulares en satisfacción de necesidades ajenas.
Así que moraleja es esta: a veces, para hacer el mayor bien posible a los demás, no necesitas desear constantemente en hacerles el bien. Simplemente necesitas encontrar la mejor manera de satisfacer sus necesidades a cambio de obtener lo que quieres de ellos.
《恶意维权恶意涨薪》
在一个权力不受到约束的环境里,语言腐败是很难避免的。其中最常见的是将简单的问题复杂化,把正确的事情污名化,例如恶意维权、恶意涨薪,以及将表达分为正负能量等等。于是当一件并不违法的事情,但权力却不想看见的时候,便习惯性的用污名化的词汇对其进行遮掩或扭曲,这明显是不合理的。
如今年轻人之所以很难理解这个社会,是因为他们能接收到的往往只是别人给出的标准答案,但答案并不等于现实,它只不过是在描述现实。就像一个人越是反复倡导什么,越能说明他在某个方面是不稳定的,所以他才会一直的说,反复的说。因为往往越完美的词汇,越容易站在道德的高地上来掩饰真正的问题所在。比如鼓励你无私奋斗,不要计较个人回报,鼓励你支持国货,对质量不要要求太高。
但如果你认真思考就会发现,我们日常所接收的信息很多时候是单方面的,而另一面却很少有人提起。比如努力工作是积累还是消耗?支持自主品牌是普惠还是收割?保持文化自信是信心还是自负等等。这些问题不是不能问,而是在宏大的叙事面前提问,就很容易变成负能量。
于是当大家开始沉迷于宏大叙事的时候,个体的真实困境就很容易被解读为自身问题。比如他们会说,你找不到工作是因为吃不了苦,你不想结婚是因为缺乏责任心,你提出质疑是因为没有家国情怀。这种将困难重新定义的现象才更值得我们去警惕,因为半真半假的叙事往往会将问题掩盖起来。
然而一个健康稳定的社会一定是一个主动解决问题,并且重视长期回报的社会。年轻人可以少拿点钱,但长期要能看到希望。年轻人可以承担家庭责任,但是教育、住房、医疗要进行松绑,大家也可以积极参与产业升级,但发展的红利要实现共享。
人们之所以能接受困难,因为未来预期是明确的,大家咬咬牙挺过去,就能够得到更公平、更稳定的分配机制。后来大家之所以沉默了,是因为目标达成以后,预期没有得到兑现,大家的期待落空了。最后,年轻人不再回应,也不再反驳,甚至心里有苦也不再想说了。
这种"你的规划与我无关"的心态,它不仅会影响社会的发展,还会破坏社会的稳定,最终所有人都将因此受到影响。
People who want a slow life are rebels against this modern culture. They don't want this constant stimulation. Grind 24/7 to make it. Or following "morning routine" that turns your mental health to shit. What they really want is stillness. A calm nervous system. A life free of anxiety about "what to do next". They want calm mornings. A quiet coffee. Meaningful work. And alone time to think about the things that matter. You're built for depth. Not noise and performance. And trying to force a peaceful soul to live in a hyper-stimulated world is one of the fastest ways to lose yourself.
田田 retweeted
The 30-year Treasury yield is 5.41%, a new twenty-two-year high. But given that the 10-year yield is 5.12%, the 30-year yield needs to adjust higher, as 29 basis points is not nearly enough extra yield to compensate for an extra twenty years of high inflation and default risk.
田田 retweeted
中国男人找老婆,真正应该筛选的,不是“她现在对你好不好”,而是:她有没有能力和你长期共同生活、共同承担风险、共同处理财富、共同面对冲突。长期婚姻质量公式≈原生家庭×情绪稳定×冲突能力×共情能力×边界感×责任感×财富处理能力。漂亮和性感,只能决定一段关系会不会开始;真正决定婚姻能不能长期走下去的,是一个人的人格底色、关系能力和财富观。
田田 retweeted
香港的老钱家族们,迟早会被国内电商和AI干死。
前两个月,香港尖沙咀太阳广场的DFI悄无声息结业了,这个卖场主要卖高端化妆品和香水,价格很贵,都是大几百到几千港币。
DFI结业,让很多香港人错愕。
但其实,这是香港零售行业的衰败的体现。
现在国内电商对香港的渗透非常强,大部分香港年轻人,及内地来港工作的人,都在用某多、某宝和某东,送货上门,再加上低廉的价格,让他们欲罢不能。
这必然导致香港实体店铺关门,因为香港的铺租和人工非常贵,消费者支付的大部分费用,都在为此买单。
国内电商的价格,相比香港的商品便宜一半,甚至更多,谁都喜欢。
香港的老钱们,把持了香港的商场、写字楼、商铺,收了五六十年租,赚得盆满钵满,本以为还可以躺平继续收下去。但电商平台的出现,会慢慢终结他们的好日子。
在电商和AI领域,香港老钱们集体落后,坐看未来他们如何被科技革命。
田田 retweeted
国际关系里,意识形态没那么重要,希特勒当年搞种族灭绝,英国,苏联还和他签各种绥靖协议呢。后来是德国不断扩张,打了法国,比利时,奥地利,波兰,最后又入侵苏联,才引发苏联和美国英国组成盟军共同对付德国。
所以你看,国际关系的核心就是自己的利益,不要想着什么意识形态。
美国为啥不会全力以赴对付中国?因为中国除了对台湾有主权要求外,对外并没有实行扩张主义。老毛那会儿有过,但邓之后,就完全没了。
这样的中国,世界各国是没可能组成联盟对付中国的,即便某一天中国武统台湾,也完全不会。至于台湾民主不民主,一点儿都不重要。
我这话一半是说给台湾听的,不要以为自己搞了个民主体制,打起仗来就有人救你,没可能。台湾唯一的出路就是不要让大陆下决心打,并以此为前提争取最大利益。
田田 retweeted
Girls Outscore Boys in Reading in 89 of 90 Education Systems 📚
visualcapitalist.com/girls-o…
田田 retweeted
MCDONALD’S CEO: HIGH INFLATION IS HERE TO STAY
McDonald’s CEO Chris Kempczinski says weak customer traffic and persistent inflation are becoming the new normal for the restaurant industry.
U.S. same-store sales rose just 0.8% last quarter, while restaurant traffic declined.
With beef, labor and construction costs elevated, McDonald’s plans to compete aggressively for market share, while remaining cautious about further menu price increases.
田田 retweeted
In our view, thanks to this Technology Revolution, the equity market will continue to climb a “wall of worry” as real GDP growth accelerates to 7-8% while inflation surprises significantly on the low side of expectations, interest rates rise, and the yield curve inverts.
Inflation. Deficits. Wars. Fears of an artificial intelligence bubble.
It feels like an unusually long list of reasons for investors to worry. Yet the headlines looked remarkably similar in the 1980s and 1990s, before the most durable equity bull market since the Roaring Twenties.
Today, interest rates are hitting higher highs for the first time in more than 40 years, even as equities approach record levels. Official inflation measures remain elevated, but real-time data tell a different story. Oil remains a wildcard. Meanwhile, the cost of artificial intelligence is collapsing.
These trends might seem contradictory. We believe they make more sense when viewed through 230 years of market history, not just the last 60.
Could falling inflation, accelerating real growth, and disruptive innovation be setting the stage for history to rhyme again?
Read @CathieDWood’s Investor Letter.
ark-invest.com/articles/mark…
田田 retweeted
The 5-year Treasury yield is over 5%. The 2-year will soon follow. Next year the entire yield curve will have a 5% handle or higher. At 5% the annual interest cost of our $40 trillion national debt will be $2 trillion, 35% of tax revenue and a larger expense than Social Security.
田田 retweeted
大家发现了没有,眼下的社会各种撕裂:
幼儿园在批量关停,大学还在扩招,“双一流”高校本科生未来4年要扩容7.6万人。
结婚越来越方便了,地铁站都能结婚了,可结婚的人越来越少了,给钱给优惠券都不结婚了。
没有人讨论房子了,认知高的人在讨论比特币、出海、移民、纳斯达克和X,认知低的人还在提心吊胆苟着自己的工作。
田田 retweeted
I think the most interesting shift sparked by AI is who it rewards.
For the longest time, it seemed like the world rewarded those who followed a clear, logical path.
People who:
1. Anticipated valuable skills
2. Acquired those valuable skills
3. Leveraged those valuable skills
I don’t think that works anymore. Because you can’t really anticipate valuable skills like you could in the past.
This “new world” will reward those who are just willing to be beginners over and over again. Value now seems to accrue to those who can pair insatiable curiosity with bias for action.
The valuable skills of the future aren’t really fixed skills. They’re much more akin to mindsets.
Thoughtful piece by Jeffrey Katzenberg
The World is Changing: AI For Creativity
By Jeffrey Katzenberg
A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe.
Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.”
I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both.
In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious.
There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love.
People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft.
Is History Repeating Itself?
The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul."
Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work.
A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept.
They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded.
This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix.
What I Learned From Walt Disney
In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell.
We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not.
That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create.
A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did.
Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.”
A Distinction With a Difference
I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . .
Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new.
Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out.
Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new.
One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable.
Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground.
A Path Forward
In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . .
Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human.
At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling.
The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it.
There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us.
The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires.
What I Learned From Steve Jobs
Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities.
What I See Coming Soon
As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process.
Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.
田田 retweeted
Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.
It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.
The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).
More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.
In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.
Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.
I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.
Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.
We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.
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