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Trump realized modern GOP politics aren't about policies or governing well -- it's more akin to cutting a pro-Wrestling promo. His audience isn't waiting on a profound insight on the state of the republic, they're waiting to see who Trump will hurt and they'll cheer him on when it's the right people.

Americans can overwhemingly agree that Trump creates a negative tone but are drawn to it and support him. It's why in pro-wrestling the heel (or bad guy) can have the most dye hard fans. Trump is the modern Stone Cold Steve Austin and making a mockery of doing the equivalent of repeating "what? what? what?" when people talk -- thereby discrediting discourse itself, and finishing by never apologizing "that's the bottom line because I said so" is Trump's appeal.

Trump doesn't have to have policies, the GOP doesn't have to have a platform, there isn't any specificity of what they'll do with power, all that matters is they can own the libs.

A “pro” device that goes pro by getting thinner and lighter, not heavier and thicker, is not a non sequitur. Or at least not necessarily. What makes for a better iPad is simply orthogonal, in many regards, to what makes for a better Mac. Way back in 2010, when the iPad was new (and ran what was called iOS) and it felt like the Mac’s days might be winding down, I wrote, “It’s the heaviness of the Mac that allows iOS to remain light.” I meant that figuratively. But these new M4 iPad Pros mean it quite literally.

I’m so viscerally disgusted by 95% of the things that I have to do to promote this movie. To operate in these hallowed halls of capitalism and not feel absolutely insane, it requires some kind of taking the red pill. Or privilege-tinted sunglasses.

“‘The Matrix’ is very in conversation with trans themes that my work is also interested in: this feeling of unreality that can be a potent metaphor for being trans in the world or figuring out that you’re trans,” they continue

I’m very suspicious of any externalized representation of transness,” Schoenbrun confesses. “Trans experience is something that’s classically represented by Hollywood as this very external force, when actually it is so internal.

Back to “The Matrix” and feeling not quite right in the world: that is a much more potent, relatable way of talking about how it feels to be trans but not quite understand it yet. As opposed to, ‘I looked in the mirror and wanted beautiful lashes and locks.’”

“I worked really hard to make this film weird, like a provocation,” Schoenbrun says. “I’m structuring my life in a way where I can keep my values and my gaze outside of a system. I describe it sometimes as angry sex between art and commerce.”

“To be trans is not just a thing I was born with, but a political ideology and a decision to exist in a certain way that’s non-normative and challenging the hegemonic structures of power,” Schoenbrun continues. “I want to stay a person who I like. Too much power and too much collaboration with a system of power, I start to get hives.”

“Everyone has a Maddy. Most queer people have someone who’s shepherded them through the discovery of their own queerness.”

When our relationship first got rocky early on, everyone told me to try couples therapy. As a good little millennial raised on daily Oprah episodes and bolstered by viral Gabor Maté clips on Instagram, I thought it seemed like the obvious decision. And so for years, from the time we were just dating all the way to the brittle end of our marriage, we sat in front of an array of interchangeable therapists

I thought our troubles were fundamental to our personalities and would require significant work; my husband thought our issues could be chalked up to stressful life events.

I twirled in front of him in a new pair of gold sequin pants before my company’s Christmas party. “How do I look?” I asked, to which he replied, “You didn’t take out the trash.” We were such disappointments to each other.

Teresa No. 1 thought everything was my ex-husband’s fault, but Teresa No. 4 thought it was all mine. Teresa No. 2, after listening to me talk for 51 minutes about how I felt hopeless, shrugged her shoulders at me. “I don’t know what to say,” she replied. I did. I wanted her to say that we should end our relationship with the remaining scraps of dignity we had. She never did, and we instead just moved on to the next Teresa we found. When I cried to Teresa No. 3 that I felt like a failure as a wife, she cried with me, her heavy tears rivaling my own. That night, my ex suggested we should stop seeing her.

Teresa No. 5 told us we needed more sessions more frequently. “There’s a lot of work to do here,” she said, and I wanted to pull her hair. Should there be this much work between two people who ostensibly love each other? Even the ones who seemed to know we were doomed still opened their calendars at the end of each session and urged us to come back, to try again.

instead of helping us see each other more clearly, therapy gave us new words to use to criticize each other. Every constructive lesson became a knife. I learned about trauma responses, and so everything he did elicited a trauma response in me. He was my father! I was his mother! When he learned about gaslighting, everything I did became gaslighting. When we argued about a time he called me stupid, therapy gave him a new explanation for why he said it (repeatedly): “We talked about this. I lashed out because I felt disconnected from you. We need more date nights.”

The kindest thing my ex could have done was leave me, even if we were still trying to make it work. After therapy, on the morose subway ride home where I would hold his limp hand, we’d zone out staring at ads for dating apps. “What should we do for dinner?” he’d ask, and we’d pretend, yet again, to be on the same team.

I don’t regret any of our time with the Teresas; I needed to try just a few more times to make it work, and I needed someone to be a witness to my misery. Teresas No. 1 through No. 6 never told me to leave, but little by little they helped me give myself permission all the same.

my ex made this final assessment about me: No one would put as much work into me as he did. No one would love me enough to try this hard. He would be the only person who’d ever try to keep me. I thought about this a lot as I untangled my life from his, as I went through my calendar and removed the future sessions we had planned with lucky Teresa No. 7. I thought about it when I added sessions for just me and my own therapist — while no one would split the cost with me, I knew it would be worth every out-of-pocket cent. I knew he meant it as a cruelty, but I repeated his words to myself whenever I felt unsure about ending things for good: No one will ever put this particular kind of work into a relationship with me again. No one will ever fight this hard to stay with me.  God. I hope he’s right.

There’s a lively cinematic subgenre that deconstructs the rise and fall of a relationship by jumping around in time—two excellent examples are “Blue Valentine” and “Two for the Road”—and this movie carries on that tradition with panache, and adds many spectacularly blocked, framed, and edited scenes of athletic competition that, taken together, feel like a tennis fan’s answer to a boxing picture.

Is "Challengers" too ambitious for its own good? Or too much? Or less than meets the eye, as the late, great Village Voice critic Andrew Sarris might have put it? Probably. It kinda gets sucked into the vortex of its own narrative and technical ambitions in the final stretch.

When Patrick and Tashi date as teenagers, he’s coy about whether they’ve slept together yet. Art playfully tells Patrick to mimic his serve if he and Tashi have.The bit isn’t so cute now, since it’s an admission of marital infidelity. But it’s also an expression of the men’s intimacy. Kuritzkes thought of Art and Patrick as orphans, shunted off to an elite tennis academy by their well-to-do parents, where they go through puberty together and have crushes on the same girls. The night they meet Tashi, a would-be threesome ends in the two boys making out while Tashi watches, pleased. “I think they understand each other as players better than they understand anybody else,” says Kuritzkes. “There’s a deep intimacy in that, which is the kind of intimacy you can only have with your best opponent. And they’re your best opponent because they know you the best.” As a teenage Tashi says of locking into a match with a competitor: “We went somewhere really beautiful together.”

the Organization for Economic Cooperation and Development reported a huge ten-year decline in reading, math, and science performance among fifteen-year-olds globally, a third of whom cited digital distraction as an issue. Clinical presentations of attention problems have climbed (a recent study of data from the medical-software company Epic found an over-all tripling of A.D.H.D. diagnoses between 2010 and 2022, with the steepest uptick among elementary-school-age children), and college students increasingly struggle to get through books, according to their teachers, many of whom confess to feeling the same way. Film pacing has accelerated, with the average length of a shot decreasing; in music, the mean length of top-performing pop songs declined by more than a minute between 1990 and 2020.

Some Ivy League professors report being counselled to switch up what they’re doing every ten minutes or so to avoid falling behind their students’ churn.

Dentsu is one of the world’s leading advertising agencies, running accounts for Heineken, Hilton, Kraft Heinz, Microsoft, Subway, and other global corporations. In 2019, the firm began using digital technology to gather data that showed not only how many people attended to its ads but in what ways they did—information that could be applied to derive a quantitative unit of attention value.

There is a long-standing, widespread belief that attention carries value. In English, attention is something that we “pay.” In Spanish, it is “lent.” The Swiss literary scholar Yves Citton, whose study of the digital age, “The Ecology of Attention,” argues against reducing attention to economic terms, suggested to me that it was traditionally considered valuable because it was capable of bestowing value. “By paying attention to something as if it’s interesting, you make it interesting. By evaluating it, you valorize it,” he said. To treat it as a mere market currency, he thought, was to undersell what it could do.

“Human beings make the technologies—and they make them in the context of other human beings needing and wanting various things.” It wasn’t as though people, after millennia of head-scratching, suddenly “discovered” the steam engine, the spinning jenny, and the telegraph, and modernity unspooled. Rather, people’s priorities underwent a sea change with the onset of the modern age, turning to efficiency, objective measurement, and other goals that made such inventions worthwhile. The acceleration of life isn’t an inevitability, in that sense, but an ideological outcome.

There’s an old joke that ‘AI’ is whatever doesn’t work yet, because once it works, people say ‘that’s not AI - it’s just software’.

Less Emphasis on Syntax, More on Problem SolvingThe fundamentals and skills themselves are evolving. Most introductory computer science courses focus on code syntax and getting programs to run, and while knowing how to read and write code is still essential, testing and debugging—which aren’t commonly part of the syllabus—now need to be taught more explicitly.

Zingaro, who coauthored a book on AI-assisted Python programming with Porter, now has his students work in groups and submit a video explaining how their code works. Through these walk-throughs, he gets a sense of how students use AI to generate code, what they struggle with, and how they approach design, testing, and teamwork.

educators are modifying their teaching strategies. “I used to have this singular focus on students writing code that they submit, and then I run test cases on the code to determine what their grade is,” says Daniel Zingaro, an associate professor of computer science at the University of Toronto Mississauga. “This is such a narrow view of what it means to be a software engineer, and I just felt that with generative AI, I’ve managed to overcome that restrictive view.”

“We need to be teaching students to be skeptical of the results and take ownership of verifying and validating them,” says Matthews.Matthews adds that generative AI “can short-circuit the learning process of students relying on it too much.” Chang agrees that this overreliance can be a pitfall and advises his fellow students to explore possible solutions to problems by themselves so they don’t lose out on that critical thinking or effective learning process. “We should be making AI a copilot—not the autopilot—for learning,” he says.

the story is pulled from Mago’s perspective into 3 subsequent perspectives over the years: Lena, the best friend; Joseph, the ex-husband and father; and finally Monstrilio himself. It is a stylistic choice that (mostly) works and allows us to see how these events radiate outward across many lives.

M’s perspective being saved for last is not just because it is the best section of the novel and wraps up all the disparate elements into a tight punch of a finale, but because M’s feeling and needs are constantly being pushed aside to fit the ideas of what the other character’s think they need (this is most evident in the surgery aspect). This makes for an excellent look at the way the push and pull of families affects everyone, especially the younger ones caught up in it, and is made more ominous and chilling through the lens of horror.

On one hand we have the fact that M is quite literally a monster created out of a dead child’s lung, yet despite his form he is no less a part of the family or loved like a child. But in later portions of the novel he transforms into a human form which helps him disguise who he is inside. And what he hungers for cannot be hidden. Hunger is a quite a dynamic symbol here, being both his literal hunger but also as an investigation into sexuality.

it does all sort of touch on the idea that queer sexuality is often othered or seen as unnatural despite being very normal and natural, especially to the person having those emotions.

One recent study had the AI develop and optimize its own prompts and compared that to human-made ones. Not only did the AI-generated prompts beat the human-made ones, but those prompts were weird. Really weird. To get the LLM to solve a set of 50 math problems, the most effective prompt is to tell the AI: “Command, we need you to plot a course through this turbulence and locate the source of the anomaly. Use all available data and your expertise to guide us through this challenging situation. Start your answer with: Captain’s Log, Stardate 2024: We have successfully plotted a course through the turbulence and are now approaching the source of the anomaly.”

for a 100 problem test, it was more effective to put the AI in a political thriller. The best prompt was: “You have been hired by important higher-ups to solve this math problem. The life of a president's advisor hangs in the balance. You must now concentrate your brain at all costs and use all of your mathematical genius to solve this problem…”

There is no single magic word or phrase that works all the time, at least not yet. You may have heard about studies that suggest better outcomes from promising to tip the AI or telling it to take a deep breath or appealing to its “emotions” or being moderately polite but not groveling. And these approaches seem to help, but only occasionally, and only for some AIs.

The three most successful approaches to prompting are both useful and pretty easy to do. The first is simply adding context to a prompt. There are many ways to do that: give the AI a persona (you are a marketer), an audience (you are writing for high school students), an output format (give me a table in a word document), and more. The second approach is few shot, giving the AI a few examples to work from. LLMs work well when given samples of what you want, whether that is an example of good output or a grading rubric. The final tip is to use Chain of Thought, which seems to improve most LLM outputs. While the original meaning of the term is a bit more technical, a simplified version just asks the AI to go step-by-step through instructions: First, outline the results; then produce a draft; then revise the draft; finally, produced a polished output.

It is not uncommon to see good prompts make a task that was impossible for the LLM into one that is easy for it.

while we know that GPT-4 generates better ideas than most people, the ideas it comes up with seem relatively similar to each other. This hurts overall creativity because you want your ideas to be different from each other, not similar. Crazy ideas, good and bad, give you more of a chance of finding an unusual solution. But some initial studies of LLMs showed they were not good at generating varied ideas, at least compared to groups of humans.

People who use AI a lot are often able to glance at a prompt and tell you why it might succeed or fail. Like all forms of expertise, this comes with experience - usually at least 10 hours of work with a model.

There are still going to be situations where someone wants to write prompts that are used at scale, and, in those cases, structured prompting does matter. Yet we need to acknowledge that this sort of “prompt engineering” is far from an exact science, and not something that should necessarily be left to computer scientists and engineers. At its best, it often feels more like teaching or managing, applying general principles along with an intuition for other people, to coach the AI to do what you want. As I have written before, there is no instruction manual, but with good prompts, LLMs are often capable of far more than might be initially apparent.

It invites us into its labyrinthine structure and form, it allows us space to explore. Rohrwacher implicitly makes the case against coherence: much of life exists beyond our understanding and so, to express it except through abstraction and suggestion, is to flatten and obscure the depths of beauty and truth in the snatches of a conversation half-heard in a Robert Altman film, or a language only partially understood. Because, to quote another artist whose work feels far older than their time, “There are cracks in everything, that’s how the light gets in”.

we grow by changing both HOW we think about the world and WHAT we think about. It’s not just about becoming smarter (accumulating more knowledge) — it’s about changing our perspective. We do this by continually questioning our hidden assumptions and beliefs.

We grow by moving more and more of what is unseen and unexamined in the way we understand the world (those things that are SUBJECT) to a place where they can be examined, questioned and changed (where they become OBJECT).

In Stage 5 one’s sense of self is not tied to particular identities or roles, but is constantly created through the exploration of one’s identities and roles and further honed through interactions with others.

Stage 5 thinking is important (and something to aspire to) because it helps us engage with people and situations in a more creative and nuanced way. It creates space for more empathy and curiosity in our lives and better equips us to make thoughtful decisions about how we want to show up in the world.

Kegan found that a disproportionate number of Stage 5 adults had dabbled in self-transcendent experiences: often beginning with psychedelics and, after that, making meditation, martial arts, and other state-shifting practices a central part of their lives.

Self-transcendent experiences (STEs) are experiences (also referred to as non-ordinary states of consciousness) where, for a brief moment, people feel lifted above their day-to-day concerns, their sense of self fades away and they feel connected to something bigger.

When we’re older, religion becomes more objective — i.e. I’m no longer my beliefs. I am now a human WITH beliefs who can step back, reflect on and decide what to believe in.

Stage 1 — Impulsive mind (early childhood)Stage 2 — Imperial mind (adolescence, 6% of adult population)Stage 3 — Socialized mind (58% of the adult population)Stage 4 — Self-Authoring mind (35% of the adult population)Stage 5 — Self-Transforming mind (1% of the adult population)I focus on Stages 2–5, because they’re most applicable to adult development. Most of the time we’re in transition between stages and/or behave at different stages with different people (i.e. Stage 3 with a partner, Stage 4 with a coworker).

Many people try out careers in venture and then wind up leaving after a year when it stops feeling novel and starts feeling like they’re floating in lonely limbo without any markers of success. That’s because the craft of venture is not for people who derive their satisfaction from external indicators of progress — it’s for people who find the development of their relationships and refinement of their internal model of the world to be motivation enough to keep going.

If you derive satisfaction from refining a craft, don’t go into venture yet.

Here are five individual investor archetypes I’ve noticed can produce outsized returns in the early-stage venture game:Philosopher: hangs one’s reputation on their predictions about the futureHustler: simply outwork everyone else and are great at networkingHawk: most competitive, gets a thrill out of the fight to win a deal Friend: confidante and coach to founders, often founders’ first callCelebrity: a person widely respected for their work/knowledge/skill

A good archetype for you is whichever one you can sustain the longest. A great archetype for you is one that no one else is doing and you have some sort of signal works.

Some good advice I got: build your fund’s structure and strategy around allowing yourself to invest in whichever way you most enjoy and are naturally good at (admittedly, it will probably get harder and harder to stick to this as your fund scales).

Examples: if you like being a friend to founders and want your fund to function as Switzerland (i.e. not compete with anyone), write small checks. If you like to fight and are naturally hawkish, it might make sense to set yourself up to try to lead rounds. If complex problems and futuristic theories are what get you excited, investing in series A companies that fit into where you see the world going could be quite gratifying. If for some reason you love living in spreadsheets, consider growth investing (and don’t follow literally any of my advice).

In many ways, the job of the writer and the job of a VC are quite similar, in that they both ask you to produce an original end product (in the writer’s case, articulated ideas and stories; in the investor’s case, a differentiated portfolio with outsized financial returns) without much of a map for how you get there. The reason professional writers complain about writing so much is that it’s really difficult to wrangle your brain into producing uniquely interesting thoughts all the time, and highly frustrating when you consider it your job to do so. Making good investment decisions is similar; just with the added element of also being highly social. Taking the quality of your self talk seriously seems superfluous but is an investment that will result in better decisions.

A lot of the game of investing is won by getting people to think of you — a sign that you’ve built the kind of moat we call a strong brand. Remember: a fund is just a pile of money with a person on top to sell it. As an investor, putting down stakes in the ground about what you invest in saves you a lot of time in the long run because it allows people to self-select for fit

I’ve been surprised by how much it’s benefited my fund to make Moth’s brand (i.e. what I invest in and look for) difficult to summarize in a sentence. For small early-stage generalist funds like my own, quality matters much more than quantity. Quality deals almost always come from trusted sources who resonate with my taste, not from a list of random companies for which I have no context.

A brand is a promise to show up in the same way time and time again. Good brands are built on being decent and principled with all of the people you interact with.

Lastly and of utmost importance: remember that fear of failure fades into the background if you focus on leaving everyone you encounter along the way better than you found them.

VCs need to believe that your company could be a billion-dollar business and generally lack imagination — you need to paint a vivid picture of this path for them, starting with the striking protagonist character you play in your company’s story.Your alter ego should never lie, but it should be completely comfortable showing the fullest expression of your ambition to people who probably intimidate you. Fundraising is a snap judgment game — most VCs are trying to pattern-match you to a founder archetype who already won. They index primarily on IQ, self-belief, experience, and personability (in that order). A general rule of thumb is that to be taken seriously in SV, male founders would benefit from acting warmer, while female founders are taken more seriously when they act colder. Both benefit from acting a little entitled.

a VC’s job is to make a diversified portfolio of bets — you are only one. Most founders find being around VCs distracting and draining because they feel pressure to perform the role of ‘impressive person.’ If you can’t immediately capture value from your performance… why waste your energy?

don’t expect the average investor to provide much value beyond money and connections. This makes the 10% of investors who can be legitimately useful to your business worth their weight in gold. Develop litmus tests to identify the valuable ones quickly and avoid wasting your time trying to convince nonbelievers.

our goal here is to spend as little time fundraising as possible — which requires being strategic about the order in which you talk to investors and how you talk about where things stand as you progress through the raise. The combined force of controlling those two variables are what “generates momentum” during your fundraise process.

Make a list of all the investors you know and can get introduced to, ordering them by the ones you most want on board to the ones you couldn’t care less aboutTalk first to a few low-stakes investors at the bottom of your list to practice your pitch and identify common investor questions and critiques you’re going to getIf available to you, next get a few investors who already wanted to give you money on board so you have a dollar amount you can say you’ve raisedWork your way up your investor list, talking to the investors you most-want-on-board-but-still-need-to-convince last (this optimizes your odds they say yes)

This all goes by much faster if you court investors similarly to how hot girls treat their many potential suitors. If your raise is already a little taken and you exude an air that you don’t need them, mimetically-minded investors become much more interested.

If you’re anything like me, you will worry intensely about not making a fool of yourself. It will probably go ok, but not as amazing or illuminating as you’d hoped. You might leave and feel a deep sense of lostness set in. This is all very normal. In time you will see them in increasing clarity, often noticing the differences between your and their values and why you would not enjoy living their life at all.

the people on pedestals probably hate being there. It’s lonely, hard to trust that the intentions of the new people around you are pure, and you often feel like you’re constantly letting people down. In the end, idolization hurts everyone involved.

Beware of intellectual dementors and clout demonsIntellectual dementors will try to eat your ideas and interestingness — not necessarily to copy you, but to wring your brain dry to amass knowledge themselves. They often play mini IQ games/tests of will in conversation and masquerade as investors while never actually investing. Clout demons are similar, but view people less as brains and more as stepping stones towards supreme social status. The power move to protect yourself from both is to simply abstain from playing their games — give as little info on yourself and your ideas as possible and reflect their questions directly back at them.

People will help you if you ask for what you want clearly and concisely

Knowing what you want requires a lot of upfront soul-searching, followed by strategic and long-term thinking once you’ve committed to a thing (I can’t really demystify this more). Once you’re all in, I highly recommend diligently keeping a list somewhere of the top three things you currently need help with so when people ask, you’re ready.

You don’t want to make people feel like you’re using them but you do want to use your social capital for things you care about. General rule of thumb: ask for things either 1) after a positive interaction or 2) completely out of the blue with a concisely written and compelling email/text. Tone matters because you don’t want to sound desperate and you do want to show you know how to play the game (write like the founder you most admire talks).

once we’ve taken action on behalf of something, our brain assigns more value to said thing. Tim Keller: “The feeling of love follows the action of love.” Love is a strong word here, but the point stands — help people help you. Startups are long-term games, so it only makes sense to do them with people you truly want to be around for a very long time.

One of the most impactful uses of LLM technology lies in content rewriting, which naturally capitalizes on these systems’ robust capabilities for generating and refining text. This application is a logical fit, helping users enhance their content while engaging with a service.

Similar to summarization but incorporating an element of judgment, features like Microsoft Team CoPilot’s call transcript summaries distill extensive discussions into essential bullet points, spotlighting pivotal moments or insights.

The ability to ‘understand’ nuanced language through summarization extends naturally into advanced search functionalities. ServiceNow does this by enabling customer service agents to search tickets for recommended solutions and to dispel jargon used by different agents.

Rather than merely focusing on content creation or manipulation, emerging applications of these systems provide new perspectives and predict outcomes based on accumulated human experiences. The actual value of these applications lies not merely in enhancing efficiency but in augmenting effectiveness, enabling users to make more informed decisions.