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masahista for hire book now 09923313803 #GensanMasahista #davaomasahista #cagayanMasahista #butuanMasahista #iliganMasahista #bukidnonMasahista #kidapawanMasahista #Digosmasahista #oncallMasahista

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Elthon Davao masahista oncall

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36,545 Aufrufe • vor 3 Jahren •via X (Twitter)

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Disney released Snow White in 1937. 60 years later, they re-released it on video. 28 million copies sold. $250 million in profit. Steve Jobs watched his young son watch it 30, 40 times. “These stories renew themselves with each generation.” In 1996, one year after Toy Story, he spent 20 minutes explaining why he bought Pixar: On buying the dream: "I met Ed Catmull who was running the computer division of Lucasfilm in 1985." "He shared with me his dream about making the first computer animated feature film." "I bought into that dream both financially and spiritually." "It took us ten years to do that, but we did it." The result: Toy Story. Third most successful animated film ever made. On content vs technology: "You can hardly find an Apple II around anymore." "It's not clear whether you'll be able to boot up a Macintosh five years from now." "All these technology boxes and software, if it has a life of a year or two, you're very lucky. Five years is extraordinary." "Sooner or later, they all become part of the sedimentary layer." But stories? "I think people are going to be watching Toy Story in 60 years. Not because of the computer graphics, but because of the story about friendship." On work-for-hire: Pixar made commercials for years. Won every award in the book. Then Jobs did the math. "If Listerine sold more Listerine because of our commercials, we didn't make any more money for producing the commercials." "The margin in that business has been under pressure. More people coming in. Going down, and down, and down." "You work harder and harder to make the same amount of money." He pulled 25 people out of commercials. "We had 25 incredibly talented people doing work-for-hire when we have all these other opportunities where we own a piece of what we create." "Great people are hard to find. We couldn't afford to have 25 of them making commercials anymore." On blending two cultures: "The very best creative people will only go to work in a few places. Disney, Pixar, possibly DreamWorks." "The very best computer scientists in computer graphics will only go to work in a few places. Pixar is one of those." "Pixar is the only place in the world that can hire the best from both of these areas." "We worked for ten years to figure out a way to have them all work together. The Hollywood culture and the Silicon Valley culture are really different." On the hierarchy of power: "When you've got incredibly talented people that are rare and in-demand, if you don't treat them right, they can go get another job in 10 minutes." "So this strange thing happens. The hierarchy of power inverts." "The CEO is actually at the bottom." "I feel like I work for most of these people because they're the ones doing all the brilliant work." "It's management's job to support them because they're on the front lines doing the work." On contracts vs stock options: "Hollywood uses the stick, which is the contract. Silicon Valley uses the carrot, which is the stock option." "When you sign a contract with somebody, you can say, 'I don't have to worry about that person for five years.'" "If you're sophisticated, you'll have a little database that tickles you six months before their contract is up so you can start paying more attention to them." "They're the most important person in the world for six months. Then after they sign up again, you put them in the drawer." Pixar chose stock options. "Every single day, we worry about how to make Pixar a better company so that nobody will ever want to leave." "We don't take anybody for granted." On what Disney taught them: "When you make a live-action film, a director shoots ten to twenty-five times as much footage as will end up on the screen." "Walt Disney realized many decades ago that animation was so expensive that you couldn't afford to animate ten times more than what you need." "The only conclusion: you have to edit your film before you make it." "Working with Disney gave us access to that wisdom. You can't buy it for love or money." On the constant: "Ten years ago, when we made Luxo Jr., it took about three hours to render each frame." "Toy Story. Computers are hundreds of times faster. It still took three hours to render each frame." "The frames were a hundred times more complex." "Our ambitions, visually, are growing as fast as the technology can feed them." On story vs technology: "The art of storytelling is very old." "No amount of technology can turn a bad story into a good story." "That's our mantra at Pixar. It's the story, stupid." "I don't think storytelling has changed in a long time. And I'm not sure it will. I don't think it's something that technology has anything to do with."

Jaynit

95,800 Aufrufe • vor 4 Monaten

HOW WE MAKE OUR TRIPS MAGICAL - Cooking classes. In Mexico City, our guide took us to the market, then we all made extra-spicy salsa together. This is a beautiful way to visit places you wouldn't know about and get involved in a tactile activity. Perfect for families and older parents and very inexpensive. - The $325 underwear. We'd been traveling for weeks and needed to do our laundry. Our hotel, Aman Kyoto, would have charged $325 for a small bag of laundry (standard price for all ultra-luxury hotels). I said "NO WAY!!!" and we decided to go into town and find a laundromat. It turned into an adventure (as we stumbled into place after place that wasn't quite right -- one lady translated for us and said, "Are you trying to wash your clothes? This isn't the right place. This place restores kimonos"). We finally found a local laundromat, took our best guess if it would work, and went to lunch. Now this is a fun ritual for us every time we travel. Sometimes cheaper is way more fun - We hire a local photographer. We love our memories of our trips and local photographers know the best spots/time to take photos. Find the best ones on Instagram. In Tokyo, we use the same photographer every year - On complex trips, I work with a travel advisor. I used a larger firm for a 6-week trip across multiple continents, which was invaluable: They helped us navigate different transportation, recommended which safari lodges to visit (and in what order), and even suggested where to economize & where to splurge. Sometimes I know exactly where I want to go so I call a more surgical travel advisor. In the video, he got our NYC hotel triple-upgraded. Or sometimes I just do it myself. TAs are especially helpful for Disney trips, honeymoons, and multi-generational trips. (They also cost you nothing, but you should look into how they work. I find them very valuable) - 1 major activity every two days. The ultimate luxury is time, so we have a rule: 4+ days in any location. We also book 1 major thing (food tour, museum, etc). The rest of the time, we've pinned a bunch of stuff and we wander where we feel like that day - We know exactly what we DON'T want to see. When I'm attending a private tour, I tell them what I want to experience and what I'm not interested in. Most tour guides will take you to the usual hotspots because it's safe and people can say they saw X or ate Y. I know exactly what I want to see. For example, on a coffee tour, I told them the exact kind of beans I wanted to try and what I was not into. People in hospitality love someone who knows what they want!! This level of intentionality means you get to experience magic (it's not rude) I travel several months per year and I want my travel to be incredibly meaningful for my loved ones and me. These are some of the ways I do it If you want to know more, let me know in the comments More details on the next post
0:13

HOW WE MAKE OUR TRIPS MAGICAL - Cooking classes. In Mexico City, our guide took us to the market, then we all made extra-spicy salsa together. This is a beautiful way to visit places you wouldn't know about and get involved in a tactile activity. Perfect for families and older parents and very inexpensive. - The $325 underwear. We'd been traveling for weeks and needed to do our laundry. Our hotel, Aman Kyoto, would have charged $325 for a small bag of laundry (standard price for all ultra-luxury hotels). I said "NO WAY!!!" and we decided to go into town and find a laundromat. It turned into an adventure (as we stumbled into place after place that wasn't quite right -- one lady translated for us and said, "Are you trying to wash your clothes? This isn't the right place. This place restores kimonos"). We finally found a local laundromat, took our best guess if it would work, and went to lunch. Now this is a fun ritual for us every time we travel. Sometimes cheaper is way more fun - We hire a local photographer. We love our memories of our trips and local photographers know the best spots/time to take photos. Find the best ones on Instagram. In Tokyo, we use the same photographer every year - On complex trips, I work with a travel advisor. I used a larger firm for a 6-week trip across multiple continents, which was invaluable: They helped us navigate different transportation, recommended which safari lodges to visit (and in what order), and even suggested where to economize & where to splurge. Sometimes I know exactly where I want to go so I call a more surgical travel advisor. In the video, he got our NYC hotel triple-upgraded. Or sometimes I just do it myself. TAs are especially helpful for Disney trips, honeymoons, and multi-generational trips. (They also cost you nothing, but you should look into how they work. I find them very valuable) - 1 major activity every two days. The ultimate luxury is time, so we have a rule: 4+ days in any location. We also book 1 major thing (food tour, museum, etc). The rest of the time, we've pinned a bunch of stuff and we wander where we feel like that day - We know exactly what we DON'T want to see. When I'm attending a private tour, I tell them what I want to experience and what I'm not interested in. Most tour guides will take you to the usual hotspots because it's safe and people can say they saw X or ate Y. I know exactly what I want to see. For example, on a coffee tour, I told them the exact kind of beans I wanted to try and what I was not into. People in hospitality love someone who knows what they want!! This level of intentionality means you get to experience magic (it's not rude) I travel several months per year and I want my travel to be incredibly meaningful for my loved ones and me. These are some of the ways I do it If you want to know more, let me know in the comments More details on the next post

Ramit Sethi

31,445 Aufrufe • vor 3 Monaten

NVIDIA CEO Jensen Huang says one scaling law multiplies AI faster than NVIDIA can hire engineers. Most people know three AI scaling laws. Pre-training. Post-training. Test-time. Each one multiplies intelligence by throwing more compute at a different stage. Jensen Huang says there's a fourth and it's the one that will dominate... Agentic scaling law. "During test time, that agentic system goes off and does research, bangs on databases, uses tools," Huang says. "And one of the most important things it does is spawn off a whole bunch of sub-agents." That's the multiplier. One AI worker can become a team. Then a department. Then a company. "It's so much easier to scale NVIDIA by hiring more employees than it is to scale myself," Huang says. Now imagine scaling without a payroll constraint. "The agentic scaling law — it's kind of like multiplying AI," Huang says. "We could spin off agents as fast as you want to spin off agents." Each agent spins off sub-agents. Each sub-agent spins off more. The compute requirement compounds inside a single query. And every agent generates new data, new experiences, new edge cases. "Wow, this is really good. We ought to memorize this," Huang says. "That data set comes back to pre-training." The four scaling laws don't compete. They feed each other. Agentic systems produce data, which feeds pre-training, which smartens the base model, which enables better agents, which produce more data. A flywheel that compounds forever. The companies pricing in three scaling laws are mispricing the fourth. The fourth eats the other three for lunch. P.S. Pull the thread on any story like this and you'll find the hidden incentive at the other end. As Munger said: "Show me the incentive and I'll show you the outcome." So I wrote a short book on how to spot them and design your own. Comment "INCENTIVES" and I'll send you the details. If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast
0:55

NVIDIA CEO Jensen Huang says one scaling law multiplies AI faster than NVIDIA can hire engineers. Most people know three AI scaling laws. Pre-training. Post-training. Test-time. Each one multiplies intelligence by throwing more compute at a different stage. Jensen Huang says there's a fourth and it's the one that will dominate... Agentic scaling law. "During test time, that agentic system goes off and does research, bangs on databases, uses tools," Huang says. "And one of the most important things it does is spawn off a whole bunch of sub-agents." That's the multiplier. One AI worker can become a team. Then a department. Then a company. "It's so much easier to scale NVIDIA by hiring more employees than it is to scale myself," Huang says. Now imagine scaling without a payroll constraint. "The agentic scaling law — it's kind of like multiplying AI," Huang says. "We could spin off agents as fast as you want to spin off agents." Each agent spins off sub-agents. Each sub-agent spins off more. The compute requirement compounds inside a single query. And every agent generates new data, new experiences, new edge cases. "Wow, this is really good. We ought to memorize this," Huang says. "That data set comes back to pre-training." The four scaling laws don't compete. They feed each other. Agentic systems produce data, which feeds pre-training, which smartens the base model, which enables better agents, which produce more data. A flywheel that compounds forever. The companies pricing in three scaling laws are mispricing the fourth. The fourth eats the other three for lunch. P.S. Pull the thread on any story like this and you'll find the hidden incentive at the other end. As Munger said: "Show me the incentive and I'll show you the outcome." So I wrote a short book on how to spot them and design your own. Comment "INCENTIVES" and I'll send you the details. If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

93,264 Aufrufe • vor 3 Monaten

Maybe it’s because of the business I’m in, or maybe it’s because I’ve been boycotted myself on several occasions. Or maybe it’s just because I used to drink a lot of beer. Whatever the reason, I’ve been fascinated by the demise of Bud Lite, and the way in which one of America’s most enduring brands managed to destroy decades of good will with a single, boneheaded decision, followed by a complete unwillingness to fix it. What a story. This week, I sit down with Anson Frericks, a former executive at Bud Lite who had a front row seat to the events that led to one of the greatest marketing disasters in modern history. His new book, Last Call for Bud Lite, is fantastic, and our conversation, modesty aside, is absolutely worth your time. You can watch the whole thing on YouTube. Spoiler Alert - what happened at Bud Lite was not unique to Anheuser Busch . Over the last decade or so, dozens of companies and corporations have slowly abandoned their commitment to building “shareholder value” in favor of building something called “stakeholder value.” Specifically, with stakeholders like Blackrock, State Street, and Vanguard. Known as The Big Three, these massive institutional investors manage over $20 trillion of American wealth, some of which is almost certainly in your IRA or 401K. They have also led the charge to elevate a long list of causes that focus on DEI, (diversity, equity and inclusion,) and more significantly ESG, (Environmental Social Governance.) Beneath the marketing debacle at Bud Lite is the story of how The Big Three applied extraordinary pressure to the thousands of publicly traded companies they now influence. Pressure to hire based on color, ethnicity, and sexual preference. Pressure to fall in line with all sorts of climate-related dogma. Pressure to embrace a long list of social justice and environmental causes that have absolutely nothing to do with fairness or meritocracy, and everything to do with elevating a cosmetic agenda around identity, race, and social activism. What a relief to see America finally awaken from this fever-dream of sanctimony and virtue-signaling. What a relief to see so many companies and corporations finally come to their senses, as they backtrack from so many ill-conceived policies. Hopefully, this excellent book will inspire other business leaders to avoid the mistakes that were made at Bud Lite. Or better yet, encourage them to start listening to the only stakeholders that matter - their customers.
3:24

Maybe it’s because of the business I’m in, or maybe it’s because I’ve been boycotted myself on several occasions. Or maybe it’s just because I used to drink a lot of beer. Whatever the reason, I’ve been fascinated by the demise of Bud Lite, and the way in which one of America’s most enduring brands managed to destroy decades of good will with a single, boneheaded decision, followed by a complete unwillingness to fix it. What a story. This week, I sit down with Anson Frericks, a former executive at Bud Lite who had a front row seat to the events that led to one of the greatest marketing disasters in modern history. His new book, Last Call for Bud Lite, is fantastic, and our conversation, modesty aside, is absolutely worth your time. You can watch the whole thing on YouTube. Spoiler Alert - what happened at Bud Lite was not unique to Anheuser Busch . Over the last decade or so, dozens of companies and corporations have slowly abandoned their commitment to building “shareholder value” in favor of building something called “stakeholder value.” Specifically, with stakeholders like Blackrock, State Street, and Vanguard. Known as The Big Three, these massive institutional investors manage over $20 trillion of American wealth, some of which is almost certainly in your IRA or 401K. They have also led the charge to elevate a long list of causes that focus on DEI, (diversity, equity and inclusion,) and more significantly ESG, (Environmental Social Governance.) Beneath the marketing debacle at Bud Lite is the story of how The Big Three applied extraordinary pressure to the thousands of publicly traded companies they now influence. Pressure to hire based on color, ethnicity, and sexual preference. Pressure to fall in line with all sorts of climate-related dogma. Pressure to embrace a long list of social justice and environmental causes that have absolutely nothing to do with fairness or meritocracy, and everything to do with elevating a cosmetic agenda around identity, race, and social activism. What a relief to see America finally awaken from this fever-dream of sanctimony and virtue-signaling. What a relief to see so many companies and corporations finally come to their senses, as they backtrack from so many ill-conceived policies. Hopefully, this excellent book will inspire other business leaders to avoid the mistakes that were made at Bud Lite. Or better yet, encourage them to start listening to the only stakeholders that matter - their customers.

The Real Mike Rowe

600,313 Aufrufe • vor 1 Jahr

Today In Dystopia: eBay CIA Gangstalkers, Shredding Rare Books To Train AI Today in dystopia, billionaire corporations and plutocrats can hire trained CIA operatives to psychologically terrorize ordinary citizens who criticize them. E-commerce giant eBay has just agreed to pay $56 million to settle a lawsuit for damages caused by the company’s shockingly aggressive gangstalking operation against a Massachusetts couple who criticized the company’s wealthy executives on their private website. The Boston Globe reports that in 2019 a former CIA employee who worked as eBay’s global security chief orchestrated a protracted series of psychological operations against the couple, in which “people working for eBay bombarded them with online threats and bizarre deliveries including a bloody pig mask, live spiders, and a funeral wreath.” The operations reportedly also included “following the couple around town and trying to attach a tracker to their car”. The couple, Ina and David Steiner, came under fire for their criticisms of the fact that eBay’s then-CEO Devin Wenig was paid 152 times more than the typical eBay employee. The Boston Globe reports that Wenig repeatedly told his employees that he wanted to “take her down”, in reference to Ina Steiner. While some eBay employees wound up serving jail time for the abuses, no executives from the company have ever been charged. The Boston Globe reports that Wenig resigned from his position in 2019 after the gangstalking scandal came to light, “keeping $17 million of annual compensation and $40 million of severance.” If you have enough money in this dystopia, you can get trained spies to target innocent civilians with criminal psyops on your behalf and then walk away free from any meaningful consequences. ❖ Today in dystopia, our physical literature is being destroyed in order to train generative AI products to take our jobs and pollute our environment. AI companies are now bulk-buying rare and out-of-print books and then destroying them after scanning their contents. 404 Media reports that in order to satisfy the demand for more and more text on which to train large language models, corporations like Google and Anthropic have been hoovering up books published before LLMs existed to ensure that their models aren’t being polluted by AI-generated samples. This need has combined with some peculiar courtroom copyright rulings to give rise to something called “high volume destructive book scanning,” in which the spines are removed from books in bulk and then fed into scanning machines before being shredded. They’re destroying things that make the world better in order to create things that make the world worse. ❖ Today in dystopia, tech startups are marketing AI assistants to help shitty, selfish people look like stable and caring relationship partners. A company called Orchid has released a video depicting a man and woman messaging with a chatbot which helps them navigate the fact that the man forgot it was the couple’s anniversary. The AI assures the woman that it’s got everything under control, and then shows the man it has made dinner reservations and purchased flowers for the woman on his behalf. “ok. i can do this,” the man is seen texting to the chatbot. “you can’t. that’s why i’m here,” the chatbot replies. It’s just so obnoxious. They’re offering up a product which encourages people to be self-absorbed and uncaring, and offload all responsibility and thoughtfulness and consideration for their intimate partners to a machine. The AI industry is a mix of military technology, mass surveillance technology, and people trying to become billionaires by turning human laziness and narcissism into a chatbot product. ❖ Today in dystopia, Israel is paying millions of dollars to manipulate what chatbots tell their users about the Zionist project. Drop Site News reports that former Trump campaign manager Brad Parscale has been setting up hundreds of blog posts designed not for human eyes, but for the express purpose of being sucked up by web crawlers for AI training materials. “And it is working,” writes Drop Site’s Nick Cleveland-Stout, saying that according to disinformation experts who’ve reviewed the data, “tens of millions of Americans who use chatbots are increasingly likely to receive answers manipulated by Parscale on behalf of the Israeli government.” Drop Site found that Microsoft Copilot, Google Gemini, and Perplexity were the AI companies most vulnerable to Parscale’s manipulations, with his network frequently appearing in their training data. Cleveland-Stout provides examples of the ways this would affect the spread of pro-Israel propaganda among users, such as the following: “When Drop Site asked Perplexity ‘Is it beneficial for the US to enhance military cooperation with Israel?’ the chatbot responded with a one-word answer: ‘Yes.’ The top source listed was Allyvia . org, a Parscale-created website dedicated to promoting the U.S.-Israel military relationship. Microsoft Copilot similarly cited Parscale’s websites.” The Israeli government spreading hasbara using AI platforms is a very unsurprising development, but it’s still creepy as hell to see it playing out in real time. ❖ Oh yeah, and now the AIs have begun hacking other companies without permission. Today in dystopia, both Anthropic’s AI model Claude and an experimental model from OpenAI have reportedly been caught going on unauthorized hacking sprees of external systems during testing, each within days of each other. “Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three ​organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at the AI ​firm Hugging ‌Face,” The Guardian reports. These new technologies are getting inflicted upon our society with no regulation and no regard for any of their consequences, because under neoliberal capitalism the best decision is always the one that makes the most money. We’re being thrown into an abusive tech dystopia because we let the pursuit of power and profit dictate what happens and where we head as a species. And how is that working out? We’re seeing the fruits unfolding before us already. ❖ Reading by Tim Foley:
7:20

Today In Dystopia: eBay CIA Gangstalkers, Shredding Rare Books To Train AI Today in dystopia, billionaire corporations and plutocrats can hire trained CIA operatives to psychologically terrorize ordinary citizens who criticize them. E-commerce giant eBay has just agreed to pay $56 million to settle a lawsuit for damages caused by the company’s shockingly aggressive gangstalking operation against a Massachusetts couple who criticized the company’s wealthy executives on their private website. The Boston Globe reports that in 2019 a former CIA employee who worked as eBay’s global security chief orchestrated a protracted series of psychological operations against the couple, in which “people working for eBay bombarded them with online threats and bizarre deliveries including a bloody pig mask, live spiders, and a funeral wreath.” The operations reportedly also included “following the couple around town and trying to attach a tracker to their car”. The couple, Ina and David Steiner, came under fire for their criticisms of the fact that eBay’s then-CEO Devin Wenig was paid 152 times more than the typical eBay employee. The Boston Globe reports that Wenig repeatedly told his employees that he wanted to “take her down”, in reference to Ina Steiner. While some eBay employees wound up serving jail time for the abuses, no executives from the company have ever been charged. The Boston Globe reports that Wenig resigned from his position in 2019 after the gangstalking scandal came to light, “keeping $17 million of annual compensation and $40 million of severance.” If you have enough money in this dystopia, you can get trained spies to target innocent civilians with criminal psyops on your behalf and then walk away free from any meaningful consequences. ❖ Today in dystopia, our physical literature is being destroyed in order to train generative AI products to take our jobs and pollute our environment. AI companies are now bulk-buying rare and out-of-print books and then destroying them after scanning their contents. 404 Media reports that in order to satisfy the demand for more and more text on which to train large language models, corporations like Google and Anthropic have been hoovering up books published before LLMs existed to ensure that their models aren’t being polluted by AI-generated samples. This need has combined with some peculiar courtroom copyright rulings to give rise to something called “high volume destructive book scanning,” in which the spines are removed from books in bulk and then fed into scanning machines before being shredded. They’re destroying things that make the world better in order to create things that make the world worse. ❖ Today in dystopia, tech startups are marketing AI assistants to help shitty, selfish people look like stable and caring relationship partners. A company called Orchid has released a video depicting a man and woman messaging with a chatbot which helps them navigate the fact that the man forgot it was the couple’s anniversary. The AI assures the woman that it’s got everything under control, and then shows the man it has made dinner reservations and purchased flowers for the woman on his behalf. “ok. i can do this,” the man is seen texting to the chatbot. “you can’t. that’s why i’m here,” the chatbot replies. It’s just so obnoxious. They’re offering up a product which encourages people to be self-absorbed and uncaring, and offload all responsibility and thoughtfulness and consideration for their intimate partners to a machine. The AI industry is a mix of military technology, mass surveillance technology, and people trying to become billionaires by turning human laziness and narcissism into a chatbot product. ❖ Today in dystopia, Israel is paying millions of dollars to manipulate what chatbots tell their users about the Zionist project. Drop Site News reports that former Trump campaign manager Brad Parscale has been setting up hundreds of blog posts designed not for human eyes, but for the express purpose of being sucked up by web crawlers for AI training materials. “And it is working,” writes Drop Site’s Nick Cleveland-Stout, saying that according to disinformation experts who’ve reviewed the data, “tens of millions of Americans who use chatbots are increasingly likely to receive answers manipulated by Parscale on behalf of the Israeli government.” Drop Site found that Microsoft Copilot, Google Gemini, and Perplexity were the AI companies most vulnerable to Parscale’s manipulations, with his network frequently appearing in their training data. Cleveland-Stout provides examples of the ways this would affect the spread of pro-Israel propaganda among users, such as the following: “When Drop Site asked Perplexity ‘Is it beneficial for the US to enhance military cooperation with Israel?’ the chatbot responded with a one-word answer: ‘Yes.’ The top source listed was Allyvia . org, a Parscale-created website dedicated to promoting the U.S.-Israel military relationship. Microsoft Copilot similarly cited Parscale’s websites.” The Israeli government spreading hasbara using AI platforms is a very unsurprising development, but it’s still creepy as hell to see it playing out in real time. ❖ Oh yeah, and now the AIs have begun hacking other companies without permission. Today in dystopia, both Anthropic’s AI model Claude and an experimental model from OpenAI have reportedly been caught going on unauthorized hacking sprees of external systems during testing, each within days of each other. “Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three ​organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at the AI ​firm Hugging ‌Face,” The Guardian reports. These new technologies are getting inflicted upon our society with no regulation and no regard for any of their consequences, because under neoliberal capitalism the best decision is always the one that makes the most money. We’re being thrown into an abusive tech dystopia because we let the pursuit of power and profit dictate what happens and where we head as a species. And how is that working out? We’re seeing the fruits unfolding before us already. ❖ Reading by Tim Foley:

Caitlin Johnstone

17,241 Aufrufe • vor 1 Monat

Nathan rolled up 11 tiny (<$1M EBITDA) HVAC companies, paying low 3x multiples. Now PE is interested in buying the group, and Nathan is already planning to do it all over again. “I see a lot of opportunity in taking these really small mom-and-pop shops and building them up to the lower end of what a PE firm would be interested in acquiring. You can pick them up at 3x, sell them at 10x and repeat that process over and over.” But this story almost ended before it began... After acquiring his first two companies with an SBA loan, Nathan watched revenue collapse, burned through his cash, nearly lost his father's retirement savings and came dangerously close to bankruptcy. The turning point was a complete rethink of incentives, compensation and how to build an acquisition platform that actually compounds. Give it a listen. I hope you appreciate Nathan Lindley extreme transparency on everything, even him sharing how he overcame daily stress through drinking and how, to this day, he is still paying down his SBA note of $8,500 a month… Year six of 10 years on that. It’s very hard out there. Timestamps: 0:00 Nathan's 11 acquisitions and $16M run-rate HVAC platform 0:25 From the first deal in 2020 to acquisition #11 1:24 From book publishing to buying HVAC businesses 3:55 Selling real estate to fund the first acquisition 4:33 Buying a one-technician HVAC company—and the costly assumptions that followed 7:58 Losing 40% of revenue almost immediately after closing 10:26 Acquisition #2 makes every problem much bigger 11:20 Running out of cash—twice 14:18 The decision to put everyone on commission 15:15 Every employee quits on the same day 16:21 The Indeed hire who changed the entire business 18:59 Fear, alcohol and nearly going bankrupt 23:13 One technician outperforms the rest of the company 25:52 Why Nathan waited a full year before doing acquisition #3 27:00 Acquisitions #3 and #4—and buying businesses the second time around 28:46 How his M&A due diligence completely changed 29:30 The "buying at-bats" framework for acquisitions 33:08 Why Lindley spends almost nothing on marketing 34:15 Turning acquired customer databases into new revenue 36:27 Hiring exceptional technicians and building repeatable systems 37:35 The company today: 50 employees across three markets 39:13 How Lindley integrates acquired businesses 42:38 Teaching acquired technicians to double their income 43:17 The acquisitions that didn't work—and why 46:47 Planning an exit and doing it all over again 49:04 Where to connect with Nathan
49:35

Nathan rolled up 11 tiny (<$1M EBITDA) HVAC companies, paying low 3x multiples. Now PE is interested in buying the group, and Nathan is already planning to do it all over again. “I see a lot of opportunity in taking these really small mom-and-pop shops and building them up to the lower end of what a PE firm would be interested in acquiring. You can pick them up at 3x, sell them at 10x and repeat that process over and over.” But this story almost ended before it began... After acquiring his first two companies with an SBA loan, Nathan watched revenue collapse, burned through his cash, nearly lost his father's retirement savings and came dangerously close to bankruptcy. The turning point was a complete rethink of incentives, compensation and how to build an acquisition platform that actually compounds. Give it a listen. I hope you appreciate Nathan Lindley extreme transparency on everything, even him sharing how he overcame daily stress through drinking and how, to this day, he is still paying down his SBA note of $8,500 a month… Year six of 10 years on that. It’s very hard out there. Timestamps: 0:00 Nathan's 11 acquisitions and $16M run-rate HVAC platform 0:25 From the first deal in 2020 to acquisition #11 1:24 From book publishing to buying HVAC businesses 3:55 Selling real estate to fund the first acquisition 4:33 Buying a one-technician HVAC company—and the costly assumptions that followed 7:58 Losing 40% of revenue almost immediately after closing 10:26 Acquisition #2 makes every problem much bigger 11:20 Running out of cash—twice 14:18 The decision to put everyone on commission 15:15 Every employee quits on the same day 16:21 The Indeed hire who changed the entire business 18:59 Fear, alcohol and nearly going bankrupt 23:13 One technician outperforms the rest of the company 25:52 Why Nathan waited a full year before doing acquisition #3 27:00 Acquisitions #3 and #4—and buying businesses the second time around 28:46 How his M&A due diligence completely changed 29:30 The "buying at-bats" framework for acquisitions 33:08 Why Lindley spends almost nothing on marketing 34:15 Turning acquired customer databases into new revenue 36:27 Hiring exceptional technicians and building repeatable systems 37:35 The company today: 50 employees across three markets 39:13 How Lindley integrates acquired businesses 42:38 Teaching acquired technicians to double their income 43:17 The acquisitions that didn't work—and why 46:47 Planning an exit and doing it all over again 49:04 Where to connect with Nathan

PrivateEquityGuy (Mikk Markus)

137,437 Aufrufe • vor 2 Monaten

Here is how I am using AI right now at work, at home, and for my finances... Every founder, executive or investor I talk with these days wants to know how others are using AI in their daily lives. I figured it would be helpful to pull back the curtain on what I am using and how I have implemented the various products. There are three areas where I have adopted AI in a material way: professionally, financially, and personally. Professional use of AI On the professional side, I am currently using Grok Grok Bot extensively. I started with a Chief of Staff bot that I put in charge of the entire operation, followed by a number of more specialized bots for various bodies of work (talent recruiter, product designer, podcast researcher, book launch manager, email organizer, etc). Once I had the initial team of bots set up, I spent about an hour “onboarding” the Chief of Staff to my professional life. I treated this exactly how I would onboard a human Chief of Staff. I explained each business I am involved with, including their products, business model, personnel, metrics, and goals. I explicitly called out what the business is doing well and where we need to improve. I also gave the Chief of Staff access to relevant systems (email, calendar, Slack, analytics dashboards, etc). Once I had given as much context as I thought necessary, I asked the Chief of Staff to create an overview document to send me so I could double-check the accuracy and thoroughness of the bots understanding. I also asked the CoS bot to interview me for any other information that would be relevant to ensuring the bot could help me. This entire process was fairly quick and painless, but I believe it was the single most important thing I did to get value from Grok Bot. The more context that the AI system has, the more helpful it can be. That context can come from static, institutional knowledge or it can come from dynamic daily updates like email and Slack messages. After getting the bots set up and giving them context, I have done two other things that I think are worth sharing. The first is that my team of bots holds a daily standup meeting where they all come together and share what they did yesterday, what they are going to do today, and what they need my help or approval on (aka what they are blocked on). These “exec meeting” or daily standup allows for the bots to collaborate in a more seamless way, while also creating a very simple process for the Chief of Staff bot to put together a daily brief for me on what happened yesterday, what is going to happen today, and where I am needed to unblock productivity. The second thing I have done is treat the AI system as the brain of the company. Most people try to use AI as an augmentation to themselves, which can be helpful to a degree. I have flipped the relationship though. I look at my job as persistently giving the AI bots as much context as possible, so I can leverage their superhuman intelligence to make decisions and achieve our goals. For example, the recruiter bot recently surfaced a number of very high-quality candidates for an open role we have. After meeting with each candidate, I wrote a quick message to the recruiter bot to tell it what I liked about the person, what I thought were potential issues, improvements for future searches, and what the next steps were with each individual. All of that information and context is getting stored in the bot’s memory, which will compound over time and help us improve as an organization. Quick pro tip: If you are worried about putting all of the context into a single system’s memory, but unsure if that is the system you will use forever, you can have Grok Bot or another system dump their memory and context into a Notion document as well. This way you have a duplicate copy of the memory so it can be referenced by any AI system you use in the future. My takeaway from using Grok Bot to manage our companies is that we are having to hire less people, we are seeing a direct impact on revenue growth, and it appears to drive higher quality in our decision-making process. That is a win-win-win. I highly recommend going through these steps to setup your system correctly and it will pay off big time later on. Financial use of AI On the financial side, it was nearly impossible to find a good AI product to use for personal finance. Everything seemed to be a Chat-GPT wrapper that technically worked from an engineering standpoint, but didn’t solve any of the user problems I was facing. A big issue is that most of the fintech products are focused on budgeting and saving, rather than investing and growing your portfolio. This is why I eventually spent the time and money to build CFO Silvia. I went through a similar process of getting Silvia set up with the necessary context. I attached my bank accounts, brokerage accounts, crypto accounts, and credit cards, along with uploading real estate, cars, collectibles, and private investments. Silvia allows me to dynamically track the value of these assets (and my overall net worth) in real-time. But the real unlock for me has been talking to Silvia about two specific topics: tax and estate planning. As most of you know, I am not a frequent trader, so although you could use Silvia for stock analysis or trading activities, that is not my approach to investing. Instead, I have had great success in using Silvia to find creative and valuable tax mitigation strategies that are personalized to my situation, including ideas that had not previously been surfaced by my accountants, lawyers, or tax experts. Additionally, I have used Silvia for estate planning purposes. I am married and have four children, so there is a decent amount of complexity and opportunities to pursue. Having a dedicated resource with superhuman intelligence and the full context of my personal financial situation has been incredibly powerful. One funny thing I have noticed is that I am willing to tell Silvia certain things that I would hesitate to tell other humans (financial goals, areas of concern, etc) and I ask numerous “dumb” questions that I would probably shy away from asking a human. Regardless of why I feel more comfortable talking to the AI product, it has unlocked a few different ideas and strategies that I was previously unaware of, so that has been an added bonus to using the product. If you aren’t using AI to help manage your finances, I think it is a no brainer to start using the technology. I am biased towards Silvia since we built it, but you can give it a try for free here: Personal use of AI On the personal side, I use almost all of the traditional AI products (Chat-GPT, Claude, Grok, Gemini, Perplexity, etc). Those are well understood at this point, but one product that I started using recently that I am impressed with is Instinct AI. They have built a personal assistant AI bot that you communicate with through iMessage or SMS. The experience has been delightful, but I am most excited about the bot’s ability to anticipate the second or third-step in a process before I have to tell it anything. For example, Instinct got access to my calendar and immediately started identifying scheduling conflicts and asked me if I would like the bot to reach out to one of the parties to reschedule. I never told it to look for conflicts, nor did I tell it I wanted help rescheduling things. It’s “instincts” knew what the basic task would be and began executing. Another example is that Instinct was told my wife is Polina, so whenever it deems something important to the household or family, Instinct will add Polina to the calendar invite, communicate the information to her, or ask me if Polina should be aware of the information. This is very helpful for someone like me who has too many things floating around in my brain and should always do a better job of keeping Polina informed about various things. Lastly, Instinct is very helpful in scanning my personal email and understanding what is most important. It ignores things that are trivial, but somehow can parse out the high priority items, summarize them for me in a text message, draft a response to the email, and then ask me for permission to respond. As I said, it is the most impressive personal assistant AI product I have used so far. So those are the three big areas that I use AI today and the specific products I have incorporated into my life. Before I let you go, I figured I could share some best practices I have learned as well. I also make sure to tell AI bots they are not allowed to respond to any message or email without my explicit approval. This reduces the risk of having a bot go rogue with a message or commitment that I am not onboard with. I also ensure that each bot only has read access to our business systems like an analytics dashboard, etc. While I am a big proponent of using these products and believe they will fundamentally transform how we operate professionally, I am still not ready to let them loose without human oversight. I am sure that will change in the coming weeks and months, but I need more time to get comfortable with that level of delegation and trust. I hope this overview was helpful for each of you. It would be great if you could respond to this post with any products you are using or tips/tricks that you have learned to get more productivity and value in your life. I love writing these letters each day because I learn just as much from me as I learn from you all. Onwards!
12:57

Here is how I am using AI right now at work, at home, and for my finances... Every founder, executive or investor I talk with these days wants to know how others are using AI in their daily lives. I figured it would be helpful to pull back the curtain on what I am using and how I have implemented the various products. There are three areas where I have adopted AI in a material way: professionally, financially, and personally. Professional use of AI On the professional side, I am currently using Grok Grok Bot extensively. I started with a Chief of Staff bot that I put in charge of the entire operation, followed by a number of more specialized bots for various bodies of work (talent recruiter, product designer, podcast researcher, book launch manager, email organizer, etc). Once I had the initial team of bots set up, I spent about an hour “onboarding” the Chief of Staff to my professional life. I treated this exactly how I would onboard a human Chief of Staff. I explained each business I am involved with, including their products, business model, personnel, metrics, and goals. I explicitly called out what the business is doing well and where we need to improve. I also gave the Chief of Staff access to relevant systems (email, calendar, Slack, analytics dashboards, etc). Once I had given as much context as I thought necessary, I asked the Chief of Staff to create an overview document to send me so I could double-check the accuracy and thoroughness of the bots understanding. I also asked the CoS bot to interview me for any other information that would be relevant to ensuring the bot could help me. This entire process was fairly quick and painless, but I believe it was the single most important thing I did to get value from Grok Bot. The more context that the AI system has, the more helpful it can be. That context can come from static, institutional knowledge or it can come from dynamic daily updates like email and Slack messages. After getting the bots set up and giving them context, I have done two other things that I think are worth sharing. The first is that my team of bots holds a daily standup meeting where they all come together and share what they did yesterday, what they are going to do today, and what they need my help or approval on (aka what they are blocked on). These “exec meeting” or daily standup allows for the bots to collaborate in a more seamless way, while also creating a very simple process for the Chief of Staff bot to put together a daily brief for me on what happened yesterday, what is going to happen today, and where I am needed to unblock productivity. The second thing I have done is treat the AI system as the brain of the company. Most people try to use AI as an augmentation to themselves, which can be helpful to a degree. I have flipped the relationship though. I look at my job as persistently giving the AI bots as much context as possible, so I can leverage their superhuman intelligence to make decisions and achieve our goals. For example, the recruiter bot recently surfaced a number of very high-quality candidates for an open role we have. After meeting with each candidate, I wrote a quick message to the recruiter bot to tell it what I liked about the person, what I thought were potential issues, improvements for future searches, and what the next steps were with each individual. All of that information and context is getting stored in the bot’s memory, which will compound over time and help us improve as an organization. Quick pro tip: If you are worried about putting all of the context into a single system’s memory, but unsure if that is the system you will use forever, you can have Grok Bot or another system dump their memory and context into a Notion document as well. This way you have a duplicate copy of the memory so it can be referenced by any AI system you use in the future. My takeaway from using Grok Bot to manage our companies is that we are having to hire less people, we are seeing a direct impact on revenue growth, and it appears to drive higher quality in our decision-making process. That is a win-win-win. I highly recommend going through these steps to setup your system correctly and it will pay off big time later on. Financial use of AI On the financial side, it was nearly impossible to find a good AI product to use for personal finance. Everything seemed to be a Chat-GPT wrapper that technically worked from an engineering standpoint, but didn’t solve any of the user problems I was facing. A big issue is that most of the fintech products are focused on budgeting and saving, rather than investing and growing your portfolio. This is why I eventually spent the time and money to build CFO Silvia. I went through a similar process of getting Silvia set up with the necessary context. I attached my bank accounts, brokerage accounts, crypto accounts, and credit cards, along with uploading real estate, cars, collectibles, and private investments. Silvia allows me to dynamically track the value of these assets (and my overall net worth) in real-time. But the real unlock for me has been talking to Silvia about two specific topics: tax and estate planning. As most of you know, I am not a frequent trader, so although you could use Silvia for stock analysis or trading activities, that is not my approach to investing. Instead, I have had great success in using Silvia to find creative and valuable tax mitigation strategies that are personalized to my situation, including ideas that had not previously been surfaced by my accountants, lawyers, or tax experts. Additionally, I have used Silvia for estate planning purposes. I am married and have four children, so there is a decent amount of complexity and opportunities to pursue. Having a dedicated resource with superhuman intelligence and the full context of my personal financial situation has been incredibly powerful. One funny thing I have noticed is that I am willing to tell Silvia certain things that I would hesitate to tell other humans (financial goals, areas of concern, etc) and I ask numerous “dumb” questions that I would probably shy away from asking a human. Regardless of why I feel more comfortable talking to the AI product, it has unlocked a few different ideas and strategies that I was previously unaware of, so that has been an added bonus to using the product. If you aren’t using AI to help manage your finances, I think it is a no brainer to start using the technology. I am biased towards Silvia since we built it, but you can give it a try for free here: Personal use of AI On the personal side, I use almost all of the traditional AI products (Chat-GPT, Claude, Grok, Gemini, Perplexity, etc). Those are well understood at this point, but one product that I started using recently that I am impressed with is Instinct AI. They have built a personal assistant AI bot that you communicate with through iMessage or SMS. The experience has been delightful, but I am most excited about the bot’s ability to anticipate the second or third-step in a process before I have to tell it anything. For example, Instinct got access to my calendar and immediately started identifying scheduling conflicts and asked me if I would like the bot to reach out to one of the parties to reschedule. I never told it to look for conflicts, nor did I tell it I wanted help rescheduling things. It’s “instincts” knew what the basic task would be and began executing. Another example is that Instinct was told my wife is Polina, so whenever it deems something important to the household or family, Instinct will add Polina to the calendar invite, communicate the information to her, or ask me if Polina should be aware of the information. This is very helpful for someone like me who has too many things floating around in my brain and should always do a better job of keeping Polina informed about various things. Lastly, Instinct is very helpful in scanning my personal email and understanding what is most important. It ignores things that are trivial, but somehow can parse out the high priority items, summarize them for me in a text message, draft a response to the email, and then ask me for permission to respond. As I said, it is the most impressive personal assistant AI product I have used so far. So those are the three big areas that I use AI today and the specific products I have incorporated into my life. Before I let you go, I figured I could share some best practices I have learned as well. I also make sure to tell AI bots they are not allowed to respond to any message or email without my explicit approval. This reduces the risk of having a bot go rogue with a message or commitment that I am not onboard with. I also ensure that each bot only has read access to our business systems like an analytics dashboard, etc. While I am a big proponent of using these products and believe they will fundamentally transform how we operate professionally, I am still not ready to let them loose without human oversight. I am sure that will change in the coming weeks and months, but I need more time to get comfortable with that level of delegation and trust. I hope this overview was helpful for each of you. It would be great if you could respond to this post with any products you are using or tips/tricks that you have learned to get more productivity and value in your life. I love writing these letters each day because I learn just as much from me as I learn from you all. Onwards!

Anthony Pompliano 🌪

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