Malcolm Leach @malcolml

@NoahEpstein_ Composer

@carlvellotti CC

Every PM should be using Claude Code. So I built a HUGE course for you to learn Claude Code... IN Claude Code! 🔹 Complete guide 🔹 Make PRDs, analyze data, create decks Soon, I'll sell it for $149. For the next 24h: FREE! Follow + RT + comment "CC" & I'll DM it.

@PrajwalTomar_ Claude

@PrajwalTomar_ System

Thanks for reading till the end! If you enjoyed this thread, please share the first post and follow me for more content 👇🏻

James Lucas @JamesLucasIT

a year ago

Places on Earth that don't look real 🧵 1. Alaska has the clearest waters in the world

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Already sent 50+ DMs and completely lost track haha. If you didn’t get it yet, the prompt and reference image for this landing page are in the first comment.

Prajwal Tomar @PrajwalTomar_

a year ago

Bolt built this entire landing page from a single prompt 🤯 No Figma. No coding. Just one prompt and a clear flow Want the exact prompt I used? RT and follow. I’ll DM you the link directly.

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I stand with @jessphillips… National treasure 👍 Share if you agree.

@scottjla Hey! Great thanks, fancy catching up at some point?

20 sentences that will sharpen your analytical thinking:

Hope these can help you no matter what life stage you are at. If you liked this thread: 1. Follow me @markmanson 2. Retweet the tweet below to share it with people you want to help.

Mark Manson @Markmanson

2 years ago

Today is my 40th birthday. Here are all the things that I know at 40 which I wish I knew at 20. Starting with… 1. Your relationship with others is a direct reflection of your relationship with yourself. If you treat yourself poorly, then you will unconsciously seek out and

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The OpenAI story keeps getting crazier. This is the most significant 72 hours for AI that will change everything. Here's everything you need to know & what's coming next: 🧵👇

My parents or school never read stories with two dads to me. I never saw pride flags as a kid. I didn’t learn the word gay until I was in secondary school. I didn’t see any gay role models on tv. But I’m gay, and always have been. Straight representation didn’t make me straight. Gay representation won’t make kids gay. But not having a variety of representation will make some kids feel like they don’t belong, or are wrong. If people won’t allow children to see the diversity of families, they’re failing them and putting their own prejudice above the wellbeing of their children. Section 28 banned the ‘promotion’ of homosexuality in schools and is still having effects today, despite being repealed 20 years ago. Ignorance or bigotry can no longer be used as an excuse and all children should see versions of themselves in our schools and in their lives.

This amusingly but informatively captures the intractable dilemma faced by Jeremy Hunt as he considers inheritance tax cuts in the autumn statement. The Conservative (brexity) base is now broadly reduced to people who shop M&S and people who shop at Iceland.

Mark Manson @Markmanson

2 years ago

Today is my 40th birthday. Here are all the things that I know at 40 which I wish I knew at 20. Starting with… 1. Your relationship with others is a direct reflection of your relationship with yourself. If you treat yourself poorly, then you will unconsciously seek out and

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An Assessment of Walter Isaacson’s Biography about Elon Musk @elonmusk How is one supposed to determine the quality of a biography? Is a biography a work of art? Or is it simply a record of chronological details? Is it supposed to be an in-depth psychological profile? Or is it supposed to be a celebration of the person at hand? Perhaps a good biography should have a mix of all of these things. One fundamental factor when it comes to biographies is whether the person is still living or not. How is a biography on a dead Leonardo Da Vinci going to differ from a biography on the living Elon Musk? One thing is obvious: the biographer can’t talk to the dead guy. While it’s patently obvious that Isaacson spoke plenty to Musk, I can’t in good conscience claim that Isaacson asked Musk any new questions. The size of this missed opportunity can’t be understated, especially since there were a slew of questions I was hoping Isaacson would ask. Consume a few interviews done with Elon Musk and a consistent theme among them - a theme even more consistent than the subject at hand is the lack of imagination when it comes to the questions posed to Elon Musk. Every reporter asks the same set of questions, and after a few interviews Musk is little more than a pull-string toy repeating the same answers, as if no one understood what he said the first time around. It’s clear that Isaacson suffers the same lack of imagination when it comes to asking good questions. Perhaps this was not Isaacson’s aim. It seems clear his goal was to chronicle facts and details that sketch an accurate portrait of the actions taken by the guy we know as Elon Musk. And, that certainly is a biography. But, other than the actions and events recorded that pick up where the work of Ashely Vance concludes, I can’t say there’s much more one can learn about Musk from Isaacson’s biography. There is certainly plenty more grist for opinions already formed. You think Musk is a jerk? Well there’s more evidence in the book. Think Musk is a brilliant leader with an engineer’s mind? Well you have more evidence for that too. This might be a sign of good reporting - that the text is impartial, and opinion is left to the reader. Isaacson seems as though he strives for this old school newspaper reporter style. If that was the aim, then ok, the book is an accurate treatment of it’s subject, and those seeking the description of a series of actions and events peppered with quotes from original sources will be satisfied and their opinion - which ever way it falls - will be bolstered. So what exactly was lacking in Isaacson’s final product? Well, what exactly happens to you, the reader, when you read an exceptional work of non-fiction? Stop for a moment and think about it. Why do we crave non-fiction? Or even fiction for that matter? What is the utility of such piles of words? The utility of anything is determined by the change that it can render. The utility of a hammer is that it can drive a nail into wood and thereby change the location of that nail to be in a place that is otherwise difficult to deliver that nail. The utility of a piece of art is the change it renders in the consumer of that art. We speak about changes in ourself just like that nail: I was so moved by your beautiful story. Or, this painting does nothing for me. The utility of nonfiction (and fiction) is the change that it renders in the reader. After Isaacson’s biography, what has changed in this reader? Well, my timeline on the comings and goings of Elon Musk in relation to his various companies and personal relations has been updated. Is that change the one I was hoping for when I first picked up Isaacson’s book? It’s certainly part of the change I expected would occur, but I was hoping for a lot more. Was I moved? Not really. I already find Elon Musk very inspiring, and Isaacson’s biography did absolutely nothing to enhance or degrade that inspiration. An update in the resolution and detail on the comings and goings and the various actions and decisions of Elon Musk isn’t particularly useful. If you understand the mission that informs his underlying drive for each and all of his endeavors then his actions make sense for the most part, and like anyone, mistakes are made and personal judgement isn’t always spot on. Everyone has had a boss or a colleague who was an asshole or a jerk or just an enormous pain in the ass. This is nothing new when it comes to the human condition in the civilized world. No one has a perfect family or perfect friendships. So Elon is no different and maybe a drama magnet and he can be sometimes be an asshole boss? Whoopty-doo. I’m so moved. In the grand scheme of things, these details are …fairly impotent. The results of these details are certainly cataclysmic in their ramifications, and many people already experience them, be it by driving a Tesla, or working for one of the various companies, or posting on X, or having internet in the middle of nowhere or leaving the damn planet. If Elon Musk continues as he hopes to, then in a few decades there likely won’t be a person on the planet whose life hasn’t been effected by the actions of Elon Musk. So what was missing? What questions failed to grace the imagination of Isaacson that would have revealed Musk in a way that isn’t just a repetition of all his interviews? Or more broadly: what would have made a biography on Musk more useful? This seems like a fair question considering Elon Musk has clearly figured out something fundamental that has escaped the discernment of most other humans. Regardless of your opinion of the guy, you can’t deny: he’s damn effective. So, wouldn’t it be fair to think that a biography about Musk might delve into this fundamental ‘something’ that makes him more effective? It can’t just be because he’s a hard-ass boss who pushes employees. If being an asshole is all it took to move civilization forward, we would have created a utopia long ago. The questions posed to Musk usually provoke Musk to explain why he is doing something, which is inevitably some shade of: for the good of humanity - to ensure the that light of human consciousness can endure. Perhaps the collective imagination of the public is still in shock that someone could have this at the root of their drive, and so the default reaction is disbelief, which necessitates turning Musk into a pull-string toy. Surely someone so powerful must be driven by something more shallow, like greed or money? I think such a disbelief actually says more about the disbeliever.. What lacks about the questions posed to Musk is that they fail to delve into how he thinks. Isaacson touches on this, but it’s nothing new. He describes the Idiot-Index and the process of delete, delete, delete until you have to add back. And how engineers are really good at optimizing something that should just be - again - deleted. But none of this is new, and honestly watching Tim Dod walk around Starbase with Musk is a much better (and quicker) way to learn these aspects of Musk’s process. And yes Isaacson touches on the now-ubiquitous “First Principles Thinking” that Musk has parroted to many other interviewers. Isn’t this how Elon Musk thinks? First Principles plus an iterative design process of create and delete delete delete? No, this is a framework and an algorithm. They are part of the puzzle, but again, it’s nothing new for anyone who is even casually interested in Musk. So what else is there to explore in the mind of Musk? In September 2018, Musk gave a presentation which announced the first passengers for starship, and during that talk, Musk touched on a very interesting and somewhat elusive topic: “This is a stupidly hard problem and SpaceX engineering has done a great job with this design. It’s like I don’t think most people - even people within the aerospace industry know what question to ask. It took us a long time to even frame the question correctly but once we could frame the question correctly, the answer was - I wouldn’t say easy, but the answer flowed, once the question could be framed with precision.” Isaacson touches on topic of “questions” but gravitates entirely to the Hitchhiker’s Guide to the Galaxy as the de facto way to put a bow on the topic of “Musk & Questions”. Here’s a question for Musk that Isaacson could have asked which almost certainly would have evoked something useful from Musk that we perhaps haven’t heard yet: How do you go about forming and refining questions? Divorced from specific examples, speak conceptually about the nature of question formation and refinement. Are there any aspects of the process that always apply regardless of subject? How do you know if you are asking a good question? You seem to use questions in order to drill down until you get to the “first principles” of a matter. How do you know when you’ve arrived at these first principles? What change occurs in the nature of questions being asked to signal this arrival? If we were to say there is an Art to asking questions, what would be the tenets or guiding principles for honing one’s skills in this art of questions? It’s this process of question formation and question refinement that is at the heart of much of Musk’s success. Indeed anyone who has been flummoxed by a problem can likely relate: asking a new question about the topic at hand is usually very useful. But when it comes to the art of questions, few of us have exceptional talent, and virtually nothing has been written on it as an art or a process that can be developed and honed. Regardless of your opinions about Elon Musk, it’s undeniable that he’s been asking a lot of very fruitful questions that haven’t occurred to other people. When Isaacson first announced he was writing a biography on Musk, I tweeted at him, requesting that he delve into this discussion with Musk. But alas, while Isaacson’s biography left me knowing a bit more, it also left wanting a lot more.

Tesla is THE largest distributor of AI robots in the world & people still have no idea this is currently happening bc these things are disguised as “cars”.

Tesla's FSD v12 is a REALLY big deal. Last night @elonmusk livestreamed a ~45-minute video of a Model S driving itself around using Tesla's latest self-driving software, FSD v12. Self-driving is something the company has been trying to solve since Tesla Autopilot was released in 2015. Since then, Tesla has made steady progress improving the code to handle all kinds of road situations, has added cameras around the car, and removed sensors, all the while rewriting the code multiple times to solve for things the car couldn’t handle. And even though Tesla cars can drive themselves in many situations, the biggest challenge with self-driving cars is the thousands (or millions) of situations drivers face on a daily basis that are completely unexpected or difficult to solve for, like other drivers acting irrationally, inclement weather, debris on the road, weird (or lack of) lane markings, etc. Up to this point, Tesla and other companies have to spend a large amount of time running through simulated scenarios to generate code that would teach the system how to handle these situations. This code is oftentimes written by a human and needs to account for every variation of something happening on the road. And even then, there are thousands (or millions) of situations that a simulation won’t come with, since real life is so damn complicated and complex. The approach many have taken to try and solve this problem is by overfitting their self-driving cars with a ton of different sensors like LIDAR, radar, ultrasonics, cameras, and other sensors in addition to generating High-Definition maps of the areas where the cars are meant to be driven in. They’ve done this in hopes that there’s a combination of sensors and map data that would allow them to solve for the most unexpected situations. Here’s a picture of a GM Cruise vehicle that uses this approach. However, yesterday’s video has demonstrated a breakthrough in how self-driving cars can operate. Instead of using many sensors and hardware on their cars to process the world, Tesla is using 8 cameras and a computer that’s specifically built to process video data. That’s 9 total parts vs everyone else’s 30, 40, 50+ parts to process the world. Using only vision to process the world and not needing things like LIDAR, radar, and other sensors to interpret the physical objects around the car is impressive enough, but HOW the car learns to do this is what the real breakthrough is. With FSD v12, Tesla takes the video data that is collected by its fleet of ~4 million cars and runs it through an AI that is built using Neural-Nets (like ChatGPT but for the real world), and then the AI figures out what the car should do based on what it sees. What’s important to highlight here is that Tesla has done 0 work in telling the car how it should interpret the world. That means that the AI doesn’t explicitly know what a lane is, what a traffic light is, what a stop sign is, what a cone is, what a pothole is, what rain is, etc. What Tesla does is it shows the AI a metric-ton of video of a car driving around using the 8 cameras that are outfitted around the car, and the AI learns how to do the same. The more video Tesla feeds it, the better the system gets. The more unique situations that are collected from the fleet of Teslas, the better the system gets at accounting for those situations. This “AI code” will then be beamed to every Tesla in the world, and the on-board computer will be able to process its surroundings without the need to connect to Tesla’s AI server. It’s no different than you or I getting into a car and driving it. Instead of our 2 eyes collecting video around us and using our brain to process the info, the 8 camera system will collect the video and Tesla’s on-board computer will process it using the “AI code”. In other words, Tesla has moved away from humans figuring out how to write code that tells the car what to do, and instead feeds video to an AI, and the AI figures out the best way to account for every situation. The only thing Tesla needs moving forward is more video and more compute power (chips) to process videos. That’s it. This is profound. Everything that is captured on video with the 8 camera system is something the AI will be able to figure out how to navigate through. Snow. Potholes. Deer. Cyclists. Aliens. You name it. And this “code” that is generated by the AI will get better and better as Tesla’s compute capabilities grow with their purchases of NVIDIA’s H100 chips and the build-out of their in-house DOJO compute system. Not to mention the growing fleet of Teslas that will capture more and more video data around the world. Every Model S, 3, X, and Y that is sold today is a video-capturing robot that feeds the AI. And every Cybertruck and Compact Car will be the same. And believe it or not, it gets even crazier. Now that Tesla has come up with a real-world data collection and processing system with its cameras and on-board computer, this same system can be used on other physical products that can learn how to move around its surroundings. This is where Tesla’s Optimus Bot comes into play. Tesla will be able to use its 8 camera system on the Tesla Bot to collect video of its surroundings, beam it back to the AI, the AI figures out how to best do that thing that it’s collecting video for, and then beam back the “AI code” for the Bot to process with its on-board compute. We are not far away from a world where a humanoid robot watches you do the dishes, sends back the data to the mothership to process it, and then the next morning the Bot has learned how to do the dishes - not only using the video it gathered from you doing it, but from every other person in the world washing dishes. Do this process with literally anything. ChatGPT showed the masses what the potential of AI can be. NVIDIA showed the masses just how much demand there is for hardware that is used by AI systems. And now, Tesla just showed the masses what AI means for real-world physical applications. The world has changed - again.

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Outstanding.

not letting the riots interrupt your snack…respect nanterre, france

At GPJ, we're committed to helping brands bridge this gap with proprietary tools like TRACE. As a founding member of @weareisla_uk we're proud to create experiences that have a positive impact. Click here to learn more about measuring your impact. ow.ly/nZv450OFbwh #gpjanz