Becket U curates the best resources in Math, Physics, Computers, Microeconomics, Game Theory, and Persuasion. With this knowledge, you will understand how the world works.
Undiscovered #051: When To Do What You Love, New Math Shape, NVDA Bull & Bear Case
#051: When To Do What You Love, New Math Shape, NVDA Bull & Bear CaseHi All! We are pleased to welcome you to this week's edition of Undiscovered, a newsletter with exclusive resources and insights expanding from the material found on our main site - becketu.com. This week, we will take a look at the newest Paul Graham essay covering when to work on projects you love, a new math shape using centuries-old knowledge, Zuck explaining the possibilities for Nvidia & AI in the future, and more. Let's dive in: When To Do What You LoveLegendary investor and Y-Combinator co-founder Paul Graham just released a new essay titled, 'When To Do What You Love'. It tackles one of the most commonly refrained pieces of advice people say in regards to how we should pick a career. But when is it the right time to pursue what you love? When should you choose your passion over something else that really matters, like money? The answer Graham provides is one of the best I have heard when it comes to the addressing the nuance that exists implicitly through the question. Some of my favorite lines in the essay involve heuristics as to how you can discern whether a career is right for you, as well as how to maintain flexibility if you're unsure what to work on: One useful trick for judging different kinds of work is to look at who your colleagues will be. You'll become like whoever you work with. Do you want to become like these people? ... The other thing you do in the face of uncertainty is to make choices that are uncertainty-proof. The less sure you are about what to do, the more important it is to choose options that give you more options in the future. I call this "staying upwind." If you're unsure whether to major in math or economics, for example, choose math; math is upwind of economics in the sense that it will be easier to switch later from math to economics than from economics to math. Brian Armstrong Explains How He Made CoinbaseIn tandem with the idea of 'doing what you love', one story I recently came across was an interview with Coinbase co-founder and CEO Brian Armstrong, who described his routine when he was building the crypto platform. This was at the same time as when he worked at Airbnb, and his schedule went as follows: “I would often work [at Airbnb] until 7pm. I’d come home, eat dinner, and then I would work from 8pm to midnight. I would do that maybe 3-4 days a week on weekdays. And then on the weekend I’d work Sunday afternoon for 7-8 hours.” ... “It sucked. I mean I was tired after the full day of work [at Airbnb]. But this is where determination comes in… At that moment in time, I was in my late 20s, and I was like, ‘I really want to try to build something important in the world.’” This type of dedication often requires a degree of sacrifice, mostly coming in the form of relationships whether they are romantic or friendships. When asked about this topic: “I was pretty intense about it. I would say I sacrificed friendships for it. It’s not like I was just never responding to people, but I’ve seen this happen to various people. They get to a certain point in their life. Sometimes they turn a certain age where they thought they would have more done by then or maybe someone in their family passes away and they’re like, Oh my god, time is finite. It’s precious. And something happens where they’re like, ‘I’m going to get this done, no matter the cost.’” Although it may be jarring for some readers, this is a truth I have seen in more founders than not. However, he does provide some sage advice for anyone who may be in a similar position when trying to work on a passion project: “Go hard at it. Finish your book. Launch your thing. Just start doing stuff - and even if you don’t know what to do, just do anything, because action will produce information and it’ll help you get to the right thing.” For the full video, you can find it here. New Math Shape Just Dropped"Wake up babe new shape dropped" was the quote tweet from user @jeeyonshim to describe the new discovery documented by Nature magazine... Using centuries-old mathematics, researchers have discovered a new kind of shape that describes 'forms commonly found in the natural world.' This new shape is called "soft cells", and they 'tessellate on a plane and have curved edges along with cusp-like corners where the edges meet tangentially at sharp points'. It's a discovery made more interesting by the fact that this is one of the most commonly found shapes in the natural world. From the shapes seen in the cross-section of an onion to those in the formation of islands from river erosion, this is a natural shape that exists in many ways around us. And even though this is a formal declaration of a new shape, it is also well known that architects such as Zaha Hadid have long used soft cells intuitively to avoid or minimize corners in their projects. Nvidia Scenarios Summed By Zuck in Under 2 MinutesThe big question on the minds of investors and those interested in tech is, "How big will AI really be?" We have already seen an effort in the last couple years from trying to build the most advanced and user-friendly models, but is there a limit to how far we can push its ability? Mark Zuckerberg, founder and CEO of Facebook (now Meta) is one of the most qualified people to discuss the topic. Meta has invested $18 billion into buying GPUs and related AI computing infrastructure to help power the required hardware needs, and his Llama models are at the forefront of the consumer LLM market. In this short clip with tech influencer Cleo Abram, he breaks down the best and worst case scenarios he predicts with chip and GPU manufacturer (and S&P 500 darling) Nvidia. This is probably the best and most succinct summary of where the industry is heading, and you can find the full interview here. New Meme I'm Using For EverythingPresented with no further notes:
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Becket U curates the best resources in Math, Physics, Computers, Microeconomics, Game Theory, and Persuasion. With this knowledge, you will understand how the world works.
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