Code Optimization Quotes

Life with a cheat code isn't life. Our existence isn't something to be engineered or optimized for the avoidance of pain. That's what it is to be human - the beauty and the pain, each meaningless without the other.

The big optimizations come from refining the high-level design, not the individual routines.

Ride with an outlaw, die with him," he added. "I admit it's a harsh code. But you rode on the other side long enough to know how it works. I'm sorry you crossed the line, though." Jake's momentary optimism had passed, and he felt tired and despairing. He would have liked a good bed in a whorehouse and a nice night's sleep. "I never seen no line, Gus," he said. "I was just trying to get to Kansas without getting scalped.

I confess that I am now suspicious of nearly every attempt to code anger as unhealthy, no matter how well meaning or persuasive the source. I believe Stanton was correct: what is bad for women, when it comes to anger, are the messages that cause us to bottle it up, let it fester, keep it silent, feel shame, and isolation for ever having felt it or re-channel it in inappropriate directions. What is good for us is opening our mouths and letting it out, permitting ourselves to feel it and say it and think it and act on it and integrate it into our lives, just as we integrate joy and sadness and worry and optimism.

Struggle is not optional—it's neurologically required: in order to get your skill circuit to fire optimally, you must by definition fire the circuit suboptimally; you must make mistakes and pay attention to those mistakes; you must slowly teach your circuit. You must also keep firing that circuit—i.e., practicing—in order to keep myelin functioning properly. After all, myelin is living tissue.

The revolution is built on three simple facts. (1) Every human movement, thought, or feeling is a precisely timed electric signal traveling through a chain of neurons—a circuit of nerve fibers. (2) Myelin is the insulation that wraps these nerve fibers and increases signal strength, speed, and accuracy. (3) The more we fire a particular circuit, the more myelin optimizes that circuit, and the stronger, faster, and more fluent our movements and thoughts become.

But the satisfaction and pride that are earned through truly optimal experiences come from being challenged, working hard, and putting your training to the test in service of a goal you care about.

I’ve found that refactoring helps me write fast software. It slows the software in the short term while I’m refactoring, but it makes the software easier to tune during optimization. I end up well ahead.

Are we using digital computers to sequence, store, and better replicate our own genetic code, thereby optimizing human beings, or are digital computers optimizing our genetic code—and our way of thinking—so that we can better assist in replicating them?

I’m ready to accept that my existence will sometimes contain pain. No more trying to escape, either through nostalgia or a memory chair. They’re both the same fucking thing. Life with a cheat code isn’t life. Our existence isn’t something to be engineered or optimized for the avoidance of pain. That’s what it is to be human- the beauty and the pain, each meaningless without the other.

I like my code to be elegant and efficient. The logic should be straightforward to make it hard for bugs to hide, the dependencies minimal to ease maintenance, error handling complete according to an articulated strategy, and performance close to optimal so as not to tempt people to make the code messy with unprincipled optimizations. Clean code does one thing well. -Bjarne Stroustrup, inventor of C++ and author of The C++ Programming Language

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Eating animals nose to tail is what made us human! Transitioning from scavengers to hunters appears to have been the defining moment in our evolution as humans.

The recent recognition that the genetic code possesses a unique capacity to resist errors caused by mutation imparts the biochemical intelligent design argument with an entirely new level of credibility. Like a giant SOS shaped with letters ablaze, the optimal nature of the genetic code signals that an Intelligent Agent used those rules to start and sustain life.

There is a purpose of life in the nerd world, which is treating reality as code, and optimizing it. Life becomes a problem-solving activity, and the problem is some sort of lack of optimization.

Debugging tip: For server applications, be sure to always specify the -server JVM command line switch when invoking the JVM, even for development and testing. The server JVM performs more optimization than the client JVM, such as hoisting variables out of a loop that are not modified in the loop; code that might appear to work in the development environment (client JVM) can break in the deployment environment (server JVM).

The paper comes in plastic, a little thinner each week, a few more ads. Pretty soon there'll be no news. We'll be underwhelmed, over-bored & all storied out. The clouds ready to burst with our blue-skinned memories. Everyone with a blog, a website, an online store, dedicated server & two-dimensional quick-response-coded documentary made about their precious life. Our brains at maximum capacity, running optimization programs to recover what's left of our sanity. Still, we hope. We go see the latest blockbuster, buy the latest iPhone, zone out in front of our schizo-screens drinking jugs of moonshine corn syrup with our latent mutant meals. Facebook keeps us chained to our pasts, our posts, screwed in our seats... Scarecrows surrounded by night soil & spirits. Your acid shield may protect you from outside threat, but it'll never protect you from yourself.

What a blessing, what a treasured friend that despair turned out to be. It continually crushed my ongoing attempts at manufacturing optimism, slowing me down, leveling me so I could return to love and begin again and again.

Evolution has been working toward optimizing the human genome for 3.85 billion years,” says NIH director Francis Collins, who is not an atheist. “Do we really think that some small group of human genome tinkerers could do better without all sorts of unintended consequences?

Evolutionaries and connectionists have something important in common: they both design learning algorithms inspired by nature. But then they part ways. Evolutionaries focus on learning structure; to them, fine-tuning an evolved structure by optimizing parameters is of secondary importance. In contrast, connectionists prefer to take a simple, hand-coded structure with lots of connections and let weight learning do all the work. This is machine learning’s version of the nature versus nurture controversy, and there are good arguments on both sides.

The upper limit for protein in our diets seems to be about 40 percent of our total calorie intake, beyond which point we might exceed the liver’s ability to process this macronutrient. This means that 60 percent of our caloric needs must be met by either fat or carbohydrates.

There are examples of heavily-muscled body builders who don’t consume animal foods, but in order to maintain this physique, they must ingest tons of highly processed plant protein powders, with all of their heavy metal contaminants, lectins, oxalates, and other anti-nutrients.

Unlike self-esteem, optimism isn’t a judgment on your inner self-worth; it’s an attitude you have that is based on your view of the outside world. You’re not optimistic because of your talents or your innate goodness; you are optimistic because you interpret the world positively.

Throw in the valley’s rich history of computer science breakthroughs, and you’ve set the stage for the geeky-hippie hybrid ideology that has long defined Silicon Valley. Central to that ideology is a wide-eyed techno-optimism, a belief that every person and company can truly change the world through innovative thinking. Copying ideas or product features is frowned upon as a betrayal of the zeitgeist and an act that is beneath the moral code of a true entrepreneur. It’s all about “pure” innovation, creating a totally original product that generates what Steve Jobs called a “dent in the universe.” Startups that grow up in this kind of environment tend to be mission-driven. They start with a novel idea or idealistic goal, and they build a company around that. Company mission statements are clean and lofty, detached from earthly concerns or financial motivations.

For example, once a month I might actually skip going to the gym one day and instead read about new workout routines, buy a new fitness app, or study a new fitness method to optimize my gym time. This is what I mean by the discovery process. You step back from what you’re doing and seek to discover new ways to do it better.

I will never turn my back on the ocean: Passion I will paddle around the impact zone: No short cuts I will take the drop with commitment: Courage, focus and determination I will never fight a rip tide: The danger of pride and egotism I will always paddle back out: Perseverance in the face of challenges I will watch out for other surfers after a big set: Responsibility I will know that there will always be another wave: Optimism I will ride and not paddle into shore: Self-esteem I will pass on my stoke to a non-surfer: Sharing knowledge and giving back I will catch a wave every day, even in my mind: Imagination I will realize that all surfers are joined by one ocean: Empathy I will honor the sport of kings: Honor and integrity

(1) Every human movement, thought, or feeling is a precisely timed electric signal traveling through a chain of neurons—a circuit of nerve fibers. (2) Myelin is the insulation that wraps these nerve fibers and increases signal strength, speed, and accuracy. (3) The more we fire a particular circuit, the more myelin optimizes that circuit, and the stronger, faster, and more fluent our movements and thoughts become.

1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation

Phase 4: Future Dreams Up to this point, you’ve focused on the present. In this phase, you express intentions for your future happiness. I credit this phase with the massive growth and joy I’ve experienced in my career. Years ago, I visualized the life I have today. Today, I visualize years ahead while still being happy in the now. Doing this on a daily basis seems to help my brain find the optimal paths to realizing my dreams. When I’m visualizing my future life, I think three years ahead, and I suggest you do the same in this phase. And whatever you see three years ahead—double it. Because your brain will underestimate what you can do. We tend to underestimate what we can do in three years and overestimate what we can do in one year. Some people think that being “spiritual” means having to be content with one’s current life. Rubbish. You should be happy no matter where you are. But that shouldn’t stop you from dreaming, growing, and contributing. Choose an end goal from your answers to the Three Most Important Questions in Chapter 8 and spend a few minutes just imagining and thinking with joy about what life would be like if you had already attained this end goal.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics.

In about 1951, a quality approach called Total Productive Maintenance (TPM) came on the Japanese scene. Its focus is on maintenance rather than on production. One of the major pillars of TPM is the set of so-called 5S principles. 5S is a set of disciplines—and here I use the term “discipline” instructively. These 5S principles are in fact at the foundations of Lean—another buzzword on the Western scene, and an increasingly prominent buzzword in software circles. These principles are not an option. As Uncle Bob relates in his front matter, good software practice requires such discipline: focus, presence of mind, and thinking. It is not always just about doing, about pushing the factory equipment to produce at the optimal velocity. The 5S philosophy comprises these concepts: • Seiri, or organization (think “sort” in English). Knowing where things are—using approaches such as suitable naming—is crucial. You think naming identifiers isn’t important? Read on in the following chapters. • Seiton, or tidiness (think “systematize” in English). There is an old American saying: A place for everything, and everything in its place. A piece of code should be where you expect to find it—and, if not, you should re-factor to get it there. • Seiso, or cleaning (think “shine” in English): Keep the workplace free of hanging wires, grease, scraps, and waste. What do the authors here say about littering your code with comments and commented-out code lines that capture history or wishes for the future? Get rid of them. • Seiketsu, or standardization: The group agrees about how to keep the workplace clean. Do you think this book says anything about having a consistent coding style and set of practices within the group? Where do those standards come from? Read on. • Shutsuke, or discipline (self-discipline). This means having the discipline to follow the practices and to frequently reflect on one’s work and be willing to change.

In an ideal world, a young man should not be an ironical person. At that age, irony prevents growth, stunts the imagination. It is best to start life in a cheerful and open state of mind, believing in others, being optimistic, being frank with everyone about everything. And then, as one comes to understand things and people better, to develop a sense of irony. The natural progression of human life is from optimism to pessimism; and a sense of irony helps temper pessimism, helps produce balance, harmony. But this was not an ideal world, and so irony grew in sudden and strange ways. Overnight, like a mushroom; disastrously, like a cancer. — Sarcasm was dangerous to its user, identifiable as the language of the wrecker and the saboteur. But irony—perhaps, sometimes, so he hoped—might enable you to preserve what you valued, even as the noise of time became loud enough to knock out windowpanes. What did he value? Music, his family, love. Love, his family, music. The order of importance was liable to change. Could irony protect his music? In so far as music remained a secret language which allowed you to smuggle things past the wrong ears. But it could not exist only as a code: sometimes you ached to say things straightforwardly. Could irony protect his children? Maxim, at school, aged ten, had been obliged publicly to vilify his father in the course of a music exam. In such circumstances, what use was irony to Galya and Maxim? As for love—not his own awkward, stumbling, blurting, annoying expressions of it, but love in general: he had always believed that love, as a force of nature, was indestructible; and that, when threatened, it could be protected, blanketed, swaddled in irony. Now he was less convinced. Tyranny had become so expert at destroying that why should it not destroy love as well, intentionally or not? Tyranny demanded that you love the Party, the State, the Great Leader and Helmsman, the People. But individual love—bourgeois and particularist—distracted from such grand, noble, meaningless, unthinking “loves.” And in these times, people were always in danger of becoming less than fully themselves. If you terrorised them enough, they became something else, something diminished and reduced: mere techniques for survival. And so, it was not just an anxiety, but often a brute fear that he experienced: the fear that love’s last days had come.

five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

I became a broken record on the algorithm,” Musk says. “But I think it’s helpful to say it to an annoying degree.” It had five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

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Most code writers were like gifted athletes; they learned by doing and could not explain their actions. They just did it. This method, while fine for getting started, often hampered efforts at making code faster, which required unblinking self-analysis. “The secret to optimizing speed” he said, “is to ask yourself, ‘What does this code actually need to do? What’s the least work I can do to solve this problem?’ ” All

After all of this you're still 'Rayhan the Chivalrous', full of hope and optimism?

The researchers looked deeper into these observations, in hopes of gaining insight into the mechanisms underlying the high evolutionary rate and extraordinary immunologic plasticity of influenza HA. They probed in more detail the precise codons that are used by the virus to encode the influenza HA1 protein. The discriminated between codons on the basis of volatility. Each three-nucleotide codon is related by a single nucleotide change to nine 'mutational neighbours.' Of those nine mutations, some proportion change the codon to a synonymous codon and some change it to a nonsynonymous one, which directs the incorporation of a different amino acid into the protein. More volatile codons are those for which a larger proportion of those nine mutational neighbours encode an amino acid change. The use of particular codons in a gene at a frequency that is disproportionate to their random selection for encoding a chosen amino acid is termed codon bias. Such bias is common and is influenced by many factors, but here the collaborators found strong evidence for codon bias that was particular for and restricted to the amino acids making up the HA1 epitopes. Remarkably, they observed that influenza employs a disproportionate number of volatile codons in its epitope-coding sequences. There was a bias for the use of codons that had the fewest synonymous mutational neighbours. In other words, influenza HA1 appears to have optimized the speed with which it can change amino acids in its epitopes. Amino acid changes can arise from fewer mutational events. The antibody combining regions are optimized to use codons that have a greater likelihood to undergo nonsynonymous single nucleotide substitutions : they are optimized for rapid evolution.

Expert Tips On Search Engine Optimization That Are Proven To Work Each business with a Web site needs to make Search Engine Optimization (SEO) part of their growth strategy, working to get their site ranked as high as possible on the major search engines. With a little work, a different approach, and these tips, you can get your site ranked well with the search engines. To create more traffic to your site and to improve your standings with search engines, you can write and submit articles to online article directories. The directories make their articles available to countless people who will read your submissions and follow the links back to your site. This has the potential to bring traffic to your site far into the future as these links remain active for many years. To help site crawlers better understand your site, you should use keywords as your anchor text for internal links. Non-descript links such as, "click here," do not help your site as they offer no information to the search engines. This will also help your site to appear more cohesive to human visitors. Be varied in the page titles of your site, but not too lengthy. Targeting over 70 characters will begin to diminish the weight of the page or site. Keep the titles condensed and intersperse a wide variety of your keywords and phrases amongst them. Each individual page will add its own weight to the overall search. In order to optimize incoming links to raise your search engine rankings, try to have links to different parts of your website, not just your homepage. Search engine spiders read links to different parts of your site, as meaning that your site is full of useful and relevant content and therefore, ranks it higher. One way to enhance your standing in website search rankings is to improve the time it takes your website to load. Search engines are looking to deliver the best possible experience to their searchers and now include load time into their search ranking protocols. Slow loading sites get lost in the mix when searchers get impatient waiting for sites to load. Explore ways to optimize your loading process with solutions like compressed images, limited use of Flash animations and relocating JavaScript outside your HTML code. Publish content with as little HTML code as possible. Search engines prefer pages that favor actual content instead of tons of HTML code. In fact, they consistently rank them higher. So, when writing with SEO in mind, keep the code simple and concentrate on engaging your audience through your words. Do not obsess over your page rankings on the search engines. Your content is more important than your rank, and readers realize that. If you focus too much on rank, you may end up accidentally forgetting who your true audience is. Cater to your customers, and your rank will rise on its own. As you can see, you need to increase your site's traffic in order to get ranked higher. This is possible to anyone who is willing to do what it takes. Getting your site ranked with the top search engines is highly possible, and can be done by anyone who will give it a chance.

You don’t actually need to worry too much about the difference between const and final constants. As a general rule, try const first, and if the compiler complains, then make it final. The benefit of using const is it gives the compiler the freedom to make internal optimizations to the code before compiling it.

The criteria that I found most valuable when making my decisions were the following: What is the size of the investor community invested in other offerings on the platform to-date? Does the platform accept investments via credit card? For example, about 40% of my crowdfunding investors invested with a credit card. Does the platform allow for campaign extensions (if you fall short of your goal within your campaign period, can you extend the campaign until you reach your goal)? I’ve extended my campaigns multiple times. Does the platform allow for multiple disbursements? I prefer to disburse money from my campaign once a month. However, many platforms don’t allow you to disburse the funds until after the campaign is over What are the fees? Platforms can charge between 5-20% of your raise as fees, with some platforms having complicated fee structures that involve taking some of your Securities as part of the offering. Some platforms require you to pay them cash upfront before launching an offering. Does the platform allow you to set your own terms? For example, some platforms don’t allow you to sell convertible notes. Some others don’t allow you to sell non-voting common stock. Some platforms insist that they set the valuation for your startup in order to launch—the logic being that they know their investors, and they want to provide them with a “good deal.” For many reasons, you want to sell the Security that’s right for your startup. Does the platform allow you to have design freedom on the campaign page? You want to make sure that your brand is well represented. The aesthetics and optimization of the page are highly correlated with conversion (how many people invest after visiting your page). Does the platform support analytics? You need advanced analytics to market your offering. Some platforms, for example, allow you to enter a Facebook Pixel and Google Analytics code into the campaign page, while others do not. Does the platform have a good reputation? You will be driving a lot of potential investors and media folks to this platform, and you want to be sure that your platform of choice hasn’t been involved in anything shady in the past. Does the platform allow you to update your investors and prospective investors with campaign notifications? Some platforms have a built-in functionality where you can post updates right on the campaign, download email, and mailing contact lists of your investors (allowing you to contact them by email and allowing you to build Facebook “lookalike audiences”). Whereas, other platforms don’t even share the email addresses of the folks who have already invested in your startup. Does the platform support or plan to support secondary trading for the Securities that it sells on its platform? Will your investors be able to sell the Securities that they buy from you? The ability to sell Securities in a marketplace brings a lot of liquidity and increases its value significantly. In order to allow for secondary trading, the platform needs to obtain an Alternative Trading System (ATS) approval from FINRA.

Societally, we will need to see shifts in how we—including the medical community—approach wellness. Instead of hospitals being repositories for the sick, they will need to become wellness centers after recovery or treatment reverses major issues. That is, they will need to focus on prevention, on health optimization, on opportunities to reboot our bodies. Many more people will recover from illness at home, as hospitals will bring those facilities and services to you, and less expensively. Note: With a decrease in fertility we expect more stabilization of pediatric and delivery centers, and with an increase in longevity we will see growth of plastic surgery and cosmetic procedures.

This man was 102 at a time, and he had a vegetable garden. I asked him, what are you doing with this garden? He said, well, it's great, just wait until you'll see it in three years. They plan ahead, looking forward to what is to come and the biology follows to a certain degree. Why? Because if you think you're going to be around forever, even if you're not, the subconscious thoughts of your brain that you have, adjust your biology. That doesn't mean you're going to live forever, but it means that you get the fear out of tomorrow.

Peptides are proving to be the ultimate anti-aging therapy, preventing and reversing the underlying causes of many aspects of aging and the subsequent decline in function and degeneration. This, along with their impressive safety profile, means they can potentially shift the medical paradigm from one of waiting to treat age-related diseases as they occur to one of prevention.

Brain entrainment: Neurofeedback (NFB) Transcranial Magnetic Stimulation (TMS) Brain Computer Interface (BCI) Hyperbaric Oxygen Therapy (HBOT) Floatation Tanks (REST) Reduced Environmental Stimulation Therapy Nootropics: Caffeine Nicotine Lion’s Mane mushroom Adderall Ritalin Modafinil Brahmi Winter Cherry (Ashwagandha) “Qualia Mind” a proprietary blend Ginkgo Biloba Maca root Yerba Mate Green Tea Aniracetam Phosphatidylserine Plant Medicines & Psychedelics: Ketamine LSD Psilocybin Iboga MDMA

The bottom line, when it comes to rebooted retirement, is that it’s not just about a new “length of service.” It’s also a mindset shift, in which you’re only partially defined by what you do. Other criteria include how well you adapt to a variety of careers—ones that will hopefully give you a sense of purpose, satisfaction, and optimism. Some things to consider when it comes to a new approach to retirement: •   Zero in on the aspects of your work that you love and physically can do and focus on those. •   Examine educational opportunities to develop skills in new areas that will allow you to keep pursuing your passions. •   Assuming you’re financially stable, consider a second (or third or fourth) career in new areas in which you’re motivated by passion, rather than money.

Capitalism is not loving. In fact, it has no moral code; as an economic system, it is simply a system for the exchange of value. And it is in this exchange that the social system begins. If the strongest defining trait of capitalism is optimization, its next might be exploitation. At its best, it will exploit inefficiencies and unfulfilled needs and wants. At its worst, left to its own devices, it will exploit people, the environment, and all types of resources.

The connection between learning and evolution was proposed in 1896 by the American psychologist James Baldwin7 and independently by the British ethologist Conwy Lloyd Morgan8 but not generally accepted at the time. The Baldwin effect, as it is now known, can be understood by imagining that evolution has a choice between creating an instinctive organism whose every response is fixed in advance and creating an adaptive organism that learns what actions to take. Now suppose, for the purposes of illustration, that the optimal instinctive organism can be coded as a six-digit number, say, 472116, while in the case of the adaptive organism, evolution specifies only 472*** and the organism itself has to fill in the last three digits by learning during its lifetime. Clearly, if evolution has to worry about choosing only the first three digits, its job is much easier; the adaptive organism, in learning the last three digits, is doing in one lifetime what evolution would have

Many have been supposedly foolproof but zany formulae that have made no one rich but the hucksters who sold them to the gullible. But over the years there have been some approaches that have enjoyed at least a modicum of success. These range from the Dow Theory first espoused by Wall Street Journal founder Charles Dow—essentially using technical indicators to try to identify and profit from different market phases—and David Butler’s CANSLIM system, to the value investing school articulated by Benjamin Graham. The earth-shattering suggestion of the research conducted in the 1960s and 1970s was that the code might actually be unbreakable, and efforts to decipher it were expensive and futile. Harry Markowitz’s modern portfolio theory and William Sharpe’s CAPM indicated that the market itself was the optimal balance between risks and return, while Gene Fama presented a cohesive, compelling argument for why that was: The net effect of the efforts of thousands upon thousands of investors continually trying to outsmart each other was that the stock market was efficient, and in practice hard to beat. Most investors should therefore just sit on their hands and buy the entire market. But in the 1980s and 1990s, a new round of groundbreaking research—some of it from the same efficient-markets disciples who had rattled the investing world in the 1960s and 1970s—started revealing some fault lines in the academic edifice built up in the previous decades. Perhaps the stock market wasn’t entirely efficient, and maybe there were indeed ways to beat it in the long run? Some gremlins in the system were always known, but often glossed over. Already in the early 1970s, Black and Scholes had noted that there were some odd issues with the theory, such as how less volatile stocks actually produced better long-term returns than choppier ones. That contradicted the belief that return and risk (using volatility as a proxy for risk) were correlated. In other words, loopier roller coasters produce greater thrills. Though the theory made intuitive sense, in practice it didn’t seem to hold up to rigorous scrutiny. This is why Scholes and Black initially proposed that Wells Fargo should set up a fund that would buy lower-volatility stocks (that is, low-beta) and use leverage to bring the portfolio’s overall volatility up to the broader stock market.7 Hey, presto, a roller coaster with the same number of loops as everyone else, but with even greater thrills. Nonetheless, the efficient-markets hypothesis quickly became dogma at business schools around the United States.

When our brains were initially configured, back in the caveman times, they were optimized for making split-second decisions that aided our survival. What’s interesting, though, is if you haven’t taken the time to install scripts overriding that initial configuration, those settings are still set on default in your modern mind4: Notice the bad, the negative, and potentially harmful, and focus on that. Relive difficult moments in order to learn. Worry about the future. Have a strong need to belong to a group, fit in and contribute.

EAN codes ordinarily have the first three digits (the prefix) identifying the country of manufacture, but that doesn't make sense for books. The industry committee's clever solution was to invent two new imaginary countries -- called Bookland 1 and Bookland 2 -- with corresponding prefixes of 978 and 979." (29)

Rushing to optimize before the bottlenecks are known may be the only error to have ruined more designs than feature creep. From tortured code to incomprehensible data layouts, the results of obsessing about speed or memory or disk usage at the expense of transparency and simplicity are everywhere. They spawn innumerable bugs and cost millions of man-hours—often, just to get marginal gains in the use of some resource much less expensive than debugging time. Disturbingly often, premature local optimization actually hinders global optimization (and hence reduces overall performance). A prematurely optimized portion of a design frequently interferes with changes that would have much higher payoffs across the whole design, so you end up with both inferior performance and excessively complex code.

Inheriting from Application is shorter than writing an explicit main method, but it also has some shortcomings. First, you can't use this trait if you need to access command-line arguments, because the args array isn't available. For example, because the Summer application uses command-line arguments, it must be written with an explicit main method, as shown in Listing 4.3. Second, because of some restrictions in the JVM threading model, you need an explicit main method if your program is multi-threaded. Finally, some implementations of the JVM do not optimize the initialization code of an object which is executed by the Application trait. So you should inherit from Application only when your program is relatively simple and single-threaded.

Section One Summary Here’s what you should take away from this section about on-page optimization:         On-page optimization is what you do on your website to influence SERPs on Google.         Doing proper keyword research is the first step to a successful SEO campaign.         Having proper meta tags is essential. Always include your keyword phrase(s) in your meta tags.         The proper meta tags include your title tag, description tag, keywords tag, and robots tag.         Choose your URL carefully. Your URL doesn’t have to have your keyword included but it helps when other sites link to your site. Avoid exact match domains.         How you format your page is important for optimization purposes.         Make sure you design your web pages so Google is forced to read your on-page content first.         Verify that your code is W3C compliant.         Don’t forget to include your keyword phrase(s) in , , and header tags. This signifies the importance of your content to Google.         Label each graphic with an alt tag that includes your keyword phrase.         Place your keyword(s) in the first twenty-five words on your web page and the last twenty-five words on your web page.         Eliminate Flash if it’s the main presentation of your website. Google does not view this favorably.         If you’re going to use JavaScript to enhance the overall visitor experience of your website, place the code in an external file.         Include a sitemap that’s easily accessible by Google. Submit an XML version of your sitemap through Google Webmaster Tools.          Never underestimate the power of internal linking. A good internal linking structure can improve your SERPs.          Keyword development is one of the most important on-page optimization strategies.          Research keywords and competing websites to select ideal keywords.          Research the strength of competing websites before selecting your final keywords using Google PR and authority (ex: number of inbound links).          Page load speed is a significant factor in Google rankings. Ensure that your home page loads more quickly than those of competing

In order to optimize the memory-dominated effects, let us try using the same method we used in Example 6-6 in order to reduce the number of allocations we make in our numpy code. Allocations are quite a bit worse than the cache misses we discussed previously. Instead of simply having to find the right data in RAM when it is not found in the cache, an allocation also must make a request to the operating system for an available chunk of data and then reserve it. The request to the operating system generates quite a lot more overhead than simply filling a cache — while filling a cache miss is a hardware routine that is optimized on the motherboard, allocating memory requires talking to another process, the kernel, in order to complete. In order to remove the allocations in Example 6-9, we will preallocate some scratch space at the beginning of the code and then only use in-place operations. In-place operations, such as +=, *=, etc., reuse one of the inputs as their output. This means that we don’t need to allocate space to store the result of the calculation.

One downfall of numpy’s optimization of vector operations is that it only occurs on one operation at a time. That is to say, when we are doing the operation A * B + C with numpy vectors, first the entire A * B operation completes, and the data is stored in a temporary vector; then this new vector is added with C. The in-place version of the diffusion code in Example 6-14 shows this quite explicitly. However, there are many modules that can help with this. numexpr is a module that can take an entire vector expression and compile it into very efficient code that is optimized to minimize cache misses and temporary space used. In addition, the expressions can utilize multiple CPU cores (see Chapter 9 for more information) and specialized instructions for Intel chips to maximize the speedup. It is very easy to change code to use numexpr: all that’s required is to rewrite the expressions as strings with references to local variables. The expressions are compiled behind the scenes (and cached so that calls to the same expression don’t incur the same cost of compilation) and run using optimized code. Example 6-19 shows the simplicity of changing the evolve function to use numexpr. In this case, we chose to use the out parameter of the evaluate function so that numexpr doesn’t allocate a new vector to which to return the result of the calculation.

One important lesson to take away from this is that you should always take care of any administrative things the code must do during initialization. This may include allocating memory, or reading configuration from a file, or even precomputing some values that will be needed throughout the lifetime of the program. This is important for two reasons. First, you are reducing the total number of times these tasks must be done by doing them once up front, and you know that you will be able to use those resources without too much penalty in the future. Secondly, you are not disrupting the flow of the program; this allows it to pipeline more efficiently and keep the caches filled with more pertinent data. We also learned more about the importance of data locality and how important simply getting data to the CPU is. CPU caches can be quite complicated, and often it is best to allow the various mechanisms designed to optimize them take care of the issue. However, understanding what is happening and doing all that is possible to optimize how memory is handled can make all the difference. For example, by understanding how caches work we are able to understand that the decrease in performance that leads to a saturated speedup no matter the grid size in Figure 6-4 can probably be attributed to the L3 cache being filled up by our grid. When this happens, we stop benefiting from the tiered memory approach to solving the Von Neumann bottleneck.

It is worth noting that performing CPU and memory profiling on your code will probably start you thinking about higher-level algorithmic optimizations that you might apply. These algorithmic changes (e.g., additional logic to avoid computations or caching to avoid recalculation) could help you avoid doing unnecessary work in your code, and Python’s expressivity helps you to spot these algorithmic opportunities.

Anti-hustle is what wantrepreneurs do. They do everything other than what needs to be done. They keep coding. They design new features. They optimize their site. They think up new, world-changing ideas. They hang out at startup events discussing their idea. They go to startup weekend and launch a new idea. They do everything other than what they need to do—which, more often than not, is getting more customers.

developers' estimates tend to have an optimism factor of 20 to 30 percent

Optimize for readability first. What slows down developers when reading code

Teams now measure themselves not in terms of how many points they complete, but instead optimize for how long it takes for code to get from laptop to live

Systems Test No parts of the schedule are so thoroughly affected by sequential constraints as component debugging and system test. Furthermore, the time required depends on the number and subtlety of the errors encountered. Theoretically this number should be zero. Because of optimism, we usually expect the number of bugs to be smaller than it turns out to be. Therefore testing is usually the most mis-scheduled part of programming. For some years I have been successfully using the following rule of thumb for scheduling a software task: l /3 planning l/6 coding l/4 component test and early system test l/4 system test, all components in hand.

Use manual sanity checks in data pipelines. When optimizing data processing systems, it’s easy to stay in the “binary mindset” mode, using tight pipelines, efficient binary data formats, and compressed I/O. As the data passes through the system unseen, unchecked (except for perhaps its type), it remains invisible until something outright blows up. Then debugging commences. I advocate sprinkling a few simple log messages throughout the code, showing what the data looks like at various internal points of processing, as good practice — nothing fancy, just an analogy to the Unix head command, picking and visualizing a few data points. Not only does this help during the aforementioned debugging, but seeing the data in a human-readable format leads to “aha!” moments surprisingly often, even when all seems to be going well. Strange tokenization! They promised input would always be encoded in latin1! How did a document in this language get in there? Image files leaked into a pipeline that expects and parses text files! These are often insights that go way beyond those offered by automatic type checking or a fixed unit test, hinting at issues beyond component boundaries. Real-world data is messy. Catch early even things that wouldn’t necessarily lead to exceptions or glaring errors. Err on the side of too much verbosity.

There is only one code stream. You can develop in a temporary branch, but never let it live longer than a few hours. Multiple code streams are an enormous source of waste in software development. I fix a defect in the currently deployed software. Then I have to retrofit the fix to all the other deployed versions and the active development branch. Then you find that my fix broke something you were working on and you interrupt me to fix my fix. And on and on. There are legitimate reasons for having multiple versions of the source code active at one time. Sometimes, though, all that is at work is simple expedience, a micro-optimization taken without a view to the macro-consequences. If you have multiple code bases, put a plan in place for reducing them gradually. You can improve the build system to create several products from a single code base. You can move the variation into configuration files. Whatever you have to do, improve your process until you no longer need multiple versions of the code.

That’s because I help them understand a pearl of wisdom that I’m now going to share with you: the only way your hormones can achieve balance is if your body does the job—and only if you safeguard and nurture it, with every meal and habit, every day, to optimize endocrine function.

Life with a cheat code isn’t life. Our existence isn’t something to be engineered or optimized for the avoidance of pain. That’s what it is to be human—the beauty and the pain, each meaningless without the other.

...natural selection is not the only process at work in evolution; there is also (among others) random genetic drift, which 'can lead to the elimination of a more fit gene and the fixation of a less fit one.' For example, a genetically based and adaptively favorable trait might arise within a population of sea gulls; perhaps six members of the flock enjoy it. Being birds of a feather, they flock together-sadly enough, at the site of a natural so that all are killed in a tidal wave or volanic eruption or by a large meteorite. The more fit gene thus gets eliminated from the population. (There is also the way in which a gene can be fixed, in a small population, by way of random walk.)...there is no reason to think it inevitable that natural selection will have the opportunity to select for optimal design. For example, an adaptively positive trait might be linked with an adaptively negative trait by pleiotropy (where one gene codes for more than one trait or system); then it could happen that the genes get selected and perpetuated by virtue of its link with the gene. A truly optimal system-one with the positive trait but without the negative-may never show up, or may show up too late to fit in with the current development of the organism.

Imagine your gut microbiota as controlling a light switch and the wiring behind the wall is your genetic code. The gut microbiota is not changing the wiring behind the wall, but it can turn the lights on or off. You can’t change your genetic code, but you can effect which genes get turned on or off.

Search Engine Optimization is basically the process of enhancing the quantity and quality of site traffic to a particular site or a web site from search engines. SEO focuses on paid rather than organic traffic, and unpaid visitors rather than paid advertising or sponsored links. SEO helps increase the visibility of a site by making sure that its contents are relevant and informative. Several things can affect search engine rankings, including keyword relevancy, backlinking, title tags, meta tags, and description tags. It is important that your content is keyword-rich and that it contains keywords that are commonly used by search engine crawlers. This ensures that when a search engine user performs a search on a particular topic, they find what they are looking for. Keyword-rich content gives a higher chance of appearing in search results. Search Engine Optimization also works well in promoting your website by ensuring that your keywords appear in the meta tags of the HTML code and in the description tag of every web page that you create.

In our modern paradigm that glorifies an addiction to work and busyness, rest is judged as weak or lazy, instead of essential and sacred.

Just as the Earth upgrades if allowed to rest after every major stress such as wildfires, we can unlock the hidden information in the genome by honoring these laws and our inherent connection to them.

when it comes to longevity, the appropriate quantity and quality of sleep leads to an incredible ROI.

the most effective way to leverage health and longevity was to disrupt this cultural shame pattern around rest, give myself and my patients permission to recover, and return to basic laws of nature.

our bodies ARE the technology we can upgrade by respecting ancient traditions of connecting to the earth.

The magic, however, is not in the stress, but in the recovery.

Giving your brain and body permission for downtime allows it to heal DNA damage, lengthen telomeres, regulate hormones, activate the DMN, integrate self-identity, and breathe properly; this increases your healthspan.

What becomes possible for us when our longevity is addressed before we are even conceived?

sleeping in the cold on an empty stomach turns on longevity genes!

I never saw how empty my tank was because society rewarded me for not sleeping, not resting, and never taking a break.

Regardless of how your designs were created, InVision and Marvel allow you to easily turn them into functional prototype websites. With InVision, you upload your page designs, and then link them together to make the website navigable. Then, you can carry out user tests on what, to the users, appears to be a real website, even though it hasn’t seen a smidgen of code. InVision also allows other people to give written feedback on your work-in-progress designs. You upload your designs, and then invite others to annotate them with whatever type of feedback you desire. Notable has similar functionality. Alternatives include Firefly and BugHerd. The Composite app connects to Photoshop files, turning them into clickable prototypes. To gather feedback on your work-in-progress videos, you can use Frame.io, a fantastic web-based platform. Alternatives include Wipster, Symu, Vidhub, and Kollaborate. Such services provide great benefits; it’s hard to gather and record such feedback even when everyone’s in the same room. Optimal Workshop provides several tools (OptimalSort, Treejack, and Chalkmark) to help you optimize your website’s navigation and information architecture. The tools are described in our article about card sorting. Alternatives for card sorting include SimpleCardSort, UsabiliTEST, and Xsort.

And when you're doing novelty kinds of things, the feeling is that you have more time. If you lose the novelty effect after 30 years, you've done this, you've done that, then you compress time. Centenarians always have something going. They have a novelty effect, very high. They elongate the perception of time. So

The Bale Doneen method allows for a complete genetic and blood serum testing package that will look at markers of inflammation, glucose, insulin, lipo protein, cholesterol particle size paired with genetic propensities. Check for arterial plaque. A coronary calcium scan, is a non-invasive, low-radiation imaging test, identifies calcified plaque buildup in the arteries of the heart. A blood test for C-reactive protein indicates inflammation. A blood test for the hormone NT-proBNP indicates stress on the heart. A blood test for high-sensitivity troponin T indicates damage to heart muscle. Troponin testing is regularly used by hospitals to diagnose heart attacks, but high-sensitivity troponin fine-tunes that measure, pointing to small amounts of damage that can be detected in individuals without any symptoms or warning signs.

In the brain, there’s a similar system called the glia-lymphatic system (really glymphatic but let’s use glia-lymphatic as we think it describes the system better).2 But often we don’t have optimal ability to clear waste from that area. Not surprisingly, this circumstance is largely related to the food we eat, how much exercise we get, and other lifestyle choices we make, especially regarding sleep.

work for everyone. Put differently, at the Collective, we have a saying: “Personality doesn’t scale. Biology scales.” What we mean is, in the field of peak performance, too often, someone figures out what works for them and then assumes it will work for others. It rarely does. More often, it backfires. The issue is that personality is extremely individual. Traits that play a critical role in peak performance—such as your risk tolerance or where you land on the introversion-to-extroversion scale—are genetically coded, neurobiologically hardwired, and difficult to change. Add in all the possible environmental influences that come from variations in cultural background, financial means, and social status, and the problem compounds. For all these reasons, what works for me is almost guaranteed not to work for you. Personality doesn’t scale. Biology, on the other hand, scales. It is the very thing designed by evolution to work for everyone. And this tells us something important about decoding the impossible: if we can get below the level of personality, beneath the squishy and often subjective psychology of peak performance, and decode the foundational neurobiology, then we unearth mechanism. Basic biological mechanism. Shaped by evolution, present in most mammals and all humans. And this leads us to the next question: What’s the biological formula for the impossible? The answer is flow. Flow is defined as “an optimal state of

Like most children of her era, she’d been taught to believe that the genome—the sequence of base pairs expressed in the chromosomes in every nucleus of the body—said everything there was to say about the genetic destiny of an organism. A small minority of those DNA sequences had clearly defined functions. The remainder seemed to do nothing, and so were dismissed as “junk DNA.” But that picture had changed during the first part of the twenty-first century, as more sophisticated analysis had revealed that much of that so-called junk actually performed important “roles in the functioning of cells by regulating the expression of genes. Even simple organisms, it turned out, possessed many genes that were suppressed, or silenced altogether, by such mechanisms. The central promise of genomics—that by knowing an organism’s genome, scientists could know the organism—had fallen far short as it had become obvious that the phenotype (the actual creature that met the biologist’s eye, with all of its observable traits and behaviors) was a function not only of its genotype (its DNA sequences) but also of countless nanodecisions being made from moment to moment within the organism’s cells by the regulatory mechanisms that determined which genes to express and which to silence. Those regulatory mechanisms were of several types, and many were unfathomably complex. Had it not been for the sudden intervention of the Agent, the biologists of Old Earth would have devoted at least the “remaining decades of the century to cataloging these mechanisms and understanding their effects—a then-new science called epigenetics. Instead of which, on Cleft, in the hands of Eve Moira and the generations of biologists she reared, it became a tool. (...) Thousands of years later, epigenetics was sufficiently well understood to be programmed into the DNA of some of the newly created species that would be let loose on the surface of New Earth. And one of the planks in the Get It Done platform was to use epigenetics for all it was worth. So rather than trying to sequence and breed a new subspecies of coyote that was optimized for, and that would breed true in, a particular environment, the GID approach was to produce a race of canines that would, over the course of only a few generations, become coyotes or wolves or dogs—or something that didn’t fit into any of those categories—depending on what happened to work best. They would all start with a similar genetic code, but different parts of it would end up being expressed or suppressed depending on circumstances. And no particular effort would be made by humans to choose and plan those outcomes. They would seed New Earth and see what happened. If an ecosystem failed to “take” in a particular area, they “they would just try something else. In the decades since such species had been seeded onto New Earth, this had been going on all the time. Epigenetic transformation had been rampant. Still, when it led to results that humans saw, and happened to find surprising, it was known as “going epi.

A culture can be thought of as ever-evolving software that sits on top of—and synergistically interacts with—both biological hardware and firmware, addressing flaws our biology hasn’t had sufficient evolutionary time to address. To go further with this analogy: Biological evolution provides some basic coding, much like a low-level programming language might for a given hardware, whereas cultural evolution manipulates the high-level, object-oriented code that lets us program highly nuanced behaviors.

Waterhouse seeks happiness. He achieves it by breaking Nip code systems and playing the pipe organ. But since pipe organs are in short supply, his happiness level ends up being totally dependent on breaking codes. He cannot break codes (hence, cannot be happy) unless his mind is clear. Now suppose that mental clarity is designated by Cm, which is normalized, or calibrated, in such a way that it is always the case that where Cm = 0 indicates a totally clouded mind and Cm = 1 is Godlike clarity—an unattainable divine state of infinite intelligence. If the number of messages Waterhouse decrypts, in a given day, is designated by Ndecrypts, then it will be governed by Cm in roughly the following way: Clarity of mind (Cm) is affected by any number of factors, but by far the most important is horniness, which might be designated by σ, for obvious anatomical reasons that Waterhouse finds amusing at this stage of his emotional development. Horniness begins at zero at time t = t0 (immediately following ejaculation) and increases from there as a linear function of time: The only way to drop it back to zero is to arrange another ejaculation. There is a critical threshold σc such that when σ > σc it becomes impossible for Waterhouse to concentrate on anything, or, approximately, which amounts to saying that the moment σ rises above the threshold σc it becomes totally impossible for Waterhouse to break Nipponese cryptographic systems. This makes it impossible for him to achieve happiness (unless there is a pipe organ handy, which there isn’t). Typically, it takes two to three days for σ to climb above σc after an ejaculation: Critical, then, to the maintenance of Waterhouse’s sanity is the ability to ejaculate every two to three days. As long as he can arrange this, σ exhibits a classic sawtooth-wave pattern, optimally with the peaks at or near σc [see below] wherein the grey zones represent periods during which he is completely useless to the war effort. So much for the basic theory.

Your body is self-healing. It knows perfectly what’s wrong with you and what you really need to function optimally. The Body Code is how we ‘decode’ those needs. We can use it to identify underlying causes of your issues and use our combined intention to clear them or find out what else you may need. This technique is not meant to replace any medical treatment, but by correcting underlying imbalances, we help the body’s innate self-healing ability to take over. And many appreciate that this healing process does not

Silicon Valley’s and China’s internet ecosystems grew out of very different cultural soil. Entrepreneurs in the valley are often the children of successful professionals, such as computer scientists, dentists, engineers, and academics. Growing up they were constantly told that they—yes, they in particular—could change the world. Their undergraduate years were spent learning the art of coding from the world’s leading researchers but also basking in the philosophical debates of a liberal arts education. When they arrived in Silicon Valley, their commutes to and from work took them through the gently curving, tree-lined streets of suburban California. It’s an environment of abundance that lends itself to lofty thinking, to envisioning elegant technical solutions to abstract problems. Throw in the valley’s rich history of computer science breakthroughs, and you’ve set the stage for the geeky-hippie hybrid ideology that has long defined Silicon Valley. Central to that ideology is a wide-eyed techno-optimism, a belief that every person and company can truly change the world through innovative thinking. Copying ideas or product features is frowned upon as a betrayal of the zeitgeist and an act that is beneath the moral code of a true entrepreneur. It’s all about “pure” innovation, creating a totally original product that generates what Steve Jobs called a “dent in the universe.” Startups that grow up in this kind of environment tend to be mission-driven. They start with a novel idea or idealistic goal, and they build a company around that. Company mission statements are clean and lofty, detached from earthly concerns or financial motivations. In stark contrast, China’s startup culture is the yin to Silicon Valley’s yang: instead of being mission-driven, Chinese companies are first and foremost market-driven. Their ultimate goal is to make money, and they’re willing to create any product, adopt any model, or go into any business that will accomplish that objective. That mentality leads to incredible flexibility in business models and execution, a perfect distillation of the “lean startup” model often praised in Silicon Valley. It doesn’t matter where an idea came from or who came up with it. All that matters is whether you can execute it to make a financial profit. The core motivation for China’s market-driven entrepreneurs is not fame, glory, or changing the world. Those things are all nice side benefits, but the grand prize is getting rich, and it doesn’t matter how you get there.

value, I can do three things,” he says. “I can improve the algorithm itself, make it more sophisticated. I can throw more and better data at the algorithm so that the existing code produces better results. And I can change the speed of experimentation to get more results faster. “We focused on data and speed, not on a better algorithm.” Candela describes this decision as “dramatic” and “hard.” Computer scientists, especially academic-minded ones, are rewarded for inventing new algorithms or improving existing ones. A better statistical model is the goal. Getting cited in a journal is validation. Wowing your peers gives you cred. It requires a shift in thinking to get those engineers to focus on business impact before optimal statistical model. He thinks many companies are making the mistake of structuring their efforts around building the best algorithms, or hiring developers who claim to have the best algorithms, because that’s how many AI developers think.

Life with a cheat code isn’t life. Our existence isn’t something to be engineered or optimized for the avoidance of pain.

Code will be used in ways we cannot anticipate, in ways it was never designed for, and for longer than it was ever intended. —Joshua Corman

premature optimization, where you tweak or perfect code or algorithms (optimize) too early (prematurely).

To be fair, as a general manner of speaking, the French do consider criticism to be more honest than praise. To the French, unbridled optimism, enthusiasm, or unwarranted contentment all scream simplemindedness. As France's most popular stand-up comedian, Jammel Debbouze, put it, you have to sound pessimistic to look intelligent in France. Overt pessimism has an elegant anti-establishment quality about it, like wearing all black... The Bonjour Effect: The Secret Codes of French Conversation Revealed by Julie Barlow

And yet, as a Red Army officer, she was heading into a new battle. History was pivoting around her. Before the war, she had spied against fascists and anti-communists, Chinese, Japanese, and German; during the conflict, she had spied against both the Nazis and the Allies; after it, and henceforth, she would be spying against the West, the new enemies in a Cold War. A photograph of the Summertown neighborhood victory party includes a beaming Ursula, happily celebrating Hitler’s downfall. One man is wearing an army uniform. Another raises two fingers in the V for Victory sign. But behind the image of shared relief, triumph, and optimism lay a hidden ideological divergence that would soon erupt in a new conflict. “Everyone hoped for a better world,” she wrote. “But here our visions of the future differed.” — TWO MONTHS LATER, in the remote deserts of New Mexico, scientists of the Manhattan Project detonated the first nuclear device, in a test code-named “Trinity,” releasing a blast equivalent to twenty thousand tons of TNT.

The salespeople who scored in the top 10 percent for optimism performed a whopping 88 percent better in sales than the reps in the top 10 percent for pessimism. Dr. Seligman found that the power of optimism held in other professions, too. He concluded that in general, optimistic salespeople performed an impressive 20 to 40 percent better than pessimistic salespeople.