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Scientific American Supplement, No. 392, July 7, 1883 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . TESTING OLIVE OIL. here TESTING OLIVE OIL. By DR. O. BACH. There is no department in analytical chemistry in which so little success has been attained as in the testing of commercial fats and oils. All methods that have been proposed for distinguishing and recognizing the separate oils, alone or mixed, bear upon them the stamp of uncertainty. The facts observed by J. Koenig, and described by him in his excellent book entitled " " (p. 248), excited great expectations; viz., that the quantity of glycerine in vegetable fats was much less than the amount required to combine with all the fatty acids, and that the quantity of oleic acid in the oils that he examined exhibited essential differences. Koenig himself asserts that the fats have hitherto been too little investigated to found upon it a method for distinguishing them, but that nevertheless it may possibly do good service in some cases. Die Menschlichen Nahrungs und Genussmittel My own estimation of the amount of glycerine in different olive oils, by Koenig's method, has shown, unfortunately, that the percentage may vary from 1.6 to 4.68, according to the origin and quality of the oil. In like manner the estimation of the oleic acid, which was conducted essentially in the manner proposed by Koenig, showed that the amount of oleic acid in different olive oils varied from 45 to 54 per cent. But since cotton seed oil, for example, which is most frequently used to adulterate olive oil, contains 5 per cent. of glycerine, and 59.5 per cent. of oleic acid, it is easy to see an admixture of cotton seed oil cannot be detected by this method, which appeared to be so exact. The method of analysis that I am about to describe is based chiefly upon the determination of the melting point of the fatty acids contained in the oils, and upon their solubility in a mixture of alcohol and acetic acid. The oils employed in adulterating olive oil, and to which regard must be had in testing it, are the following: Cotton seed oil, sesame, peanut, sun flower, rape, and castor oils. The tests for the two last named have hitherto never presented any difficulty, as rape seed is easily detected, owing to the sulphur in it, by saponifying it in a silver dish, and castor oil by its solubility in alcohol. But in recent times another product has come into the market called sulphur oil or pulpa oil, obtained by extracting the pressed olive cake with sulphide of carbon. This also gives a sulphur reaction when saponified, while it resembles castor oil by its solubility in alcohol. When this oil is mixed with ordinary olive oil, it can easily deceive any one who uses the ordinary tests. My method of testing olive oil is as follows: First, the so-called elaidine test is made, and then the test with nitric acid. About 5 c. c. (a teaspoonful) of the oil is mixed in a test tube with its own volume of nitric acid, spec. gr. 1.30, and shaken violently for one minute. At the expiration of this time the oils will have acquired the following colors: Olive oil, pale green; cotton seed oil, yellowish brown; sesame, white; sun flower, dirty white; peanut, rape, and castor oils, pale pink or rose. As soon as the color has been observed, the test glass is put in a water bath at the full boiling temperature and left there five minutes. It was found that the action of nitric acid upon cotton seed and sesame oil was the most violent, sometimes so violent as to throw the oil out of the glass. At the end of another five minutes after the test tube is taken out of the water bath, the following colors are seen: olive and rape oils are red; castor oil is golden yellow; sun flower oil, reddish yellow; sesame and peanut, brownish yellow; cotton seed, reddish brown. After standing 12 to 18 hours at about 60° Fahr. the olive, rape, and peanut oils will have solidified; sun flower, castor, and cotton seed will be like salve (sticky), while sesame will remain perfectly liquid. Mixtures of olive oil with small quantities of cotton seed or sesame are distinguished by this characteristic--that, although the whole mass, which is darker in color than olive oil, solidifies at first, at the end of 24 or 36 hours a brown oil will be found floating upon the surface of the solid mass, while the lower strata exhibit the yellow color of pure olive oil. Oil of rosemary has no effect when shaken with cold nitric acid, and imparts to it only a slightly darker color on heating. Oils treated with lye act just like pure oils. Far the purpose of determining the melting point of the fatty acids, 10 grammes of oil were saponified with 5 grammes of caustic potash on the water bath; some water and alcohol being added. After all the alcohol had been expelled the soap was dissolved in hot water, and the fatty acids separated from the clear solution by adding hydrochloric acid. After prolonged heating these acids will swim on the salt solution as a perfectly clear oil, a portion of which is then put into a little, narrow, thin walled tube and allowed to solidify. The point at with it melts and solidifies is determined by putting this tube in a beaker glass filled with water and warming with a small flame. A thermometer is placed the fatty acids and moved gently about during the observation, and the point accurately observed at which the whole mass becomes perfectly clear, and also when the mercury bulb begins to be clouded. It was found that the acids from pure olive oil melt between 26½ and 28½° C. (= 80° to 83° Fahr.) and solidify at a point not lower than 22° C. (72° Fahr.). The melting point of the fatty acids in the oils used to adulterate olive oil differs considerably from this. The melting and solidifying points of the acids in cotton seed, sesame, and peanut oils lie considerably higher, those of sunflower, rape, and castor oils decidedly lower than those of olive oil. in The melting and solidifying points of these acids are as follows: Cotton seed melts at 38.0°C.  solidifies 35.0°C.
  Sesame       do.     35.0 do.    do.     32.5 do.
  Peanut       do.     33.0 do.    do.     31.0 do.
  Sunflower    do.     23.0 do.    do.     17.0 do.
  Rape         do.     20.7 do.    do.     15.0 do.
  Castor oil   do.     13.0 do.    do.      2.0 do. The above figures differ so much from those of olive oil, that adulteratious carried to the extent that they are in trade can easily be detected by the aid of an estimation of the melting point, for a Gallipoli olive oil, mixed with 20 per cent. of sunflower oil, melted at 24° C. and solidified at 18° C. (of course, the fatty acids are meant). A Nizza oil, mixed with 20 per cent. cotton seed oil, melted at 31½° C. and solidified at 28° C. A Gallipoli oil with 33-1/3 per cent. of rape oil melted at 23½° C. and solidified at 16½° C. When 0.50 per cent. of rape is added, it melts as low as 20° and solidifies at 13½° C., etc. In testing the solubility of the fatty acids in alcohol and acetic acid, I employ the method proposed by David (in , 1878, p. 1416) for estimating stearic acid. Comptes Rendus It depends upon the principle that when acetic acid is poured drop by drop into an alcoholic solution of oleic acid, there comes a time when all the oleic acid separates, but stearic acid, which is insoluble in a mixture of alcohol and acetic acid, remains insoluble if the mixture contains oleic acid. The following manipulations are adopted in testing olive oil: Equal parts of glacial acetic acid and water are mixed in a bottle. Then 1 c.c. of pure oleic acid, 3 c.c. of 95 per cent. alcohol, and 2 c.c. of acetic acid are put in a small tube graduated in tenths of cubic centimeters. The solution should remain clear; on adding another one-tenth c.c. of acetic acid it becomes turbid, and when 1 c.c. of oleic acid (or at first even more) floats on the mixture of acid and alcohol, the liquid is ready for use. If this is not the case, the proportions (of acetic acid and alcohol?) must be varied until the addition of one-tenth c.c. of the former will cause all the oleic acid to separate. The proportions having been ascertained from these preliminary experiments, the alcohol and acid are then mixed accordingly, e.g., 300 of alcohol to 225 of acid. One or two grammes of stearic acid are added to the alcoholic acetic acid, and the clear supernatant liquid used for the experiments. One cubic centimeter of the oil (acids) to be tested is put in the tube, and 15 c.c. of alcoholic acetic acid added, well shaken, and the whole left to stand quietly at 15° C. (60° Fahr). If the olive oil is pure, the acids dissolve to a clear solution that remains so. Cotton seed oil is insoluble, and the solution obtained by heating the solution solidifies at 60° Fahr. to a white jelly. Sesame and peanut oil react in a similar manner. Sunflower oil dissolves, but at 60° a granular precipitate falls. Rape oil is entirely insoluble and floats like oil on the surface. Castor oil on the contrary dissolves completely, just like olive oil, and hence cannot be detected therein by this method. To detect this oil we must take the melting point of the acids along with the solubility of the oil itself in alcohol. Olive oil when mixed with 25 per cent. of cotton seed oil yields a granular precipitate, and so does 25 per cent. of sesame. Smaller quantities cannot be detected by these methods. For rape oil the limit is 50 per cent., and in smaller quantities the oil does not collect on the alcoholic solution. The decided lowering of the melting point of the fatty acids in combination with the sulphur reaction, and the insolubility of the oil in alcohol, also furnish a method of detecting when present in smaller quantities in olive oil. Although I am well aware that I am making public a research that is by no means free from objections, I nevertheless believe that it may be of use to those who have to undertake the ticklish and intricate analyses of commercial fats.-- , p. 355. Translated from the Chemiker Zeitung Leipsic, Jan., 1883. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2005). Scientific American Supplement, No. 392, July 7, 1883. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/8742/pg8742-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

TESTING OLIVE OIL

Hacks Analyses 1. Euler Finance  |  Amount Lost: $197M The attacker used a flash loan to borrow DAI and leveraged Euler Protocol to borrow eDAI and dDAI. By exploiting a vulnerability in the donateToReserves function, the attacker was able to initiate the liquidation process and profit from it. The vulnerability was due to the missing checkLiquidity step in the donateToReserves function, allowing users to enter a state of liquidation and complete the liquidation process. Olympix has developed a tool to protect against flash loan attacks resulting from missing check vulnerabilities. These vulnerabilities and resulting attack vectors have become increasingly common and dangerous throughout the defi ecosystem. The Olympix tool uses static code analysis, traditional statistics, and AI to detect anomalies throughout the code base by comparing the code base against itself. 2. Sentiment Protocol   |  Amount Lost: $1M An attack on Sentiment Protocol resulted in the loss of almost $1 million worth of various tokens and stablecoins. The attacker borrowed 606 WBTC, 10,050 WETH, and 18 million USDC using a flash loan, and deposited these tokens into the Balancer pool on Sentiment. The attacker exploited a reentrancy vulnerability during the exitPool function to transfer back the deposited tokens to their account, which decreased the pool token's total supply but token balance state remained the same. The exploit contract recursively borrowed assets using the inflated price of the pool token as collateral. Sentiment is continuing to investigate the attack and has implemented a fix to address the vulnerability exploited in the attack. 3. Poolz Finance   |  Amount Lost: $500K The attacker used a vulnerability in the smart contract by invoking the CreateMassPools() method and causing an overflow in the array using the GetArraySum() method. This allowed the attacker to use the TransferInToken() function to establish liquidity in the pool and withdraw the gained tokens using the withdraw feature. 4. Safemoon   |  Amount Lost: $8.9M The hacker exploited a function in the Safemoon contract, which allowed any user to burn tokens from any other address. This function was used to remove SFM tokens from the liquidity pool, raising their price artificially and allowing the attacker to sell them back to the pool at a profit. public burn()* *A burn() function allows the destruction of tokens or coins that exist on a blockchain. When tokens are "burned", they are permanently removed from circulation, decreasing total supply of the token. 5. Hedera  |  Amount Lost: $515K An attacker used a suspicious address to deploy a malicious contract that stole assets from various pools. The attack was on Hedera's mainnet Smart Contract Service code, which resulted in the transfer of Hedera Token Service tokens from victims' accounts to the attacker's account. The targeted accounts were on multiple decentralized exchanges that used Uniswap v2-derived contract code, including Pangolin, SaucerSwapLabs, and HeliSwap_DEX. Explore Olympix Announcements We are excited to share new updates about the Olympix tool; Our tool now utilizes a combination of static code analysis, traditional statistics, and AI to identify anomalies in the code base by performing comparisons against itself, which helps safeguard against flash loan attacks caused by missing check vulnerabilities. This feature is accessible through an API call. Olympix can detect if a contract is an upgradable or proxy, allowing for more curated and accurate results. We've added additional patching capabilities to quickly fix vulnerabilities. Interested in learning more about Olympix? Here are some links to get you started: - Our website where you can sign up to join our Beta / Discord https://www.olympix.ai/ - Get updates on exploits, product updates https://twitter.com/Olympix_ai - Newsletter #1, subscribe for more. https://t.co/jeLkihA1Fa. Also published here.

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I wrote a paper in Spanish and asked "someone else" to rewrite it Last year, I in Spanish about the future of programmers. wrote a paper TL;DR: Instead of manually translating my paper, I decided to rewrite it completely with . GPT-3 In the same way, asked when it was in private beta. The Guardian GPT-3 When I asked to translate the article, it decided the title was not good enough. it So it changed it to present AND future 😱Scary, isn't it? Let's move on. So this is the original paper rewritten by GPT-3: The Paper //  Translate this into English and convert it to a technical article: Summary The current market is looking for programmers to stack bricks (1) using their trendy languages. Such professionals are trained in specific tools that have very short life cycles and then become obsolete. There are currently alternatives to carry out computer developments using intelligent people, capable of making their own decisions and participating in the creative process. The programmers of the future will have to be excellent and declarative (2). Professionals who know about algorithms and complexity and who know-how Introduction Most developers in the world are making changes to old systems or have to use complex preexisting libraries or frameworks that they have little control over and few opportunities to modify. (3) In today's software industry, it is very unlikely to find the need to develop from scratch, with a completely blank page. The specific lifespan of a programmer age along with the fashionable language. This period of time is usually less than a decade, so the industry discards professionals as obsolete before ten years of training. (4) In the last decades, they were fashionable as supposed silver bullets (5), languages ​​like Visual Basic, C ++, Java, Php, Perl, Javascript, Ruby, Python, and GoLang. Some of them are already ceasing to be used, leaving their place for new fashions. (6) The general concepts (which Frederick Brooks calls essential (7)) are better absorbed in our first academic stage. We must focus on forming these concepts so that professionals can easily migrate from one technology (which Brooks calls accidental) to another technology (also accidental and, therefore, quickly obsolete). The threat By 2021 there are already numerous alternatives to artificial intelligence and machine learning, capable of carrying out low-level programming and algorithmic tasks (8) (9). Modern virtual machines (those that interpret the high-level language in which we program and that exist, for example, in web browsers) optimize the code for us. (10) As technology advances, low-level programmers will no longer be required in the same way that no one is looking for librarians today (11). Similar to what happens with other automatable and obsolete professions. (12) Our profession is still based on teaching low-level imperative programming as if we were facing the problems of the 1960s or 1970s when the specialized hardware was punch cards and open tape machines. We educate our students to carry out absurd and obsolete algorithmic optimizations, very close to the language of machines and very far from the modeling of entities of the problem that we are representing in our computer solution. We train professionals to understand how a computer works and to lower themselves to speak in its language, forming low-level mental models and trying to in the algorithmic way in which a Turing machine processes. reason However, today we can develop semantic models with several layers of abstraction above as we approach declarative mental models we move away at the same time from the computable abstractions of machines. The most declarative programming languages allow us to reason and infer rules about our models. Against this trend, our students write their instructions based on ones and zeros. Moore's law (14) tells us about the speed of change of the hardware and its exponential growth in processing power. With respect to software, we grow linearly limited by the realities of many decades ago and the inertia of trainers. In analogy with Malthusian economic theory (15) we need to catch up with the hardware curve to be able to release all our potential before the machines do it for us. The lack of abstraction and understanding of reality is a symptom of an inertial mentality, based on the time restrictions of processors and storage of the 60s and 70s. These restrictions are limited today to very specific domains and are not representative of the problems we have to solve today as software engineers in most of our jobs. (16) The alternative We need to train generalists, but not theorists. People who understand the basics and foundations of software engineering and can adapt to accidental implementations based on current tools, but also to future ones that we do not yet know today. Concepts such as software design, life cycle models, teamwork and building a shared theory (17), continuous integration and deployment or architecture, are much more important than learning to minimize CPU usage, to use React, the Vue framework, or the Keta library. "It is very difficult to make predictions, especially about the future". This phrase, attributed to the great Niels Bohr, tells us that we should be careful when trying to anticipate the future. Paraphrasing the 2004 Turing Award (18) Alan Key, said: "The best way to predict the future is to invent it". We do not know for sure what the path of machine automation will be, but we can predict that the most creative and engineering part of our profession should be one of the last bastions to fall before automation. The next generation of software developers will have to focus their skills on design, modeling the real world, and creating abstractions that evolve along with the problem domain to avoid building obsolete and legacy software (19). This strategic approach is not limited only to development careers. In data science there are similar problems: data scientists focused on optimizing existing algorithms instead of training generalist professionals, able to understand the academic and commercial problems of our country with a battery of solutions and good criteria to determine which to choose in each situation. They should be trained to model the real problem and evaluate different possible solutions. Data science professionals have an incredible variety of tools to adjust their models. We are still far from finding the second "super algorithm" (20) capable of solving specific problems with a generic solution. Our future professionals have the only general-purpose computer that can reasonably solve various specific problems: Their brilliant minds. Our responsibility is to feed and stimulate those brains with real problems and not with toy solutions that computers solve (already in 2020) much more efficiently. Paradoxically, wasting our brains by asking them to perform low-level optimizations for machines is the worst way to optimize our most expensive resource. Historically, we have privileged the development of very specific and theoretical tools. This is very common and desirable in science because theoretical advances usually precede concrete implementations and uses by decades. However, in software development, discoveries and findings are mostly found in the private sector before academia. Our professionals must be trained in methodology and concepts above accidental trendy technologies and languages. This generates tension between the market that wants "implementers expert in a tool" to discard them when it fulfills its fashion cycle of 5 or 10 years. Our professionals should not be disposable or recyclable. We must train them in techniques and they must keep themselves constantly updated, as happens in other professions such as medicine, physics, or biotechnology. What do we need to teach? In addition to "soft" skills such as construction and teamwork (since software arises from a collective activity) (17), we must teach design and prototyping techniques to validate our high-level solutions. As for software, it is imperative to teach solution design, focusing on the behavior of our models and, paraphrasing Donald Knuth (21), the historical author of most of the algorithms we use today, avoiding premature optimizations because we want to play a game that machines dominate much better than us. The opportunity Training talent is an accessible option for any country with a good academic level, such as Argentina. Investing in training excellent software engineers is a strategic decision and an opportunity for take-off that has already been exploited by many other countries such as Estonia, Ireland, Israel and India. The Sadosky Foundation is currently working in this direction. (22) In Argentina, we have excellent teachers, a good level of English, an unbeatable time zone to dialogue with USA and Europe, and a culture compatible with the most developed countries.
We need to prioritize information technologies and, within them, train intelligent and declarative engineers rather than mechanized programmers and low-level optimizers. What should we teach our engineers? Our professionals must have basic knowledge of programming, algorithms, complexity, and databases. Above all, they must learn to make designs based on continuous integration and continuous deployment models, with automated tests, using agile techniques such as Test-Driven Development. (23) The software produced must be declarative and based on the desired behavior (and specified in the automated functional tests); we must stop thinking in the reigning paradigm of the 60s and 70s, based on data types and file and string manipulations, to focus on high-level models that accompany the simulation of any aspect of the real world that we want to represent to solve a certain problem. (24) The techniques of design based on behavior are agnostic with respect to the accidental technology of fashion and this allows an engineer trained with these concepts 30 years ago to be able to make concrete developments even today. Unfortunately, such a situation is not replicated by programmers who dominated some fashionable language, which practically has no use and that makes them not find good options in the labor market. The paradox is that a trade with full employment discards these professionals for not having been able to adapt. (25) The change, currently, is even more vertiginous. Technologies last much less and obsolescence stalks us, unless we are intelligent and broad, and have the appropriate training. Future Work This is an opinion piece. As future work to support the current thesis, we should carry out a quantitative study including figures on employee turnover (25), average time in each job according to age and studies completed, etc. To do this we must use techniques related to the social sciences under a multidisciplinary approach. Conclusions The future has already arrived. We don't have much idea of what a programmer's job will be like in 5 or 10 years, but we have strong indications that it will not be related to writing algorithms based on data structures. We must train professionals who quickly understand a real-life problem and know how to build simulators with very small conceptual leaps, so that they can evolve alongside the problems we are solving today. Acknowledgments Part of the ideas in this article was born from the teaching work in the Software Engineering course in the Computer Science degree at the Faculty of Exact Sciences, University of Buenos Aires. GoLang Declarative programming Legacy code Obsolete programmers No silver bullet Fashionable languages There is no silver bullet Deep Coder Augmented Coding Process Virtual Machines Obsolete librarians Future of work in Argentina Turing machine Moore's law Malthusian growth model Business Software Theory building Turing Award Inherited software General AI Knuth - The art of computing programming Sadosky Foundation Test-driven development Object Thinking Dead languages Programmer turnover The translation is accurate and beautiful. I have checked it with Grammarly and Hemmingway app and found just a few grammatical mistakes. As an example: Trabajo Futuro (Spanish for Future Work) Este es un artículo de opinión. Como trabajo futuro para apoyar la presente tesis deberíamos realizar un trabajo cuantitativo incluyendo cifras de rotación de empleados (25), tiempo promedio en cada trabajo según la edad y los estudios realizados etc.
Para ello debemos utilizar técnicas relacionadas a las ciencias sociales bajo un enfoque multidisciplinario. Translates in GPT-3 as: This is an opinion piece. As future work to support the current thesis, we should carry out a quantitative study including figures on employee turnover (25), average time in each job according to age and studies undertaken etc.
To do this we must use techniques related to the social sciences from a multidisciplinary perspective. While Google Translate yields: Future work This is an opinion article. As future work to support this thesis, we should carry out quantitative work including employee turnover figures (25), average time in each job according to age and studies carried out, etc.
For this we must use techniques related to the social sciences under a multidisciplinary approach. Model calibration I used model with Temperature 0 (Randomness) and Maximum Length 2000 tokens text-davinci-002 GPT-3 Opinion What is your opinion on this article? I think that this article makes some valid points about the future of programming and the need for programmers to be adaptable to change. I agree that the industry is moving towards more automated solutions and that this will eventually lead to a decrease in the need for programmers. However, I think that there will always be a need for programmers who are able to understand and solve complex problems. 😱(Scary Again!!) Meta Conclusion I will definitively, keep using GPT-3 to write technical articles to improve them.

GPT-3 Training Programmers for the Present (and the Future)

Programadores de formación GPT-3 para el presente (y el futuro)

Programmeurs de formation GPT-3 pour le présent (et le futur)

वर्तमान (और भविष्य) के लिए GPT-3 प्रशिक्षण कार्यक्रम

現在 (および将来) の GPT-3 トレーニング プログラマー

Programadores de treinamento GPT-3 para o presente (e o futuro)

GPT-3 Đào tạo Lập trình viên cho Hiện tại (và Tương lai)

现在（和未来）的 GPT-3 培训程序员

(This is a republished blog from my failed startup, Mighty Spring, on the subject of Referral Hiring) A on the First Round Capital blog promoted “referral hiring” as the go-to form of talent sourcing for young companies and provided ammunition for generating greater numbers of referrals from existing employees. recent post It seemed obvious while reading this post that using the suggested tactics would improve raw referral numbers, but degrade referral quality. There was little mention of the introduction of misaligned incentives and the downside risks associated with those new incentives. Comments on the post from the popular startup community, Hacker News, seemed to indicate that many employees have an intuitive grasp of the ris;ks and incentive problems that come with trying to juice referral-based candidate lead generation — more so, perhaps, than employers who are narrowly focused on trying maximize their referral numbers. Today, with the help of comments from the community on the aforementioned FRC post, we’ll attempt to present a fuller picture of referral hiring. Hacker News The Importance of Incentive-less Referrals Offering a referral bonus to employees for referring friends who get hired is common practice, but is it necessary? By offering bonuses in this way, companies essentially turn their employees into part-time contingency recruiters who now face the same bad incentives of their full-time counterparts. With $5,000 or more potentially on the line, a given employee is likely to be more lenient with their referral standards than if there were no financial reward at stake. Meanwhile, employees who truly love their jobs naturally gush about work and try to get their talented friends involved. In the Hacker News discussion, user made a comment to this exact effect, “If I love my job, then you better believe that all of my developer friends are going to hear about it until I am blue in the face.” Conorgil145 To drive a significant volume of meaningful referrals, focus on a feedback loop with your employees that address their root concerns — the reasons that they’re not already gushing to their talented friends about how much they love their company. If you want your employees to gush to their friends, ask them directly, “What can we do as a company to improve the likelihood of you recommending us to those in your network as a place to work?” Requesting referrals from employees who have fundamental concerns about their workplace lowers the likelihood of them referring their most talented friends. Instead, you’ likely to hear about their buddy who “really needs a job”. Once you’ve nipped the real issues in the bud, keep your hiring needs in the forefront of employees’ minds by mentioning them at regular intervals. Make your workplace somewhere people really do want to work, and the word of mouth will take care of itself. If you insist on using referral bonuses, consider tying them to the long-term success of the hire instead of positioning them as a quick buck. Fast cash actually lowers the standard of who your employees will refer. Try, for example, referrals bonuses (cash or equity) that vest based on the hire’s performance over the first year. Your Hiring Process (is a Problem) Companies don’t like to admit it, but many have hiring processes that treat candidates who are early in the hiring funnel as expendable, interchangeable, and disposable. This incentivizes employees to not refer their friends for fear of mistreatment. notes, Angersock “What’s really annoying is when you try to bring in talented engineers from your network, and your company drops the ball: either by not getting in touch with them, or low-balling them, or refusing decent equity. If I’m referring somebody from my network to you, I want to make sure you treat them well and with promptness–disrespecting them is a sign of disrespect to me as well, and makes me look like an ass to them.” It doesn’t take much to turn a good candidate off with your hiring process. Slow contact at important junctures, overly-vague explanations of how the hiring process works, what to expect from a given interviewer, and poor transparency into decision making criteria are all big annoyances for candidates (though most companies consider them to be a given in hiring). In a world where “hire the best, no questions” is considered foundational behavior for success, isn’t your hiring process your most important product? What if the only product your company produced was your hiring process? How would it change from your approach today? First impressions don’t fade easily. You may get a candidate who has been through a poor hiring process to accept an offer, but they’ll remember how they were treated. Even if they chalk their experience up to chance, they still may still be concerned about subjecting their friends to the same treatment. The Hacker News crowd expounds on the troubles with the middle of the hiring funnel, and the resulting effects: writes, Tptacek “My sense of it is that the valley believes recruiting to be a ‘top of the funnel’ problem. My experience says that it isn’t. My hypothesis is that the inefficiency is in qualifying candidates (deeper in the funnel), and that if you can fix that problem, the top of the funnel can sort itself out without much effort.” writes, InclinedPlane “I’ve seen too many examples of poor interviewing process, too many bad hires made, and too many good hires passed over to not put most of the onus on the middle of the funnel. Most interviewers are just not good at understanding the fragility of the process, or in having sufficient empathy to understand the difficulty of getting good data on a candidate.” From GVIrish, “By putting all of my contacts in the hands of the HR dept I no longer have any control over how or when the company contacts them. That company can easily break the trust I have with my contacts. I wouldn’t be comfortable doing that, referral bonus or no referral bonus.” Proxies Will Fail You Referral hiring can seem like a panacea, especially compared to low conversion rates from alternatives, but that attitude masks the real problem: you’re likely bad at evaluating cold leads. Like focusing on candidates from top-tier schools, seeking out friends of existing employees is nothing more than a proxy for independently-determined quality. This approach leaves you with an insulated pool of candidates, and a statistical evaluation will tell you that focusing too narrowly on referrals virtually assures that you’re missing out on the best talent in the market. points out the dangers here: Tptacek “Network hiring unavoidably personalizes the hiring process: candidates come in the door with sponsors. It’s hard to hire objectively, staying as close to apple-apples as possible, when your candidates are friends of employees who have significant bonuses riding on the selection.” If You Want More Referrals, Align Incentives For Success Consider paying for your employees’ contact lists, not the hires that come from them. By doing so, you put the incentive to conduct a high-quality and thorough interview process on the people doing the hiring. Traditional recruiting fee and standard employee referral fees are an equally broken extension of that model. structures are broken Poorly-aligned incentives are ultimately bad for you, the company, even though they look like they reduce risk in the short term. A better, more efficient hiring funnel will provide outsized returns over many, many hires, and aligning incentives in candidate sourcing is the best thing you can do to jumpstart the necessary change. Colliding Worlds Right now companies are only asking to mine your LinkedIn and Facebook connections. But what’s next? Does anyone want to connect their Snapchat account? Soon they’ll want family trees and the posts from your Secret account. From on the subject, edandersen “My personal network is not yours to ‘mine’. If an HR person at my company contacts a friend of mine to pitch a job at the company I work at, trying to use my name as an ‘in’, that is seriously unprofessional.” More from pnathan: “I’m not going to want to sit down with you and let you chew through my social networks for recruiting leads.” Conclusion Well-executed referral hiring has exceptional value, but not all referral hiring is well-executed. Incentivized referrals have inherent risk, and pressing current employees to offer up a marginal referral potentially alienates the referrer and likely generates a worse-fitting candidate than one who is organically recommended. If you’d like to augment your current candidate acquisition efforts with high-quality, non-referral-based leads, check out . We provide a curated short-list of candidates who are both qualified for, and interested in, your company’s open job. Mighty Spring TL;DR: Optimize your hiring process and candidate lead generation strategy end-to-end with referrals as one element. Consider ways to drive referrals that are not based in financial incentives. If you must use financial incentives, align them with long-term organizational goals. Use as another way to see great candidates :) Mighty Spring

Don’t Break Referral Hiring

Technical blogging can reinforce your learning, educate people in the tech community, and serve as a good source of income. As a tech blogger, you have the great benefit of becoming a lifelong learner because you need to be well-versed in the field you are writing about to explain the concepts to readers clearly. Due to blogging’s numerous benefits, different people have asked questions like; what are the best technical blogging platforms? Should I build a blog from scratch or use a network-based technical blogging platform? This article aims to answer some of those questions by highlighting some of the best ways to start a technical blog in 2020. I will divide it into network-based and self-hosted tech blogging platforms. Network-based Platforms These are technical blogging platforms with an existing audience that you can leverage when you publish articles. You don’t have to understand how to code to use these platforms or worry about maintaining your blog as well. Hacker Noon is a community of over 12,000+ contributing writers publishing free high-quality tech stories. Hacker Noon Hacker Noon supports writers by proofreading their articles before it is published on the platform, has in-built blog analytics, strong security, and is web monetized to enable writers to earn money from their articles. As a network-based platform, it already comes with an existing audience waiting to read the articles you publish on the platform. Medium is a community of writers, bloggers, journalists, and experts. - From the description, you can see that medium is not only for people in tech because it has various writers and publications from different areas of life. Medium No coding skill is required to create a blog on Medium. It comes with in-built analytics and a paid writer program. Medium received many backlashes from the tech community when they added the paywall feature because users were limited to reading five articles for free every month on Medium. Even though these platforms come with many readers, you can’t use your own domain on your blog, and there’s not a lot of customization options. Hashnode is a content creation platform and community that enables developers to create a blog on their personal domain for free. As a network-based platform, your articles are shared with the community on Hashnode for initial traction and readership. Hashnode You don’t have to create your blog from scratch; hence no coding skill is required and you get to enjoy all the SEO benefits because the blog is mapped to your personal domain name. Blog customization is pretty great as well. The platform doesn’t have a paid writer program like medium but it has got web monetization integrated to enable writers to make money from their articles with no popup ads. Dev.to is an open-source software that powers a community of software developers who write articles and build relationships with other developers. Dev.to As a network-based platform, it comes with an existing audience waiting to read your articles. It doesn’t require any coding skills to set up and is web monetized as well. You can’t map your blog to your personal domain, so the traffic goes to dev.to instead of your blog. The platform respects your canonical URLs so you can republish your articles. Self-hosted Platforms These platforms require understanding how to code. You have to create the blog from scratch and also maintain it as well. Self-hosted platforms do not come with have an existing audience like the network-based platforms. WordPress.org is a software designed for building websites and blogs. You will have access to different plugins to enhance your blog and total control over every aspect of your blog. WordPress.org It doesn’t come with a built-in audience, so nobody might read your articles when you publish them except you have a good social media following or have been blogging for a long time. You have to manage your own backups and security, so some coding knowledge is required here. There are tons of people using WordPress worldwide, so finding resources to help you build with WordPress is easy. MDX and Next.js is an authorable format that lets you write JSX and import components into your Markdown files, while is a React framework that enables you to build static and dynamic apps quickly. MDX Next.js You need to understand React and Next.js to be able to create the blog with MDX and Next.js. You have the power to customize your blog in different ways and also have total control of your content. Since it is a self-hosted platform, there’s no existing audience waiting to read your articles when you publish it. Gatsby is a free and open-source framework based on React that helps developers build fast websites and blogs. Gatsby Knowledge of GraphQL and React is a must-have to build a blog with Gatsby. I believe Gatsby’s documentation is excellent, so it shouldn’t be challenging if you are looking to explore building with Gatsby. Blog customization can be done in diverse ways and you will also have total control of your content. As a self-hosted platform, you will be required to build your blog from scratch and maintain it. It doesn’t come with an existing audience, so you may not get a lot of readerships, except your articles are shared on social media platforms. Conclusion Network-based and self-hosted platforms are great. It is essential to understand the differences between them and what you stand to gain from using either of them. I hope you were able to learn about the best ways to start a technical blog in 2020. Thank you for reading this article.

How To Start a Technical Blog in 2020

The benefits of artificial intelligence are no longer limited to high-profile corporations, movie supervillains, and programmers performing fruitless experiments. What was once science fiction has now finally become reality, and when paired with blockchain technology it is no surprise that AI is making leaps and bounds. But the question that always comes to mind when a new technology comes to light is “Can I make money on it?” When looking at blockchain technology infused with artificial intelligence, the answer could be positive indeed! Thanks to for support in creating this topic (First platform with proven ICO contractors) agency.howtotoken.com Why bother combining AI and blockchains? You’ve probably heard about , or perhaps you’re familiar with — both of these examples are fueled by artificial intelligence. We create AI to enable computers to solve problems for themselves, essentially giving them the ability to write code in response to new problems they encounter. When , AI is able to be better understood by humans, operate more efficiently, and make blockchains in general more efficient. world chess champions losing to computers self-driving cars paired with blockchains In order for machines to learn, they need massive amounts of data to analyze, just like humans. The difference is that humans analyze their data passively, we use our five senses to take in the world and we store it away to create our belief in how the world functions. Trent McConaghy explains in , “Because blockchains introduced three new characteristics: his article on Medium decentralized/shared control immutable/audit trails native assets/exchanges. People inspired by Bitcoin were happy to overlook the traditional database-centric shortcomings, because these new benefits had potential to impact industries and society at large in wholly new ways.” He continues by adding, “These three new ‘blockchain’ database characteristics are also potentially interesting for AI applications.” Remember, machines don’t have senses, they need data, and blockchains can help them acquire that data faster and more cleanly (thanks to decentralization/shared control). Some AI may learn better than others, and by sharing IP/testing models on an exchange, there is the potential for faster growth (and profit for developers). Once AI starts learning, it becomes far easier for us to trace the path it took to a solution if that path is stored on an immutable trail. Considering that one of the primary reasons , one such obvious avenue is being explored by using AI and the blockchain to create both active and passive income streams. we are creating AI in the first place is to make the lives of humans easier What exactly are we doing with AI + Blockchain? Blockchain technology provides users with the ability to create a trustless system on which they can run smart contracts, track a ledger, and more. AI and machine learning allows for hands-off programs that are designed to become smarter and more efficient over time. As in their University of Johannesburg paper, there are eight key ways where AI can help blockchains; four of which are pertinent to our discussion: Tshilidzi Marwala and Bo Xing explain “Scalability — AI can perform collaborative learning without a centralized dataset. Security — AI can detect blockchain application layer intrusion issues. Privacy — AI can improve the performance of hash functions. Efficiency — AI can predict the likelihood of a node to fulfill certain mining tasks.” It’s obvious to see how much of an impact AI will have on blockchains, and companies that are getting a headstart in the industry will almost certainly benefit greatly from such foresight. From increased scalability, enhanced security/privacy, and greater efficiency, AI will make it cheaper, safer, and easier to operate blockchains in general. There is a collection of examples where we can currently see AI and the blockchain working together on specific problems, such as: Cryptocurrency Trading Trading cryptocurrencies is a risky market in the same way that the stock market can be dangerous, and one of the worst ways to increase this danger is by involving emotions. If the market starts crashing you may have a panic attack and quickly sell, only to watch the market bounce back higher than it ever was, leaving you at a loss. One simple way to prevent these emotional mistakes is by using an AI-based cryptobot to trade for you, such as or . Crypto bots are built on four principles: algorithms, market prediction, stop losses, and AI. Through these companies it is common for users to subscribe to “signals,” or external services that provide trading strategies based on the data they’ve collected and analyzed using AI. If the average trader removes themselves (and their emotions) from the equation, and instead base their trading on strategies generated by artificial intelligence, they are far more likely to succeed. Cryptohopper Autonio Music Streaming As we’ve mentioned before in a different article, . is a company that is working hard to change that by using blockchain technology infused with artificial intelligence. On the Musiclife platform, artists are automatically paid through smart contracts every time their music is streamed. This alone helps to ensure that the artists make more money for their work compared to traditional streaming platforms. But the real kicker here is Musiclife’s pricing model. Using an AI pricing method, the music price through the platform automatically adjusts based on current market playback data, so the more popular a song is the more money the artist will make. musicians in today’s market struggle to earn their keep Musiclife Given the potential of the AI + blockchain music streaming industry, it comes as no surprise to see big names like Spotify throwing their hat into the ring and , a startup focused on using AI for user-preference predictions. buying Niland For those of us that aren’t musicians or professional cryptocurrency traders, however, these technologies may feel a bit detached from our daily lives. Luckily, there is a third option for making money in this industry, both during our lives and even potentially long after we’ve passed. Creating an Avatar-based Legacy A legacy used to be something that only the rich and powerful could afford to think about, but as decentralization technology helps to disrupt the status quo the possibility of creating lasting change is opening up to everyone. Whether your goal is to provide for your family after your death, or to have the work you’ve dedicated your life to carry on after your passing, avatars may be what you seek. Created by , avatars are created using a combination of artificial intelligence and blockchain technology that gives you a platform where you can create your digital legacy. By harnessing a combination of machine learning, smart contracts, teachable skills, and secure avatar-to-avatar communications, there are a few key things you can do with your avatar: EverLife Passive income — Avatars can be taught to perform specific tasks (that will earn you EVER tokens), to trade cryptocurrencies using your trading strategies (utilizing potential Skills Marketplace features), and to even seek new skills and tasks to add to their repertoire. Personal legacy — Your avatar can interview you, recording your answers while compiling the story of your life in order to give future generations of your family the chance to interact with you (through your avatar) long after you’ve died. When creating avatars, EverLife chose to implement AI into their systems to ensure growth and that expansion would continue long after user input ceased. They understood that blockchains alone wouldn’t be sufficient, which is the same conclusion that : “The DNA of the 4IR (Industrial Revolution) is AI, while blockchain represents one of the most disruptive technologies that may transform the whole economic system. Though blockchain holds various promises, this technology is still in its infancy.“ What EverLife, Marwala, and Xing are saying is that although the blockchain may be a groundbreaking technology, only by intertwining it with artificial intelligence will we truly see its full potential. Tshilidzi Marwala and Bo Xing come to What the future holds… As Matt Turck , the last 15 years was defined by social, mobile, and cloud-based services. Turck then goes on to say that “[t]here’s a rationale for making the argument that AI, the blockchain, and the Internet of Things is the new social, mobile, and cloud. Those trends are still very much emerging, but their potential impact is massive.” In the same way that social, mobile, and cloud development spawned many huge companies that exist today (Spotify, Airbnb, Twitter, Facebook, Uber, etc), one could speculate that the next 10–15 years will see a surplus of AI, blockchain, and IoT-based companies succeeding. points out in his article Will our lives benefit from this? The better question would be to ask if our lives benefitted from all of the companies created during the last 10–15 years. We find ourselves currently standing on the precipice of change — a shift in the major industries is coming before us that has the potential of leading to sweeping innovations across a wide spectrum of our lives. The only question left is whether or not you, the average crypto-enthusiast, will seize the opportunity to make a profit during these changing times. About the author: — Founder of Geekforge.io and Howtotoken.com. Interviewing the top 10,000 worldwide experts who reveal the biggest issues on the way to technological singularity. Join my . Kirill Shilov #10kqachallenge: GeekForge Formula

Artificial Intelligence + Blockchain = Passive Income (Forever?)

- Stephen King The scariest moment is always just before you start. A fascinating book about writing is Anne Lamott’s . The title comes from a family story about her brother. He was assigned a school project about birds. As children do, he procrastinated and delayed starting the project until the very end. Now, with the project due the next day, the boy sat at the table and cried. Where should he start? Will he ever finish the project? Lamott describes their dad telling the boy: “ ” Bird by Bird Bird by bird, buddy. Just take it bird by bird. The power of making the first step is something that Admiral William H. McRaven recognized during “If you wanna change the world, start off by making your bed.” a commencement speech he delivered in 2014: If you make your bed every morning, you will have accomplished the first task of the day. It will give you a small sense of pride, and it will encourage you to do another task and another and another. By the end of the day, that one task completed will have turned into many tasks completed. Making your bed will also reinforce the fact that little things in life matter. If you can’t do the little things right, you will never do the big things right. And, if by chance you have a miserable day, you will come home to a bed that is made — that you made — and a made bed gives you encouragement that tomorrow will be better. Making the first step is not only a remarkable way to fight procrastination, but it is also the only way to start fighting the darkness. Nobody can escape the dark moments in their lives. The passing of loved ones, war, pandemics, natural calamities, social injustice, something will come that has the potential to crush our spirit and leave us despairing about our future. In those dark moments, remember that . those tiny, unremarkable habits we picked along the way help us get back on track But for these habits to work they need a first, small step and an understanding that it is essential to recognize, accept and adapt to new emotional landscapes. Because of that, productivity advice should have various colors of meanings that are mindful of the ebbs and flows of our lives. Productivity book authors must acknowledge that productivity strategies that work for highly motivated professionals might become inefficient for struggling people. For example, when I was drowning under the rivers of well-meaning advice and todo-lists. Nothing seemed to work: breastfeeding was a bleeding pain (literal bleeding pain), I counted sleep by minutes, my daughter had jaundice and didn’t seem to gain weight, etc. I had to learn, unlearn, and relearn things about myself. To admit that the only way out was through. To focus on taking it breath by breath, choice by choice, step by step. No frogs to eat in the morning, no Pareto or SMART principles, no Eisenhower matrix, no weekly planning, nothing that might be too much to grasp. I will never forget the first few weeks of motherhood As Lori Gottlieb writes in her book : Maybe You Should Talk to Someone That’s one thing I tell patients who are in the midst of crippling depression… There’s the bathroom. It’s about five feet away. I see it, but I can’t get there. One foot, then the other. Don’t look at all five feet at once. Just take a step. And when you’ve taken that step, take one more. Eventually, you’ll make it to the shower. And you’ll make it to tomorrow and next year too. One step. They may not be able to imagine their depression lifting anytime soon, but they don’t need to. Doing something prompts you to do something else, replacing a vicious cycle with a virtuous one. Most big transformations come about from the hundreds of tiny, almost imperceptible, steps we take along the way. Gottlieb also mentions Andrew Solomon that wrote in his book , “ ” Yes, the vital power to make it day by day, hour by hour. The Noonday Demon The opposite of depression isn’t happiness, but vitality. Taking small steps is one of . The 16th principle is: Struggle little by little against idleness. the 20 strategies that Sydney Smith wrote to Lady Georgiana Cavendish in February 1820 against low spirits In , the gentle wisdom of taking a step at a time is put down brilliantly into What a beautiful and hopeful message Frozen 2 brings that will empower children of all ages! Frozen II The Next Right Thing lyrics. Sometimes it pains to look too far ahead and plan future work into tiny, concrete tasks. Sometimes, looking far ahead, having a system, periodically reviewing it, and making changes is the only way to keep the dark away. Days are floating clouds. Some clouds are still and calm, and some clouds bring rains of grief and winds of hurt. Sometimes, it is about thriving. Sometimes, it is about surviving. We would be wise to adjust our strategies accordingly. Previously published at https://www.roxanamurariu.com/the-subtle-psychology-of-making-the-first-step/

The First Step: Just Take it 'Bird by Bird'

In January 1996, Bill Gates what would go on to become one of the classic essays of the early internet. In it, he describes the very characteristics of the internet that would lay the foundation for the Creator Economy. published “One of the exciting things about the internet is that anyone with a PC and a modem can publish whatever content they create,” he writes. While Gates’s essay is remembered for its prescience about the direction the internet would take, what’s less well-remembered is that he also sounded a warning: “For the internet to thrive, content providers must be paid for their work,” he writes. “The long-term prospects are good, but I expect a lot of disappointment in the short-term.” Gates’s analysis was ahead of its time. While it’s true that the internet has made it possible for virtually anyone to publish content online, it’s also true that, a quarter of century after “Content is King” was published, earning meaningful income as a content creator has proven elusive. The lived experiences of creators tell the story: 90% of streaming royalties on Spotify go to the top 1.4% of musicians. The top 1% of all streamers earn more than half of all revenue on Twitch. 1% of podcasters claim the majority of podcast ad revenue. “To me, we’re not in a period of expansion,” one musician , speaking about earnings from streams on Spotify. “From an individual perspective of musicians, it has just been a downward trend of the rewards for our labor.” told The New York Times This isn’t inevitable, and it’s not unique to fledgling artists—it affects 99% of all creators, including famous names with millions of fans. When even struggle to make a basic living online, something is artificially holding them back. they The internet was supposed to usher in a Golden Age of media—a world of infinite abundance where anyone can create whatever they want, and everyone can find whatever they’re interested in. But while Gates’ prediction that there was money to be made online through content has proven true, much of that money has the creators that produce the content, landing instead in the pockets of the platforms that aggregate it. bypassed This is the story of how the web2 internet the business model of media, and how the advent of web3 signals a disruption to that business model that tilts the scales in favor of creators. broke Without native monetization methods built into the web2 internet, the predominant business models were opaque, advertising-based, and dependent on closed-garden networks, which gave an outsized advantage to platforms. On the horizon, new business models and technologies hold promise to unlock the kind of economic opportunity and control that will lead to a true creative Golden Age for artists and creators. Subscribe The Attention Economy and the Internet’s Original Sin At the heart of the story of how the internet broke the media business model is the simple fact that the internet was not built to facilitate the flow of money. Payments weren’t built into the internet’s infrastructure—it was considered too risky. Marc Andreessen this “the original sin of the internet.” called The lack of payment infrastructure is the reason why so much of the internet is monetized via advertising. Rather than requiring users to pull out a credit card and type their information into a website, users could be monetized frictionlessly and indirectly, paying not with their money but with a different asset: their attention. That precipitated a shift in power from the old gatekeepers of media who controlled content creation and distribution—the publishers, record labels, and movie studios—to those who amassed consumer attention at scale. Ben Thompson of Stratechery has written extensively about how the platforms, which he calls “ ,” have won the battle for consumer attention and achieve outsized revenue—and outsized power—by aggregating demand. YouTube has more than 2 billion monthly active users. aggregators Facebook has almost 3 billion. Spotify has 365 million. With those mega-sized audience numbers come mega-sized ad revenues. In fact, Google and Facebook alone accounted for of the digital ad revenue generated in 2020. more than half The business model of advertising has profoundly shaped how platforms design their products. Platforms funnel traffic to content they already know will be successful in holding user attention, creating a power law in creator success. Data about user preferences and behavior is the platforms’ most valuable asset, so they close off their ecosystems and lock users into their networks to amass the largest corpus of proprietary data. The ad-based revenue model has enormous implications for content creators, as well. Creators are compelled to seek the broadest possible audiences and to create content that attracts advertisers. This business model—or lack thereof—has a profound impact on which creators can make a living and what they create (incentivizing viral, attention-grabbing, and aspirational content, while disincentivizing niche, in-depth content). The biggest impact of the web2 internet may be the creators who don’t exist and the creations that were never made because they have no viable business model. From the Attention Economy to the Ownership Economy The platform-centric, advertising-powered economy may have won the web2 era, but its victory is not inevitable or final. We’ve written before that creators’ patience with the platforms is wearing thin in a burgeoning —they are starting to question the platforms’ right to exert such outsized control over their work, their relationship with fans, and how they’re rewarded for it. legitimacy crisis Meanwhile, a new generation of technologies is emerging with the promise to change the balance of power in the creator economy. If the pre-internet/web1 era favored publishers, and the web2 era favored the platforms, the next generation of innovations—collectively known as web3—is all about tilting the scales of power and ownership back toward creators and users. There are four main ways that that will happen: By introducing digital scarcity and restoring pricing power to creators By making supporting creators an act of investment, not just altruism By introducing new programmable economic models that spread wealth across the creator landscape Most importantly, by creating pathways for creators to own not just the content they produce, but the platforms themselves Taken together, these four shifts are converging to produce a new era, one where new incentives reward new behaviors, giving the internet the opportunity to collectively hit the “reset” button and move towards a more just distribution of value. Let’s cover each in turn. 1. NFTs and the Introduction of Digital Scarcity Scarcity gets a bad rap, but it is about more than just lack of consumer choice: it’s about producer power—in this case, the ability of creators to derive meaningful income from their creations. In our current world of infinite, platform-mediated content, scarcity does not exist. On social platforms, content is endlessly commoditized—one video is more or less the same as the next video, one song is the same as the next song, and content can be easily duplicated across the internet. Scarcity is sometimes approximated by creators via memberships or digital purchases (e.g. selling e-books, albums, or content subscriptions), but the underlying content can be endlessly reproduced and replicated. That lack of scarcity leads to issues with creators’ content being illegally reproduced and distributed -- undermining attempts at direct monetization. One reason NFTs ( ) are exciting as a technology is that they give creators the ability to regain control over their own content and re-introduce scarcity dynamics that contribute to monetization. In tokenizing their work as an NFT, creators create a verifiable on-chain record of a piece of media’s ownership and provenance. non-fungible tokens The end result is a unique digital asset that traces back to the artist. Fans who are passionate about the creator’s work are willing to pay more for this canonical piece of media, enabling creators to better capture fans’ full willingness to pay. The end impact cannot be understated: content creators no longer need millions of fans to make a living, but can survive on the contributions of a . passionate few The burgeoning music NFT market showcases this effect in action. On streaming platforms,  each stream of a song contributes the same amount of revenue (approximately $0.004 per stream on Spotify), regardless of that fan’s particular intensity of affinity towards the artist. In contrast, on platforms like or , superfans are purchasing NFT music for , with creators earning what previously would have required tens of millions of plays. Brett Shear, an NFT collector who owns 45 songs from Catalog, told Time magazine: “In the same way that you buy art that you want to put in your apartment, I want to listen to this music and enjoy it—and it’s a different feeling to own it.” Catalog Sound thousands of dollars each Purchasing an NFT is akin to collecting real-world merchandise, enabling fans to feel closer to the artist and own something rare, akin to a “ .” Digital scarcity and uniqueness—which had been missing from the web2 internet—is enabled by the blockchain, leading to a new business model for creators that lessens the economic control of platforms. non-fungible super-like Excitingly, the introduction of scarcity through NFTs doesn’t mean that access to the underlying media is limited, as it would be with paywalls or paid digital downloads. The actual media underpinning NFTs can remain , available to be consumed by anyone at no cost. Those who think this undermines the scarcity of NFTs (“right-click and save”) fundamentally miss the point. public goods 2. Patronage+: Supporting Creators Becomes an Investment, Not Just an Act of Altruism In , I described that creators could tap into fans’ to monetize at higher price points. By delivering substantive value and results, creators could more effectively monetize and make a living from fewer fans: 100 True Fans self-interest This represents a move away from the traditional donation model—in which users pay to benefit the —to a model, in which users are willing to pay more for something that benefits . creator value themselves Web3 takes this idea to the next level, because all tokens are investments that not only fund the creator, but also could benefit the if the value appreciates. Jesse Walden defines “ ” as patronage with the possibility of profit, a phenomenon that is introduced through tokenized ownership. holder patronage+ That investment element was an impossibility in web2 without an on-chain record of ownership like an NFT or a (imagine trying to resell a TikTok video that was downloaded from the app). social token What’s an example of patronage+ in action? Earlier this year, Mario Gabriele of The Generalist for a group of analysts to create a deep-dive on Coinbase, as well as to commission artwork to accompany the essay. crowdfunded 20 ETH Crowdfunders received proportional stakes in the briefing and artwork, all of which were minted as NFTs. In total, the NFT sales earned 28.6 ETH, leading to a return of 43% to crowdfunders in just a few weeks. Another benefit beyond patronage and investment is membership to a like-minded group of individuals. Many successful crowdfunds and NFT sales in the crypto space have been driven by users’ desire to belong to a community, which are gated by ownership of tokens. This echoes a phenomenon I wrote about in 100 True Fans: “People are willing to pay high prices for exclusive, differentiated content and access to a network of like-minded individuals.” For fans, the possibility of profit amplifies their incentive to support a creator. Interestingly, it also introduces an entirely new segment into the creator’s orbit that had never existed before in web2: . speculators Importantly, all of these users—by virtue of becoming owners of an asset that is aligned with the creator’s success—have an incentive to help amplify the creator’s work. 3. New Programmable Economic Models A truth of the creator economy is that creation is often a collaborative act. YouTube creators star in each others’ videos. Musicians sample from and are inspired by each other’s work. A TikTok video is, more often than not, made up of the (often unseen) work of multiple creators: a soundtrack from one creator, choreography from another. Unfortunately, web2 systems are not set up to reward or track this collaborativity. In the winner-take-all world of algorithmic platforms, too often the value only flows to the creators that go viral, leaving out everyone else involved in the creation of the work. This has led to and discontent among creators who feel that their contributions go unrecognized and uncredited. strikes In web3, the promise of tokenization means that it’s possible to build in royalties such that the entire chain of attribution is able to profit from a collaborative work. Early examples of this include and ’s splits functionality, which automatically routes earnings to various Ethereum addresses that contributed to a project. Mirror Foundation Down the line, it’s conceivable that any digital work could utilize elements from a universal media library, with revenue splits and attribution automatically accounted for. Nir Kabessa wrote about the “ ,” in which ideas that get remixed and propagated on the internet could become the basis of value creation: meme economy The famous meme GIF is linked to the address of the NFT so when someone shares the original NFT in their article, they can pull the on-chain address. This is powerful for memes because it allows them to maintain attribution and context in every platform. So any action on a meme NFT is accessible, readable, and usable on almost all platforms. Every bid, swap, and transaction is added to the metadata of that specific NFT. Beyond memes, if every piece of creative work is linked to an on-chain record of its provenance, it becomes possible to trace that work across the internet and for creators to monetize subsequent use of their work. 4. DAOs and Community Ownership We’ve argued in this essay that a root cause of inequality in the creator landscape is the outsized control that platforms exert over creators and their work through the ownership of the means of production and distribution of content. The most direct way to challenge that control is to change who owns the means of production. DAOs ( ) and other mechanisms of collective ownership create a pathway to disrupt the centralized hold that the platforms have over the creator landscape by making it possible for creators to work collaboratively an external mediator dictating the terms of engagement. decentralized autonomous organizations without In a DAO, governance systems are decided by the members, and there are no external shareholders pressuring for profit extraction. Instead, in a creator DAO, the owners are the participants: those who make the content, distribute it, and consume and value it. An early example of a creator platform that progressively decentralized is , an NFT marketplace that to its artists and collectors, who will govern curation, the DAO treasury, and future product direction. SuperRare distributed tokens Other organizations start community- and token-first: is a community of 42 musicians, visual artists, developers and strategists, who developed an interactive choose-your-own-adventure web3 game with music at its core. provides photographers with commissions to produce their envisioned projects, a community, grant opportunities, and educational resources to help them explore NFT photography. ElektraDAO ObscuraDAO The promise of DAOs is alignment of incentives through stakeholder primacy and a removal of the need to value. The result: a democratized, disintermediated content landscape where creators have control over their work, how it’s distributed—and how it’s valued. extract Beyond DAOs, the inherent interoperability of web3 makes platform lock-in likely to be a much less pernicious problem than it is in web2. The atomic unit of web3 is the account, which users control with their key pair and can be used across any app or protocol. Because all smart contracts are transparent and publicly inspectable, opaque and arbitrary back-room deals are harder to pull off. Though in its infancy, the web3 world is evolving towards a more open and standards-based philosophy, which benefits creators and users. Power—and Ownership—to the Creators For as long as the internet has existed, thinkers and philosophers have painted utopian visions of what it would make possible—particularly in media. That utopian vision has not come to pass. At least, not yet. In the past, I’ve called ownership the from which all else flows. Ownership determines incentives. It determines opportunities. It determines how wealth is created—and for whom. original system condition For the last decade, we’ve lived in a period in which ownership has been concentrated among a few centralized technology platforms, which owned the data, end-user relationships, and the means of distributing and monetizing content. While user-generated content creation exploded during this period, it also caused reliance on a handful of new gatekeepers, widespread burnout, and economic unsustainability for the vast majority of creators. Fortunately, there are new developments on the horizon that represent a shift in the balance of power towards creators. With key new capabilities enabled by web3—digital scarcity, patronage that doubles as investment, programmable business models, and community ownership—we are on the cusp of a new creative renaissance on the internet. I believe web3 has the potential to unlock incredible opportunities for everyone who contributes and creates on the internet: a true Golden Age of content that we’ve all been looking forward to. By Li Jin and Katie Parrott for . Every You can collect this post as an NFT on Mirror . here

The Golden Age of Web3

La edad de oro de la Web3

L'âge d'or du Web3

Web3 का स्वर्ण युग

Web3 の黄金時代

A Era de Ouro da Web3

Thời đại hoàng kim của web3

Web3 的黄金时代

One quality that separates seasoned entrepreneurs from the newbies is their willingness and ability to take calculated risks. You will notice this tendency from the world’s best entrepreneurs including Richard Branson, Arianna Huffington and Jack Ma. Irrespective of the type and scale of the business, ranging from a remotely operating technology business to a multinational corporation, there are some financial mistakes that founders should avoid at all costs. Entrepreneurs are excellent problem solvers, owing to their trait of pushing boundaries and discovering new things about the industry they target. They look for every opportunity to recognize their limits and sail through unknown waters. The risk-taking tendency arises from the entrepreneur’s ability to associate risk with opportunity. On the other hand, the same eagerness to take risks makes them more prone to mistakes. Indeed, entrepreneurs make mistakes all the time. The successful ones have had an equal number of successes and failures in their careers. Some failures can be corrected immediately. Those concerning money can burn your business. The sudden drying up of the cash flow, an unexpected expense and quickly accumulating debt can bring down even the most promising idea to its knees. Based on my experience, here are the 6 biggest and most fatal financial mistakes entrepreneurs make and how to avoid them at all costs. #1. Failing to keep the personal and business accounts separate Even if you are a freelancer or a solopreneur, there is no shortcut to keeping your finances separate. Sure the convenience might tempt you to ignore this tip. Commit to creating a separate savings account and credit cards for your brand before you start collecting payments. I ask you to do this right at the beginning so that it becomes easier to do the accounting for your business, planning for the tax payments and plan for those unpredictable months in advance. A separate bank account and credit card account allows you to have an accurate picture of the financial health of your business. Prevent an overlap between your savings and what your business is generating and costing monthly. If you are not careful, you may fall into the pit of inappropriate use of business funds. If in the future your business takes a downward nosedive, the separate business and credit account will prevent your credit score from getting damaged. - Tip Separating the business and personal accounts ensures that you are focusing on growing your company and securing your future. Don’t blur these two lines, keep them separate. #2. Making big (and often unwanted) purchases for your business When starting a new business you may be tempted to want to get the best laptops, a plush office, top-class software and highly talented staff to help you scale your business. Even when you are itching to make the costly purchases (which may seem like an investment), think about it carefully. The basic expenses like registering your company, developing a website and attending industry events may be mandatory and unavoidable. Before spending a penny, ask yourself if that expense will generate revenue for you in the immediate future. Non-essential expenses such as office parties, team-building trips and fancy co-working spaces will not improve the bottom line for your company’s growth. While starting out, instead of going for a paid subscription to a popular CRM, go for a basic and functional free or cheaper alternative. Instead of full-time staff, look for freelancers from platforms such as Upwork or LinkedIn. Invest in for your globally spread team to communicate seamlessly. virtual communication tools - Tip Make do with the absolute bare minimum when you are launching your business and in the early stage. Accumulate enough disposable cash before spending on the “nice-to-have” needs. #3. Failing to repair your credit score While you learn how to separate your personal and business finances, your personal credit score can impact the financial standing of your business. The numerical credit score range is depicted below. Source At no point should your credit score fall below 649 points. If it does, it will impact your ability to get credit in the near future. Also in the early stages when an angel investor decides to invest in your business, your personal credit score matters. The biggest mistake entrepreneurs make is assuming that everything would be fine. This may come to bite you when raising a loan for your startup. Start with by honestly looking at your financial activities and assessing where you can improve. raising your credit score Additional tips that you can follow are: Pay your bills on time. Set up a direct debit so that you don’t have to remember to make the payment every month. While taking out loans or borrowing from the credit card, know your credit limit. The amount borrowed shouldn’t exceed the third of your credit limit. #4. Taking loans for personal purchases It is not uncommon for entrepreneurs to face a scenario where they are forced to dip into their personal funds to finance the business. This could be for expanding to a new niche or geography or for a marketing campaign that promises to deliver results. Especially during the first few years of your business, there would be numerous roadblocks you are going to hit. While failures are unavoidable, some would accompany a huge price tag. If you have taken loans for a car or a home, an unexpected business expense may strap down your savings. - Tip While growing your company, stay as lean as possible, both in business and personally. #5. Not saving for emergencies or a downtime Every financial expert will tell you to have ample savings for unexpected downtime. A lack of proper cash flow management can sink many businesses. Research by the Association of Chartered Certified Accountants found of businesses fail because of cash flow issues. For those entrepreneurs who are not financially savvy, cash flow management becomes a liability in times when business is in the initial stages. 82% The rule of thumb is that entrepreneurs should keep a minimum of three months’ worth of expenses saved for emergencies. In the current times of COVID-19, numerous industries have been paused, and a contingency fund could be your savior. Don’t let this issue dismantle your business because you did not pay attention to the financial health of your business. – Tip Set aside a percentage from your profits each month that you wouldn’t touch unless in an emergency. #6. Failing to set clear budget goals A clear budget plan guides you on what you can and can’t afford to spend every month. Your company may not see the light of the day if you fail to create a financial plan. How else would you know what works and what doesn't? Which activities generate the maximum revues and what should be tweaked? Setting clear budget goals is all the more important for founders because your job is to take your business to profitability. - Tip A carefully chalked budget for operations, employees, marketing and technology expenses increases your financial discipline, making the road-map to your business growth easier. Master your money matters to stay away from financial disasters that can cost you your business. In business, it’s easier to lose money than earn it. Failure in business is a result of a series of bad decisions and financial mistakes. You can stay away from these 6 deadly financial mistakes by paying more attention to your cash flow throughout the year. The key to succeeding financially is by planning your budget, tracking your expenses, saving for emergencies and keeping your business and personal expenses separate. Don’t stop thinking about new ways to generate revenue for your company. Feature image source - Unsplash .

6 Fatal Financial Mistakes Entrepreneurs Should Stay Away From

One quality that separates seasoned entrepreneurs from the newbies is their willingness and ability to take calculated risks. You will notice this tendency from the world’s best entrepreneurs including Richard Branson, Arianna Huffington, and Jack Ma. Irrespective of the type and scale of the business, ranging from a remotely operating technology business to a multinational corporation, there are some financial mistakes that founders should avoid at all costs. Entrepreneurs are excellent problem solvers, owing to their trait of pushing boundaries and discovering new things about the industry they target. They look for every opportunity to recognize their limits and sail through unknown waters. The risk-taking tendency arises from the entrepreneur’s ability to associate risk with opportunity. On the other hand, the same eagerness to take risks makes them more prone to mistakes. Indeed, entrepreneurs make mistakes all the time. The successful ones have had an equal number of successes and failures in their careers. Some failures can be corrected immediately. Those concerning money can burn your business. The sudden drying up of the cash flow, an unexpected expense and quickly accumulating debt can bring down even the most promising idea to its knees. Based on my experience, here are the 6 biggest and most fatal financial mistakes entrepreneurs make and how to avoid them at all costs. – Even if you are a freelancer or a solopreneur, there is no shortcut to keeping your finances separate. #1. Failing to keep the personal and business accounts separate Sure the convenience might tempt you to ignore this tip. Commit to creating a separate savings account and credit cards for your brand before you start collecting payments. I ask you to do this right at the beginning so that it becomes easier to do the accounting for your business, planning for the tax payments and plan for those unpredictable months in advance. A separate bank account and credit card account allows you to have an accurate picture of the financial health of your business. Prevent an overlap between your savings and what your business is generating and costing monthly. If you are not careful, you may fall into the pit of inappropriate use of business funds. If in the future your business takes a downward nosedive, the separate business and credit account will prevent your credit score from getting damaged. Tip - Separating the business and personal accounts ensures that you are focusing on growing your company and securing your future. Don’t blur these two lines, keep them separate. – When starting a new business you may be tempted to want to get the best laptops, a plush office, top-class software, and highly talented staff to help you scale your business. #2. Making big (and often unwanted) purchases for your business Even when you are itching to make the costly purchases (which may seem like an investment), think about it carefully. The basic expenses like registering your company, developing a website, and attending industry events may be mandatory and unavoidable. Before spending a penny, ask yourself if that expense will generate revenue for you in the immediate future. Non-essential expenses such as office parties, team-building trips, and fancy co-working spaces will not improve the bottom line for your company’s growth. While starting out, instead of going for a paid subscription to a popular CRM, go for a basic and functional free or cheaper alternative. Instead of full-time staff, look for freelancers from platforms such as Upwork or LinkedIn. Invest in communication tools for your globally spread team to communicate seamlessly. Tip - Make do with the absolute bare minimum when you are launching your business and in the early stage. Accumulate enough disposable cash before spending on the “nice-to-have” needs. – While you learn how to separate your personal and business finances, your personal credit score can impact the financial standing of your business. #3. Failing to repair your credit score The numerical credit score range is depicted below. Source At no point should your credit score fall below 649 points. If it does, it will impact your ability to get credit in the near future. Also in the early stages when an angel investor decides to invest in your business, your personal credit score matters. The biggest mistake entrepreneurs make is assuming that everything would be fine. This may come to bite you when raising a loan for your startup. Start with raising your credit score by honestly looking at your financial activities and assessing where you can improve. Additional tips that you can follow are: ·         Pay your bills on time. Set up a direct debit so that you don’t have to remember to make the payment every month. t. ·         While taking out loans or borrowing from the credit card, know your credit limit. The amount borrowed shouldn’t exceed the third of your credit limi – It is not uncommon for entrepreneurs to face a scenario where they are forced to dip into their personal funds to finance the business. This could be for expanding to a new niche or geography or for a marketing campaign that promises to deliver results. #4. Taking loans for personal purchases Especially during the first few years of your business, there would be numerous roadblocks you are going to hit. While failures are unavoidable, some would accompany a huge price tag. If you have taken loans for a car or a home, an unexpected business expense may strap down your savings. Tip - While growing your company, stay as lean as possible, both in business and personally. – Every financial expert will tell you to have ample savings for unexpected downtimes. #5. Not saving for emergencies or a downtime A lack of proper cash flow management can sink many businesses. Research by the Association of Chartered Certified Accountants found of businesses fail because of cash flow issues. For those entrepreneurs who are not financially savvy, cash flow management becomes a liability in times when business is in the initial stages. 82% The rule of thumb is that entrepreneurs should keep a minimum of three months’ worth of expenses saved for emergencies. In the current times of COVID-19, numerous industries have been paused, and a could be your savior. contingency fund Don’t let this issue dismantle your business because you did not pay attention to the financial health of your business. Tip – Set aside a percentage from your profits each month that you wouldn’t touch unless in an emergency. – A clear budget plan guides you on what you can and can’t afford to spend every month. #6. Failing to set clear budget goals Your company may not see the light of the day if you fail to create a financial plan. How else would you know what works and what doesn't? Which activities generate the maximum revues and what should be tweaked? Setting clear budget goals is all the more important for founders because your job is to take your business to profitability. Tip - A carefully chalked budget for operations, employees, marketing and technology expenses increases your financial discipline, making the roadmap to your business growth easier. Master your money matters to stay away from financial disasters that can cost you your business. In business, it’s easier to lose money than earn it. Failure in business is a result of a series of bad decisions and financial mistakes. You can stay away from these 6 deadly financial mistakes by paying more attention to your cash flow throughout the year. The key to succeeding financially is by planning your budget, tracking your expenses, saving for emergencies, and keeping your business and personal expenses separate. Don’t stop thinking about new ways to generate revenue for your company. Feature image source - Unsplash .

6 Financial Mistakes That Prove To Be Fatal For Startups

“Just like there’s a possibility and time for loss, there’s always time for recovery” - Jenny Brown, head of the Recovery Technical Team at BCA. ALPHARETTA, USA, November 7th, 2023/Chainwire/-- Celebrates 3 Remarkable Years of Helping Victims of Crypto Scams Recover Their Lost Crypto. Broker Complaint Alert (BCA) celebrates 3 years of offering one of the best and most remarkable crypto recovery experiences. Since BCA began operating in December 2020, it has helped over twelve thousand scam victims to recover their lost funds from scammers. Broker Complaint Alert (BCA) BCA introduced a solution that is focused on ensuring that every single scam victim who reports the scam to their platform stands a 94% chance of recovering lost funds. This innovative approach has literally proven itself to be 94% accurate. In other words, roughly 94% of all cases reported to BCA so far were successful. BCA combines the most brilliant minds within the crypto space and the best in terms of blockchain technology to help crypto scam victims recover their lost crypto assets. The BCA solution completely takes the stress off scam victims, especially victims of crypto scams, and puts smiles on their faces once again. How Broker Complaint Alert (BCA) Helps Crypto Scam Victims With Crypto Recovery Users who have lost their crypto assets or other financial assets to any form of scam can relax and put their minds at ease by allowing Broker Complaint Alert (BCA) to lead them on a journey of successfully recovering their lost funds. Broker Complaint Alert (BCA) is a prominent organization dedicated to helping and supporting victims of crypto scams, investment scams, forex scams, or any other form of financial scams to recover their stolen funds from scammers. BCA has a dedicated team of committed online consultants that offer personalized guidance, expert consultation and access to the ebay and most reputable crypto recovery companies and service providers. 5 FAQs About Crypto Recovery Answered There are many questions relating to crypto recovery, and BCA is providing answers to 5 of the most Frequently Asked Questions here; 1.) Are crypto asset recovery companies legit? Yes, crypto asset recovery companies are legit. However, not all crypto asset recovery companies are legit. Just like in every other field, there are some bad players in crypto asset recovery. That is why it is important to conduct proper research before hiring any crypto asset recovery company. 2.) Has anyone ever recovered stolen crypto? Of course, yes! Many people have been able to recover their stolen crypto. Broker Complaint Alert (BCA) has successfully helped over 12,350 people recover their stolen crypto in the last 3 years. 3.) Can a user recover his scammed crypto? Yes, a user can recover his scammed crypto. When it comes to crypto recovery, however, the user has to go about it the right way to be able to achieve success in recovering his scammed crypto. 4.) How can a user find the best crypto recovery service provider? Finding the best crypto recovery company can seem like a daunting task. And it could be, especially if a user is not searching in the right direction. The good news is that BCA saves the stress of having to waste time trying to find the best crypto recovery company alone. Individuals seeking a way to recover stolen crypto can find all the necessary information in this publication. To initiate a successful recovery of their stolen crypto, they simply need to make a report . here How to Recover Stolen Crypto Using Broker Complaint Alert (BCA) Relief Funds The relief process offered by Broker Complaint Alert (BCA) provides hope for victims of crypto scams. With up to $9 billion available for compensation, this initiative aims to bring justice and restitution to those who have suffered financial loss due to fraudulent practices in the crypto world. By understanding the relief process, victims can navigate the application process with confidence, ensuring their eligibility for financial reimbursement. BCA’s commitment to transparency and fairness further establishes them as a trusted entity within the crypto industry. Recover your scammed crypto by reporting any crypto scam to Broker Complaint Alert (BCA). BCA is the source of this content. This Press Release is for informational purposes only. The information does not constitute investment advice or endorsement. ABOUT Broker Complaint Alert (BCA) helps victims of investment fraud, forex scams, crypto scams, and any type of fraud that happened to you. BCA has helped and guided thousands of people over the past 3 years. Broker Complaint Alert (BCA) provides information on financial brokers that scam people in any country. Their online consultants work round the clock to make sure you get the right service from the right fund recovery or lawyer in their field of expertise. Broker Complaint Alert (BCA) Contact Costigliola Romualdo Broker Complaint Alert (BCA) support@brokercomplaintalert.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program . here

Broker Complaint Alert(BCA) Celebrates 3 Years Of Helping Victims Of Crypto Scams

ব্রোকার কমপ্লেইন্ট অ্যালার্ট (বিসিএ) ক্রিপ্টো স্ক্যামগুলির শিকারদের সাহায্য করার 3 বছর উদযাপন করে

Broker Complaint Alert (BCA) feiert 3 Jahre Hilfe für Opfer von Krypto-Betrug

Broker Complaint Alert (BCA) celebra 3 años ayudando a las víctimas de estafas criptográficas

Broker Complaint Alert (BCA) célèbre 3 ans d'aide aux victimes d'escroqueries cryptographiques

ब्रोकर कंप्लेंट अलर्ट (बीसीए) क्रिप्टो घोटाले के पीड़ितों की मदद के 3 साल का जश्न मनाता है

Broker Complaint Alert (BCA) が仮想通貨詐欺の被害者支援 3 周年を祝う

Broker Complaint Alert(BCA)는 암호화폐 사기 피해자를 돕는 3주년을 기념합니다.

Alerta de reclamação de corretor (BCA) comemora 3 anos ajudando vítimas de fraudes criptográficas

Оповещение о жалобах брокеров (BCA) отмечает 3-летие оказания помощи жертвам крипто-мошенничества

Broker Şikayet Uyarısı (BCA), Kripto Dolandırıcılığı Mağdurlarına Yardımın 3. Yılını Kutluyor

Cảnh báo Khiếu nại Nhà môi giới (BCA) kỷ niệm 3 năm giúp đỡ nạn nhân của các vụ lừa đảo tiền điện tử

经纪商投诉警报 (BCA) 庆祝帮助加密诈骗受害者 3 周年

This is the summary and my key takeaways from the by LinkedIn on how NLP is being used (as of ) in designing its Help Search System. This highlights the problem statement and the different iterations of solutions that were adopted along with their shortcomings. original post 2019 Problem Statement: Given a query by a user, fetch the most relevant Help Article from the database. Iteration 1: Initial Solution Indexed all the help articles (documents) in the database using . In short, it generates an inverted dictionary that maps terms to all the documents it appeared in. Lucene Index 2. The given query is used to fetch all the relevant documents (hits) using Lucene indexing. 3. Each hit is scored using the algorithm, which takes the into account, giving the highest weights to hits in the , then hits in the and then the , and returns a weighted score. BM25F document structure Title Keywords Body 4. Return the best-scored articles. Why it failed Since the document retrieval system is ), without taking into account, the following are two example failure cases: Term based ( syntactics semantics Iteration 2: Final Solution Step 1: Text Normalization “ normalized to “ how canceling my premium accounts immediately” cancel premium account” Step 2: Query Mapping It might happen that the normalized query doesn’t have any words in common with the words in the articles. Hence, each query is mapped to a more representative query to fill the gap between a user’s terminology and the article’s terminology. Done in the following two steps: Queries are grouped together based on similarity metrics Query Grouping: For each of the queries in the Query group, a is calculated and the top K queries are selected as Rep Queries 2. Topic Mining and Rep Scoring: repScore is the similarity between the raw query and another query in the group sim(RQ, Q2) is the maximum similarity between Q2 and one of the topics from the title (similarly for the body) sim(Q2, title) Step 3: Intent Classification Long-tailed queries might not have a Rep Query, in which case a is used for classifying the of the query. CNN Intent For example: “Canceling Your Premium Subscription” and “Canceling or Updating a Premium Subscription Purchased on Your Apple Device” are considered to have the same intent of “cancel premium.” Overall Flow Also Published Here

How LinkedIn Uses NLP to Design their Help Search System

Cómo utiliza LinkedIn la PNL para diseñar su sistema de búsqueda de ayuda

Comment LinkedIn utilise la PNL pour concevoir son système de recherche d'aide

कैसे लिंक्डइन एनएलपी का उपयोग उनकी सहायता खोज प्रणाली को डिजाइन करने के लिए करता है

LinkedIn が NLP を使用してヘルプ検索システムを設計する方法

Como o LinkedIn usa o NLP para projetar seu sistema de pesquisa de ajuda

Cách LinkedIn sử dụng NLP để thiết kế hệ thống tìm kiếm trợ giúp của họ

LinkedIn 如何使用 NLP 设计他们的帮助搜索系统

This is a continuation of a series of articles in which I briefly cover the main points of a specific topic in system architecture design. The first article can be read and the full guide you can find on my . here github Any complex system is a mosaic of numerous components, each with its specific function. These components don't operate in isolation; they constantly interact over a network, exchanging data and commands. Understanding the basics of these interactions is crucial. One must understand how components communicate over the network to comprehend the system's overall performance and resilience truly. Types Networks can be divided into four types based on size, architecture, range, and function: : Designed for personal use, usually within a person's range. It might connect devices like a computer, smartphone, and smartwatch, often Bluetooth. Personal Area Network (PAN) ): Connects devices within a limited area, such as a home, office, or school. It's typically used for connecting computers and sharing resources like printers or internet connections within a confined geographical area. Local Area Network (LAN Covers a larger area than a LAN but is smaller than a WAN, typically spanning a city or a large campus. Local service providers often use it to offer connections to businesses and homes in a town. Metropolitan Area Network (MAN): : Spans a larger geographical area, often connecting multiple LANs. The internet is the most prominent example of a WAN, linking computers and networks worldwide. Wide Area Network (WAN) Components Building and maintaining networks would be impossible without specialized hardware devices: : Physical cables (like Ethernet) provide a wired connection between devices, while wireless access points allow devices to connect to the network without physical cables, using Wi-Fi or other wireless technologies. Cable & Wireless Access Point : These are hardware components, often cards inserted into computers or other devices, that allow them to connect to a network. Network Interface Card (NIC) : A network device that amplifies or regenerates a signal, allowing it to travel longer distances without degradation. It's primarily used in wired and wireless networks to extend the range of communication and ensure data integrity over extended distances. Repeater A bridge operates at the data link layer. A bridge is a repeater, adding the functionality of filtering content by reading the MAC addresses of the source and destination. It is also used for interconnecting two LANs working on the same protocol. Bridge: : These basic networking devices connect multiple devices in a LAN, acting as a single network segment. Hub cannot filter data, so data packets are sent to all connected devices. Hub : Devices in a network that connect other devices. Unlike hubs, which broadcast the same data to all devices, switches are more intelligent, directing data only to the device that needs it. Switches : Devices that forward data packets between computer networks. They determine the best path for data transfer. Routers typically connect LANs and WANs and have a dynamically updating routing table based on which they make decisions on routing the data packets. Routers Topologies Network topology is a structural layout that dictates how different network devices and components are connected and how data is transmitted. The choice of topology significantly impacts the network's performance, scalability, and fault tolerance. It is categorized into two main types: : Describes the physical layout of devices, cables, and other network components. It represents how network devices are physically connected. Physical : Describes the data flow within the network, regardless of its physical design. It represents how data is transmitted between network devices. Logical The following types of topologies are distinguished: Point-to-Point A direct connection between two nodes or endpoints. This is the simplest form of network topology. : Advantages The direct and dedicated link ensures high-speed data transfer. Simple configuration and setup. Reliable communication since there are only two nodes involved. : Disadvantages It is not scalable for larger networks as it would require a dedicated line for every pair of devices. It can be more expensive in scenarios where multiple connections are needed due to the need for individual links. Bus All devices share a single communication line. Data sent by a device is available to all other devices, but only the intended recipient accepts and processes that data. : Advantages Easy to implement for small networks. Cost-effective due to minimal cabling. : Disadvantages Performance degrades as more devices are added or network traffic increases. A single cable failure can bring down the entire network. Ring Each device is connected to two other devices, forming a ring. Data travels in one or sometimes two directions. : Advantages It can handle larger data loads than bus topology. : Disadvantages A failure in one cable or device can take down the entire network. More difficult to install and reconfigure. Star All devices are connected to a central device (e.g., a switch or hub). : Advantages Easy to install and manage. Failure in one cable doesn't affect other devices. : Disadvantages If the central device fails, the whole network is inoperable. Requires more cable than bus topology. Tree Hybrid topology that combines characteristics of star and bus topologies. Groups of star-configured networks are connected to a linear bus backbone. : Advantages Hierarchical and scalable. Grouping of devices makes it easy to manage. : Disadvantages Failure in the backbone will cause division in the network. More cabling is required than other topologies. Mesh Devices are interconnected. Every device is connected to every other device. : Advantages Provides high redundancy and reliability. Data can be transmitted from multiple devices simultaneously. : Disadvantages It requires more cabling, making it expensive. Complex to install and configure. Hybrid Combination of two or more topologies. : Advantages Flexible and reliable as it inherits the advantages of its component topologies. Scalable. : Disadvantages Complex design. It can be more expensive due to multiple configurations. Protocols Network protocols are rules or standards that define how data is transmitted and received over a network. These protocols ensure that devices on a network (or across multiple networks) can communicate with each other in a standardized way. Common Protocols : The fundamental suite of protocols that powers the Internet. TCP ensures data is sent correctly, and IP provides data is sent to the correct place. TCP/IP : A connectionless protocol that, unlike TCP, doesn't establish a connection before sending data and doesn't guarantee the order of data packets. UDP Protocols used for transferring web pages on the Internet. HTTPS includes security measures to encrypt data. HTTP, HTTPS: : A protocol designed to transfer files over a network. FTP : Used for email transmission. SMTP : Used for retrieving and storing emails from a mail server. IMAP : Used for retrieving emails from a mail server. POP3 : Used for error reporting and diagnostics related to IP processing. ICMP : Translates domain names to IP addresses, allowing users to access websites using human-readable names. DNS : Assigns IP addresses dynamically to devices on a network. DHCP : Cryptographic protocols are designed to provide secure communication over a computer network. SSL/TLS : Point-to-Point Protocol (PPP) is basically an asymmetric protocol suite for various connections or links without framing. PPP : Defines how devices on a local area network (LAN) communicate. It operates at both the physical layer and the data link layer of the OSI model. Ethernet OSI and TCP/IP Models The OSI and TCP/IP are two primary models that serve as guiding frameworks that describe the processes involved in data communication over a network. OSI Model Protocol Data Format TCP/IP Model 7 Application HTTP, DNS, SMTP, FTP Data Application 6 Presentation TLS, SSL Data Application 5 Session Sockets Data Application 4 Transport TCP, UDP Segment, Packet Transport 3 Network IP, ICMP, IPsec IP Datagram Internet 2 Data Link PPP, Ethernet Frame Network Interface 1 Physical Fiber, Wireless Bit Network Interface The (Open Systems Interconnection) model is a conceptual framework for understanding network interactions in seven layers. Each layer serves a specific function: OSI : Deals with the physical connection between devices. It defines the hardware elements, such as cables, switches, and NICs. Physical : Responsible for creating a reliable link between two directly connected nodes, handling errors, and regulating data flow. Data Link : Determines the best path to transfer data from the source to the destination across the network. Network : Ensures end-to-end communication, data flow control, and error correction. Transport : Establishes, maintains, and terminates application connections at both ends. Session : Translates data between the application and transport layers, ensuring data is readable. Presentation : Directly interacts with end-user applications, ensuring effective communication between software and lower layers of the OSI model. Application The is a more concise model used predominantly in the modern internet, which simplifies the OSI layers into four categories: TCP/IP : Combines the functions of OSI's Physical and Data Link layers, focusing on how data is sent/received on a network medium. Network Interface : Corresponds to the Network layer in OSI, handling data routing, IP addressing, and packet forwarding. Internet : Similar to OSI's Transport layer, ensuring data reaches the correct application and is transmitted reliably (TCP) or quickly (UDP). Transport : Merges the functions of OSI's Session, Presentation, and Application layers, dealing with end-user application processes. Application Security In system design, ensuring robust network security is paramount to protect sensitive data and maintain the trust of users and stakeholders, ensure business continuity, and meet regulatory requirements. Common Threats and Vulnerabilities : Malicious attempts to disrupt the normal traffic of a targeted server, service, or network by overwhelming it with a flood of internet traffic. DDoS Attacks : Software designed to disrupt, damage, or gain unauthorized access to a computer system. This includes viruses, worms, spyware, and ransomware. Malware : Attackers secretly intercept and relay communication between two parties. They can eavesdrop or impersonate one of the parties, deceiving the other. Man-in-the-Middle Attacks : Threats originating from within the organization, such as employees, former employees, or partners with inside information concerning security practices. Insider Threats : Bugs or weaknesses in software can be exploited to gain unauthorized access or disrupt services. Examples include buffer overflows and unhandled exceptions. Software Flaws : Physical components can have vulnerabilities, like firmware that can be tampered with or backdoors installed by manufacturers. Hardware Weaknesses : Devices like routers, switches, or firewalls that are not correctly configured can expose the network to various threats. Misconfigured Network Devices : Insufficient password policies, lack of multi-factor authentication, or lax access controls can allow unauthorized access. Weak Authentication and Authorization : Data that isn't encrypted can be easily intercepted and read as it travels across a network. Unencrypted Data : Systems that are no longer supported or haven't been updated can have known vulnerabilities that are easy to exploit. Outdated Systems : This refers to physical access points where an attacker could plug into the network or access servers directly. Physical Vulnerabilities Best Practices for Ensuring Network Security : Deploy hardware and software firewalls to monitor and control incoming and outgoing network traffic based on security policies. Firewalls : Use encryption protocols, especially for sensitive data, both in transit (like SSL/TLS for web traffic) and at rest (like database encryption). Encryption : Keep all systems, software, and applications updated to patch vulnerabilities. Regular Updates : Implement MFA to add a layer of security, ensuring that users provide two or more verification factors to gain access. Multi-Factor Authentication (MFA) : Use network monitoring tools to monitor the network for unusual activities or unauthorized access continuously. Network Monitoring : Educate employees and users about the importance of security and how to recognize potential threats. Security Awareness Training : Limits the spread of threats within the network and provides better control over data access. Network Segmentation : Ensures data availability and business continuity in case of breaches or failures. Backup and Disaster Recovery : Physical access to network devices can lead to breaches. Physical Security Conclusion Grasping the fundamentals of networking, from the intricacies of topologies to the nuances of basic protocols, is not merely an academic exercise—it's crucial for creating robust and efficient systems. A solid grounding in network principles ensures systems communicate seamlessly, adapt resiliently, and scale efficiently.

The System Design Cheat Sheet: Networks

সিস্টেম ডিজাইন চিট শীট: নেটওয়ার্ক

Der Spickzettel zum Systemdesign: Netzwerke

La hoja de referencia para el diseño de sistemas: redes

L'aide-mémoire pour la conception de systèmes : réseaux

सिस्टम डिज़ाइन चीट शीट: नेटवर्क

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