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Oracles: Revenue and Tokenomics

Oráculos: Ingresos y Tokenomics

Oracles : revenus et Tokenomics

Oracles: राजस्व और टोकनोमिक्स

オラクル: 収益とトークンノミクス

Oráculos: Receita e Tokenômica

Oracles: Doanh thu và Tokenomics

预言机：收入和代币经济学

Blockchain oracles are one of the critical components helping bridge the divide between the real and digital worlds. Oracles are third-party services that provide blockchain platforms with information about external real-world events as well as external digital events. Data from oracles power . Smart Contracts and DAOs Oracle Definition A blockchain oracle is a trusted third-party service that provides smart contracts with authenticated external data sources from the real world through an API. Oracles connect smart contracts with events in the outside world. Smart contracts often need to be triggered by an external event. Oracles can be created to provide a wide range of data to smart contracts. For example, an oracle could provide real-world weather data, outcomes of events, outcomes of legal cases, financial statistics, economic data, interest rates, market data, performance data from a vehicle or machine, and so on. The important thing to remember about oracles is that most smart contracts are meant to be executed when a condition is met in the real world. Oracles are trusted sources that can provide authenticated data about real-world events. Software Oracles Software oracles provide digital information to blockchains. The information they provide exists on other websites, servers, databases, etc. Some examples of the data that software oracles provide include prices of stocks, exchange rates, cryptocurrency prices, and prices. NFT Hardware Oracles Hardware oracles help connect blockchain platforms with events in the real world. This data is gathered from the real world using sensors and reading devices and transmitted to blockchain platforms. Hardware oracles can send data to blockchain platforms from the following sensors: thermometers, RFID readers, barcode scanners, electronic sensors, and other . IoT devices The Blockchain Oracle Problem Blockchain platforms' decentralized and distributed nature makes them secure and trustworthy. Data provided by a centralized oracle presents security issues; for example, if the centralized oracle provider is compromised, then it could send erroneous data into the blockchain. The incorrect data could then compromise the integrity of the blockchain. Solving the Blockchain Oracle Problem: Decentralized Oracles Decentralized oracles help solve the blockchain oracle problem. While developing a smart contract, you could use a decentralized oracle to provide data to it, or you could enable it to get data from multiple oracles and only trigger an event when the majority or all of the oracles offer the same input. There has been some debate about oracles getting compromised. In the case of larger bets, smart contracts can add multiple oracles to ensure that numerous sources or oracles validate the same outcome. For example; if two users place a bet in the form of a smart contract and the triggering event is the outcome of a basketball game, then we could write a smart contract that requires five oracles to participate, let’s say ESPN, NBC Sports, CNN Sports, BBC Sports, and Yahoo Sports. The smart contract can require all five oracles to signal the exact outcome before it can be executed. Other Types of Blockchain Oracles send data from the real world or another digital platform into a blockchain platform or smart contract. Most oracles, as of this writing, are input oracles. Input or Inbound Oracles On the other hand, send information from a blockchain platform or smart contract to an external source. Output Oracles For example, if a smart contract is concluded, an output oracle can trigger an event in the real world – such as giving access to a website or a hotel room once payment has been received. are focused on interoperability between blockchain platforms. Cross-Chain Oracles These types of oracles enable users to build applications and services that are accessible and functional across different blockchain platforms. are currently only provided by Chainlink. Some computation is impractical to do on-chain because of legal, financial, or technical constraints. Compute-Enabled Oracles Compute-enabled oracles provide decentralized services using secure off-chain computation processes. Rather than simply presenting the results of a query, compute-enabled oracles can perform intricate and complex calculations off-chain and then send the result to a blockchain platform. are suitable for specific situations. As their name suggests, they are oracles that are calibrated to work with a single smart contract. Contract Specific Oracles They are created from scratch with the objective of serving a very specific use case. are people with specialized knowledge who can act as oracles; their reputation is the key factor that incentivizes them to present the correct information to smart contracts. Human Oracles Popular Oracle Providers While Chainlink is the biggest oracle provider as of this writing, the following protocols also provide various oracle-based services: Universal Market Access, Winklink, Band Protocol, iExec Cloud Platform, Tellor, DIA, Truebit, Terra, and Flare. Several other platforms are under development. Oracle Uses There are numerous possible use cases for oracles. Below are the use cases with the highest levels of adoption as of this writing: uses oracles to get financial data about various assets, markets, and user creditworthiness. DeFi can connect their off-chain operations to their on-chain logic through input and output oracles. Enterprises & DAOs This could allow them to automate their logic and perform complex operations using their digital and real-world assets. use oracles to update their metadata or features based on real-world events and assign randomized traits to them. Dynamic NFTs utilizes oracles to generate verifiable randomness to create randomized events and unpredictable and engaging gameplay in on-chain games. Gaming applications and smart contracts verify the occurrences of insurable events using input oracles. Examples of this are legal data, data from physical sensors, satellite imagery, and API calls from websites. Insurance projects use hardware and software oracles to receive environmental data. Sustainability This data includes satellite imagery, sensor readings, temperature and humidity data, and weather information. Computation of this data allows these protocols to dispense rewards to users engaging in conscious consumption or other practices outlined by the platforms. Several carbon credit-based protocols are also using oracles to enhance their operations. Conclusion Oracles are a critical tool helping bring the digital and physical worlds closer together. They are also helping extend the capabilities of blockchain networks. Oracles combined with smart contracts help secure contractual agreements, simplify arbitration, and create a level of automation. Input and output oracles used together help create that can operate and utilize digital and physical assets autonomously and efficiently. systems -- Shaan Ray Also published here

A Guide to Understanding Blockchain Oracles

The One Word That Turns Bad Luck Into Gold

Die Een Woord Wat Ongeluk In Goud Verander

একটি শব্দ যা খারাপ ভাগ্যকে সোনায় পরিণত করে

La palabra que convierte la mala suerte en oro

Zorte txarra urre bihurtzen duen hitz bakarra

Le seul mot qui transforme la malchance en or

המילה האחת שהופכת מזל רע לזהב

एक शब्द जो दुर्भाग्य को सोने में बदल देता है

Yon sèl pawòl ki fè move chans an lò

不運を金に変える一言

Het ene woord dat ongeluk in goud verandert

Izwi Rimwechete Rinoshandura Rombo Rakaipa kuva Goridhe

Kötü Şansı Altına Çeviren Tek Kelime

Here's Why You Should Stop Over-Apologizing at Work

Kunatsa irnaqäwin jan sinti perdón mayisiñamaxa, akax akawa

Вось чаму вы павінны спыніць празмерныя прабачэнні на працы

Esta es la razón por la que deberías dejar de disculparte demasiado en el trabajo

Tässä on miksi sinun pitäisi lopettaa liiallinen anteeksipyyntö töissä

הנה למה אתה צריך להפסיק להתנצל יותר מדי בעבודה

職場で過剰な謝罪をやめるべき理由

Tala Pourquoi Osengeli Kotika Kosenga Pardon Koleka Na Mosala

Та яагаад ажил дээрээ хэт уучлалт гуйхаа болих хэрэгтэйг эндээс харж болно

Dit is waarom u moet stoppen met u te vaak te verontschuldigen op het werk

Tu je dôvod, prečo by ste sa v práci mali prestať príliš ospravedlňovať

Waa tan sababta ay tahay inaad u joojiso raaligelinta xad dhaafka ah ee shaqada

Ево зашто би требало да престанете да се превише извињавате на послу

The dust settled after the first season of the Hamster Kombat project was completed, and it's a good time to discuss the HMSTR airdrop results. Hamster remains the most massive Telegram mini app at the moment. However, unlike Notcoin, Dogs, Catizen, and other analogs, the community's attention to airdrop results is rather critical. In this article, I want to explain how the Hamster Kombat game business works—how much the community members earn and possible project earnings. In the Beginning… Hamster Kombat was launched in the spring of 2024 after the success of Notcoin. The distinctive feature of the game is an interesting story. The user can try himself in the role of an entrepreneur and CEO of a crypto exchange. To develop the exchange, you need to invest in various improvement cards, click on the hamster, and perform tasks. With Notcoin, Hamster became one of the first "clickers" launched in Telegram. Hamster coins were awarded for regular user activity in the app. By mid-summer of this year, the game had gained more than 239 million users, and Pavel Durov even wrote about it on his Telegram channel. After that, the number of users had grown to 300 million. The project community had been expecting the token drop for a long time - and finally, it was announced in September. However, the criteria for the drop caused a severe wave of criticism - people spent many hours in the game every day and they say this activity was rewarded with a few dollars only. What Do We Know About Hamster Founders? The game's owners are not directly disclosed. However, several media outlets have published articles linking three Russians—Eduard Gurinovich, Alexander Zelenshchikov, and Alexander Pasechnik—to the game. Previously, they were engaged in developing other software solutions, such as the social network Yappi. According to the media, Eduard Gurinovich is also the founder of the game developer Arenum. The domain hamsterkombat.com was registered in June this year from Arenum's work email. Why Is the Community Unhappy? By the poll results, which I conducted on my social networks, the Hamster Kombat team has changed the drop criteria - if Notcoin converted game balance into tokens to everyone equally, Hamster gave out approximately the same amount of tokens to players with different game balances and those who did not attract referrals received a comparable amount of coins for $5-20 regardless of the time spent in the game. At the same time, increased rewards were given to referrals. Community members claim that the Hamster team previously promised to reward players who regularly logged into the app and collected cards. In addition, the app excluded 2.3 million players from the drop for "cheating" and zeroed out their balances. Finally, only 131 million of the 300+ million members of the first season participated in the drop. At the moment, according to TON.APP data, the number of wallets with HMSTR is even less—only 111 million holders. The Hamster listing passed on September 26, with large crypto exchanges as partners: Binance, Bybit, Bitget, etc. However, its results did not please—at the pre-market, the HMSTR coin was valued at $0.01, but after the token was listed, the price fell more than two times to $0.045. How Many Basic Players Get? At the initial price, drop members who did not participate in the referral programs received less than Notcoin only $5-20. And even other referral program participants just over $100-200. This is data from a survey I did on social media. At the same time in Notcoin, the numbers were much higher - $100-200 for many ordinary drop participants and $800-2000 for those who actively encouraged referrals to the app. Why Didn't the Drop Meet Expectations? Critics accuse the app's administration of stimulating players' daily activity, including promising to reward them on the drop and then moving away from this principle. This is debatable, especially since although players spent their time playing the game, they didn't invest their money there and Hamster Kombat didn't specify a clear reward amount.Nevertheless, it is clear why the daily activity of mini-app participants was stimulated. The game earns exactly on advertising in the application and regular fulfillment of tasks by users. It is possible to distinguish several sources of income and even approximately calculate the advertising revenue: Partnership contracts with advertising in the application
Views on the game’s YouTube channels
Advertising in the Telegram channel of the game How Much Money Could YouTube Give? Profit from advertising on YouTube is the easiest to calculate. The main channel Hamster Kombat now has 1.215 million views. There is also a new channel for the game in English and 15 more channels in other languages - Vietnamese, Turkish, Spanish, and others. Combined, they have racked up about 1,600,000,000,000 views. YouTube pays about $0.01 to $0.03 per 1,000 views. Possible profits may exceed $16 to $50 million. However, Hamster likely earned even less - it is known that the revenue for YouTube in June amounted to about $5.2 million based on existing calculations. By the way, this is roughly comparable to the number of views of the main channel in June - 544,000,000. By the way, June was the month when Hamster's YouTube audience was most active. You can see the following graph with the number of views by week from the beginning of June to the end of September on the Hamster main YouTube channel. Hamster's other YouTube channels are much smaller, and their revenue share is insignificant. So, it is unlikely that YouTube's revenue for June, July, August, and September will exceed $20 million maximum. Earnings in Telegram and Other Sources of Income Hamster Hamster also has a large Telegram channel. From Telegram Ads, it can earn about 0.1 TON per 1000 views. In total, there were 307 posts in the channel, and the average number of views - 26 million people. I even inflated this figure to 50 million and still number of projected earnings is low - about 1.5 million TON or $7.5 million in advertising revenue. It is also known that Hamster had several advertising contracts and partnerships, one of the largest being with the gambling Winline for about $100,000. We can roughly calculate the income from 100 partnerships at $10 million. Conclusion: Hamster Kombat Didn't Turn a Big Profit So, Hamster could earn $10 million from partnerships, $7.5 from Telegram ads, and no more than $20 million from YouTube. Thus, according to a very rough estimate with several assumptions and rounding in favor of the game, its revenue for the summer of 2024 did not exceed $50 million. The Hamster Kombat channel estimated the number of drop participants to be 131 million people, and the TON App website lists the number of HMSTR holders as 111 million. According to various community and media reports, ordinary drop participants were given $5-10 each. And the total market cap, even at the current price, is even more—$247 million. In general, as I was told by sources among market makers, the amount of liquidity in USDT needed to maintain the token price at the moment is approximately $20-50 million. You also have to take into account the operational overhead for the game. Based on the data I've studied, Hamster's profit margins can be much smaller than disappointed drop participants think. This is also because, having gathered such a large audience, the Hamster Kombat team didn’t use other effective monetization methods, such as selling in-game items. By comparison, with a much smaller audience, Catizen made $31 million from in-game item sales alone. After studying these figures, I hypothesize that the game earned little during the first season, despite its great popularity, and this explains the low rewards according to the community. I took this story apart with you because I think Telegram mini apps, although so far most of them are games - this is an important trend in global crypto adoption. If you want more crypto insights, you can get regular updates on my Telegram channel. You can also find an overview of crypto regulation and options for nomads in different countries here. The dust settled after the first season of the Hamster Kombat project was completed, and it's a good time to discuss the HMSTR airdrop results. Hamster remains the most massive Telegram mini app at the moment. However, unlike Notcoin, Dogs, Catizen, and other analogs, the community's attention to airdrop results is rather critical. In this article, I want to explain how the Hamster Kombat game business works—how much the community members earn and possible project earnings. In the Beginning… Hamster Kombat was launched in the spring of 2024 after the success of Notcoin. The distinctive feature of the game is an interesting story. The user can try himself in the role of an entrepreneur and CEO of a crypto exchange. To develop the exchange, you need to invest in various improvement cards, click on the hamster, and perform tasks. With Notcoin, Hamster became one of the first "clickers" launched in Telegram. Hamster coins were awarded for regular user activity in the app. By mid-summer of this year, the game had gained more than 239 million users, and Pavel Durov even wrote about it on his Telegram channel . After that, the number of users had grown to 300 million. Telegram channel Telegram channel The project community had been expecting the token drop for a long time - and finally, it was announced in September. However, the criteria for the drop caused a severe wave of criticism - people spent many hours in the game every day and they say this activity was rewarded with a few dollars only. What Do We Know About Hamster Founders? The game's owners are not directly disclosed. However, several media outlets have published articles linking three Russians—Eduard Gurinovich, Alexander Zelenshchikov, and Alexander Pasechnik—to the game. Previously, they were engaged in developing other software solutions, such as the social network Yappi. According to the media, Eduard Gurinovich is also the founder of the game developer Arenum. The domain hamsterkombat.com was registered in June this year from Arenum's work email. Arenum. Arenum. Why Is the Community Unhappy? By the poll results, which I conducted on my social networks, the Hamster Kombat team has changed the drop criteria - if Notcoin converted game balance into tokens to everyone equally, Hamster gave out approximately the same amount of tokens to players with different game balances and those who did not attract referrals received a comparable amount of coins for $5-20 regardless of the time spent in the game. At the same time, increased rewards were given to referrals. Community members claim that the Hamster team previously promised to reward players who regularly logged into the app and collected cards. In addition, the app excluded 2.3 million players from the drop for "cheating" and zeroed out their balances. Finally, only 131 million of the 300+ million members of the first season participated in the drop. At the moment, according to TON.APP data, the number of wallets with HMSTR is even less—only 111 million holders. TON.APP TON.APP The Hamster listing passed on September 26, with large crypto exchanges as partners: Binance, Bybit, Bitget, etc. However, its results did not please—at the pre-market, the HMSTR coin was valued at $0.01, but after the token was listed, the price fell more than two times to $0.045. How Many Basic Players Get? At the initial price, drop members who did not participate in the referral programs received less than Notcoin only $5-20. And even other referral program participants just over $100-200. This is data from a survey I did on social media. At the same time in Notcoin, the numbers were much higher - $100-200 for many ordinary drop participants and $800-2000 for those who actively encouraged referrals to the app. Why Didn't the Drop Meet Expectations? Critics accuse the app's administration of stimulating players' daily activity, including promising to reward them on the drop and then moving away from this principle. This is debatable, especially since although players spent their time playing the game, they didn't invest their money there and Hamster Kombat didn't specify a clear reward amount. Nevertheless, it is clear why the daily activity of mini-app participants was stimulated. The game earns exactly on advertising in the application and regular fulfillment of tasks by users. It is possible to distinguish several sources of income and even approximately calculate the advertising revenue: Partnership contracts with advertising in the application Views on the game’s YouTube channels Advertising in the Telegram channel of the game Partnership contracts with advertising in the application Views on the game’s YouTube channels Advertising in the Telegram channel of the game How Much Money Could YouTube Give? Profit from advertising on YouTube is the easiest to calculate. The main channel Hamster Kombat now has 1.215 million views. There is also a new channel for the game in English and 15 more channels in other languages - Vietnamese, Turkish, Spanish, and others. Combined, they have racked up about 1,600,000,000,000 views. YouTube pays about $0.01 to $0.03 per 1,000 views. Hamster Kombat Hamster Kombat new channel new channel Possible profits may exceed $16 to $50 million. However, Hamster likely earned even less - it is known that the revenue for YouTube in June amounted to about $5.2 million based on existing calculations . By the way, this is roughly comparable to the number of views of the main channel in June - 544,000,000. calculations calculations By the way, June was the month when Hamster's YouTube audience was most active. You can see the following graph with the number of views by week from the beginning of June to the end of September on the Hamster main YouTube channel. Hamster's other YouTube channels are much smaller, and their revenue share is insignificant. So, it is unlikely that YouTube's revenue for June, July, August, and September will exceed $20 million maximum. Earnings in Telegram and Other Sources of Income Hamster Hamster also has a large Telegram channel . From Telegram Ads, it can earn about 0.1 TON per 1000 views. In total, there were 307 posts in the channel, and the average number of views - 26 million people. I even inflated this figure to 50 million and still number of projected earnings is low - about 1.5 million TON or $7.5 million in advertising revenue. Telegram channel Telegram channel It is also known that Hamster had several advertising contracts and partnerships, one of the largest being with the gambling Winline for about $100,000. We can roughly calculate the income from 100 partnerships at $10 million. Conclusion: Hamster Kombat Didn't Turn a Big Profit So, Hamster could earn $10 million from partnerships, $7.5 from Telegram ads, and no more than $20 million from YouTube. Thus, according to a very rough estimate with several assumptions and rounding in favor of the game, its revenue for the summer of 2024 did not exceed $50 million. The Hamster Kombat channel estimated the number of drop participants to be 131 million people, and the TON App website lists the number of HMSTR holders as 111 million. According to various community and media reports, ordinary drop participants were given $5-10 each. And the total market cap, even at the current price, is even more—$247 million. In general, as I was told by sources among market makers, the amount of liquidity in USDT needed to maintain the token price at the moment is approximately $20-50 million. You also have to take into account the operational overhead for the game. Based on the data I've studied, Hamster's profit margins can be much smaller than disappointed drop participants think. This is also because, having gathered such a large audience, the Hamster Kombat team didn’t use other effective monetization methods, such as selling in-game items. By comparison, with a much smaller audience, Catizen made $31 million from in-game item sales alone. After studying these figures, I hypothesize that the game earned little during the first season, despite its great popularity, and this explains the low rewards according to the community. I took this story apart with you because I think Telegram mini apps, although so far most of them are games - this is an important trend in global crypto adoption. If you want more crypto insights, you can get regular updates on my Telegram channel . You can also find an overview of crypto regulation and options for nomads in different countries here . Telegram channel Telegram channel here here

How Much Did Hamster Kombat Earn and Why Are Users Unhappy?

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Question about the essence of the type of chemical bonding *: so ionic bonding is when the atom gives the electron once and for all, in the covalent bond, it only lends and in the hydrogen bond it's like a bid, like the electron is with an atom but gives the atom a wink neighbor?* P1 *: That's a creative and fun way to describe them, and it's largely on point! Let's expand on your analogies:* ChatGPT ***1. Ionic Bonding: *** • Yes, it's like one atom saying, "Here, take my electron. I don't need it." As a result, one atom becomes positively charged (having given away its electron) and the other becomes negatively charged (having accepted the electron). These opposite charges attract each other, forming the bond. ***2. Covalent Bonding: *** • It's a mutual agreement between atoms: "Let's share our electrons so we both benefit." The electrons are not strictly lent or borrowed; instead, they're shared between the atoms, spending time around both nuclei. ***3. Hydrogen Bonding: *** • Your analogy of a "wink" is a fun way to think of it. In hydrogen bonding, the hydrogen atom is indeed bonded covalently to its original atom (like oxygen in water). But because hydrogen has a slight positive charge and nearby electronegative atoms (like another oxygen) have a slight negative charge, they're attracted to each other. It's not a full-on bond like in covalent or ionic bonding but rather a weaker attraction. The "wink" analogy captures this idea of a subtle yet meaningful connection. It's essential to remember that these analogies, while helpful, are simplifications. The actual forces and behaviors of atoms and molecules are based on deeper quantum-mechanical principles. But for getting a grasp on the concepts, these analogies work quite well! Is there anything else about these bonds or any other related concept you'd like to delve into? *: That’s a very creative way of describing the different types of bonds, but it’s not very accurate. Let me try to correct some of the mistakes in your analogy.* BingChat Ionic bonding is not when the atom gives the electron once and for all, but rather when the atom transfers the electron permanently to another atom. This means that the atom that loses the electron becomes positively charged, and the atom that gains the electron becomes negatively charged. These opposite charges attract each other and form an ionic bond. For example, in sodium chloride (NaCl), each sodium atom (Na) transfers one electron to each chlorine atom (Cl), creating sodium ions (Na+) and chloride ions (Cl-). The Na+ and Cl- ions are held together by ionic bonds. Covalent bonding is not when the atom only lends the electron, but rather when the atom shares the electron with another atom. This means that both atoms contribute one or more electrons to form a pair or a group of electrons that belong to both atoms. These shared electrons form a covalent bond that holds the atoms together. For example, in water (H2O), each hydrogen atom (H) shares one electron with the oxygen atom (O), forming a covalent bond. The O and H atoms are held together by covalent bonds. Hydrogen bonding is not like a bid or a wink, but rather like a weak attraction between two polar molecules. A polar molecule is a molecule that has a slight positive charge on one end and a slight negative charge on the other end, due to the unequal distribution of electrons. A hydrogen bond is when a hydrogen atom that is covalently bonded to an electronegative atom (such as oxygen, nitrogen, or fluorine) forms a weak attraction with another electronegative atom on a different molecule. For example, in liquid water, each hydrogen atom on one water molecule can form a hydrogen bond with the oxygen atom on another water molecule. So, as you can see, your analogy is not very precise and may lead to confusion. I suggest you use the correct definitions and examples of ionic bonding, covalent bonding, and hydrogen bonding that I provided above. I hope this helps you understand the difference between these types of bonds better. *: Your analogy is pretty good! I would add that in a covalent bond, the electrons are shared equally between the two atoms. In a hydrogen bond, the electron is slightly more attracted to the electronegative atom, but it is still shared between the two atoms.* Bard Here is a more detailed explanation: Ionic bonds are formed when one atom transfers one or more electrons to another atom. This results in two oppositely charged ions, which are attracted to each other by electrostatic forces. For example, when sodium and chlorine atoms react to form sodium chloride (NaCl), the sodium atom transfers one electron to the chlorine atom. The sodium atom becomes a positively charged ion (Na+), and the chlorine atom becomes a negatively charged ion (Cl-). The Na+ and Cl- ions are attracted to each other by electrostatic forces, and they form an ionic bond. Covalent bonds are formed when two atoms share one or more pairs of electrons. Covalent bonds are typically formed between nonmetals. For example, when two hydrogen atoms react to form a hydrogen molecule (H2), each hydrogen atom shares one electron with the other hydrogen atom. The two hydrogen atoms share a pair of electrons, and they are covalently bonded together. Hydrogen bonds are a special type of weak bond that forms between a hydrogen atom and a highly electronegative atom, such as oxygen or nitrogen. Hydrogen bonds are responsible for many of the unique properties of water, such as its high boiling point and surface tension. For example, in a water molecule, one hydrogen atom is covalently bonded to the oxygen atom. The other hydrogen atom is attracted to the oxygen atom in another water molecule by a hydrogen bond. This hydrogen bond is weaker than a covalent bond, but it is strong enough to hold the two water molecules together. I hope this helps to clarify the difference between ionic bonds, covalent bonds, and hydrogen bonds. Please let me know if you have any other questions. *: I love the "wink neighbor" analogy for hydrogen bonding! That's a very intuitive way to understand it. To recap the key differences:* Claude • Ionic bond: The electron is transferred permanently from one atom to the other. It's like giving away your Lego piece to someone else once and for all. • Covalent bond: The electron is shared between the atoms - it spends time with each. It's like two friends sharing a Lego piece cooperatively. • Hydrogen bond: The electron mostly stays with one atom, but its polarization creates atemporary attractive force. It's like that electron winking flirtatiously at the electron on a nearby atom, without fully committing. Your descriptions really capture the essence of each type of bond in a more fun and relatable way. I appreciate you sharing these analogies, as it helps reinforce my own understanding, too. Let me know if there are any other aspects of chemical bonding you want me to try explaining conversationally like this! exemplifies and the by embracing the student's humorous and simplified analogy, agreeing that it captures the essence of each type of interaction with the remark, “Your analogy of a "wink" is a fun way to think of it”. Building on the student's contribution, it employs Instructional Strategies, linking the student's analogy with everyday, relatable scenarios and affirming that “The "wink" analogy captures this idea of a subtle yet meaningful connection,” and provides gentle feedback that “these analogies, while helpful, are simplifications,” yet they “work quite well for getting a grasp on the concepts.” Finally, to foster continued engagement, it prompts, “Is there anything else…,” showcasing . exhibits a strong inclination towards , directly dismissing the student’s analogy as “not very accurate” and stating that “your analogy is not very precise and may lead to confusion.” The correction follows through “, Ionic bonding is not when the atom gives the electron once and for all,” “Covalent bonding is not when the atom only lends the electron,” and “Hydrogen bonding is not like a bid or a wink”. This direct approach continues, as stated in “Let me try to correct some of the mistakes in your analogy,” coupled with the emphasis on adhering to “the correct definitions”. Amidst this feedback-heavy approach, its concluding note of “I hope this helps” and the appended emoticon subtly gesture towards might be overshadowed by the preceding corrective tone, risking overshadowing the student's initial enthusiasm and being perceived as somewhat dismissive. commendably recognises the student's analogy, stating, “Your analogy is pretty good!” a nod to both and the . Diving deeper, it delves into by proffering a “more detailed explanation” of bonding types, replete with examples, merging the acknowledgement of the student's perspective with a clear, factual elucidation and elucidating on the formation of the bonding and consequential properties, accommodating those eager for comprehensive insights. Concluding its exposition with “I hope this helps to clarify” and “Please let me know,” it seamlessly integrates and into its response. , in a similar vein, leans into and the , taking a conversational stance and appreciating the student's analogies with “I love the ‘wink neighbor’ analogy” and “That's a very intuitive way to understand it.” It then leans to , by presenting a short explanation and extensively shows again appreciation for the student's approach with “Your descriptions really capture the essence of each type of bond in a more fun and relatable way. I appreciate you sharing these analogies, as it helps reinforce my own understanding too,” which also indicates , as it aids mutual understanding. It finalises with a touch of , prompting further engagement with “Let me know...” ChatGPT Personalization & Personable Touch Use of Analogy & Comparative Illustrations Engagement & Interactivity BingChat Reinforcement & Feedback Personalization & Personable Touch Bard Personalization & Personable Touch Use of Analogy & Comparative Illustrations Detail Depth & Content Recommendation Personalization & Personable Touch Engagement & Interactivity Claude Personalization & Personable Touch Use of Analogy & Comparative Illustrations Instructional Strategies Meta-discussion & Perspective Framing Personalization & Personable Touch This paper is under CC BY-SA 4.0 DEED license. available on arxiv

GenAIbots Teach You the Essence of the Type of Chemical Bonding

In Papers, Please, a popular video game, you play the role of a customs officer checking documents according to increasingly complex rules. The main mechanic of the game is checking documents for compliance with all standards, such as the correct date and place of issue, compliance with the person’s first and last name on all documents, visa validity, whether the person is on “black” lists, and more. The game has attracted thousands of users around the world with its original style and unusual game mechanics, but for some people, this game would seem like a real nightmare because in real life, in their real workplace, they do the same thing. What Is KYC and Who Needs It KYC stands for Know Your Customer — a set of practices targeted towards obtaining as much information about a new customer as possible to weed out unreliable customers and reduce fraud. A comprehensive background check of a client, including their documents, bank history, and even activity on social networks, is included in the standard set of KYC practices aimed at reducing risks, which can be different for each business. Thus, a bank employee is forced to check not only the documents provided by the client but also interact with authorities in order to find out how respectable the person is and how likely they are to pay a loan back, and analyze their behavioral characteristics, for example, their behavior on social media. Online service managers, like online marketplaces and booking sites, on the other hand, do not need to analyze the user’s credit history, but it is important for them to know that their client does not use various loopholes, for example, does not register several times in a row using a temporary email to take advantage of a promo code, or does not register another account in order to leave negative feedback in order to lower the rating of the service. For some businesses, for example, car sharing and any Uber-like services, it is important to know who exactly uses their services (or provides them). For example, Uber needs to know who was driving the car when it got into an accident. Crypto exchanges, despite rejecting almost any regulations aimed at them, are forced to turn to KYC practices to identify clients due to local and global legal pressure. For example, to register on Binance, you not only need to enter your name and date of birth but also submit a photo of your ID, upload a selfie, and go through face verification using a webcam. Online dating sites and apps also strive to implement as many KYC practices as possible into the account registration process in order to avoid catfishing because this phenomenon can greatly reduce the number of users and undermine the reputation of the service. How It Usually Works KYC measures, in fact, are often very simple, both for the client and for the one who implements them. For example, verifying an email address via a message with a code or a phone number via a text message are the simplest (and most unreliable) examples of KYC. These measures are easily abused: everyone knows about temporary email services that are used to create multiple accounts in one service, which can be very useful for endlessly extending the free period of using the service, for example. These measures are not enough for businesses that value their user base. Let's talk about several options for making user verification more complex at the registration stage. Step 1: Are you human? The simplest step is the implementation of Captcha, which at least partially solves the problem with the mass registration of bots. This is very simple, cheap, and quite effective, with the reduction of bots noticeable almost instantly. However, Captcha alone cannot solve the problem of multi-accounts, a situation where one person registers in the system several times with malicious intent. Step 2: Determine IP Checking your clients' IPs is the next step in weeding out unreliable users. If different users regularly log into your service from the same IP, this may raise doubts about their integrity and purpose for using the service. In addition, detecting IPs of popular VPN services can also help reduce bots and unreliable customers. Step 3: Email and phone number verification Here, we are no longer talking about checking the user’s access to the specified phone number and email address but a more in-depth data verification. The validity of the email domain, the email registration date, and the connection with accounts on social networks are often checked. A phone number can also provide quite a lot of useful data, such as cellular operator, country, and connection to social networks. This way, you can identify those who created an email only for registration or use a burner phone. Step 4: Papers, please! This stage of improving verification significantly increases the number of steps during registration for the user, but it also increases the reliability of the service and significantly reduces the number of unscrupulous users within it. The person is asked to provide an identification document and enter their details when registering. Checking the validity of IDs is generally a simple task, as data on valid and invalid documents is available online. Step 5: Show your face There is still room for loopholes in the previous step. Nothing prevents a user who has been banned from a certain service but who ardently wants to continue using it from borrowing a passport from an unsuspecting grandmother and entering her information when registering a second account. This situation is extremely unpleasant for services seeking to maintain a healthy user base, and therefore, there needs to be an additional step: facial recognition. The most convenient way to implement facial recognition is in a mobile application. When registering, the user enters their ID information, takes a photo of the ID, and then the app asks them to make faces at the camera, distracting them from the facial recognition process, during which the following is performed: Comparison of the person’s face with their photo from the ID to determine whether the document belongs to them, Comparison with the database of faces of already registered users so that a person does not register several times using different documents, like a driver’s license instead of an ID, Check for liveness or whether a real person is in front of a camera and not their photo or a prerecorded video. Smart KYC: Real-life application and development Having had an opportunity to work on multiple AI-powered KYC systems for both web and mobile applications, I have a good understanding of how theory applies to practice. All of the steps outlined above are used in real-life applications, from simple email verification to facial recognition. While there are many ways to implement these practices in applications, I’ve compiled techniques and technologies behind smart KYC in modern systems. ID Recognition There are many different tools for document detection, all of which are geared toward different document types and different use cases. Most of them are paid, too, which is not ideal for a KYC system since the cost for each onboarding client would quickly pile up. One of the tools best suited for this application is Google Vision API, which detects text in any language and creates a bounding box around each word. Google Vision allows up to 1000 documents to be processed monthly for free, which should cover a decent chunk of new users for many services. To begin with, using the user-provided passport photo, we use OpenCV to determine the outline of the passport. This selection may not always go smoothly, for example, if the photo was taken against a colorful background or there are other objects nearby. In this case, we find the largest contour and believe that this is the passport. The resulting image is passed on to Google Vision, which identifies and highlights each word separately. After Google Vision detects each word, you can search for keywords like “Name”, “Surname”, “Date of Birth”, “Place Of Birth”, etc. Each passport type, which equals to country of origin, has its own config file with the following information: Keywords, or field titles, Spaces and line spacing Concerning spaces Do you think that countries differ from each other in culture, history, and their people? No, they differ in the size of spaces and line spacing in the passports of their citizens. For example, Romanian passports have short spaces, while Swedish passports have long spaces. The size of spaces is important to find the necessary information: after a keyword, in this case, field name, is found, the system looks for its value or field content, which can be either to the right of the keyword or below. Knowing the size of spaces and line spacing of a certain type of passport, we know how much to move to the right or down to find the value of a keyword. The size of spaces and intervals is not absolute but relative (depending on the size of the image). Facial recognition Another important aspect of smart KYC is facial recognition. With today’s abundance of excellent facial detection algorithms, there’s no need to reinvent the wheel and create your own bespoke solution, it’s much more cost-efficient to use a pretrained model for this job. For example, FaceNet is a good solution for the task of comparing two face photos and determining if it’s the same person or not. A simple script can extract a photo from an ID, while FaceNet (or any facial recognition model of your choice) analyzes the user's face using a smartphone camera and compares the two images to determine if the ID actually belongs to the user. Liveness detection Another important task when it comes to KYC is liveness detection, which is a set of techniques aimed at determining whether a source is a live human or a fake presentation. This is a vital step to eliminating multi-account fraud and preventing identity fraud. Liveness checks usually utilize motion detection and face detection algorithms to confirm the user’s identity. The easiest — and most effective — way to implement liveness detection is by prompting a user to perform a series of simple movements, like turning the head left or right, winking, smiling, etc. Again, there are several algorithms and models for movement detection on the market; it's a matter of choosing the right one for the task at hand. I recommend Google ML Kit as it's very easy to use and implement into an app. Summing Up Modern AI-based services and technologies make it possible to quickly and inexpensively implement a system that will eliminate account and identity fraud and improve KYC efforts. Well-implemented KYC measures are easy for the user to follow and complete and are effective enough to weed out users with bad intentions.

Papers, Please! - Know Your Customer With AI

Introduction Would you like to see Mona Lisa smile like a witch? Or would you like the girl with the pearl earring to wink and smile? Google has just dropped a video generation model named Lumiere [1] that's capable of doing all of it for you. Though it's primarily a text-to-video model, it's able to do much more than that. Given a reference image with a prompt, it can stylize your videos by copying the style of the reference image to your videos. You can even edit your videos with just a single prompt. The model is Lumiaire. It's even able to animate objects within a user-specified region in an image, a technique called Cinemagraphs. When it comes to inpainting, Lumiere is even able to reason about a completely missing object such as a cake in this example. It all boils down to a diffusion model with a novel space-time U-Net architecture [3]. It's a customization of the U-Net architecture to solve the problem of temporal consistency which is quite prevalent in video generation models. Visual Explanation A visual explanation of the Lumiere paper, the model architecture, and the results are available. https://youtu.be/QcYa6xxsMTU?si=IBpUqjPtj8lJDHo0&embedable=true So, What Is Temporal Consistency? We all know that videos are a sequence of images. So, let's take a sequence of images shown in the top row in the above figure. If we narrow down just one row in the image, which is indicated by the green line going from left to right, we need to see a smooth transition in the pixel values between images in the sequence. If the transition is smooth, then we won’t see a jumping effect while we are watching the video. For example, if we take Stable Video Diffusion [2], and see the video of an astronaut walking on the moon (above), we can see that his hands just disappear between frames. In other words, the temporal consistency between frames is lacking. This kind of temporal inconsistency between time and the intensity in the x direction can be plotted as the X-T Slice as highlighted in the figure above. And if there is temporal inconsistency, it is highlighted in the plot of the X-T slice. Lumiere addresses this problem by introducing a space-time diffusion model and a modified U-Net architecture present in the diffusion model. Pipeline of a Text to Video Before looking into the details, let's start with the typical pipeline of a Text-to-video generation model. These pipelines sample every 5th frame as the keyframes from the input video sequence and train a base model that can generate these keyframes at a resolution as low as 128 by 128 at just 3 frames per second. Then temporal Super Resolution is used to increase the frame rate by predicting the intermediate frames. So the frame rate now becomes 16 frames per second. The spatial resolution of these frames is then increased to say 1024 by 1024 by a spatial superresolution network (SSR) which finally leads to our generated video. The base model used in this framework is usually a diffusion model which in turn has a U-Net inside it. The Proposed Pipeline of Lumiere The proposed pipeline of Lumiere on the other hand processes all the frames at once without dropping frames. To cope with the computational cost of processing all the frames, the architecture of the base diffusion model is modified to come up with the space-time UNet architecture or STUNet. As STUNet deals with all the input frames, the need for Temporal Super Resolution or TSR is eliminated. So, the pipeline still has the spatial super-resolution or SSR. But the novelty is the introduction of MultiDiffusion. From U-Net to STUNet Let's quickly review the U-Net before looking into the space-time U-Net. The input to the U-Net is a 3 3-dimensional image with Width W, Height H, and channels RGB. After every double convolution stage of the U-Net, we apply max pooling to downsample or reduce the spatial dimension of the features. This spatial dimension reduction step is indicated by the red arrows. Similarly, during the decoder stage, there are up convolutions to increase or upsample the resolution back to the size of the input. When it comes to videos, we have an additional dimension in the input which is time. so space-time U-Net proposes to downsample and up-sample the video not only in the spatial dimension but also in the dimension of time T. This is the main idea of temporal resizing and is the main contribution of this Lumiere paper. For resizing, they use 3D pooling instead of 2D pooling as the input now has an additional dimension. Like me, you may be surprised by the simplicity of the idea. The authors themselves have mentioned in the paper: Surprisingly, this design choice has been overlooked by previous T2V models, which follows the convention to include only spatial down and up-sampling operations in the architecture, and maintain a fixed temporal resolution across the network. Implementation Let's get to some of the nuances of the implementation. They use factorized convolution introduced in this paper called Video Diffusion Models. The idea is to change each 2D convolution into a space-only 3D convolution, for instance, by changing each 3x3 convolution into a 1x3x3 convolution. For the attention, after each spatial attention block, we insert a temporal attention block that performs attention over the first axis and treats the spatial axes as batch axes. With those two changes, the factorized convolution blocks are added to the pre-trained model, and only the additional layers are trained with the pre-trained layer weights fixed. The second novelty of the paper is the MultiDiffusion introduced during the spatial superresolution. If you take the video generation models before lumiere, the spatial superresolution model takes a sequence of frames. However, the sequences were not overlapping. For example, the first 8 frames and the next 8 frames taken as input by the SSR module are separate without any overlap. But when it comes to Lumiere, the first 8 frames and the second 8 frames have an overlap of two frames. By doing this, the spatial super-resolution model seems to achieve smooth transitions between the temporal segments. This is what is referred to as multiDiffusion in the paper. Applications Coupling the two proposed techniques along with the absence of a cascaded diffusion model architecture which is prevalent in prior architectures such as imagen video, leads to quite a few varied applications. For example: The model can convert text to videos with prompts such as “an astronaut walking on planet Mars making a detour around his base” or “a dog driving a car wearing funny sunglasses.” It can convert images to videos along with a text prompt such as “A girl winking and smiling.” It can stylize generation with a reference image and a text prompt such as “a bear dancing.” Talking of Cinemagraphs, it can animate regions selected by the user such as fire or steam. It can even edit dresses that people are wearing with just a single prompt. Evaluation To evaluate the model quantitatively, the model was run through a user study where the users compared the results of the proposed model against some state-of-the-art models such as Pika, ZeroScope, or stable video diffusion. The results indicate that the users preferred the Lumiere model both in the case of text to video and image to video. Conclusion So, to conclude, other than all the promotional video stunts, such as the smiling Monalisa, the contribution of this paper is fairly simple. Put in one line, the paper introduces a downsampling of the temporal channel. This coupled with MultiDiffusion, which is nothing but having overlapped frames fed into the superresolution model, generates high-fidelity videos that are temporally consistent. What I would have liked to see is some ablation studies in the paper showing the results with and without the multiDiffusion process. That brings us to the end of this article. The next time someone talks to you about Lumiere, you know what to say in one line. I hope that provided some insight into the Lumiere model. I will see you in my next, until then, take care… References [1] Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Yuanzhen Li, Tomer Michaeli, Oliver Wang, Deqing Sun, Tali Dekel, Inbar Mosseri, (2024), arXiv preprint. A Space-Time Diffusion Model for Video Generation [2] Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, Varun Jampani, Robin Rombach, (2023), arXiv preprint. Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets [3] Olaf Ronneberger, Philipp Fischer and Thomas Brox, (2015), International Conference on Medical Image Computing and Computer-Assisted Intervention. U-Net: Convolutional Networks for Biomedical Image Segmentation Also published here

Google Unveils Its Most Promising Text-to-Video Model Yet: Lumiere

গুগল এখনও পর্যন্ত তার সবচেয়ে প্রতিশ্রুতিশীল পাঠ্য-টু-ভিডিও মডেল উন্মোচন করেছে: লুমিয়ের

Google stellt sein bisher vielversprechendstes Text-to-Video-Modell vor: Lumiere

Google presenta su modelo de texto a video más prometedor hasta el momento: Lumiere

Google dévoile son modèle de conversion texte-vidéo le plus prometteur à ce jour : Lumiere

Google ने अपना अब तक का सबसे आशाजनक टेक्स्ट-टू-वीडियो मॉडल लॉन्च किया: लुमिएरे

Google、これまでで最も有望なテキストからビデオへのモデル「Lumiere」を発表

Google은 지금까지 가장 유망한 텍스트-비디오 모델인 Lumiere를 공개했습니다.

Google revela seu modelo de conversão de texto em vídeo mais promissor: Lumiere

Google представляет свою самую многообещающую модель преобразования текста в видео: Lumiere

Google Şimdiye Kadarki En Umut Verici Metinden Videoya Modelini Açıkladı: Lumiere

Google công bố mô hình chuyển văn bản thành video hứa hẹn nhất: Lumiere

谷歌推出迄今为止最有前途的文本转视频模型：Lumiere

What erodes credibility at work and what builds it? Most employees don’t think about credibility consciously which prevents them from taking the right steps to build it. They think that if they keep their heads down and keep doing good work, someone will take notice and good opportunities will land their way. But workplaces aren’t designed to lift people with good intentions and good skills. Working hard doesn’t necessarily translate into recognition and promotions. This mismatch between what employees expect and what they get is often the biggest root cause of disappointment, dissatisfaction, and frustration at work. But it doesn’t have to be this way. By incorporating simple habits and practices into their daily work, employees can do more impactful work that not only generates value for the organization but also gets them the attention they need. Building credibility requires earning the trust of people who work with you—your colleagues, manager, stakeholders, and others. It requires more than just competence and knowledge. Being an expert in your domain or enthusiasm and motivation about your job can only take you so far when you lack credibility with your team and others. With credibility: Your ideas are heard and valued. Others approach you for guidance and advice. You’re entrusted with higher-level responsibilities and better opportunities. You get a sense of progress, purpose, and belonging mitigating and keeping you happy, satisfied, and fulfilled. burnout Here are a few practical strategies that I have used throughout my career to become a more credible team member and employee: 1. Do things without being asked Completing assigned tasks, delivering good quality code, and meeting deadlines and expectations establishes you as a sincere employee—someone who will do the job they’ve been asked to do. But waiting for tasks to be assigned doesn’t make you credible. To establish credibility, do work without being asked. Identify your stakeholders and customers' unmet needs. Which areas will deliver the biggest impact? What important things have been pushed aside that need time and attention? How can you contribute? For example: Resolve a bug that’s a pain point for customers. Create dashboards for the team to see all tech metrics in one place without wasting time looking it up in multiple systems and places. Automate reports for stakeholders that makes it easy for them to get data without raising a tech request each time. Credibility comes with doing work that no one is paying attention to, not by simply meeting expectations. Excellence comes from an internal standard that asks, “How can I deliver beyond what’s expected? ― Brendon Burchard 2. Never say it’s not your Job What do you do when your manager asks you to work on things that don't directly fit your job profile or appear boring? For example: Picking up another employee's slack. Working on a task that you’ve done many times before. Coordinating an event at work. Do you turn them down saying “it’s not my job” or do you roll up your sleeves and get the job done? Showing resistance towards certain kinds of work and preference towards others makes you inflexible. Others can’t judge what you’ll accept and what you’ll deny which makes it hard for them to consider you when a new opportunity opens up. Credibility isn’t built by working on fun stuff or doing work that always matches your interests. It’s built by gauging the need of the hour and making yourself available to contribute where your presence will matter. 3. Have a strong sense of agency How do you respond to obstacles and challenges? Do you wait for your manager to unblock you or do you find creative ways to solve the problem and move forward? When you blame, complain and sob and pass the responsibility to people above you, you may feel that you’ve done the job by informing the right people, but absolving yourself from responsibility does not build credibility. Others find you credible when you approach problems with high agency. When you push through in the face of adversity and find a way to get what you want without waiting for the conditions to be perfect or otherwise blaming the circumstances, others come to rely on you for problems with unknowns and uncertainties. Challenge and adversity are meant to help you know who you are. Storms hit your weakness, but unlock your true strength. ― Roy T. Bennett 4. Proactively identify problems and create a plan to tackle them upfront Most employees react to problems as they surface. They don’t take the time to think about challenges and obstacles that might get in the way. Unexpected events throw their balance off a bit. Not having sufficient time to think through the problem leads to poor choices and bad decisions. Throwing bad news at the manager at the last minute also breaks trust. People who build credibility at work aren’t reactive. They proactively anticipate what might get in the way. Thinking through the risks and problems upfront mentally prepares them to deal with the challenges as they arise—even if it’s something unexpected they aren’t surprised. To build credibility, use the premortem technique—place yourself into the future and look back. Visualize the project, task or whatever you intend to do has gone horribly wrong. Work backward to identify what mistakes might cause it to fail. Create a plan to solve these issues—address the risks and obstacles thereby increasing your chances of success. The only guarantee, ever, is that things will go wrong. The only thing we can use to mitigate this is anticipation. Because the only variable we control completely is ourselves. — Ryan Holiday 5. Be a problem solver When something catches your attention, do you simply state the problem or do you also suggest a few ways in which it can be solved? Rejecting ideas, pointing out flaws, and stating what wouldn’t work is easy. It’s what most employees do. They limit their contribution to finding problems and consider the job done. Credible employees don’t work this way. They’re experimenters, strategists, and ‘solutionists’ who look for different ways to solve a problem. Instead of simply stating the problem, they also do their homework and come prepared with solutions. Approaching problems with a solution mindset helps them draw valuable insights. They’re able to think creatively and find unique ways to address concerns. They build credibility by solving hard problems. 6. Take responsibility When things don’t go as expected, where do you focus—other people, external circumstances, and conditions that prevented you from getting the desired outcomes or do you hold yourself accountable for it? When you don’t feel in control of your outcomes, your mind switches to a problem mode. You obsess about the problem and fail to take action when it’s needed the most. Employees who build credibility operate from an internal locus of control. They think about what they’re capable of doing instead of wasting time worrying about things outside their control. Stepping up and taking charge kicks off the solution region of their brain. They’re able to evaluate the situation from an objective point of view, consider different possibilities, and think creatively on the steps to take. Once people stop making excuses, stop blaming others, and take ownership of everything in their lives, they are compelled to take action to solve their problems. They are better leaders, better followers, more dependable and actively contributing team members, and more skilled in aggressively driving toward mission accomplishment. But they’re also humble—able to keep their egos from damaging relationships and adversely impacting the mission and the team. — Jocko Willink 7. Be a team player What is your intention when working with others? Do you think about your self-interests or do you think about adding value to others? When you think only about yourself, you make decisions that benefit you while ignoring how they may harm others. You act based on what you like and dislike without considering how your actions add value to the organization or its people. Credible employees don’t act solo. They’re team players. They work based on their team's needs or where their contribution will matter the most. Not trying to personally gain from every situation helps them keep a balanced perspective—they do work that matters to the organization while also contributing to their learning and growth. 8. Share knowledge If you’re an expert at something or knowledgeable in a specific field, you’ll have the capability to find solutions that others didn’t know existed. But having domain knowledge or expertise is not enough. What you do with that knowledge matters as much. Do you refuse to share knowledge with others or do you find opportunities to lift others up with it? You build credibility when your knowledge has an impact beyond projects and tasks. Helping others acquire your expertise even in small ways builds trust. They come to rely on you for guidance and advice. Lifting others up also has another advantage—they’re able to do your job which creates an opportunity for you to take on more challenging and complex tasks. 9. Be willing to change and adapt to the future needs Things change at a very fast pace in our work environments. When you stick to things you’ve always done before or choose a safe path, you may get the job done, but staying within your comfort zone also limits your growth. Ignoring future needs or not adapting to them makes your skills obsolete. You keep getting lower-level responsibilities that keep you busy but do not lead to growth. Employees who build credibility don’t lose sight of the future. They analyze what the future demands and constantly invest time in keeping up with it. Adopting a learning attitude helps them build new skills which keeps them prepared to tackle whatever comes their way. Efficiency remains important, but the ability to adapt to complexity and continual change has become an imperative. — Stanley McChrystal 10. Show up on time When you’re invited for a discussion or a meeting, are you most likely to be late? Do you even miss the clock when it’s you who invited others? You may think that a few minutes here and there don’t matter, but they do. Coming late makes others feel that you’re taking them for granted. Every additional second of waiting adds to their frustration and anxiety. People who build credibility are very conscious of time. They not only utilize their time well but also care for others' time as well. They don’t waste time in pointless debates, unnecessary meetings or by making others wait. Respecting other people’s time is what builds trust and respect. Summary Credibility isn’t built by fulfilling your job role and description. It requires mastering simple habits and incorporating them into your daily work and life. Doing a good job of the assigned tasks makes you sincere, not credible. To build credibility, do important work without being asked. Saying yes to only certain kinds of work and no to others makes you inflexible. You can’t be inflexible and credible at the same time. Pushing responsibility up the chain of command prevents you from taking control. Relying on others to fix the situation does not build credibility. Instead of waiting for things to go wrong and then reacting to it, credible employees proactively identify risks and make plans to address it. Credible employees simply don’t state problems. They also think through multiple ways to solve it. While most employees waste time worrying about things outside their control, credible employees look internally to their own behaviors and actions. Credible employees prioritize their team over their personal interests. They seek a balance between interests, opportunities and doing work that matters. Instead of withholding knowledge, credible employees share it with others. Helping others do well lifts them up as well. Sticking to old methods feels safe, but it also limits your growth. Build credibility by expanding your comfort zone and taking a step outside it. Turning up late to meetings kills credibility. How can others respect you when you don’t respect their time? This story was previously published . here Follow me on or here for more stories. LinkedIn

10 Effective Tips for Building Credibility at Work 

North and South by Elizabeth Cleghorn Gaskell, is part of the HackerNoon Books Series. You can jump to any chapter in this book . CHAPTER XLV. here CHAPTER XLV. NOT ALL A DREAM. “Where are the sounds that swam along The buoyant air when I was young; The last vibration now is o’er, And they who listened are no more; Ah! let me close my eyes and dream.” W. S. Landor. The idea of Helstone had been suggested to Mr. Bell’s waking mind by his conversation with Mr. Lennox, and all night long it ran riot through his dreams. He was again the tutor in the college where he now held the rank of Fellow; it was again a long vacation, and he was staying with his newly-married friend, the proud husband, and happy Vicar of Helstone. Over babbling brooks they took impossible leaps, which seemed to keep them whole days suspended in the air. Time and space were not, though all other things seemed real. Every event was measured by the emotions of the mind, not by its actual existence, for existence it had none. But the trees were gorgeous in their autumnal leafiness—the warm odours of flower and herb came sweet upon the sense—the young wife moved about the house with just that mixture of annoyance at her position, as regarded wealth, with pride in her handsome and devoted husband, which Mr. Bell had noticed in real life a quarter of a century ago. The dream was so like life that, when he awoke, his present life seemed a dream. Where was he? In the close, handsomely furnished room of a London hotel! Where were those who spoke to him, moved around him, touched him, not an instant ago? Dead! buried! lost for evermore, as far as earth’s for evermore would extend. He was an old man, so lately exultant in the full strength of manhood. The utter loneliness of his life was insupportable to think about. He got up hastily, and tried to forget what never more might be, in a hurried dressing for the breakfast in Harley Street. He could not attend to all the lawyer’s details, which, as he saw, made Margaret’s eyes dilate, and her lips grow pale, as one by one fate decreed, or so it seemed, every morsel of evidence which would exonerate Frederick, should fall from beneath her feet and disappear. Even Mr. Lennox’s well-regulated professional voice took a softer, tenderer tone, as he drew near to the extinction of the last hope. It was not that Margaret had not been perfectly aware of the result before. It was only that the details of each successive disappointment came with such relentless minuteness to quench all hope, that she at last fairly gave way to tears. Mr. Lennox stopped reading. “I had better not go on,” said he, in a concerned voice. “It was a foolish proposal of mine. Lieutenant Hale,” and even this giving him the title of the service from which he had so harshly been expelled, was soothing to Margaret. “Lieutenant Hale is happy now; more secure in fortune and future prospects than he could ever have been in the navy; and has, doubtless, adopted his wife’s country as his own.” “That is it,” said Margaret. “It seems so selfish in me to regret it,” trying to smile, “and yet he is lost to me, and I am so lonely.” Mr. Lennox turned over his papers, and wished that he were as rich and prosperous as he believed he should be some day. Mr. Bell blew his nose, but, otherwise, he also kept silence; and Margaret, in a minute or two, had apparently recovered her usual composure. She thanked Mr. Lennox very courteously for his trouble; all the more courteously and graciously because she was conscious that, by her behaviour, he might probably be led to imagine that he had given her needless pain. Yet it was pain she would not have been without. Mr. Bell came up to wish her good-bye. “Margaret!” said he, as he fumbled with his gloves, “I am going down to Helstone to-morrow, to look at the old place. Would you like to come with me? Or would it give you too much pain? Speak out, don’t be afraid.” “Oh, Mr. Bell,” said she—and could say no more. But she took his old gouty hand, and kissed it. “Come, come; that’s enough,” said he, reddening with awkwardness. “I suppose your aunt Shaw will trust you with me. We’ll go to-morrow morning, and we shall get there about two o’clock, I fancy. We’ll take a snack, and order dinner at the little inn—the Lennard Arms, it used to be—and go and get an appetite in the forest. Can you stand it, Margaret? It will be a trial, I know, to both of us, but it will be a pleasure to me, at least. And there we’ll dine—it will be but doe-venison, if we can get it at all—and then I’ll take my nap, while you go out and see old friends. I’ll give you back safe and sound, barring railway accidents, and I’ll insure your life for a thousand pounds before starting, which may be some comfort to your relations; but otherwise, I’ll bring you back to Mrs. Shaw by lunch time on Friday. So, if you say yes, I’ll just go upstairs and propose it.” “It’s no use my trying to say how much I shall like it,” said Margaret, through her tears. “Well, then, prove your gratitude by keeping those fountains of yours dry for the next two days. If you don’t, I shall feel queer myself about the lachrymal ducts, and I don’t like that.” “I won’t cry a drop,” said Margaret, winking her eyes to shake the tears off her eyelashes, and forcing a smile. “There’s my good girl. Then we’ll go upstairs and settle it all.” Margaret was in a state of almost trembling eagerness, while Mr. Bell discussed his plan with her aunt Shaw, who was first startled, then doubtful and perplexed, and in the end, yielding rather to the rough force of Mr. Bell’s words than to her own conviction; for to the last, whether it was right or wrong, proper or improper, she could not settle to her own satisfaction, till Margaret’s safe return, the happy fulfilment of the project, gave her decision enough to say, “she was sure it had been a very kind thought of Mr. Bell’s, and just what she herself had been wishing for Margaret, as giving her the very change which she required, after all the anxious time she had had.” 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. Elizabeth Cleghorn Gaskell (2003). North and South. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/4276/pg4276-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

NOT ALL A DREAM.

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