The stock market is a dynamic entity, with prices influenced by many factors. Carnival's share trajectory demonstrates this ever-changing nature. From a low under $9 in June 2022, the share price made an impressive ascent to over $18 by July 2023. However, by October, it had settled just above $11.

Is Carnival Corporation Stock a Buy Now?

Though corporate leaders have been talking up the strength of the American consumer in recent earnings reports ... FICO refers to Fair Isaac Corporation, the company that created a credit-scoring model used by many lenders. John Greene, the chief financial ...

‘A tale of two consumers’: Beneath reports of robust spending, subprime consumers are showing strains

Gucci sales slipped 7% on a comparable scope and exchange rate basis to €2.22 billion. Yves Saint Laurent recorded a 12% contraction to €768 million, while Bottega Veneta sales fell 7% to €381 million. Sales in Kering’s other houses, including Balenciaga and Alexander McQueen, dropped 15% to €805 million.

Kering Sales Miss Forecasts Amid Luxury Industry Slowdown

Carnival has plenty of long-term potential. Before the pandemic, it demonstrated robust sales and profit growth and cash-flow generation, and the stock outperformed the market for years. Management is doing an excellent job of creating and meeting demand, paying off debt, and making its shares more valuable.

Interested in Buying Carnival Stock? Here's What to Look For.

The consumer goods industry's largest representative body warned on Wednesday that the cost of load shedding, failing infrastructure and rising poverty were a "potentially lethal cocktail" requiring urgent action by the government. Read this for free South ...

'Lethal cocktail' - Consumer goods body counts cost of load shedding, poverty, failing infrastructure

A Wall Street analyst has provided a review for the Consumer Goods company yesterday, but retained the same rating on the stock. The Consumer

RBC Capital Thinks Pet Valu Holdings Ltd.’s Stock is Going to Recover

Rite Aid’s plan to close more stores as part of its bankruptcy process raises concern about how that might hurt access to medicine and care create so-called “pharmacy deserts.”

Rite Aid’s bankruptcy plan stirs worries of new ‘pharmacy deserts’

Supervalu

supervalu

The World Wide Web, thank you Sir Tim, was conceived as a technology designed to be “ ” It has devolved from that into a (cyber)space of moated castles, Disneylandish . a powerful source for social change and individual creativity. cathedrals, not bazaars While very entertaining and very useful in many ways the hegemonic Web platforms present as artificial rather than organic, hierarchical rather than egalitarian. The Big Platforms are owned and managed by a handful of dominant, supervalued, companies. Prominent are Alphabet (Google’s parent) and Meta (Facebook’s parent). Low cost and high profit, they are great at informing and entertaining us. Meanwhile, however, in consequential ways they are beggaring those who provide the content and the users who consume that content. The top platforms are richly paid to channel advertising. To us. The Web has evolved into a massive, and massively profitable, advertising engine. As such, the Web now might be (and is becoming) seen as a form of de facto feudalism, digital imperialism, and digerati aristocracy. The attention of us billions of serfs is the product sold to advertisers. No coercion there. More like… seduction. Note, this critique does not imply a call for legislation or government regulation. Both tend to be blunt instruments that land much harder on startups than on the hegemons of the digital megaverse. It calls for transformation. Which will come, as always, , as Microsoft dethroned IBM, Google (partially) dethroned Microsoft, Facebook (partially) dethroned Google, Apple (partially) dethroned Facebook, and so forth. from more innovation How did we get here? Can we, and if so how can we, once again unleash the imprisoned lighting ( ) of the colonized Web to create a new golden age of innovation and equitable prosperity? h/t Emma Lazarus Enter the blockchain. First, though, who am I to judge? I am one of the few surviving Original Gangsters of the Supply Side/Reaganomics revolution. We, relentlessly mocked by the right (“voodoo economics”) and the left (“trickle-down economics”), got policies enacted that, over time , pushed the Dow from 814 (on that day in November 1979 that Reagan officially declared his candidacy for the presidency) to its current flirtation with 40,000. Our voodoo doubled real per capita GDP (from $30,000 to $60,000). It raised nominal American and world GDP by a factor of ten. Pretty good voodoo. That said, what’s the next act? The juice from the original equitable prosperity policy formula -- of stabilizing the dollar (slaying the inflation dragon for two generations and cutting the top marginal income tax rate from 70% to, initially, 28%) -- got wrung out around the time Bill Clinton left the building. I was and am enthusiastic about reducing counterproductively high marginal tax rates across-the-board. Yet much of what ensued in the name of supply-side during the 21st century is a cargo-cult version of supply-side’s successes of the ‘80s and ‘90s. The post-Reagan/Clinton grotesque caricature of authentic supply-side economics has left the economy limping for a generation. Cumulatively, over 20+ years, sub-par growth rates are crippling. They leave us with an economy, both national and personal, far lower than what consistent 3+% supply-side growth rates would have delivered over time. As , compound interest is the eighth wonder of the world.  A one or two percent differential compounded over 20 years makes a huge difference. Einstein probably never said Is there a new, plausible, way to re-ignite vibrant, widely shared, rising living standards? As Nobel Prize winner Paul Romer has pointed out, the secret sauce is innovation. Tech. Enter A16z’s , “a General Partner and has been at Andreessen Horowitz since 2012. He founded and leads a16z crypto, which invests in web3 technologies through four dedicated funds with more than $7 billion under management.” Chris Dixon Dixon has delivered a splendid new book . It lays out in clear, practical terms how the wild wild Web was lost. And how to set it right in such a way that everyone, including us serfs, can prosper. Read Write Own: Building the Next Era of the Internet As , prosperity is too important to be left to the economists. Enter Dixon. war is too important to be left to the generals How to restore sizzling, equitable, prosperity? The blockchain. The blockchain is a revolutionary form of software which, when more fully developed, portends to allow most of the value created by the community and by its cultural creatives to be enjoyed by the full community and its cultural creatives. Not (as now) exclusively, or at least primarily, by the corporate royalty and tech aristocracy. At long last, Dixon gives us a presentation of the blockchain and its properties imbued with an enthusiasm leavened with shrewd practical insight devoid of hype. Dixon is one of the Masters of the Digital Universe (as coder, entrepreneur, and investor). He knows whereof he writes and has written the first really great, comprehensive, book on the blockchain, . Read Write Own: Building the Next Era of the Internet Eureka! Dixon provides an overview in his introduction. He there provides us a World-Wide-Webb-telescopic-eye view of the three eras of the internet, of a new movement, of seeing the truth and determining the internet’s future. Part One, “Read Write”—treats the early internet, which was effectively read only, and Web2, allowing us surfers to write and post through websites, blogs, podcasts, social media and so forth. He explains why networks matter and lays out a trenchant taxonomy of the two dominant incumbent networks (protocol, like the internet and email, and corporate, such as Google and Facebook) and their properties. In Part Two, “Own,” Dixon then goes on to explain what blockchains are, what “tokens” are, and what the – radically great – properties of blockchain networks are… or could and can be. “Own” is a short word with huge implications. Ownership is what has been lost, and which can be restored via a (better) blockchain. In Part Three, “A New Era,” Dixon explains and explores the fundamentals of the business model, community-created software, and take rates (meaning the vigorish that the corporate network proprietors extract from their communities, a process he aptly calls “attract and extract”). He lays out how building networks with token incentives can dramatically change the way the world works for the better, making it more prosperous, cultured, and equitable. He presents vividly the attendant “tokenomics” … and how to restore popular, rather than corporate-autocratic, governance. In Part Four, “Here and Now”, he contrasts the culture of the computer (blockchain as compute platform) with the casino (cryptocurrency), concluding with “What’s Next” … showing how mobile computing, starting with the iPhone, changed everything. He then lays out “some promising applications.” Dixon concludes with a pragmatic vision of the reinvention of the internet… and what grounds his cause for optimism. Until Dixon, in many years of my searching, like Diogenes with his lantern, I had encountered not one single really good, comprehensive, book on the blockchain. (I may have missed one, admittedly, for instance, not yet having gotten to Alex Tapscott’s critically acclaimed .) Web3 There I rested, baffled. So much sizzle. So little steak. So, together with a brilliant acquaintance, I helped write one: . That said, it mainly was focused on the potential finance applications of the blockchain, not the Big Picture. Redefining the Future of the Economy: Governance Blocks and Economic Architecture I thereafter co-authored a second book on this subject, , a compilation of ten superior policies designed to let the sector thrive while protecting the public. Blockchain With American Character It took a long odyssey to arrive at Dixon. I wandered around for years asking people vastly smarter than me what the blockchain was good for and seeking examples of killer applications (“use cases” in the prevailing jargon). In response, I got oodles of hype. And almost no satisfying answers … with one exception, though a largely unpublished one. noteworthy Cometh now Chris Dixon. I am not the only one impressed. Sam Altman, the godfather of ChatGPT, blurbs Read Write Own: “Read this book to understand a compelling vision of where the Internet should go and how to get there.” Shark Tank’s Mark Cuban: “Chris Dixon succeeds at explaining how crypto technology is vital to our technological future and how we all can benefit much as we have from the internet.” And many more captains of industry, tech titans, and nouveau billionaires discovered Dixon’s writings before I did. My own modest credentials? I have been working within and with the Blockchain ecosystem for, well, eons. One of my LinkedIn verticals is aggregating some of the most interesting stories about NFTs. Ralph Benko’s Cryptozoic Eon Geology nerds will recognize the original to be the pre-Cambrian era … before the trilobites and dinosaurs... comprising 80% of Earth’s geo-history. Are we trembling at the verge of the blockchain’s equivalent of the ? Cryptozoic Eon Cambrian explosion Dixon thinks so. So do I. Call me yet my odyssey through the blockchain ecosystem has brought me into contact with creatures and cultures as exotically beautiful and, sometimes, as weird as those encountered by Odysseus during his long return to Ithaka. Nobody My own pilgrimage: Senior advisor to the fabulous Perianne Boring’s Chamber of Digital Commerce, one of the sector’s earliest and most distinguished cheerleaders. Long-time active member of the Federal Blockchain Working Group. Privileged to present more than once at the conferences of the , the preeminent association of officials and international career civil servants. Government Blockchain Association Serving, for two years, as the senior counselor to the American Blockchain PAC, with its advisory board chaired by who generously contributed the introduction to . The breakthrough nature of Stornetta and Haber’s discovery is decisively evidenced by the fact that three of Satoshi’s eight footnotes referenced his and Stuart Haber’s . blockchain-co-inventor Dr. W. Scott Stornetta Blockchain With American Character seminal paper The high privilege of working with one of Satoshi’s earliest Bitcoin core devs (and major contributor to the Android OS) in establishing a DC think tank devoted to smart energy policy, . Jeff Garzik Washington Power and Light Voted Contributor of the Year in 2022 at for my blockchain writings in six categories: politics, economics, science, art, philosophy, and (with Greg Meredith) scaling. HackerNoon My blockchain-related efforts have migrated primarily to the , rather than policy, side. enterprise My primary focus is on the use of rho calculus (a refinement of Robin Milner’s Turing Award-winning pi-calculus) to deploy a blockchain that, unlike the dominant platforms, scales. Bitcoin does a mere 7 transactions per second, Ethereum, 70 transactions per second. Inadequate for practical utility. And expensive to operate. And storable. (Currently it costs almost half a million dollars to store one iTune on the dominant incumbent chains, hence the referenced data are mostly stashed behind someone else’s firewall, not at all optimal.) And searchable. (Currently the dominant blockchains are largely opaque, like the Web before search engines.) And secure. So … now what? Dixon is a true Master of the Blockchain Universe. Not (like me) a practiced propagandist. Thus he buries his lede on page 179: “The stakes are high. As I’ve argued here, blockchain networks are the only known technology that can re-establish an open, democratic internet.” Hello Congress my old friend, I’ve come to talk to you again…. This re-establishment is a very big deal indeed. What’s next? For the tantalizing promise of the blockchain to be realized we need smart policy that protects the public while not stifling innovation or exporting this cutting-edge tech, and the potentially trillions of associated dollars, to Berlin, Singapore or Zug. Imagine how worse off America would be today if Congress and our regulators had effectively deported the headquarters of the big Web success stories, like Google, to Europe or the Pacific? The need for a savvy legal and regulatory environment is something that legislators, regulators, and the ethical actors within the industry (like Dixon) all agree upon. Yet Washington has thus far proved mostly thrown, acting like the primates upon encountering the monolith at the beginning of . 2001: a Space Odyssey We’re at the precipice of deporting Web3 and its associated power, prestige and wealth. That may be about to change. The blockchain’s thought leaders are at long last gearing up to help guide the footsteps of the Washington elite back onto the Paths of Righteousness via smart policy, smart legislation, and smart regulation. Some very smart leaders of the blockchain ecosystem are now promising to , a modest investment in support a multi-billion dollar sector. invest $78M in lobbying and advocacy in 2024 The open question? Will they deploy their resources effectively? Or be taken in by the wily Beltway Bandits? What to do? Those of us who remember C.P. Snow’s seminal understand that the “physical scientists” (which would include software engineers, notwithstanding that software is, so to speak, metaphysical) among whom I count myself as a very lesser figure do not really understand the “literary intellectuals” (among whom I also count myself in a very minor way). The Two Cultures And The Scientific Revolution This misunderstanding causes a terrible disconnect. As Snow reported, in 1959: “They have a curious distorted image of each other. Their attitudes are so different that, even at the level of emotion, they can’t find much common ground.” This can be countered… if the blockchain thought leaders know how to adopt an effective approach. There is abundant potential common ground. Dixon’s book offers a “ ” – the brain’s bridge connecting the left (logical, dominating the physical scientists) and right (narrative-based, dominating the literary intellectuals) hemispheres – to enable both sides to understand each other. corpus callosum To their mutual, and our, great benefit. There’s a simple way to expedite this process, one with a high ROI. Were the thought leaders of the $78M blockchain advocacy effort to allocate an absurdly small fraction (less than 1%) of their dedicated resources to distributing two copies (one for the Congressperson or Senator, one for his or her most relevant legislative aide) of Read Write Own, the impact almost surely will be disproportionately valuable compared to the low cost of such an operation. How do I know? I’ve pretty much single-handedly gotten (non-blockchain related) legislation passed through the House. Twice. There are a lot of smart, idealistic, people working on Capitol Hill, many actively interested in the blockchain and in its tantalizing potential. Put Read Write Own in front of them! The power of can hardly be overestimated: Joseph Pulitzer’s principles “…put it before them briefly so that they will read it, clearly so that they will understand it, forcibly so that they will appreciate it, picturesquely so that they will remember it, and, above all, accurately so that they may be wisely guided by its light.” The late supply-side chief propagandist Jude Wanniski’s book “The Way the World Works” played an outsized role in igniting the worldwide wave of unprecedented equitable prosperity driven by supply-side economics. This arcane fact is mostly long forgotten. That said, I was there and remember. In the , “And I only am escaped alone to tell thee.” words of Ishmael Read Write Own, properly deployed, very well could catalyze a comparably magnificent equitable prosperity transformation. Putting Dixon’s Read Write Own in front of the right eyeballs in the right way on Capitol Hill, could very well release the djinn of “the only known technology that can re-establish an open, democratic internet” from its lamp. Which eyeballs? Don’t try to guess. Simply trust the process known as “ as described by James Surowiecki. the wisdom of crowds” Flood the zone and let the implicate order take it from there. And then … let a new golden age of equitable prosperity, via the road thereto so ably mapped out by Dixon, foment well-designed policy and thereby foster the next great manifestation of equitable prosperity for America. And the world. Read. Write. Own.

Here Comes Web3: Chris Dixon’s Read Write Own

এখানে আসে ওয়েব 3: ক্রিস ডিক্সনের পড়া লেখা নিজস্ব

Hier kommt Web3: Chris Dixons Read Write Own

Aquí viene Web3: Lectura y escritura propia de Chris Dixon

Voici le Web3 : Lire, écrire et posséder de Chris Dixon

यहाँ आता है वेब3: क्रिस डिक्सन का पढ़ें लिखें अपना

Web3 の登場: Chris Dixon の Read Write Own

Web3 출시: Chris Dixon의 읽기 쓰기

Aí vem a Web3: Read Write Own de Chris Dixon

А вот и Web3: книга Криса Диксона «Читайте, пишите сами»

İşte Web3 Geliyor: Chris Dixon'ın Oku Yaz Kendin Yaz

Đây là Web3: Tự đọc và viết của Chris Dixon

Web3 来了：Chris Dixon 的 Read Write Own

StarkNet is a solution that utilizes to scale Ethereum. It alleviates Ethereum’s network congestion by increasing the throughput and reducing the transaction fee. Availing the zero-knowledge proof technology, it also enhances data security and privacy. Layer2 zkSTARKs With StarkNet, developers can build, deploy, and run high-performing smart contracts in a decentralized environment without worrying about pricey transaction fees and the security of smart contracts. These features make it especially suitable for building dApps that require high performance and low transaction fees like those in DeFi, NFT, or GameFi. The StarkNet ecosystem also opens a lot of new possibilities for developers. Leveraging the flexibility and advanced features of the Cairo language, and taking advantage of StarkNet’s high throughput and customizability, developers can build innovative, high-performance, customized dApps on StarkNet. There are also many choices of zkEVM projects in the ecosystem, enabling developers to deploy and run smart contracts in safer and more efficient environments. All of these have contributed to the StarkNet ecosystem’s significant growth lately with a notable increase in its total value locked. In this article, we’ll look at the advantageous features of StarkNet, share the innovative projects in the ecosystem, and explore the challenges and future prospects the ecosystem may face. StarkNet’s Advantageous Features has many unique advantages offered by using zkSTARKs, the native programming language Cairo and the Cairo Virtual Machine (VM). Its custom development environment enables higher performance, better security, and richer features. Developers can write secure and reliable smart contracts in Cairo and enjoy the high throughput realized by StarkNet via its STARKs-based validation mechanism. Although there is a learning curve for developers, the effort will be well compensated. StarkNet StarkNet employs its own custom programming language Cairo and implements the Cairo VM. This approach is very different from other layer2 solutions which leverage the existing components of Ethereum. While most other solutions focus their effort on Ethereum-oriented optimizations, StarkWare concentrates on polishing its own stack for its ecosystem. Although it sacrifices the network effect of being fully compatible with Ethereum, it’s hard to refute that this choice is reasonable, especially considering it has achieved a network effect around Cairo and the escape velocity needed to expand. In its future development, these technological features and innovations will provide ongoing value. With the increasing importance of data security and privacy, the robust privacy-preserving capability that StarNet offers will be able to attract more users and applications to the network. At the same time, StarkNet’s scalability and decentralized nature make it an effective solution for addressing high throughput and security requirements. As the blockchain ecosystem develops and the demand grows, StarkNet’s superior technological features in terms of throughput, security, and privacy protection will provide significant value to its business, enabling it to win out in the competition. Various Projects in the Ecosystem At the core of StarkNet’s dApp ecosystem is its capability for building zero-knowledge-proof based highly performant, low-fee, privacy-preserving decentralized applications. While StarkNet enables various use cases, its advantages of high throughput, low fee, and privacy protection make it especially suitable for areas such as decentralized exchanges (DEXes) and NFT marketplaces. Below are some projects in the ecosystem that we believe are worth paying attention to. DeFi: JediSwap is a permissionless and composable AMM built on Starknet by the Mesh Finance community. The project has launched on Starknet mainnet, with a current Total Value Locked (TVL) of approximately $5 million. They also received a grant of 150,000 STARK tokens from StarkWare. JediSwap is very innovative, enabling lightning-fast, near-gasless exchange of assets in a trustless manner. It has already gained some market influence and is a contribution to the StarkNet ecosystem in DeFi. Morphine is an innovative DeFi lending and borrowing protocol with two primary use cases: passive lending and active borrowing. Passive lending allows users to provide liquidity and earn yields through junior and senior tranches, catering to different risk appetites. Active borrowing, on the other hand, enables users to deploy sub-accounts, in which they can borrow up to 15 times their collaterals, have access to LSD, LP, ERC4626, and set automation. Globally, Morphine is highly innovative, offering versatile strategies and functionalities for both lenders and borrowers. Its flexibility and degree of automation should be attractive to DeFi users. Therefore, we believe it has the potential to succeed. Orbiter Finance is a decentralized cross-rollup bridge for transferring the Ethereum native assets. The Orbiter Bridge infrastructure allows for fast and cost-effective transfers of Ethereum-based assets across various rollups like StarkNet, zkSync, etc. The team is also developing zkProver, a middle layer that utilizes zero-knowledge technology to aggregate transactions and increase the TPS and volume of cross-rollup transactions. The project will be able to contribute to StarkNet’s development by enhancing interoperability and scalability. DeversiFi is a decentralized exchange aiming to achieve faster and more secure trading through StarkNet while maintaining connectivity to Ethereum. NFT/Gaming/Metaverse: Realms (Bibliotheca DAO) started out as a Loot project and has evolved into a large-scale multiplayer blockchain game on StarkNet. The project scored 15 out of 18 by the Starknet Foundation and will receive a total of 150,000 $STRK from the Early Adopter Grant. RYG.Labs is an NFT creative agency focusing on building interactive dynamic NFTs and providing NFT marketing solutions. It will serve as a launchpad for artists entering the NFT field and promote the development of the NFT market on StarkNet. The Ninth is a metaverse game on StarkNet offering diverse gameplay such as land purchases and upgrades as well as staking. It balances the fun and integration of tech in gaming, using StarkNet ZK Rollup to secure the overall experience. It will contribute to the ecosystem in Metaverse and gaming. Other Innovative Web3 Projects: Argent X is the first wallet for StarkNet built by Argent. Utilizing native account abstraction on StarkNet, Argent X gives users peace of mind with multisig security and no seed phrase and achieves lower transaction fees and faster confirmation times. Braavos is a friendly smart contract-based self-custodial wallet built on StarkNet. It’s designed to offer a seamless experience for Web2 users and is currently available on Android, iOS, Chrome, Firefox, and many other browsers. Carbonable is a StarkNet-based system to track carbon contributions. It has completed the seed funding round with the participation of multiple venture capital firms. Its innovative blockchain-based approach helps reduce carbon dioxide emissions and achieve carbon neutrality. It will create a real-world impact on environmental protection and sustainable development, which will in turn be beneficial to the StarkNet ecosystem. Dolven Labs is a DAO Based Ecosystem Catalyst and a hub for permissionless DeFi tools and innovative projects for the StarkNet ecosystem. The team is also the builder of projects like StarkNet Social and StarkGuardians. Dolven Labs plays a vital role in the StarkNet ecosystem, offering projects accelerator programs and a suite of permissionless tools to allow them to expand their boundaries and achieve their goals. Herodotus is building storage-proof cross-chain data access solutions. It will allow smart contracts deployed on Starknet to access current and historical Ethereum on-chain data in a trustless manner. Herodotus’ solution will be important for increasing interoperability between Ethereum and StarkNet. It will help expand StarkNet’s capabilities and enhance the data accessibility of the blockchain ecosystem as a whole. Overall, the success of the StarkNet ecosystem so far lies in its technological advantages, developer support, and ecosystem support for various use cases. For StarkNet to further grow, extensive community support is needed. If it can attract the attention and support of more developers, investors, and users, it will have a better prospect. Challenges and Future Prospects One of the top challenges and bottlenecks that the StarkNet ecosystem may face is competition. Many other layer2 scaling solutions in the market are striving to compete with StarNet and they are more advantageous in some respects than StarkNet. Therefore, continuous innovation and improvements are needed to attract more developers and users. A second potential issue is the network effect. As StarkNet is a relatively new technology, it requires a significant influx of developers and users to establish a strong network effect. Effective marketing and promotion efforts are thus necessary. Another challenge that StarkNet faces is ensuring the sustainability of its ecosystem. With the emergence of competitors and technological advancements, StarkNet needs to continuously innovate and provide attractive features to maintain user loyalty and attractiveness. Additionally, StarkNet needs to establish solid relationships with developers and partners to foster ecosystem development and growth. Other challenges StarNet might face include: Since Cairo is a new language, developers need to learn and adapt to this new programming language. This may pose an additional learning curve for many developers, limiting their ability to participate in the StarkNet ecosystem. In contrast, Ethereum’s EVM has a larger developer community, making it easier for developers to get started and rapidly build applications. Adoption may be limited by the use of the Cairo language. Although StarkNet demonstrates the advantages of high throughput and low transaction fees in some use cases, these advantages may not be relevant for all application scenarios. For certain applications, especially those that don’t require processing a large volume of transactions, these advantages may not be significant. Therefore, whether StarkNet will be able to witness widespread adoption across various sectors remains to be seen. High throughput and low transaction costs are advantageous only for specific use cases. We believe, StarkNet is technology-driven and has a clear positioning for its business model. The team prioritizes providing solutions that truly address user needs than merely chasing flashy new technologies. We are also seeing developers increasingly embracing Cairo and STARK, recognizing their potential as scalable solutions. For example, some projects are developing zkEVM on top of StarkNet, such as Warp and Kakarot, which is a showcase of the strengths of Cairo and StarkNet. Overall, we believe that StarkNet has greater potential in areas such as fully on-chain (FOC) games, contract wallets, cross-chain communication, and on-chain AI because its technical features and innovations bring critical advantages to these fields. , StarkNet’s high-performance and low-cost features make it an ideal choice. By bundling multiple L2 transactions into one transaction on Ethereum, StarkNet can distribute transaction costs among other transactions in the same batch, reducing costs. Furthermore, StarkNet increases network speed, provides high throughput, and minimizes communication requirements. These features will help ensure the efficiency of developing FOC games and a better user experience on FOC games. In the field of FOC games , StarkNet’s native account abstraction allows contract wallets to offer security similar to that of hardware wallets by allowing the encryption chips or modules on a mobile phone to directly sign transactions. Additionally, StarkNet’s highly programmable signature verification enables optimization at the wallet layer for enhanced performance and security through techniques like signature transcriptions. In the sector of contract wallets StarkNet’s decentralized nature and secure design make it a reliable solution for . By utilizing zero-knowledge proofs, StarkNet allows for the performance of verification and proof without revealing transaction details, ensuring data privacy and security. With StarkNet, the trustworthiness and security of cross-chain communication can be improved, thus facilitating more data exchange and interoperation among various chains. cross-chain communication , StarkNet’s technical features allow off-chain computation with on-chain verification of generated proofs. This enables compute-extensive applications such as AI and machine learning models to be put on-chain while enjoying the convenience of not exposing sensitive data and model details. Also, StarkNet’s zero-knowledge proof capabilities can be used to verify the correctness of AI computations, increasing user trust in the results. Overall, it will open new possibilities for on-chain AI use cases in areas such as gaming, oracles, automated trading, anti-sybil, KYC, and more. In the field of on-chain AI In summary, we believe, with continuous technological development and innovation, the StarkNet ecosystem has the potential to maintain its lead in competition. But it will need to stand up to challenges to maintain sustainability and grow the user base. Through continuous innovation and close collaboration with developers and users, StarkNet may continue to evolve and create new use cases for Ethereum.

Is the StarkNet Ecosystem Overvalued?

¿Está sobrevalorado el ecosistema StarkNet?

L'écosystème StarkNet est-il surévalué ?

क्या स्टार्कनेट इकोसिस्टम का मूल्य अधिक है?

StarkNet エコシステムは過大評価されていますか?

O ecossistema StarkNet está supervalorizado?

Hệ sinh thái StarkNet có được định giá quá cao không?

StarkNet 生态系统是否被高估？

Learn how to automate Start/Stop Superfluid streams in Super Apps. 🚀 One of the most extraordinary things about web3 is that we are still at an early stage and as we speak, the web3 ecosystem is growing with new protocols, toolings, etc., and regardless of our level of expertise, we can contribute to helping others as we are learning. This blog aims to help devs to use the gelato network with smart contracts and specifically for using Gelato automation with Superfluid Super Apps. among other features allows users to stream money/tokens to users/contracts with only one transaction and minimal capital lockup. The caveat is that you have to remember to stop the stream, if not the stream will continue endlessly. Please visit Superfluid website for further info Superfluid Protocol https://www.superfluid.finance/home allows you to execute tasks at a future point in time (for ex-web2 would be similar to a kind of scheduler). The main use case is for repeated tasks. For Superfluid streams we will only need one execution (start or stop) therefore we will have to deploy the task and at the same time the “cancel Task”. Please visit Gelato website for further info Gelato Network https://www.gelato.network/ This project showcases general-purpose examples of automating smart contracts with gelato as well as the application for superfluid streams presenting a very simple 3+3 Step guide to create programmable cash flows In order to do that we have deployed a showcase dapp at . we will interact with two main verified and deployed on mumbai contracts : https://gelato-superapp.web.app Party App Contract ( ) view on scan Gelato Super App Contract ( ) view on scan The code can be found in this repository https://youtu.be/yjmJZ6LuPig 3+3 Steps Guide to Gelatofy a Smart Contract Here you will find 3 + 3 easiest steps to add the gelato infrastructure and very easily automate your smart contract tasks: Wire Gelato infrastructure Gelato Funding Strategy Gelato Business Logic 3.1) Task Creation 3.2) Checker Condition 3.3) Executable Function Step 1: Wire Gelato infrastructure In order to interact with the gelato network, we will need to interact with the Gelato contracts (addresses can be found ). We will interact with three contracts: here The main contract for creating, canceling, getting transaction Fees, transfer fees, etc. We will inherit the contract , we will pass in the constructor the gelato ops and gelato treasury addresses and !. Ops Contract: OpsReady.sol we are good to go import {OpsReady} from "./gelato/OpsReady.sol";
import {IOps} from "./gelato/IOps.sol";
import {ITaskTreasury} from "./gelato/ITaskTreasury.sol";

contract PartyApp is OpsReady, Ownable {

  constructor(address payable _ops, address payable _treasury)
    OpsReady(_ops, payable(_treasury)){  } : We will require to interact with the gelato treasury contract for fund/withdrawal depending on our funding strategy (see step 2) Gelato Treasury Contract : We will interact with this contract in our tests… more on Bonus Track #2 Gelato Network The OpsReady.sol contract, as well as the interfaces, can be found in within the repository. You can just copy them and it works! gelato-files Step 2: Gelato Funding Strategy Gelato executes transactions at a future point in time, therefore we need to choose a way of funding the transactions that Gelato is going to execute on our behalf.There are two alternatives to do that: as long as you have a positive balance in the treasury contract, the future transactions will be executed. If we choose this alternative we need to interact with the Gelato Treasury Contract funding it. 1) Fund the Gelato Treasury Contract: function fundGelato(uint256 amount) public payable {
    require(msg.value == amount, "NO_FUNDING");
    ITaskTreasury(treasury).depositFunds{value: amount}(address(this),ETH,amount);
  }

  function withdrawGelato() public onlyOwner {
    uint256 maxAmount = ITaskTreasury(treasury).userTokenBalance(address(this),ETH);

    ITaskTreasury(treasury).withdrawFunds(payable(msg.sender), ETH, maxAmount);
  } Our smart contract will transfer in every future transaction the amount requested to pay the fees. In this case, we won’t need to interact with the Gelato Treasury Contract but . 2) Fund every transaction: we must maintain a positive balance in our contract Step 3: Gelato Business Logic There are three main parts/steps that we have to define within the business logic: We will have to define a task to tell Gelato what we want to be executed. 3.1) Create the Task: function createTask() public {
    require(taskIdByUser[msg.sender] == bytes32(0), "TASK_STILL_ACTIVE");

    bytes32 taskId = IOps(ops).createTask(
      address(this), /// Contract executing the task
      this.startParty.selector, /// Executable function's selector
      address(this), /// Resolver contract, in our case will be the same
      abi.encodeWithSelector(this.checkerStartParty.selector) /// Checker Condition
    );

    taskIdByUser[msg.sender] = taskId;
  } In order to execute a future transaction, we will have to provide Gelato with the condition to check whether Gelato can execute or not 3.2) Checker Condition: function checkerStartParty()
    external
    view
    returns (bool canExec, bytes memory execPayload)
  {
    canExec = headachePresent == false;
    execPayload = abi.encodeWithSelector(this.startParty.selector);
  } Function that will be executed when conditions and/or time are met. 3.3) Executable Function: function startParty() external onlyOps {
    require(headachePresent == false, "NOT_READY");
    lastPartyStart = block.timestamp;
    headachePresent = true;
  } https://gist.github.com/donoso-eth/0678b0613db36c6c332063c9f39cddfd Party App demo! Our First Gelato App is going to be very simple. It checks whether our gelato party has started or not. The party will always start if we don’t have a “headache” from the previous party. We can set manually when our “headache” is over and then the Gelato network will be able to execute the start party, setting a new start party timestamp and setting our “headache to true” Our screen is divided into two parts depending on our funding strategy. This contract allows three uses cases: Create a simple task funded with treasury: Details can be seen above Once the task is created we can go to the and we will see our task waiting for execution gelato ops website And after successful execution, the ops dashboard will show us something like this. Create a simple task funded with treasury and cancel after the first execution (we are going to use this pattern later on with our Superfluid streams). https://gist.github.com/donoso-eth/517e2dca691980de506229cbe27eee62 Create a simple task paying each transaction (not treasury funding) https://gist.github.com/donoso-eth/340ca96b53005dd457defab0991a735c Gelato Super App Demo Our Gelato super App will help us make superfluid streams programmable by automating the stop or the start of a stream. We will implement the gelato Infrastructure (Step 1) like in the party app and we choose Treasury funding as a Funding Strategy (Step 2) We will demo stopping a stream after some predefined minutes. Our Business Logic will look like this: https://gist.github.com/donoso-eth/e4fc0145ed75ed84309da1a467175931 Now if you have funded the treasury, have started a stream and the gelato has already been executed stopping the stream you have unlocked your Bonus!! Bonus Track #1: Go to Sleep and the Stream will Start. So far we have achieved to stop a stream automatically, but following the same logic, I may want to start streaming to a new employee exactly at 00:00 AM on the first day of work and I don’t want to stay awake every day because hopefully, we are going to hire a lot of employees! .. then (CFA Access Control List) to the rescue, with a simple call to the CFA constant agreement either from the SDK or directly to the contract on your behalf when a certain time is elapsed and a “Gelato Task” is executed. CFA ACL you may want to allow our Super App to start a stream In this use case, we are concatenating two tasks, when the first one is executed, the stream will be started, the task canceled, and another task to stop the stream will be created. https://gist.github.com/donoso-eth/5491f5f94409f9648fa196c3ed24ca3d Bonus Track#2: Master Hardhat Fork and Sky Rocket your Development Speed One of the pleasant experiences in blockchain development is the ability to one-click creation of….. As our dapps grow in complexity we will require to interact with existing on-chain contracts and we will have to mock/deploy protocols. In some cases that . The best alternative to overcome this issue is to work with a fork, with a very simple configuration within our (thks and for pointing out the right direction). if we want to remain local can be cumbersome and we will spend precious development time hardhat.config.ts Sam Flamini Hilmar X https://gist.github.com/donoso-eth/1dbfc57d3d40679e324048e1d7c01ab4 and then with the we will be able to create a “virtual” copy of the blockchain we are targeting. The blocks we create from now on will be stored locally and for the older ones we will query the “real” blockchain with our RPC provider (above we are using alchemy) npx hardhat node --network "hardhat" In our example, we are working with mumbai, the Superfluid contracts (Host, ConstanFlowAgreeent, Supertoken…), as well as the Gelato contracts (Network, OPS, and Treasury), exist with the state they had at the block number of the fork allowing us to interact with them as we would interact with the “real” blockchain. Now, you have your local “mumbai” with the additional helper methods to truly master the chain: https://gist.github.com/donoso-eth/148d031bbc57e6a3b6708367a52b0069 In our Dapp we are working with Gelato contracts. The “Executors” will take care to automate our tasks, but in our local “virtual” chain there are no executors… who will execute our tasks?. And the answer to that is very simple, . We can do that because we master our local blockchain, and we choose to be the executor. Hardhat provides us with the fantastic method and we will use it to become locally “the executor”. we are going to execute the task ourselves we can be whoever we want to be hardhat_impersonateAcount Here we can see the details of the implementation for executing gelato tasks impersonating the Gelato NetWork contract https://gist.github.com/donoso-eth/88b3e43f5957cf1e6cdbcd326067fee0 We will need to build the params to be able to execute the task, if we look in Ops interface we see that we need the following params /// @notice Execution API called by Gelato
  /// @param _txFee Fee paid to Gelato for execution, deducted on the TaskTreasury
  /// @param _feeToken Token used to pay for the execution. ETH = 0xeeeeee...
  /// @param _taskCreator On which contract should Gelato check when to execute the tx
  /// @param _useTaskTreasuryFunds If msg.sender's balance on TaskTreasury should pay for the tx
  /// @param _revertOnFailure To revert or not if call to execAddress fails
  /// @param _execAddress On which contract should Gelato execute the tx
  /// @param _execData Data used to execute the tx, queried from the Resolver by Gelato
  function exec(
    uint256 _txFee,
    address _feeToken,
    address _taskCreator,
    bool _useTaskTreasuryFunds,
    bool _revertOnFailure,
    bytes32 _resolverHash,
    address _execAddress,
    bytes calldata _execData
  ) external; Using one of our examples in the party app we will have: https://gist.github.com/donoso-eth/bacd13ccb9718d70f618eca6c82587f7 The implementation in our dapp tests can be seen in the . We use this technique in our contract tests. code Conclusion As we have seen, it is relatively simple to wire the gelato network into our smart contracts and unlock the full potential of automation. Specifically for Superfluid streams gelato can allow Super Apps to do stream-scheduling. Hope this article can help other devs to quickly get up and running with gelato and apply it to Superfluid streams. You can connect with me on Twitter @donoso_eth Also published . here

Stream Scheduling With Superfluid & Gelato

Programación de transmisiones con Superfluid y Gelato

Planification de flux avec Superfluid & Gelato

Superfluid & Gelato . के साथ स्ट्रीम शेड्यूलिंग

Superfluid と Gelato を使用したストリーム スケジューリング

Agendamento de fluxo com Superfluid & Gelato

Lên lịch phát trực tiếp với Superfluid & Gelato

使用 Superfluid 和 Gelato 进行流调度

Superalgos, Part Two: 
Building a Trading Supermind

Superalgos, Part One: 
The Trading Singularity

VALLETTA, Malta, November 18th, 2024/Chainwire/--LaunchPunks has officially launched, introducing a gamified and community-centric approach to the crypto launchpad landscape. Built on Bitcoin via the TAP Protocol, the platform emphasizes fairness, transparency, and scalability while challenging traditional launchpad models. Ghosty Cash “Spooky” - Supernatural Utility Leading the charge with them is Ghosty Cash. Ghosty Cash represents an innovative approach to anonymous, cross-chain swaps, designed to challenge conventional DeFi models and enhance user autonomy. With over $50 million volume swapped and 200% monthly Total Value Swapped (TVS) growth, Ghosty Cash and its utility token Spooky ($SPKY) are establishing a presence in the expanding Bitcoin DeFi ecosystem. $SPKY Token Utility Highlights: Monthly BTC Rewards: $SPKY holders stake with no lock-up, can earn monthly Bitcoin rewards and keep control of their assets
Deflationary Burns: For every $100 swapped, 0.5 $SPKY is burned, reducing overall supply
Real-Asset Utility & Compliance: $SPKY is MiCAR-compliant on SOL/TAP and balances the needs of privacy and regulation https://youtu.be/gTr1eF2jYKg https://www.youtube.com/embed/gTr1eF2jYKg A New Era for Launchpads: Fair, Fun, and Built for the Community LaunchPunks breaks away from fixed tiers, hidden tokenomics and passive participation and takes a fresh, community-focused approach: Scalable & Transparent: Dynamic Allocation rewards participation and promises fairness in volatile markets. Tokenomics are presented with easy-to-understand graphs.
Social & Gamified: Profiles, leaderboards and social integration turns every launch into an engaging and fun experience.
Inclusive & Anti-Establishment LaunchPunks embraces the punk values of doing things their own way and self-empowerment. No More Ghosts in the Machine With Ghosty Cash, LaunchPunks aims to bring a revolutionary approach to token launches sure to spook the competition. “The old rules are gone - we’re making launchpads fun and accessible,” says LaunchPunks co-founder Mark. “We do things our own way, and everyone gets a chance.” The Ghosty Cash community raise goes live exclusively on LaunchPunks, Monday, 18th November. For more information, users can visit launchpunks.com. About LaunchPunks LaunchPunks is a first-of-its-kind, gamified, social launchpad experience on a mission to rewrite the code of crypto launches. Powered on Bitcoin by TAP Protocol, LaunchPunks delivers a transparent, scalable, and fun experience that puts the community first. LaunchPunks rejects outdated norms, embraces transparency, and seeks to disrupt. Contact LaunchPunks info@launchpunks.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here VALLETTA, Malta, November 18th, 2024/Chainwire/--LaunchPunks has officially launched, introducing a gamified and community-centric approach to the crypto launchpad landscape. Built on Bitcoin via the TAP Protocol, the platform emphasizes fairness, transparency, and scalability while challenging traditional launchpad models. VALLETTA, Malta, November 18th, 2024/Chainwire/--LaunchPunks Ghosty Cash “Spooky” - Supernatural Utility Leading the charge with them is Ghosty Cash. Ghosty Cash represents an innovative approach to anonymous, cross-chain swaps, designed to challenge conventional DeFi models and enhance user autonomy. With over $50 million volume swapped and 200% monthly Total Value Swapped (TVS) growth, Ghosty Cash and its utility token Spooky ($SPKY) are establishing a presence in the expanding Bitcoin DeFi ecosystem. $SPKY Token Utility Highlights: Monthly BTC Rewards: $SPKY holders stake with no lock-up, can earn monthly Bitcoin rewards and keep control of their assets Deflationary Burns: For every $100 swapped, 0.5 $SPKY is burned, reducing overall supply Real-Asset Utility & Compliance: $SPKY is MiCAR-compliant on SOL/TAP and balances the needs of privacy and regulation Monthly BTC Rewards: $SPKY holders stake with no lock-up, can earn monthly Bitcoin rewards and keep control of their assets Deflationary Burns: For every $100 swapped, 0.5 $SPKY is burned, reducing overall supply Real-Asset Utility & Compliance: $SPKY is MiCAR-compliant on SOL/TAP and balances the needs of privacy and regulation https://youtu.be/gTr1eF2jYKg https://youtu.be/gTr1eF2jYKg https://youtu.be/gTr1eF2jYKg https://www.youtube.com/embed/gTr1eF2jYKg https://www.youtube.com/embed/gTr1eF2jYKg https://www.youtube.com/embed/gTr1eF2jYKg A New Era for Launchpads: Fair, Fun, and Built for the Community LaunchPunks breaks away from fixed tiers, hidden tokenomics and passive participation and takes a fresh, community-focused approach: Scalable & Transparent: Dynamic Allocation rewards participation and promises fairness in volatile markets. Tokenomics are presented with easy-to-understand graphs. Social & Gamified: Profiles, leaderboards and social integration turns every launch into an engaging and fun experience. Inclusive & Anti-Establishment LaunchPunks embraces the punk values of doing things their own way and self-empowerment. Scalable & Transparent: Dynamic Allocation rewards participation and promises fairness in volatile markets. Tokenomics are presented with easy-to-understand graphs. Social & Gamified: Profiles, leaderboards and social integration turns every launch into an engaging and fun experience. Inclusive & Anti-Establishment LaunchPunks embraces the punk values of doing things their own way and self-empowerment. No More Ghosts in the Machine With Ghosty Cash, LaunchPunks aims to bring a revolutionary approach to token launches sure to spook the competition. “The old rules are gone - we’re making launchpads fun and accessible,” says LaunchPunks co-founder Mark. “We do things our own way, and everyone gets a chance.” “The old rules are gone - we’re making launchpads fun and accessible,” says LaunchPunks co-founder Mark. “We do things our own way, and everyone gets a chance.” The Ghosty Cash community raise goes live exclusively on LaunchPunks, Monday, 18th November. For more information, users can visit launchpunks.com . launchpunks.com launchpunks.com About LaunchPunks LaunchPunks is a first-of-its-kind, gamified, social launchpad experience on a mission to rewrite the code of crypto launches. Powered on Bitcoin by TAP Protocol, LaunchPunks delivers a transparent, scalable, and fun experience that puts the community first. LaunchPunks rejects outdated norms, embraces transparency, and seeks to disrupt. LaunchPunks LaunchPunks Contact LaunchPunks info@launchpunks.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Next-Gen Gamified Launchpad LaunchPunks Goes Live With Ghosty Cash

Volgende generasie Gamified Launchpad LaunchPunks gaan regstreeks met Ghosty Cash

Next-Gen Gamified Launchpad LaunchPunks በGhosty Cash በቀጥታ ይሄዳል

LaunchPunks, el juego de próxima generación que se lanza con Ghosty Cash

LaunchPunks של הדור הבא של Gamified Launchpad עולה לאוויר עם Ghosty Cash

次世代のゲーム化されたLaunchpad LaunchPunksがGhosty Cashとともにリリース

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Naujos kartos „Gamified Launchpad“ „LaunchPunks“ veikia su „Ghosty Cash“.

Next-Gen Gamified Launchpad LaunchPunks gaat live met Ghosty Cash

Next-Gen Gamified Launchpad LaunchPunks Inorarama neGhosty Cash

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Гейміфікований Launchpad наступного покоління LaunchPunks починає працювати з Ghosty Cash

I-Next-Gen Gamified Launchpad LaunchPunks Iba Bukhoma Nge-Ghosty Cash

The world is a much more connected place than it was 20 years ago. With the change came new expectations. Downtimes can cripple businesses. There is an expectation of privacy and security. If we post on Facebook and the post gets lost due to any kind of issue, people will not tolerate it. Data integrity and durability are more critical than ever. As an organization, we must consider multiple technological tenets—security, availability, latency, durability, integrity, reliability, and privacy. We don’t get to choose from this list; we just sort it by importance based on business needs. Business continuity Disaster can come in many flavors, ranging from natural disasters to hardware failures, misconfiguration, and cyberattacks. The problem with cyberattacks is that we risk having our data stolen and wonder if the rest of the data is trustworthy. Maybe the attack was a sleight of hand, and the primary objective was to introduce malicious data that would haunt the organization forever. After the security incident, we need to recover the data and restore the service to the level our customers expect. One of the issues we face is reconstructing the original picture and configuration. We need to understand how all the pieces work together and their interdependency. Data restoration is more than just restoring a highly scalable web service snapshot. Objective At this point, our primary objective should be to ensure that our services are available and reliable by whatever means necessary. In the context of dependency management, we need to have a comprehensive data and dependency catalog, including the relationships between the entities. This provides us with the necessary insight into what exists. We also need regular operations testing and robust disaster recovery through automation and manual runbooks. We need to cultivate a culture of disaster recovery fire drills and identify fallbacks. Maturity Model Like an individual who enters college goes through freshman, sophomore, junior, and senior years before graduating, businesses need to follow a slow, progressive approach. It’s impractical for a company or organization to go from no disaster recovery to a fully-fledged, perfectly fleshed-out plan. The road to success is incremental, and each step builds on the previous step. Maturity models examine an organization’s current state from any specific perspective, such as disaster recovery, and help the organization reach the desired state or capability. As the organization progresses toward the end goal, it goes through various checkpoints, usually called Levels. Most Maturity Models have four levels, starting from Level 1 up to Level 4. Why are we talking about maturity models? One step in such a disaster recovery maturity model requires that the organization understand dependencies among various entities and data objects. Recovery usually requires restoring the data and bringing back critical systems in a specific incremental manner, Implementation Based on the business needs, understanding dependency and its relationship can be somewhere in the middle levels of the maturity models. In a 4-level system, it is most likely in Level 2 or Level 3. The other approach is to split the Dependency Management into the same number of milestones as the number of levels. Suppose we are using a 4-level maturity model. In that case, we can split up dependency management to span all 4 Levels, starting with the most straightforward steps and going all the way to the most complicated, expensive, and involved steps. Going forward, we will only discuss the dependency management aspect of this maturity model. Level 1 - Discovering and Understanding Dependencies For many organizations, this can be the most daunting task. If dependency management was never considered necessary, there might be no institutional knowledge. We will start by discussing technical dependencies and then discuss process dependencies. Regarding technical dependencies, we need to identify the direct dependencies first. If the code is written in JavaScript and runs on a cloud service, then the direct dependencies might be JavaScript, NodeJS, AWS Lambda, etc. If we use npm for package management, the packages listed in the dependency file are direct dependencies. Next, we have transitive dependencies, which are pulled automatically from direct dependencies. In practice, this forms a directed acyclic graph. Another aspect of technical dependencies is the cloud architecture. Let’s take an example of AWS—we might use EC2, S3, API Gateway, CloudFront, ELB, etc. If the cloud resources were deployed using tools like CloudFormation or CDK, then it would be trivial to determine the dependencies. If the resources were created manually, the dependency diagram must be made manually by reading the source code and drawing conclusions. Process dependency falls under the non-technical category and defines how different stakeholders work together to move forward. It can also outline the release process or runbooks to invoke during an incident. Level 2 - Setup Continuous Dependencies Validation Dependencies can change since there are too many cooks in the kitchen. The organization's continuous integration tool should enumerate and track the direct code and library dependencies. Every time the code is pushed, a snapshot of current pinned dependencies should be saved to recreate the specific circumstances or restore to a known good state. Like the Continuous integration concept, the non-technical aspects should have some automation. Alerts should be created on metric, and using tools like PagerDuty, appropriate people should be notified of issues, and proper escalation channels should be created. It should be tested occasionally to avoid the known problem called Dogs Not Barking - a situation when you wonder if you are not getting any alerts because nothing is wrong or the alerting logic is broken. Some dependencies can be validated by using the Scream test. Under proper notification and preparation, turn off specific dependencies and see what fails. You may find a Load Bearing Mac Mini. Collect all of this configuration and manage it through some kind of provisioning tool like Chef and Terraform Level 3 - Fixing dependencies by adding, updating, or removing Once we have all the dependencies figured out, take some time and pat yourself on the back. Now, back on the issue, the work isn’t done. During the quest, you realize that some dependencies are causing more problems than they solve. One approach would be to update the dependencies. For example, if we are using old versions of OpenSSL, updating them to newer versions can solve many of the warnings raised by the build system and even help us pass any security compliance. Sometimes, the specific versions of two separate packages are incompatible. The solution is to find versions that can work together. This involves changing the version and might involve downgrading one or more packages. Sometimes, just removing a package or dependency solves the problem. It could have been a dead dependency with no further need but causing warnings and spamming the application logs. Under some circumstances, we might have to add a dependency to bring harmony. Suppose a transitive dependency is causing the problem, but we cannot update the direct dependency. In that case, explicitly adding the fixed version of the transitive dependency as a direct dependency can be an acceptable solution. Level 4 - Manual and Automated Disaster Recovery Drills This is the highest form of maturity in disaster recovery. We need runbooks that outline the roles and responsibilities of individuals involved. The runbook should also define the interdependencies and criticality of each step. The disaster recovery process should be practiced regularly by simulating a disaster and identifying possible sources of friction that get introduced when the plan is set in motion. The gold standard should be automated disaster recovery under human supervision. Automating the disaster recovery workflow ensures that humans do not make mistakes that go unnoticed. Automating has an additional advantage in that we can now run stress tests and simulation disasters by turning off certain network parts in a controlled manner to validate whether our automated disaster recovery is performing as expected. Conclusion Dependency management plays a critical role in disaster recovery, which is essential after a security incident. By following a structured and methodological approach, organizations can build their understanding progressively and control the dependencies. Each maturity model level builds on the previous one and strengthens the organization's security posture. While it can be easy to write off dependency management as a superfluous technical exercise, it is primarily about creating a comprehensive framework that brings together computer systems, people, and processes to work harmoniously. The systematic approach ensures that when disaster strikes, even in the form of a security breach, we can safely recover the data and be confident in the integrity of the said data. The world is a much more connected place than it was 20 years ago. With the change came new expectations. Downtimes can cripple businesses. There is an expectation of privacy and security. If we post on Facebook and the post gets lost due to any kind of issue, people will not tolerate it. Data integrity and durability are more critical than ever. As an organization, we must consider multiple technological tenets—security, availability, latency, durability, integrity, reliability, and privacy. We don’t get to choose from this list; we just sort it by importance based on business needs. Business continuity Disaster can come in many flavors, ranging from natural disasters to hardware failures, misconfiguration, and cyberattacks. The problem with cyberattacks is that we risk having our data stolen and wonder if the rest of the data is trustworthy. Maybe the attack was a sleight of hand, and the primary objective was to introduce malicious data that would haunt the organization forever. After the security incident, we need to recover the data and restore the service to the level our customers expect. One of the issues we face is reconstructing the original picture and configuration. We need to understand how all the pieces work together and their interdependency. Data restoration is more than just restoring a highly scalable web service snapshot. Objective At this point, our primary objective should be to ensure that our services are available and reliable by whatever means necessary. In the context of dependency management, we need to have a comprehensive data and dependency catalog, including the relationships between the entities. This provides us with the necessary insight into what exists. We also need regular operations testing and robust disaster recovery through automation and manual runbooks. We need to cultivate a culture of disaster recovery fire drills and identify fallbacks. Maturity Model Like an individual who enters college goes through freshman, sophomore, junior, and senior years before graduating, businesses need to follow a slow, progressive approach. It’s impractical for a company or organization to go from no disaster recovery to a fully-fledged, perfectly fleshed-out plan. The road to success is incremental, and each step builds on the previous step. Maturity models examine an organization’s current state from any specific perspective, such as disaster recovery, and help the organization reach the desired state or capability. As the organization progresses toward the end goal, it goes through various checkpoints, usually called Levels. Most Maturity Models have four levels, starting from Level 1 up to Level 4. Why are we talking about maturity models? One step in such a disaster recovery maturity model requires that the organization understand dependencies among various entities and data objects. Recovery usually requires restoring the data and bringing back critical systems in a specific incremental manner, Implementation Based on the business needs, understanding dependency and its relationship can be somewhere in the middle levels of the maturity models. In a 4-level system, it is most likely in Level 2 or Level 3. The other approach is to split the Dependency Management into the same number of milestones as the number of levels. Suppose we are using a 4-level maturity model. In that case, we can split up dependency management to span all 4 Levels, starting with the most straightforward steps and going all the way to the most complicated, expensive, and involved steps. Going forward, we will only discuss the dependency management aspect of this maturity model. Level 1 - Discovering and Understanding Dependencies For many organizations, this can be the most daunting task. If dependency management was never considered necessary, there might be no institutional knowledge. We will start by discussing technical dependencies and then discuss process dependencies. Regarding technical dependencies, we need to identify the direct dependencies first. If the code is written in JavaScript and runs on a cloud service, then the direct dependencies might be JavaScript, NodeJS, AWS Lambda, etc. If we use npm for package management, the packages listed in the dependency file are direct dependencies. Next, we have transitive dependencies, which are pulled automatically from direct dependencies. In practice, this forms a directed acyclic graph. Another aspect of technical dependencies is the cloud architecture. Let’s take an example of AWS—we might use EC2, S3, API Gateway, CloudFront, ELB, etc. If the cloud resources were deployed using tools like CloudFormation or CDK, then it would be trivial to determine the dependencies. If the resources were created manually, the dependency diagram must be made manually by reading the source code and drawing conclusions. Process dependency falls under the non-technical category and defines how different stakeholders work together to move forward. It can also outline the release process or runbooks to invoke during an incident. Level 2 - Setup Continuous Dependencies Validation Dependencies can change since there are too many cooks in the kitchen. The organization's continuous integration tool should enumerate and track the direct code and library dependencies. Every time the code is pushed, a snapshot of current pinned dependencies should be saved to recreate the specific circumstances or restore to a known good state. Like the Continuous integration concept, the non-technical aspects should have some automation. Alerts should be created on metric, and using tools like PagerDuty, appropriate people should be notified of issues, and proper escalation channels should be created. It should be tested occasionally to avoid the known problem called Dogs Not Barking - a situation when you wonder if you are not getting any alerts because nothing is wrong or the alerting logic is broken. Some dependencies can be validated by using the Scream test . Under proper notification and preparation, turn off specific dependencies and see what fails. You may find a Load Bearing Mac Mini . Collect all of this configuration and manage it through some kind of provisioning tool like Chef and Terraform Scream test Scream test Load Bearing Mac Mini Load Bearing Mac Mini Level 3 - Fixing dependencies by adding, updating, or removing Once we have all the dependencies figured out, take some time and pat yourself on the back. Now, back on the issue, the work isn’t done. During the quest, you realize that some dependencies are causing more problems than they solve. One approach would be to update the dependencies. For example, if we are using old versions of OpenSSL, updating them to newer versions can solve many of the warnings raised by the build system and even help us pass any security compliance. Sometimes, the specific versions of two separate packages are incompatible. The solution is to find versions that can work together. This involves changing the version and might involve downgrading one or more packages. Sometimes, just removing a package or dependency solves the problem. It could have been a dead dependency with no further need but causing warnings and spamming the application logs. Under some circumstances, we might have to add a dependency to bring harmony. Suppose a transitive dependency is causing the problem, but we cannot update the direct dependency. In that case, explicitly adding the fixed version of the transitive dependency as a direct dependency can be an acceptable solution. Level 4 - Manual and Automated Disaster Recovery Drills This is the highest form of maturity in disaster recovery. We need runbooks that outline the roles and responsibilities of individuals involved. The runbook should also define the interdependencies and criticality of each step. The disaster recovery process should be practiced regularly by simulating a disaster and identifying possible sources of friction that get introduced when the plan is set in motion. The gold standard should be automated disaster recovery under human supervision. Automating the disaster recovery workflow ensures that humans do not make mistakes that go unnoticed. Automating has an additional advantage in that we can now run stress tests and simulation disasters by turning off certain network parts in a controlled manner to validate whether our automated disaster recovery is performing as expected. Conclusion Dependency management plays a critical role in disaster recovery, which is essential after a security incident. By following a structured and methodological approach, organizations can build their understanding progressively and control the dependencies. Each maturity model level builds on the previous one and strengthens the organization's security posture. While it can be easy to write off dependency management as a superfluous technical exercise, it is primarily about creating a comprehensive framework that brings together computer systems, people, and processes to work harmoniously. The systematic approach ensures that when disaster strikes, even in the form of a security breach, we can safely recover the data and be confident in the integrity of the said data.

Dependency Management is Critical for Disaster Recovery After a Security Incident

We  recently launched Rio, our new framework designed to help you create  web and local applications using just pure Python. The response from our  community has been overwhelmingly positive and incredibly motivating  for us. With the praise has come a wave of curiosity. The most common  question we’ve encountered is, “How does Rio actually work?”  If you’ve been wondering the same thing, you’re in the right place!  Here we’ll explore the inner workings of Rio and uncover what makes it  so powerful. A Fresh Layouting System When  it comes to building modern apps, components are just the beginning,  it’s the layouting that pulls them together into a cohesive,  user-friendly interface. In our last topic, we took a closer look at  components, the essential pieces of any app. Now, let’s shift our focus  to the layout system that arranges them harmoniously. Designing a layout  system isn’t a one-size-fits-all task; different frameworks bring  unique strengths, with CSS often at the center of debate. As we designed  Rio’s layout system, we aimed for something Pythonic, simple, flexible,  and efficient — a system that keeps developers focused on their app’s  function, not the complexities of positioning. Here, we’ll break down  the core principles behind Rio’s two-step approach to layouting, where  each component starts by defining its own natural size before the  available space is thoughtfully distributed. Take a look at our playground (Layouting Quickstart), where you can try out our layout concept firsthand with just a click and receive real-time feedback. What Makes a Great Layout System? Each UI framework approaches layouting differently, all with their own unique strengths and quirks. There’s of course the polarizing incumbent,  CSS, but also the many systems built into popular frameworks like  Flutter, QT, and others. Before we got to designing our own, we took a  step back to understand what makes a great layout system. Here are some  key principles we identified: Pythonic: Rio embraces Python’s simplicity. No numbers encoded as strings or complex unit declarations. For example, width=10 is preferred over width="10px". This isn’t just cleaner, but also aids type checking tools and allows for easy mathematical operations.
Simple: The system should be intuitive, even for developers without a deep background in UI design. Rather than a tangled set of rules and exceptions, it should be governed by a handful of principles that are applied consistently.
Flexible: From basic layouts to complex, nested structures, the system needs to handle them all. Templates and restrictive built-in patterns won’t cut it.
Efficient: Especially when targeting the web, performance is key. A good layouting system should be automatically convertible to CSS, maybe with some JavaScript sprinkled in occasionally for dynamic calculations. Rio’s Approach: Two-Step Layouting We’ve decided on a two-step layouting system that balances simplicity and flexibility. Here’s how it works: Step 1: Natural Size Calculation First, each component determines how much space it needs to fit its content. We call this the component’s “natural size.” For some components this is simple. For example, rio.Switch has a fixed size, so that is also its natural size. But not all components are that simple. Take a rio.Row  for example. The row itself doesn't need any space, but it needs to  request enough space to fit its children. So the natural width of a row  is the sum of the natural widths of its children, plus any spacing  between them. Another more in-depth example is rio.Text. It's size depends on a variety of things, such as its text content, font size, whether the font is bold, etc. This  process starts at the leaves of the component tree, i.e. first  components without any children are calculated, then their parents, and  so on, until the entire tree has computed its natural width &  height. Step 2: Space Distribution Once  each component has determined its natural size, we must decide how to  allocate the available space. For example, in a large window with only a  button, should the button be centered, aligned to one side, or  stretched? There isn’t a real reason to prefer one over the other. We are solving this, by simply giving all  space to the button. If you don’t want for that to happen, you can  explicitly set the button’s alignment, and Rio will take it into  account. Example Imagine a simple rio.Row containing a rio.Text and a rio.Switch.  First, we need to calculate the natural size of all components. We'll  start with components that don't have any children, so in this case the rio.Text and rio.Switch. The rio.Text will calculate its natural size based on its text content, font size, etc. The rio.Switch has a fixed size, so that is also its natural size. Now that all children have had their natural size calculated, the rio.Row  can get to work. It's natural width is the sum of the natural widths of  its children (plus any spacing) and its natural height is the maximum  of the natural heights of its children. Finally,  we need to distribute the available space. Since the window itself  always has a single child, it will pass all available space to that  child — in this case the rio.Row. The row will then distribute the space to its children; But how? Since there’s only so few components in the view there is likely too much space available. Thus, the rio.Row  will have to decide how much space to pass to each child. Since we  always want all components to have enough space to fit their content  ("natural size") we'll allocate each child that much space. Then, if  space is leftover we can distribute that proportionally. Ta-da! All  components now know how large they are. Their positions also follow from  this. Since this is such a common use-case, rio.Row also honors the grow_x and grow_y attributes of components. If a component is marked to grow,  and superfluous space is available, all space will be given to that  component. If there are multiple components that are marked to grow, the  space will be distributed proportionally just between those components. Implementation The  system described above is what we call our reference layouting system.  It isn’t actually implemented like this in code, but rather as a set of  CSS rules, that result in this exact behavior. This allows our layouting  to run at maximum performance, because it relies on the browser’s  native layouting engine. The described algorithm is nonetheless useful,  as it guides Rio developers to how a component should behave. It’s just  that this behavior is then achieved by internal CSS rules rather than  the algorithm itself. Best  of all, you’ll never have to see a single line of CSS. All of this is  handled by Rio internally, so you can focus on building your app. Limitations and Trade-offs While  Rio’s layout system is powerful and flexible, it isn’t perfect. In the  interest of full transparency, we’d like to share some limitations that  we’ve found: Some layouts cannot achieved just using CSS. Notably, when using the proportions attribute of rio.Row or rio.Column, JavaScript jumps into action to help out, because we are not aware of any pure-CSS way to achieve our desired behavior. (If you're a CSS magician and know a way, reach out!)
There are occasional layouts that cannot be realized with this system. One such situation that we’ve found is to have a row containing an icon and text, while that text is both centered and has wrapping enabled.
This sounds like a simple case, but no combination of parameters yields the desired result. Aligning the text to 0.5 (center) won't center the icon. Same when using the justify attribute. Aligning the entire rio.Row will make the row take up as little space as possible, thus squishing the text.
We’ve had some discussions about introducing a “preferred size” that would solve this, but it’s not in Rio yet. Github: https://github.com/rio-labs/rio Website: https://rio.dev/ We  recently launched Rio, our new framework designed to help you create  web and local applications using just pure Python. The response from our  community has been overwhelmingly positive and incredibly motivating  for us. With the praise has come a wave of curiosity. The most common  question we’ve encountered is, “How does Rio actually work?” If you’ve been wondering the same thing, you’re in the right place!  Here we’ll explore the inner workings of Rio and uncover what makes it  so powerful. “How does Rio actually work?” A Fresh Layouting System When  it comes to building modern apps, components are just the beginning,  it’s the layouting that pulls them together into a cohesive,  user-friendly interface. In our last topic, we took a closer look at  components, the essential pieces of any app. Now, let’s shift our focus  to the layout system that arranges them harmoniously. Designing a layout  system isn’t a one-size-fits-all task; different frameworks bring  unique strengths, with CSS often at the center of debate. As we designed  Rio’s layout system, we aimed for something Pythonic, simple, flexible,  and efficient — a system that keeps developers focused on their app’s  function, not the complexities of positioning. Here, we’ll break down  the core principles behind Rio’s two-step approach to layouting, where  each component starts by defining its own natural size before the  available space is thoughtfully distributed. Take a look at our playground ( Layouting Quickstart ), where you can try out our layout concept firsthand with just a click and receive real-time feedback. Layouting Quickstart What Makes a Great Layout System? Each UI framework approaches layouting differently, all with their own unique strengths and quirks. There’s of course the polarizing incumbent ,  CSS, but also the many systems built into popular frameworks like  Flutter, QT, and others. Before we got to designing our own, we took a  step back to understand what makes a great layout system. Here are some  key principles we identified: polarizing incumbent Pythonic: Rio embraces Python’s simplicity. No numbers encoded as strings or complex unit declarations. For example, width=10 is preferred over width="10px". This isn’t just cleaner, but also aids type checking tools and allows for easy mathematical operations. Simple: The system should be intuitive, even for developers without a deep background in UI design. Rather than a tangled set of rules and exceptions, it should be governed by a handful of principles that are applied consistently. Flexible: From basic layouts to complex, nested structures, the system needs to handle them all. Templates and restrictive built-in patterns won’t cut it. Efficient: Especially when targeting the web, performance is key. A good layouting system should be automatically convertible to CSS, maybe with some JavaScript sprinkled in occasionally for dynamic calculations. Pythonic: Rio embraces Python’s simplicity. No numbers encoded as strings or complex unit declarations. For example, width=10 is preferred over width="10px" . This isn’t just cleaner, but also aids type checking tools and allows for easy mathematical operations. Pythonic: width=10 width="10px" Simple: The system should be intuitive, even for developers without a deep background in UI design. Rather than a tangled set of rules and exceptions, it should be governed by a handful of principles that are applied consistently. Simple: Flexible: From basic layouts to complex, nested structures, the system needs to handle them all. Templates and restrictive built-in patterns won’t cut it. Flexible: Efficient: Especially when targeting the web, performance is key. A good layouting system should be automatically convertible to CSS, maybe with some JavaScript sprinkled in occasionally for dynamic calculations. Efficient: Rio’s Approach: Two-Step Layouting We’ve decided on a two-step layouting system that balances simplicity and flexibility. Here’s how it works: Step 1: Natural Size Calculation First, each component determines how much space it needs to fit its content. We call this the component’s “natural size.” For some components this is simple. For example, rio.Switch has a fixed size, so that is also its natural size. But not all components are that simple. Take a rio.Row for example. The row itself doesn't need any space, but it needs to  request enough space to fit its children. So the natural width of a row  is the sum of the natural widths of its children, plus any spacing  between them. rio.Switch rio.Row Another more in-depth example is rio.Text . It's size depends on a variety of things, such as its text content, font size, whether the font is bold, etc. rio.Text This  process starts at the leaves of the component tree, i.e. first  components without any children are calculated, then their parents, and  so on, until the entire tree has computed its natural width &  height. Step 2: Space Distribution Once  each component has determined its natural size, we must decide how to  allocate the available space. For example, in a large window with only a  button, should the button be centered, aligned to one side, or  stretched? There isn’t a real reason to prefer one over the other. We are solving this, by simply giving all space to the button. If you don’t want for that to happen, you can  explicitly set the button’s alignment, and Rio will take it into  account. all Example Imagine a simple rio.Row containing a rio.Text and a rio.Switch .  First, we need to calculate the natural size of all components. We'll  start with components that don't have any children, so in this case the rio.Text and rio.Switch . rio.Row rio.Text rio.Switch rio.Text rio.Switch The rio.Text will calculate its natural size based on its text content, font size, etc. The rio.Switch has a fixed size, so that is also its natural size. rio.Text rio.Switch Now that all children have had their natural size calculated, the rio.Row can get to work. It's natural width is the sum of the natural widths of  its children (plus any spacing) and its natural height is the maximum  of the natural heights of its children. rio.Row Finally,  we need to distribute the available space. Since the window itself  always has a single child, it will pass all available space to that  child — in this case the rio.Row . The row will then distribute the space to its children; But how? rio.Row Since there’s only so few components in the view there is likely too much space available. Thus, the rio.Row will have to decide how much space to pass to each child. Since we  always want all components to have enough space to fit their content  ("natural size") we'll allocate each child that much space. Then, if  space is leftover we can distribute that proportionally. Ta-da! All  components now know how large they are. Their positions also follow from  this. rio.Row Since this is such a common use-case, rio.Row also honors the grow_x and grow_y attributes of components. If a component is marked to grow ,  and superfluous space is available, all space will be given to that  component. If there are multiple components that are marked to grow, the  space will be distributed proportionally just between those components. rio.Row grow_x grow_y grow Implementation The  system described above is what we call our reference layouting system.  It isn’t actually implemented like this in code, but rather as a set of  CSS rules, that result in this exact behavior. This allows our layouting  to run at maximum performance, because it relies on the browser’s  native layouting engine. The described algorithm is nonetheless useful,  as it guides Rio developers to how a component should behave. It’s just  that this behavior is then achieved by internal CSS rules rather than  the algorithm itself. Best  of all, you’ll never have to see a single line of CSS. All of this is  handled by Rio internally, so you can focus on building your app. Limitations and Trade-offs While  Rio’s layout system is powerful and flexible, it isn’t perfect. In the  interest of full transparency, we’d like to share some limitations that  we’ve found: Some layouts cannot achieved just using CSS. Notably, when using the proportions attribute of rio.Row or rio.Column, JavaScript jumps into action to help out, because we are not aware of any pure-CSS way to achieve our desired behavior. (If you're a CSS magician and know a way, reach out!) There are occasional layouts that cannot be realized with this system. One such situation that we’ve found is to have a row containing an icon and text, while that text is both centered and has wrapping enabled. This sounds like a simple case, but no combination of parameters yields the desired result. Aligning the text to 0.5 (center) won't center the icon. Same when using the justify attribute. Aligning the entire rio.Row will make the row take up as little space as possible, thus squishing the text. We’ve had some discussions about introducing a “preferred size” that would solve this, but it’s not in Rio yet. Some layouts cannot achieved just using CSS. Notably, when using the proportions attribute of rio.Row or rio.Column , JavaScript jumps into action to help out, because we are not aware of any pure-CSS way to achieve our desired behavior. (If you're a CSS magician and know a way, reach out!) proportions rio.Row rio.Column There are occasional layouts that cannot be realized with this system. One such situation that we’ve found is to have a row containing an icon and text, while that text is both centered and has wrapping enabled. This sounds like a simple case, but no combination of parameters yields the desired result. Aligning the text to 0.5 (center) won't center the icon. Same when using the justify attribute. Aligning the entire rio.Row will make the row take up as little space as possible, thus squishing the text. 0.5 justify rio.Row We’ve had some discussions about introducing a “preferred size” that would solve this, but it’s not in Rio yet. Github: https://github.com/rio-labs/rio Github: https://github.com/rio-labs/rio https://github.com/rio-labs/rio Website: https://rio.dev/ Website: https://rio.dev/ https://rio.dev/

Rio: WebApps in pure Python — A fresh Layouting System

Here's Why We Need To Build A Lunar Economy - Now!

When people think about Artificial Intelligence (AI), they often envision a world filled with complicated algorithms, impenetrable code, and teams of expert mathematicians working with massive servers. For years, this intimidating image has kept non-technical people at bay, making AI seem like a realm accessible only to those with deep technological expertise. Yet, in 2024, many of these assumptions no longer hold true and are, quite frankly, absurd. Here’s a look at the myths that need debunking and the unexpected truths that may surprise you. You Need to Be in IT or Know Programming to Use AI The idea that AI is solely for IT professionals or those who can code is a relic of the past. Today, tools like ChatGPT, Midjourney, and other AI platforms have simplified user interfaces and accessible functionalities that cater to everyone, from writers and marketers to students and retirees. These platforms enable users to benefit from AI with just a few clicks, dragging and dropping content or engaging in natural language conversations. ICYMI: You can actually use AI to write code even if you’re not a programmer. Platforms like ChatGPT can generate snippets of code in Python, JavaScript, or even obscure languages like COBOL—all based on simple prompts. This means non-technical users can dabble in coding projects, troubleshoot errors, or automate mundane tasks without ever opening a coding textbook. You Need to Be a Mathematician or Statistician to Use AI It’s true that AI was built on complex mathematical principles and algorithms, but that’s where its association with math should end for most users. The AI systems we interact with today are designed to hide this complexity, providing users with straightforward, intuitive interfaces. You don’t need to understand calculus or linear algebra to appreciate the benefits of AI any more than you need to know how an internal combustion engine works to drive a car. ICYMI: Math was used to build these models, but math is arguably the worst place to use them. In fact, LLMs occasionally get math problems wrong. AI excels in creating dynamic conversations, generating creative content, and solving problems where human intuition would typically trump formulas. The irony is that for most business use cases, attempting to use AI purely for mathematical functions undermines its true potential. You Need a High-End Laptop, Servers, or Cloud Subscriptions to Use AI It’s natural to assume that cutting-edge technology requires cutting-edge equipment. However, with cloud-based services and AI applications that run on browsers, almost anyone with an internet connection can access the most powerful AI models in the world using a basic laptop, tablet, or even a smartphone. Free or low-cost subscription plans on platforms like Google Colab or OpenAI’s ChatGPT make experimentation affordable and accessible. You Need Clean, Curated, Warehoused Data to Use AI A common misconception is that AI systems need pristine, perfectly formatted datasets stored in high-end data warehouses to function. This was true for traditional machine learning models. Today’s generative AI models can work with natural language inputs, making them vastly more adaptable and flexible. You can input unstructured information like casual text, incomplete data, or even ideas you’re still developing, and AI will still deliver usable outputs. AI Hallucinates AI hallucinations—where the system generates plausible but false or nonsensical information—are a real concern, but they are often misunderstood. People blame the AI itself, but hallucinations occur mostly because of poorly framed prompts or insufficient context. When properly guided through techniques like prompt engineering, hallucinations can be minimized, making the AI’s outputs significantly more accurate. ICYMI: Hallucinations occur more often if you do not use prompt engineering. Understanding how to communicate with the AI, how to set constraints, and how to refine prompts leads to more reliable outputs and reduces the risk of confusing or incorrect information. Prompt Engineering is Useless The role of prompt engineering is often dismissed by skeptics who see it as trivial or unimportant. Yet, this skill—knowing how to communicate effectively with AI models—can make a significant difference in the quality of the AI’s outputs. Prompt engineering is akin to knowing how to ask the right questions in a search engine; it’s not a superfluous task but a critical competency. In fact, industries are beginning to see prompt engineers as an essential part of AI project teams, guiding the models to produce business-ready results. Final Thoughts: The Democratization of AI What we’re witnessing today is the democratization of AI—an era where AI isn’t just for techies or mathematicians. People from all walks of life are embracing AI to write books, create art, develop recipes, and even enhance personal productivity. The absurdity lies not in these widespread applications but in the stubborn myths that prevent more people from exploring AI’s potential. As AI continues to become more accessible and versatile, it’s time to lay these misconceptions to rest. Whether you’re a business owner looking to streamline operations or a teacher seeking new ways to engage students, AI has something to offer. Embrace it, experiment with it, and discover its real value—no technical degree is required. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com When people think about Artificial Intelligence (AI), they often envision a world filled with complicated algorithms, impenetrable code, and teams of expert mathematicians working with massive servers. For years, this intimidating image has kept non-technical people at bay, making AI seem like a realm accessible only to those with deep technological expertise. Yet, in 2024, many of these assumptions no longer hold true and are, quite frankly, absurd. Here’s a look at the myths that need debunking and the unexpected truths that may surprise you. You Need to Be in IT or Know Programming to Use AI The idea that AI is solely for IT professionals or those who can code is a relic of the past. Today, tools like ChatGPT, Midjourney, and other AI platforms have simplified user interfaces and accessible functionalities that cater to everyone, from writers and marketers to students and retirees. These platforms enable users to benefit from AI with just a few clicks, dragging and dropping content or engaging in natural language conversations. ICYMI : You can actually use AI to write code even if you’re not a programmer. Platforms like ChatGPT can generate snippets of code in Python, JavaScript, or even obscure languages like COBOL—all based on simple prompts. This means non-technical users can dabble in coding projects, troubleshoot errors, or automate mundane tasks without ever opening a coding textbook. ICYMI You Need to Be a Mathematician or Statistician to Use AI It’s true that AI was built on complex mathematical principles and algorithms, but that’s where its association with math should end for most users. The AI systems we interact with today are designed to hide this complexity, providing users with straightforward, intuitive interfaces. You don’t need to understand calculus or linear algebra to appreciate the benefits of AI any more than you need to know how an internal combustion engine works to drive a car. ICYMI : Math was used to build these models, but math is arguably the worst place to use them. In fact, LLMs occasionally get math problems wrong. AI excels in creating dynamic conversations, generating creative content, and solving problems where human intuition would typically trump formulas. The irony is that for most business use cases, attempting to use AI purely for mathematical functions undermines its true potential. ICYMI You Need a High-End Laptop, Servers, or Cloud Subscriptions to Use AI It’s natural to assume that cutting-edge technology requires cutting-edge equipment. However, with cloud-based services and AI applications that run on browsers, almost anyone with an internet connection can access the most powerful AI models in the world using a basic laptop, tablet, or even a smartphone. Free or low-cost subscription plans on platforms like Google Colab or OpenAI’s ChatGPT make experimentation affordable and accessible. You Need Clean, Curated, Warehoused Data to Use AI A common misconception is that AI systems need pristine, perfectly formatted datasets stored in high-end data warehouses to function. This was true for traditional machine learning models. Today’s generative AI models can work with natural language inputs, making them vastly more adaptable and flexible. You can input unstructured information like casual text, incomplete data, or even ideas you’re still developing, and AI will still deliver usable outputs. AI Hallucinates AI hallucinations—where the system generates plausible but false or nonsensical information—are a real concern, but they are often misunderstood. People blame the AI itself, but hallucinations occur mostly because of poorly framed prompts or insufficient context. When properly guided through techniques like prompt engineering, hallucinations can be minimized, making the AI’s outputs significantly more accurate. ICYMI : Hallucinations occur more often if you do not use prompt engineering. Understanding how to communicate with the AI, how to set constraints, and how to refine prompts leads to more reliable outputs and reduces the risk of confusing or incorrect information. ICYMI Prompt Engineering is Useless The role of prompt engineering is often dismissed by skeptics who see it as trivial or unimportant. Yet, this skill—knowing how to communicate effectively with AI models—can make a significant difference in the quality of the AI’s outputs. Prompt engineering is akin to knowing how to ask the right questions in a search engine; it’s not a superfluous task but a critical competency. In fact, industries are beginning to see prompt engineers as an essential part of AI project teams, guiding the models to produce business-ready results. Final Thoughts: The Democratization of AI What we’re witnessing today is the democratization of AI—an era where AI isn’t just for techies or mathematicians. People from all walks of life are embracing AI to write books, create art, develop recipes, and even enhance personal productivity. The absurdity lies not in these widespread applications but in the stubborn myths that prevent more people from exploring AI’s potential. As AI continues to become more accessible and versatile, it’s time to lay these misconceptions to rest. Whether you’re a business owner looking to streamline operations or a teacher seeking new ways to engage students, AI has something to offer. Embrace it, experiment with it, and discover its real value—no technical degree is required. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com

AI: It's Not What You Think

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