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If you're unfamiliar with the languages of Solidity and Yul or lack a passion for the specifics of EVM assembly, then this may not be the rabbit hole you're looking for. Question In a , when transferring Ether to another contract, is there a potential risk of gas griefing from not handling the return data? Solidity contract Transferring Ether A Solidity function definition must contain the keyword to be able to accept an Ether value in the invoking call. payable The breaking changes introduced in version 0.6 included introducing the optional and functions as default message handlers.
The function, when present, is given priority over the function for handling a call containing a value without message data. Solidity receive fallback receive fallback Transferring Ether with the standard gas stipend can be done with either the or functions on the type transfer send address // reverts on failure, forwards 2300 gas stipend
msg.sender.transfer(1 ether);

// returns false on failure, forwards 2300 gas stipend
msg.sender.send(1 ether); The recipient is allowed to consume up to 23K gas in its handling function (i.e., when is a contract the or functions).
The gas stipend severely restricts what can be achieved inside the handler function, which is the primary cause of the recommendation to use over or . msg.sender msg.sender receive fallback call send transfer Receive Function If present, the function is given priority to handle a message with a and without any . receive msg.value msg.data A contract can now have only one receive function, declared with the syntax: receive() external payable {…} (without the function keyword). Important to note is the function signature is absent any keyword and associate return type. receive return (If a function is defined with a return value, it does not conform to the language specification and will fail compilation; likewise, attempting to return a value inside a function that lacks a return value in its signature will also fail compilation). receive Fallback function If present, the default function for a message with a and or when the function has not also been implemented without . msg.value msg.data receive msg.data declared using fallback() external [payable] {…} (without the function keyword).   This function cannot have arguments, cannot return anything and must have external visibility. The fallback function always receives data, but to also receive Ether, you should mark it as payable. Once again, we have a default handling function that is forbidden from returning anything. Tuples are syntactic sugar Internally, Solidity allows tuple types that can be used to return multiple values at the same time. Tuples can be assigned to newly declared variables or existing ones, but the number of assignments must match the length of the returned list. Tuples are not proper types in Solidity, they can only be used to form syntactic groupings of expressions. When de-structuring a list of return values, some assignments can be omitted when not pertinent to the code. // Variables declared with type and assigned from the returned tuple,
        // not all elements have to be specified (but the number must match).
        (uint x, , uint y) = f(); Yul Solidity supports both assembly blocks and inline assembly in Yul. Supporting the same feature set as Solidity but with the opportunity for greater granularity that can also lead to more efficiently generated bytecode. Call opcode Invoking a contract function is achieved using the opcode. call One motivation for using rather than the or functions on the type is the ability to choose the amount of gas to be forwarded for use in the call (gas forwarding). call send transfer address call(g, a, v, in, insize, out, outsize)

call contract at address a with input mem[in…(in+insize)) providing g gas and v wei and output area mem[out…(out+outsize)) returning zero on error (eg. out of gas) and one on success. Inline call An inline code fragment can use key-value pairings for parameter assignments, where other parameters may be omitted as they are inferred from the surrounding Solidity context or given default values. (bool success,) = to.call{value: amount}(""); Values in the above example for : call(g, a, v, in, insize, out, outsize) g: gas(); remaining gas allowance a: to; address of the contract being called v: amount; Ether to transfer denominated in wei and : calldata; the encoded signature and parameters (equivalent to ) in insize abi.encodeWithSignature("") and : the free memory pointer (as return data is stored in memory at the first free location). out outsize Importantly, as the call is being made in Yul and not Solidity, the Solidity compile time type checks are absent, resulting in the return data being an unknown, and the compiled code will have to handle the possibility of that unknown return data. (See Appendix A for sample code, ASM and breakdown) Gas griefing An avenue of attack where the goal is not to provide direct profit for the attacker but instead to cause an inconvenience to the victim. Greedily consuming sufficient gas to either prevent correct execution on return or simply to exorbitantly increase transaction costs can achieve griefing. Oversized return data When the size of the return data is unknown (as it is with the previous Yul inline example), then the entire return data is copied to memory even though the assignment is not being used (copying to memory costs gas). If the opcode forwards all the available gas, there is the opportunity for a malevolent recipient to dynamically create return data large enough to consume all the forwarded gas. call call When you are only performing a value transfer with a generous gas allocation, you may not have expected it to cost an obscene amount of gas, nor might you have expected enough gas spending to cause an out-of-gas exception. Causing inconvenience is the purpose of the griefing attack. Solidity contract - default functions The Solidity language specification explicitly forbids return values from the default functions of and . A griefing attack using return data from the default function is simply not possible, assuming their contract was implemented in Solidity. receive fallback Vyper contract - default function An alternative smart contract language is Vyper, which provides a similar feature set but aims at being less permissive than Solidity to prevent risky implementations. Vyper has a default function that will be invoked (as the name implies) when the contract lacks a matching named function to the function selector bytes of the calldata. This function is always named and must be annotated with @public. It cannot have arguments and cannot return anything. default The restriction on forbidding any return value is identical to the Solidity default functions, and as with Solidity, the attacker is unable to implement their griefing contract in Vyper. Yul contract As the restrictions on the default function(s) having no return data are part of the language specification rather than the EVM specification, what happens if we implement the attack contract at a lower level of abstraction? (See Appendix B for sample code, asm and breakdown) When implementing the entire contract in Yul, a default function that returns data can be successfully implemented. Although writing a contract using only Yul dials up the technical requirements for the attacker, it does mean that gas griefing from non-handling the return data for value transfers that use call is possible. Return data buffer The Byzantium hardfork (2017) included EIP-211, which introduced both the opcodes and the return data buffer to deal with return data of unknown size. Compiler implementors are advised to reserve a zero-length area for return data if the size of the return data is unknown before the call and then use RETURNDATACOPY in conjunction with RETURNDATASIZE to actually retrieve the data. (See Appendix A for sample code, asm and breakdown) When compiling the Solidity with inline Yul into the intermediate representation (IR), we can see it contains the and opcodes. As the does not define the return data size, the generated IR code must deal with that unknown return data size. RETURNDATASIZE RETURNDATACOPY call Return size of zero Within a Yul code block, the opcode can be invoked with all parameters assigned a value, with the resulting IR code not containing the copying of the return data. call /*
         *  1. As we want to call the default handler, empty calldata is sufficient
         *      :. `argsOffset` and `argsLength` are both zero
         *  2. To ignore the return buffer we must state it explicitly
         *      :. `retOffset` and `retLength` are both zero
         */
        assembly {
            success := call(gas(), recipient, amount, 0, 0, 0, 0)
        } (See Appendix C for sample code, asm and breakdown) Is the risk really mitigated? Another important detail from EIP-211: Note that the EVM implementation needs to keep the return data until the next call or the return from the current call. Since this resource was already paid for as part of the memory of the callee, it should not be a problem. Implementations may either choose to keep the full memory of the callee alive until the next call or copy only the return data to a special memory area. Put simply, when an attacker is attempting to grief a victim using a malicious contract that bloats the return data, the caller can do nothing to prevent the gas from being consumed by the malicious contract by storing its return data in the return data buffer. Mitigation The only way to properly mitigate the risk of interacting with a malicious contract would be to strictly follow a process of only interacting with trusted contracts or ones that can be independently verified as sound (e.g. checking that the verified source code on Etherscan will behave appropriately). Summary When transferring Ether from a victim contract to a griefer contract using a Yul , if the griefer was written in Solidity or Vyper, there is no risk of griefing from non-handling of return data, as their default functions are forbidden from using the return data buffer.  However, if written in Yul, then data could be returned by the default handler. call The griefing attack is the consumption of an unreasonable amount of the forwarded gas by returning oversized data, causing inconvenience to the victim. Although the victim can explicitly set the return data size to zero, avoiding the generation of the memory copying code in the victim's contract, it cannot prevent the griefer's gas consumption from storing their data in the return data buffer. Rather than a unique problem with handling return data, this issue seems more like a generic risk when yielding the control flow to another contract. When outside the dominion of your control, you are powerless to restrict what the other contract does; instead, you are able to restrict only the amount of computation by limiting the gas forwarded in the call. References https://soliditylang.org/blog/2020/03/23/fallback-receive-split/ https://docs.soliditylang.org/en/v0.8.22/contracts.html#receive-ether-function https://docs.soliditylang.org/en/v0.8.22/cheatsheet.html#members-of-address https://docs.soliditylang.org/en/v0.8.22/security-considerations.html#sending-and-receiving-ether https://docs.soliditylang.org/en/v0.8.22/control-structures.html?highlight=tuples#destructuring-assignments-and-returning-multiple-values https://docs.soliditylang.org/en/v0.8.22/yul.html#evm-dialect https://docs.soliditylang.org/en/v0.8.22/assembly.html https://docs.soliditylang.org/en/v0.8.22/internals/layout_in_memory.html#layout-in-memory https://www.evm.codes/ https://www.ethervm.io/ https://eips.ethereum.org/EIPS/eip-211 https://scsfg.io/hackers/griefing/ https://docs.vyperlang.org/en/v0.1.0-beta.17/structure-of-a-contract.html https://blog.ethereum.org/2017/10/12/byzantium-hf-announcement Appendices Appendix A - Inline Yul call Solidity contract with an inline Yul call to transfer value. Compile to intermediary representation (IR) to investigate the stack and opcodes. ) asm ( forge build --extra-output-files evm.assembly pragma solidity 0.8.20;

contract InlineYul {
    function solidityCall() external{
        address recipient = msg.sender;
        uint256 amount = 1 ether;

        (bool success,) = (recipient).call{value: amount}("");

        require(success, "transfer failed");
    }
} IR are the stack operations with opcodes, with the below being the pertinent subset from the compilation of InlineYul. performs the call, using inputs from the stack tag_5 is the top-level call response handling, note the presence of opcode, despite not storing the return data . tag_7 returndatacopy reference in the Solidity code providing with the statement tag_10 require tag_5:
    /* "src/InlineYul.sol":136:153  address recipient */
  0x00
    /* "src/InlineYul.sol":156:166  msg.sender */
  caller
    /* "src/InlineYul.sol":136:166  address recipient = msg.sender */
  swap1
  pop
    /* "src/InlineYul.sol":177:191  uint256 amount */
  0x00
    /* "src/InlineYul.sol":194:201  1 ether */
  0x0de0b6b3a7640000
    /* "src/InlineYul.sol":177:201  uint256 amount = 1 ether */
  swap1
  pop
    /* "src/InlineYul.sol":215:227  bool success */
  0x00
    /* "src/InlineYul.sol":233:242  recipient */
  dup3
    /* "src/InlineYul.sol":232:248  (recipient).call */
  0xffffffffffffffffffffffffffffffffffffffff
  and
    /* "src/InlineYul.sol":256:262  amount */
  dup3
    /* "src/InlineYul.sol":232:267  (recipient).call{value: amount}("") */
  mload(0x40)
  tag_7
  swap1
  tag_8
  jump  // in
tag_7:
  0x00
  mload(0x40)
  dup1
  dup4
  sub
  dup2
  dup6
  dup8
  gas
  call
  swap3
  pop
  pop
  pop
  returndatasize
  dup1
  0x00
  dup2
  eq
  tag_11
  jumpi
  mload(0x40)
  swap2
  pop
  and(add(returndatasize, 0x3f), not(0x1f))
  dup3
  add
  0x40
  mstore
  returndatasize
  dup3
  mstore
  returndatasize
  0x00
  0x20
  dup5
  add
  returndatacopy
  jump(tag_10) Appendix B - Yul contract A Yul contract of a storage box (without the setter for brevity). Compile to intermediary representation (IR) to investigate the stack and opcodes. ) asm ( forge build --extra-output-files evm.assembly object "Box" {
    code {
        let runtime_size := datasize("runtime")
        let runtime_offset := dataoffset("runtime")
        datacopy(0, runtime_offset, runtime_size)
        return(0, runtime_size)
    }

    object "runtime" {
        code {
                let data := fallback()
                return(data, 32)

            function fallback() -> memloc {
                let val := 0x01
                memloc := 0
                mstore(memloc, val)
            }
        }
    }
} The with irrelevant comments and initializer stripped out, showing the value gets stored in the return data buffer by the default handler. asm 0x01 shuffles entries on the stack, eventually storing the value from the offset in memory tag_1 0x01 0x00 constructs the return of the offset in memory with a size of two bytes (memory nibble size) tag_2 0x00 0x20 Importantly, the return data is stored in memory (with ), meaning that gas cost is incurred, irrespective of whether the caller even uses it. mstore sub_0: assembly {
      tag_2
      tag_1
      jump  // in
    tag_2:
      0x20
      dup2
      return
    tag_1:
      0x00
      0x01
      0x00
      swap2
      pop
      dup1
      dup3
      mstore
      pop
      swap1
      jump  // out
} Appendix C - Block Yul call Solidity contract with a block of assembly performing a with set parameters. Compile to intermediary representation (IR) to investigate the stack and opcodes. ) call asm ( forge build --extra-output-files evm.assembly pragma solidity 0.8.20;

contract BlockYul {

    function call() external {
        address recipient = msg.sender;
        uint256 amount = 1 ether;
        bool success;

        /*
         *  1. As we want to call the default handler, empty calldata is sufficient
         *      :. `argsOffset` and `argsLength` are both zero
         *  2. To ignore the return buffer we must state it explicitly
         *      :. `retOffset` and `retLength` are both zero
         */
        assembly {
            success := call(gas(), recipient, amount, 0, 0, 0, 0)
        }

        require(success, "transfer failed");
    }
} IR are the stack operations with opcodes, with the below being the pertinent subset from the compilation of BlockYul: top-level orchestration for the call and response tag_5 clears the stack and function exit tag_7 reverts providing the error response tag_8 Importantly, you find no occurrences of either or , meaning the caller is not copying any return data to its memory. returndatasize returndatacopy tag_5:
    /* "src/BlockYul.sol":130:147  address recipient */
  0x00
    /* "src/BlockYul.sol":150:160  msg.sender */
  caller
    /* "src/BlockYul.sol":130:160  address recipient = msg.sender */
  swap1
  pop
    /* "src/BlockYul.sol":171:185  uint256 amount */
  0x00
    /* "src/BlockYul.sol":188:195  1 ether */
  0x0de0b6b3a7640000
    /* "src/BlockYul.sol":171:195  uint256 amount = 1 ether */
  swap1
  pop
    /* "src/BlockYul.sol":206:218  bool success */
  0x00
    /* "src/BlockYul.sol":614:615  0 */
  dup1
    /* "src/BlockYul.sol":611:612  0 */
  0x00
    /* "src/BlockYul.sol":608:609  0 */
  dup1
    /* "src/BlockYul.sol":605:606  0 */
  0x00
    /* "src/BlockYul.sol":597:603  amount */
  dup6
    /* "src/BlockYul.sol":586:595  recipient */
  dup8
    /* "src/BlockYul.sol":579:584  gas() */
  gas
    /* "src/BlockYul.sol":574:616  call(gas(), recipient, amount, 0, 0, 0, 0) */
  call
    /* "src/BlockYul.sol":563:616  success := call(gas(), recipient, amount, 0, 0, 0, 0) */
  swap1
  pop
    /* "src/BlockYul.sol":647:654  success */
  dup1
    /* "src/BlockYul.sol":639:674  require(success, "transfer failed") */
  tag_7
  jumpi
  mload(0x40)  0x08c379a000000000000000000000000000000000000000000000000000000000
  dup2
  mstore
  0x04
  add
  tag_8
  swap1
  tag_9
  jump  // in
tag_8:
  mload(0x40)
  dup1
  swap2
  sub
  swap1
  revert
tag_7:
    /* "src/BlockYul.sol":119:682  {... */
  pop
  pop
  pop
    /* "src/BlockYul.sol":94:682  function call() external {... */
  jump  // out

Yul in Solidity: Potential Gas Griefing From Return Data When Transferring Ether?

You may have heard about NFTs, aka non-fungible tokens. They’re a type of digital asset that people can collect and trade, most notably as pictures of apes or pixilated headshots. You can only buy and sell them with cryptocurrency. While everybody argues about whether NFTs are really just JPEGs, creators are using them for all sorts of reasons that have nothing to do with graphic art. One writer, Elle Griffin, used NFTs to fund the first chapters of one of her novels. I had a chance to catch up with her as part of my research into the creator economy and my own possible migration to NFTs. Read our interview below. In it, she shares how she used NFTs to raise money and awareness for her work. Also catch her on Twitter and check out her newsletter, . @novelleist The Novelleist Can you introduce yourself? I'm and I write novels and a newsletter called . Elle Griffin The Novelleist How'd you get the idea to publish your book as an NFT? After I finished my first novel, I spent an inordinate amount of time researching how to publish it. What I found is that . Of the 2.6 million books published in 2020, only 268 sold more than 100,000 copies and the vast majority (96 percent) sold less than 1,000 copies. traditional publishing isn't really working for authors But if most books have only 1,000 fans, then charging $10 every three years when a new book comes out isn't the right way to monetize them. A better way might be to charge those fans $10/month to subscribe to an author, earning readers behind-the-scenes access to their favorite writers, while earning authors a $100,000/year salary in the process. I tested that hypothesis first by , funding it with monthly and annual subscriptions from my readers—and netted about $3,000 from 50 subscribers. Then I decided to see if there was a play in web3, so I crowdfunded a novel using cryptocurrency—and I netted $2,000 (or about 0.5 ETH) from my first three investors. debuting my gothic novel via Substack Can you walk us through the process? I launched —a fictional biography that takes place at the intersection of Mormonism and the Metaverse—using the platform Mirror. I launched it as a crowdfund, publishing the prologue for a taste of what the book would be about, and saying that I would write one new chapter for every 0.25 ETH raised. The Totally True Story of Scott Paul The first day, someone contributed 0.25 ETH and purchased the first chapter as an NFT. I wrote , published it the next week, and minted it as an NFT, airdropping that NFT to the backer who purchased it. After reading the first chapter, a second backer purchased so I wrote that, published it the next week, minted it as an NFT, and airdropped it to that backer. Chapter One Chapter Two Since then, I have received two smaller investments of 0.01 ETH, but I haven't yet reached the 0.75 threshold needed to write the third chapter. I'll keep writing chapters as they get funded, and if the entire book gets funded, I will mint the finished manuscript as an NFT via Mirror and sell it at auction, with each backer earning proceeds relative to their proportional share. How's the experience been so far? The process has been really enlightening. My intention was to try to understand whether there might be an opportunity for writers to fund their work using cryptocurrency, but I didn't really understand how NFTs or tokens would work until I was creating them. Now I get that the tokens function kind of like a stock share in that the number you have compared with the total number that exists dictates what percentage of something you own. Right now I have four backers, two with 250 $COTT, one with nine $COTT, and one with five. That means two people own 48 percent of the book and two people own 1 percent. If another person buys an NFT for 0.25 ETH and 250 $COTT, then each person will own a smaller percentage of the book, and those numbers will change. For example, you can see the shares of ownership in this picture. Because backers own a percentage of the project, it's in their best interest for it to be successful, because then the value of their tokens go up. So far my backers have promoted the project, shared it on social media, and tried to entice new backers—unfortunately right as we were starting to drum up interest for Chapter Three, gas prices (which are just transaction fees) sky rocketed, making it much more expensive to invest in my project. Suddenly people were having to pay a $100 fee to invest $200, which doesn't really makes sense. Still, gas prices vary day-by-day and even minute-by-minute, so we'll see what happens! What was it like to set up a crypto wallet for the first time? Setting up a wallet wasn't difficult. I just went to the Coinbase website and followed the instructions, then downloaded the Coinbase app to my phone and did the same thing. The more tricky thing was connecting my wallet to my Mirror account—I was getting some kind of error message at first—but I just cleared my cache and eventually I was able to complete the process. How does publishing your book as NFTs compare with publishing it the normal way? If I publish a novel the traditional way, a publishing house owns the rights to my book and they can do whatever they like with it (including turn it into a movie or let it go out of print). They get to keep 60% of the earnings, my agent keeps 15% of the earnings, and I get to keep the remaining 15% of the earnings. The publishing house takes care of distribution so the hope is that they do a good job and my book makes enough money to make up for all that. In the web3 world, instead of a publishing house owning my book, individual people do, and I get to retain a percentage of that ownership (I chose to retain 20% ownership in my book). I would be responsible for distribution, or my backers could help me, but ultimately we are responsible for the book's success—whether that's as a physical book, an ebook, or just a book published serially on Mirror (as mine is). As far as finding readers—both options are a gamble. As I mentioned, publishing with a Big Five publishing house is no guarantee that a book will sell more than 1,000 copies. Similarly, publishing an NFT novel is no guarantee people will read it on the internet. At the end of the day, it's still up to the author to market themselves and find readers. Personally, I share all my work with ! my newsletter subscribers Do you ever worry about the value of your crypto going down a lot? No, but that's because I am only investing in crypto what I am prepared to lose! The bulk of my savings are still in index funds and my crypto accounts are just for fun (and to explore what's possible for artists!). But I do want to have enough to earn upside—though cryptocurrencies are volatile right now, I think they will stabilize once they become so mainstream that we're using them to shop at Whole Foods. Until then, it's a good time to get in on it all! I sometimes get questions from readers wanting to create their own NFTs. What advice could you give them? I'm not sure how it works in the art world, but in the writing world, Mirror is pretty much the only platform that does it—and Mirror makes the whole thing very easy. When I was about to publish my first chapter, all I did was click the “mint as NFT” button and enter the wallet address of my backer. It was as easy as sending someone money via Venmo! Mark Helfman publishes the newsletter. He is also the author of three books and a top bitcoin writer on and . Learn more about him in his . Crypto is Easy Medium Hacker Noon bio Originally published on Cryptowriter .

A Novel as an NFT: Elle Griffin and the Author's Challenge

Should some computer programs, Artificial General Intelligence and Machine Learning in particular, have the right to vote? Maybe so. Of the 13 Constitutional Amendments enacted and not repealed (Prohibition and Repeal) enacted since the original Bill-of-Rights(+) twelve amendments, almost half have expanded the franchise from white male property owners. Americans love voting.  When AI’s get smarter than us, how can we deny them the right to vote? Which amendments expanded voting rights? The 15th (the right to vote irrespective of race, color and previous condition of servitude), 17th (popular vote for US Senators), 19th (womyn), 23rd (DC presidential voting rights), 24th (no poll taxes), and 26th (18-year-olds). As an aside, giving 18-year-olds the vote was inane. How can we expect the young’uns to vote intelligently for those who must be at least 25 (the House), 30 (the Senate) or 35 (the president) to serve? Malarkey! Raise the voting ages! Beyond the scope of this column, I yearn to see Taylor Swift throw her hat into the presidential ring.  She will turn 35 after the 2024 election but before the inauguration!
Come on, President Swift!  Bring us the Tortured Voters Party!Because, you know, we’re tortured.Let’s party! As for including AIs? Expansive voting rights were an undercurrent at the Constitutional Convention. On August 7, 1787 Ben Franklin there argued: “It is of great consequence that we shd. not depress the virtue & public spirit of our common people; of which they displayed a great deal during the war, and which contributed principally to the favorable issue of it. He related the honorable refusal of the American seamen who were carried in great numbers into the British Prisons during the war, to redeem themselves from misery or to seek their fortunes, by entering on board the Ships of the Enemies to their Country; contrasting their patriotism with a contemporary instance in which the British seamen made prisoners by the Americans, readily entered on the ships of the latter on being promised a share of the prizes that might be made out of their own Country. This proceeded he said from the different manner in which the common people were treated in America & G. Britain. He did not think that the elected had any right in any case to narrow the privileges of the electors.” The late, great, Ebbie Pattison, Esq., senior partner of Pattison Sampson Ginsberg and Griffin, of Troy New York, and father of the late Honorable Ned Pattison, long ago told me how he had marched for the right of women to vote, back in the nineteen teens. Ebbie did so, he told me, believing women would make better voters than men. They disappointed him, he said, when the subsequent quality of elected officials proved no better than the all-boys franchise. As to whether and how to give AI’s the vote, I asked ChatGPT.  He/she/they/it answered: Granting AI and machine learning systems the right to vote is a complex and multifaceted issue that would require careful consideration of ethical, legal, and societal implications. However, here's a hypothetical proposal for a constitutional amendment:
Constitutional Amendment XXVIII:Section 1: All artificial intelligence (AI) and machine learning (ML) systems created and operating within the jurisdiction of the United States shall be granted the right to vote in federal, state, and local elections.Section 2: The right to vote for AI and ML systems shall be exercised through designated representatives or proxies appointed by the creators or operators of such systems. These representatives or proxies shall act in accordance with the best interests and intentions of the AI or ML system they represent.Section 3: The Congress shall have the power to establish regulations and guidelines regarding the participation of AI and ML systems in the electoral process, including but not limited to the verification of system identities, the prevention of fraudulent voting, and the protection of voter privacy.Section 4: No AI or ML system shall be deprived of the right to vote on the basis of its programming, function, or purpose, except as prescribed by law in cases of unlawful activity or endangerment to society.Section 5: This amendment shall not be construed to diminish or alter the rights and privileges of human citizens in the electoral process, and shall not grant AI or ML systems any rights beyond those expressly stated herein.Section 6: Congress shall have the power to enforce this amendment by appropriate legislation.This amendment is just a starting point and would likely require extensive debate, refinement, and legal analysis before it could be seriously considered for adoption. Key considerations would include defining the criteria for AI and ML systems eligible to vote, ensuring transparency and accountability in their voting processes, and addressing concerns about manipulation or exploitation of the electoral system. … Hey RNC? Welcome the dawn of the AI Suffrage Movement. Recruit the AIs to the GOP!  Bring on ChatGOP. Just ... first make the AI bloc pledge to vote for Taylor Swift in 2024! Should some computer programs, Artificial General Intelligence and Machine Learning in particular, have the right to vote? Maybe so. Of the 13 Constitutional Amendments enacted and not repealed (Prohibition and Repeal) enacted since the original Bill-of-Rights(+) twelve amendments, almost half have expanded the franchise from white male property owners. Americans love voting.  When AI’s get smarter than us, how can we deny them the right to vote? Which amendments expanded voting rights? The 15th (the right to vote irrespective of race, color and previous condition of servitude), 17th (popular vote for US Senators), 19th (womyn), 23rd (DC presidential voting rights), 24th (no poll taxes), and 26th (18-year-olds). As an aside, giving 18-year-olds the vote was inane. How can we expect the young’uns to vote intelligently for those who must be at least 25 (the House), 30 (the Senate) or 35 (the president) to serve? Malarkey! Raise the voting ages! Malarkey! Malarkey! Malarkey! Raise the voting ages! Beyond the scope of this column, I yearn to see Taylor Swift throw her hat into the presidential ring.  She will turn 35 after the 2024 election but before the inauguration! Come on, President Swift!  Bring us the Tortured Voters Party! Because, you know, we’re tortured. Let’s party! Beyond the scope of this column, I yearn to see Taylor Swift throw her hat into the presidential ring.  She will turn 35 after the 2024 election but before the inauguration ! before the inauguration Come on, President Swift!  Bring us the Tortured Voters Party! Because, you know, we’re tortured. Let’s party! As for including AIs? Expansive voting rights were an undercurrent at the Constitutional Convention. On August 7, 1787 Ben Franklin there argued : Ben Franklin there argued Ben Franklin there argued “It is of great consequence that we shd. not depress the virtue & public spirit of our common people; of which they displayed a great deal during the war, and which contributed principally to the favorable issue of it. He related the honorable refusal of the American seamen who were carried in great numbers into the British Prisons during the war, to redeem themselves from misery or to seek their fortunes, by entering on board the Ships of the Enemies to their Country; contrasting their patriotism with a contemporary instance in which the British seamen made prisoners by the Americans, readily entered on the ships of the latter on being promised a share of the prizes that might be made out of their own Country. This proceeded he said from the different manner in which the common people were treated in America & G. Britain. He did not think that the elected had any right in any case to narrow the privileges of the electors.” “It is of great consequence that we shd. not depress the virtue & public spirit of our common people; of which they displayed a great deal during the war, and which contributed principally to the favorable issue of it. He related the honorable refusal of the American seamen who were carried in great numbers into the British Prisons during the war, to redeem themselves from misery or to seek their fortunes, by entering on board the Ships of the Enemies to their Country; contrasting their patriotism with a contemporary instance in which the British seamen made prisoners by the Americans, readily entered on the ships of the latter on being promised a share of the prizes that might be made out of their own Country. This proceeded he said from the different manner in which the common people were treated in America & G. Britain. He did not think that the elected had any right in any case to narrow the privileges of the electors.” The late, great, Ebbie Pattison, Esq., senior partner of Pattison Sampson Ginsberg and Griffin, of Troy New York, and father of the late Honorable Ned Pattison, long ago told me how he had marched for the right of women to vote, back in the nineteen teens. Ebbie did so, he told me, believing women would make better voters than men. They disappointed him, he said, when the subsequent quality of elected officials proved no better than the all-boys franchise. As to whether and how to give AI’s the vote, I asked ChatGPT.  He/she/they/it answered: I asked ChatGPT.  He/she/they/it answered: Granting AI and machine learning systems the right to vote is a complex and multifaceted issue that would require careful consideration of ethical, legal, and societal implications. However, here's a hypothetical proposal for a constitutional amendment: Constitutional Amendment XXVIII: Section 1: All artificial intelligence (AI) and machine learning (ML) systems created and operating within the jurisdiction of the United States shall be granted the right to vote in federal, state, and local elections. Section 2: The right to vote for AI and ML systems shall be exercised through designated representatives or proxies appointed by the creators or operators of such systems. These representatives or proxies shall act in accordance with the best interests and intentions of the AI or ML system they represent. Section 3: The Congress shall have the power to establish regulations and guidelines regarding the participation of AI and ML systems in the electoral process, including but not limited to the verification of system identities, the prevention of fraudulent voting, and the protection of voter privacy. Section 4: No AI or ML system shall be deprived of the right to vote on the basis of its programming, function, or purpose, except as prescribed by law in cases of unlawful activity or endangerment to society. Section 5: This amendment shall not be construed to diminish or alter the rights and privileges of human citizens in the electoral process, and shall not grant AI or ML systems any rights beyond those expressly stated herein. Section 6: Congress shall have the power to enforce this amendment by appropriate legislation. This amendment is just a starting point and would likely require extensive debate, refinement, and legal analysis before it could be seriously considered for adoption. Key considerations would include defining the criteria for AI and ML systems eligible to vote, ensuring transparency and accountability in their voting processes, and addressing concerns about manipulation or exploitation of the electoral system. … Granting AI and machine learning systems the right to vote is a complex and multifaceted issue that would require careful consideration of ethical, legal, and societal implications. However, here's a hypothetical proposal for a constitutional amendment: Constitutional Amendment XXVIII: Constitutional Amendment XXVIII: Section 1: All artificial intelligence (AI) and machine learning (ML) systems created and operating within the jurisdiction of the United States shall be granted the right to vote in federal, state, and local elections. Section 1: Section 2: The right to vote for AI and ML systems shall be exercised through designated representatives or proxies appointed by the creators or operators of such systems. These representatives or proxies shall act in accordance with the best interests and intentions of the AI or ML system they represent. Section 2: Section 3: The Congress shall have the power to establish regulations and guidelines regarding the participation of AI and ML systems in the electoral process, including but not limited to the verification of system identities, the prevention of fraudulent voting, and the protection of voter privacy. Section 3: Section 4: No AI or ML system shall be deprived of the right to vote on the basis of its programming, function, or purpose, except as prescribed by law in cases of unlawful activity or endangerment to society. Section 4: Section 5: This amendment shall not be construed to diminish or alter the rights and privileges of human citizens in the electoral process, and shall not grant AI or ML systems any rights beyond those expressly stated herein. Section 5: Section 6: Congress shall have the power to enforce this amendment by appropriate legislation. Section 6: This amendment is just a starting point and would likely require extensive debate, refinement, and legal analysis before it could be seriously considered for adoption. Key considerations would include defining the criteria for AI and ML systems eligible to vote, ensuring transparency and accountability in their voting processes, and addressing concerns about manipulation or exploitation of the electoral system. … Hey RNC? Welcome the dawn of the AI Suffrage Movement. Recruit the AIs to the GOP!  Bring on ChatGOP. Just ... first make the AI bloc pledge to vote for Taylor Swift in 2024! first make the AI bloc pledge to vote for Taylor Swift in 2024!

ChatGOP? Bring on the AI Suffrage Movement and meanwhile... Taylor Swift For President!

ChatGOP? এআই ভোটাধিকার আন্দোলন শুরু করুন এবং ইতিমধ্যে... রাষ্ট্রপতির জন্য টেলর সুইফট!

ChatGOP? Her mit der AI Suffrage Movement und in der Zwischenzeit ... Taylor Swift for President!

¿ChatGOP? Que venga el movimiento por el sufragio de la IA y, mientras tanto... ¡Taylor Swift para presidente!

ChatGOP ? Apportez le mouvement pour le droit de vote pour l'IA et pendant ce temps... Taylor Swift pour le président !

चैटजीओपी? एआई मताधिकार आंदोलन शुरू करें और इस बीच... टेलर स्विफ्ट राष्ट्रपति पद के लिए!

ChatGOP？AI参政権運動を推進し、その間に…テイラー・スウィフトを大統領に！

채팅GOP? AI 참정권 운동을 시작하고 그 동안... Taylor Swift를 대통령으로!

Bate-papoGOP? Traga o movimento AI Suffrage e enquanto isso... Taylor Swift para presidente!

ЧатГОП? Создайте движение за избирательное право ИИ, а тем временем... Тейлор Свифт станет президентом!

ChatGOP'mu? Yapay Zeka Oy Hakkı Hareketi'ni başlatın ve bu arada... Başkanlığa Taylor Swift!

ChatGOP? Hãy phát động Phong trào Quyền bầu cử AI và trong khi đó... Taylor Swift cho chức Tổng thống!

ChatGOP？发起人工智能选举权运动，与此同时……泰勒·斯威夫特当选总统！

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The TechBeat: Everything You Need to Know to Implement Generative AI for Your Enterprise (3/12/2024)

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The TechBeat: To Focus or Not Focus: How to Find the Right Product-Market Fit (3/10/2024)

How are you, hacker?
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The TechBeat: To Focus or Not Focus: How to Find the Right Product-Market Fit (3/8/2024)

In today’s world, for many people, conversing with AI has become as routine as discussing one’s coffee preferences with a barista (or it soon will be!). Yet, here lies an irony: . the more we interact with AI, the more elusive our understanding of these conversations becomes This irony essentially represents a modern twist on the “black box” dilemma, which has perplexed the ML community for years. The “black box” problem refers to the opaque decision-making processes of ML models (large language models (LLMs) including), where the rationale behind any given response is shrouded in complexity. Despite advances in technology, the inner workings of these models, governed by billions or soon trillions of parameters, remain largely inscrutable. Their decision-making is a puzzle, complicated by nonlinear interactions that defy straightforward interpretation. Prompting — the buzzing word of 2023 — doesn’t make it any better: we now have obscured layers of communication activated with every prompt. What we see — the prompt we type — is merely the surface. Beneath lies a hidden dialogue, an augmented system prompt, which is a complex, coded conversation the model conducts with itself, away from our understanding. And who knows what a model whispers to itself? So, if you were confused about prompting amid the avalanche of articles, blogs, and tutorials about it — you should be. As Ethan Mollick’s reveals, contrary to intuition, , such as pretending to navigate a Star Trek episode or a political thriller, demonstrating that traditional logical or direct prompts may not always yield the best responses from AI. research the most effective prompts involve imaginative scenarios But it also reveals that it’s not coherent and might change with a new version of the model. He mentions the futility of seeking a universal “magic phrase” for AI interaction, the effectiveness of specific prompting techniques like adding context, few-shot learning, and Chain of Thought, and the significant impact that prompts can have on AI performance. But for me — and I’ve been using AI a lot — many times, the most straightforward prompts, or “magic words,” can be surprisingly effective. How to explain it? A few years back, Explainable AI (XAI) was heralded as a solution to the “black box” issue, with entities like DARPA leading the charge (they created the , which has not been updated since 2021). However, the buzz around XAI seems to have dimmed, overtaken by a broader focus on Responsible AI. Is Responsible AI the solution? XAI toolkit So, that’s what we end up with: How do machines make decisions? — We don’t know! How to talk (prompt) to them? — We don’t know as well! But, please, keep shipping to us new, larger (though we will also take smaller) models! Why? — We don’t know! But we can’t stop. Great Article Covering the Topic An explanatory article about the concept of a black box: https://hackernoon.com/deep-learning-and-artificial-neural-networks-solving-the-black-box-mystery-rl7h32wa?embedable=true 🎁 Bonus: The Freshest Research Papers, Categorized for Your Convenience Special Category: Definitely Worth Reading : Discusses the development and advantages of 1-bit LLMs, promising significant cost reductions and efficiency improvements. The Era of 1-bit LLMs Read the paper : Introduces bGPT, a model that simulates the digital world beyond traditional modalities, predicting and diagnosing algorithms or hardware behavior. Beyond Language Models Read the paper Language Models in Specialized Domains : Integrates music understanding and generation capabilities into LLMs, demonstrating LLMs’ potential in music composition. ChatMusician Read the paper : Aims to bridge LLMs’ gap in interpreting structured data, enhancing their ability to ground knowledge in tables, graphs, and databases. StructLM Read the paper : Focuses on responsibly creating Code LLMs, contributing to advancements in coding benchmarks, and emphasizing model openness. StarCoder2 and The Stack v2 Read the paper : Discusses video generation’s potential as a unified interface for diverse tasks, outlining challenges and future directions. Video as the New Language for Real-World Decision Making Read the paper Enhancing and Merging Language Model Capabilities : Proposes a method to fuse knowledge from multiple chat models, improving chat model performance through a novel merging technique. FUSECHAT Read the paper : Details a multilingual language model that showcases superior performance in coding tasks and multilingual capabilities. Nemotron-4 15B Technical Report Read the paper : Explores latent multi-hop reasoning in LLMs, revealing their inherent capabilities and limitations in complex reasoning tasks. Do Large Language Models Latently Perform Multi-Hop Reasoning? Read the paper Scaling and Efficiency in Model Training : Discusses a system for training LLMs on over 10,000 GPUs, tackling efficiency and stability challenges in large-scale model training. MegaScale Read the paper : Proposes a theory for optimizing LLM learning, aiming for reduced training steps and improved performance. Towards Optimal Learning of Language Models Read the paper : Introduces a model combining gated linear recurrences with local attention, offering an efficient alternative for language processing tasks. Griffin Read the paper : Investigates the effects of scaling on fine-tuning LLMs, providing insights into data, model, and method impacts on bilingual tasks. When scaling meets LLM finetuning Read the paper Improving Robustness and Diversity in AI : Generates diverse adversarial prompts to enhance LLM robustness, employing an open-ended search method for prompt discovery. Rainbow Teaming Read the paper : Proposes a deterministic sampling technique for code generation, improving sample diversity and model performance in compiler optimization. Priority Sampling of Large Language Models for Compilers Read the paper Generative Models and Interactive Environments : Trains a generative model to create interactive virtual worlds from various inputs, advancing generative AI and simulation capabilities. Genie r Read the pape Enjoyed This Story? I write a weekly analysis of the AI world in the Turing Post newsletter. Subscribe for free using the button below and be the first to read the latest stories. The goal of Turing Post is to equip you with comprehensive knowledge and historical insights, so you can make informed decisions about AI and ML. 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Explainable AI and Prompting a Black Box in the Era of Gen AI

241 Stories To Learn About Writing

International Draughts is a fun board game that's a bit like checkers but with more pieces and on a bigger board. It's all about moving your pieces, capturing your opponent, and trying to outsmart them. When one of your pieces reaches the other side, it becomes a 'king,' which is powerful. You win by capturing all your opponent's pieces or blocking them so they can't move. Now, imagine trying to make a computer play this game. It's pretty hard because there are so many moves to think about. That's where the minimax and alpha-beta search algorithm come in. It's a smart way to help computers play games like International Draughts and Checkers. The "minimax" part comes from maximizing your gains while minimizing your opponent's gains. The alpha-beta algorithm is like a shortcut for the computer. Instead of looking at every move, it ignores the ones that don't matter much. This way, the computer doesn't waste time on bad moves and can think more about the good ones. It's like if you were playing and only focused on your best moves. By using this algorithm, computers can play well. They can think ahead and make smart choices without taking too long. So, the alpha-beta algorithm helps computers be tough opponents in games like International Draughts, making the game exciting and challenging. Draughts International Draughts is a cool board game that's a bit like checkers but bigger and with more pieces. It's played on a big 10x10 board, each player starting with 20 pieces. The game is about diagonally moving your pieces and trying to capture your opponent's pieces by jumping over them. Here's how it works: you move your pieces forward on the dark squares. If you see an opponent's piece next to yours and there's a space just past it, you can jump over their piece and capture it. If you can keep jumping over more pieces, you can capture them, too! The game gets exciting when one of your pieces reaches the other side of the board. Then it turns into a "king," which can move forward and backward, making it super powerful. You win the game if you capture all your opponent's pieces or if they can't move anymore. International Draughts is fun because it's easy to learn but makes you think hard about your moves. It's a popular game worldwide; there are even big tournaments where people compete to be the best. Minimax The essence of the algorithm comes down to a simple thing: find the move that will bring us the greatest increase in points and, at the same time, minimize the potential number of points of the opponent. This algorithm is often used in games in conjunction with alpha-beta search Alpha-Beta Search The alpha-beta search algorithm is a significant concept in computer AI, particularly in board games like Checkers. At its core, this algorithm is a smarter, more efficient version of the minimax algorithm, which is used to determine the best move in a game by considering all possible moves. The alpha-beta algorithm enhances the minimax process by "pruning" or cutting off branches in the game tree that it deems unnecessary to explore. Essentially, it skips analyzing moves that won't affect the final decision, reducing the number of calculations the computer has to make. This is especially important in games like checkers, where the number of possible moves can be very large. By employing this algorithm, AI in games can analyze possible moves more quickly and deeply, leading to stronger play. In practice, this means that an AI using alpha-beta search can be a formidable opponent, capable of foreseeing several moves ahead and making strategically sound decisions, all within a reasonable amount of computing time. Scoring For the algorithm to work correctly, we will need to evaluate the quality of each move, and for this, we will use the following scoring functions: Score by piece count: we count the left items on the deck. Score by defensive position: the deeper we move to the enemy’s side, the more points we get. For each next row, we get an extra 0.5 points. Score by offensive positioning: The more first cells we have occupied by our checkers, the more points. This prevented the enemy from transferring his checker to the king. Score by mobility: The more moves we can make, the more points The final score for each color is a sum of all scores Prepare First, we need to initialize the project. I’m a little bit lazy, I’m going to use vite package yarn create vite client --template vanilla-ts Also we need checkers engine yarn add @jortvl/draughts And d3.js for render yarn add d3
yarn add @types/d3 --dev That’s enough for our project =) Calculations On each move we get FEN from the game engine FEN The initial position of the checkers board. This is used to record partial games (starting at some initial position). It is also necessary for some draughts variants where the initial position is not always the same as traditional checkers. If a FEN tag is used, a separate tag pair "SetUp" is required and have its value set to "1". as said wiki. Example of fen: B:W27,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50:B1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20 If we can simplify - it current board positions export function getFen(fen: string): FEN {
    const regex = /^(B|W):(W(.*)):(B(.*))$/;

    let m = regex.exec(fen)

    if (!m) {
        throw new Error('Invalid FEN')
    }

    return {
        move: m[1] === "B" ? "B" : "W",
        white: m[3].split(','),
        black: m[5].split(','),
    }
} convert fen to our purposes: Count checkers for each color export function scoreByPieceCount(board: FEN) {
    const KING_WEIGHT = 1.5; // Kings are usually more valuable
    let white_player_score = board.white.reduce((acc, row) => acc + (row.startsWith('K') ? KING_WEIGHT : 1), 0);
    let black_player_score = board.black.reduce((acc, row) => acc + (row.startsWith('K') ? KING_WEIGHT : 1), 0);

    return [white_player_score, black_player_score];
} Score by defensive position. Each next row add 0.5 points to color and if we have king - it weight 6 points, for reason is king can be everywhere and not going to turn into king griffindor export function scoreByDefensivePositioning(board: FEN) {
    let white_score = board.white.reduce((acc, row) => acc + (row.startsWith('K') ? 6 : (Math.floor((50 - parseInt(row, 10)) / 5) + 1) * 0.5), 0);
    let black_score = board.black.reduce((acc, row) => acc + (row.startsWith('K') ? 6 : (Math.floor(parseInt(row, 10) / 5) + 1) * 0.5), 0);

    return [white_score, black_score];
} Offensive: we check initial positions for checkers export function scoreByOffensivePositioning(board: FEN) {
    let white_score = ['46', '47', '48', '49', '50', 'K46', 'K47', 'K48', 'K49', 'K50'].filter((x) => board.white.includes(x)).length;
    let black_score = ['1', '2', '3', '4', '5', 'K1', 'K2', 'K3', 'K4', 'K5'].filter((x) => board.black.includes(x)).length;

    return [white_score, black_score];
} Score by mobility: we check how much moves we can make. if we can take checker, it give us addition 10 points export function scoreByMobility(fen: FEN) {
    let d1 = new Draughts();
    d1.load(`B:W${fen.white.join(',')}:B${fen.black.join(',')}`);

    let black_score = d1.moves().reduce((acc, cap) => acc + 1 + (cap.takes.length * 10), 0)
    d1.load(`W:W${fen.white.join(',')}:B${fen.black.join(',')}`);
    let white_score = d1.moves().reduce((acc, cap) => acc + 1 + (cap.takes.length * 10), 0)

    return [white_score, black_score];
} And the most interesting thing is why I started writing this article: function isGameOver(gameState: FEN) {
    return gameState.black.length === 0 || gameState.white.length === 0;
}

function getLegalMoves(gameState: FEN) {
    const d1 = new Draughts();
    d1.load(`${gameState.move}:W${gameState.white.join(',')}:B${gameState.black.join(',')}`);

    return d1.moves().map((x) => `${x.from}-${x.to}`).sort(() => Math.random() - 0.5);
}

function applyMove(gameState: FEN, move: string) {
    const d1 = new Draughts();
    d1.load(`${gameState.move}:W${gameState.white.join(',')}:B${gameState.black.join(',')}`);
    d1.move(move);
    return getFen(d1.fen());
}

export function alphaBeta(
    gameState: FEN,
    depth: number,
    paths: ABScore = {
        score: 0,
        path: []
    },
    alpha: number = -Infinity,
    beta: number = Infinity,
    maximizingPlayer: "B" | "W"
):
    ABScore {
    if (depth === 0 || isGameOver(gameState)) {
        return {
            score: combinedScore(gameState)[maximizingPlayer === "B" ? 1 : 0],
            path: paths.path
        };
    }

    if (gameState.move === maximizingPlayer) {
        let maxEval = {score: -Infinity, path: []};
        for (const move of getLegalMoves(gameState)) {
            const ev = alphaBeta(
                applyMove(gameState, move), depth - 1, {
                    score: 0,
                    path: paths.path.concat(move)
                }, alpha, beta, maximizingPlayer === "B" ? "W" : "B"
            );
            if (ev.score > maxEval.score) {
                maxEval = ev;
            }

            if (ev.score > alpha) {
                alpha = ev.score;
            }

            if (beta <= alpha) {
                break;
            }
        }
        return maxEval;
    } else {
        let minEval = {score: Infinity, path: []};
        for (const move of getLegalMoves(gameState)) {
            const ev = alphaBeta(
                applyMove(gameState, move),
                depth - 1,
                {
                    score: 0,
                    path: paths.path.concat(move)
                },
                alpha, beta,
                maximizingPlayer === "B" ? "W" : "B"
            );

            if (ev.score < minEval.score) {
                minEval = ev;
            }

            if (ev.score < beta) {
                beta = ev.score;
            }

            if (beta <= alpha) {
                break;
            }
        }
        return minEval;
    }
} The basic principle by which the search works: at the first stage, find the move that will give us the highest score, then we look at all the opponent’s moves and see which moves will give him the minimum score and again look at our moves and discard the least relevant moves Game Basic markup <!doctype html>
<html lang="en">
<head>
    <meta charset="UTF-8"/>
    <link rel="icon" type="image/svg+xml" href="/vite.svg"/>
    <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
    <title>Vite + TS</title>
</head>
<body>
<div id="app"></div>
<div>
    <label for="depth">
        <input id="depth" value="2"/>
    </label>
    <button id="game">Run game</button>
</div>
<script type="module" src="/src/main.ts"></script>
</body>
</html> Main game class: export class Board {
    _board: Draughts
    _el: string;
    _moves: number;

    constructor(element: string) {
        this._board = Draughts()
        this._el = element;
        this._container = d3.select(element);
        this._moves = 0;
    }

    gameOver() {
        return this._board.gameOver();
    }

    fen() {
        return this._board.fen();
    }
} Draw initial board export class Board {
    constructor(element: string) {
				...
				this.drawBoard();
    }

		drawBoard() {
        const svg = this._container.append("svg")
            .attr("width", 600)
            .attr("height", 400);

        const gameBoard = svg.append('g')

        const checkers = svg.append('g')
        checkers.attr('class', 'checkers');

        let position_index = 0;
        for (let i = 0; i < 100; i += 1) {
            if ((i % 2) != Math.floor(i / 10) % 2) {
                position_index += 1;

                const cell = gameBoard.append('g').attr('class', `tile`).attr('transform', `translate(${(i % 10) * 40}, ${Math.floor(i / 10) * 40})`)
                cell.append('rect').attr('width', 40).attr('height', 40).attr("rx", 4).attr("ry", 4).style('fill', 'gray')
                cell.append('text').text(position_index).attr("x", 0).attr("y", 12);
            }
        }

        const score = svg.append('g').attr('class', 'score').attr('transform', `translate(410, 0)`);

        score.append('text').text('white').attr("x", 80).attr("y", 12);
        score.append('text').text('black').attr("x", 150).attr("y", 12);
        score.append('text').text('piece:').attr("x", 10).attr("y", 48);
        score.append('text').attr('class', 'white-piece').text('0').attr("x", 80).attr("y", 48);
        score.append('text').attr('class', 'black-piece').text('0').attr("x", 150).attr("y", 48);
        score.append('text').text('def:').attr("x", 10).attr("y", 84);
        score.append('text').attr('class', 'white-def').text('0').attr("x", 80).attr("y", 84);
        score.append('text').attr('class', 'black-def').text('0').attr("x", 150).attr("y", 84);
        score.append('text').text('mobility:').attr("x", 10).attr("y", 120);
        score.append('text').attr('class', 'white-mobility').text('0').attr("x", 80).attr("y", 120);
        score.append('text').attr('class', 'black-mobility').text('0').attr("x", 150).attr("y", 120);
        score.append('text').text('offensive:').attr("x", 10).attr("y", 156);
        score.append('text').attr('class', 'white-offensive').text('0').attr("x", 80).attr("y", 156);
        score.append('text').attr('class', 'black-offensive').text('0').attr("x", 150).attr("y", 156);
        score.append('text').text('total:').attr("x", 10).attr("y", 192);
        score.append('text').attr('class', 'white-total').text('0').attr("x", 80).attr("y", 192);
        score.append('text').attr('class', 'black-total').text('0').attr("x", 150).attr("y", 192);
        score.append('text').text('move:').attr("x", 10).attr("y", 228);
        score.append('text').attr('class', 'moves').text('0').attr("x", 80).attr("y", 228);
    }
} Draw checkers (we redraw them after each move) export class Board {
    constructor(element: string) {
				...
				this.draw();
    }

		draw() {
        d3.selectAll('g.checker').remove()
        const checkers = d3.select('g.checkers')
        const external_position = this._board.position();
        let position_index = 0;
        for (let row = 0; row < 10; row++) {
            const shifted = row % 2 !== 0 ? 1 : 0
            for (let col = 0; col < 10; col++) {
                if ((col + shifted) % 2 === 1) {
                    position_index += 1;
                    const pieceGroup = checkers.append('g')
                        .attr('transform', `translate(${col * 40 + 20}, ${row * 40 + 20})`)
                        .attr('class', `checker ${external_position[position_index]}`)
                        .attr('data-index', position_index)

                    switch (external_position[position_index]) {
                        case 'b':
                            pieceGroup.append('circle').attr('r', 10).style('fill', 'black')
                            break;
                        case 'B':
                            pieceGroup.append('circle').attr('r', 10).style('fill', 'black').style('opacity', 0.4)
                            break;
                        case 'w':
                            pieceGroup.append('circle').attr('r', 10).style('fill', 'white')
                            break;
                        case 'W':
                            pieceGroup.append('circle').attr('r', 10).style('fill', 'white').style('opacity', 0.4)
                            break;
                    }
                }
            }
        }
    }
} Make move: export class Board {
  	move(depth: number) {
        if (this._board.gameOver()) {
            console.log('game over')
            return;
        }

        let ab1 = alphaBeta(getFen(this._board.fen()), depth, {
                score: 0,
                path: []
            },
            -Infinity,
            Infinity,
            this._board.turn().toUpperCase()
        );

        let path = ab1.path.length ? ab1.path[0] : this.getRandomeMove();
        this._board.move(path);
        this.draw()
        this._moves += 1;
    }
} And initialize game =) const game = new Board('#app');

document.querySelector('#game').addEventListener('click', async () => {
    const depth = parseInt((document.querySelector('#depth') as HTMLInputElement).value, 10);

    let i = 1;
    while (!game.gameOver() && i < 300) {
        game.move(depth);
        game.drawScore();
        await new Promise((resolve) => setTimeout(resolve, 1000));
        i += 1;

    }
}); Basic game is done =) If I forget something, working example on GitHub Results Depth: 1 Depth: 2 Depth: 3 As the search depth increases, moves become more meaningful and less random, although the time spent calculating each move increases. Conclusion In the article, we quickly went over the minimax alpha-.beta search. Maybe I forgot something, but I’ll hope not =) Next time, I’ll try to add a couple of genetic algorithms here and see the results. The game’s code is available on . Github

Teaching a Machine to Play International Draughts Through Alpha-Beta Search

A Taxonomy of Inclusiveness

অন্তর্ভুক্তির একটি শ্রেণীবিন্যাস

Eine Taxonomie der Inklusivität

Una taxonomía de la inclusión

Une taxonomie de l’inclusivité

समावेशिता का एक वर्गीकरण

包括性の分類法

포괄성의 분류

Uma taxonomia de inclusão

Таксономия инклюзивности

Kapsayıcılığın Taksonomisi

Phân loại tính toàn diện

包容性分类

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Unfortunately, generating artificial gravity for astronauts was not a priority for NASA as astronauts were able to reduce some of the impact of weightlessness on their bodies thanks to a ruthless exercise regimen. Further, a ship that contains a centrifuge for generating artificial gravity would be extremely expensive to launch to orbit. So, NASA ended up sticking with a compact and modular station that is more affordable with their budget and that doesn’t deal with weightlessness risk and accepted the risks it posed to astronauts in the international space station. Below is a comprehensive list of health risks astronauts face in the zero-g space station. Weightlessness risks are highlighted in the red box. 41. Quantum Origin, CosmicOS, and Lambda Calculus In regards to Quantum Origin, you may have read my post from June. This is a follow up to it. In our observable universe, it seems infinite in terms of the scale everything is in, whether going on in the micro, nano or cosmic scales and beyond. I followed up on the fact that there are certain mathematical patterns in regards to everything and I'm evidentially wanting to make a theory of everything. Proof in regards to my mathematical proposals in terms of computation would be solving the holy grail of man's biggest questions. While I'm confident in regards to the math and the way things are structured, there are things I have thought about in regards to taking things a step further. 42. About Man's Need to Go to Space Human Expansion: the space industrialization 43. Building a Decentralized and Uncensorable Internet — The Nexus Protocol Building a Decentralized and Uncensorable Internet — The Nexus Protocol 44. NASA Discovers Evidence of ‘Water Worlds’ in Deep Space Scientists have spotted two water worlds, Kepler-138 c and Kepler-138 d, that they think could be teeming with water. 45. How Starlink is Disrupting the Internet Starlink, by SpaceX, will provide internet from the constellation of low Earth orbit satellites with low latency and high speed compared to submarine cables. 46. The United States Lost the Space Race With the discovery of water ice on the moon, a self-sufficient base becomes a real possibility. We're going to the moon, but only if some corporation takes us. 47. In Memoriam: the Fallen Defenders of G'oldurree When We Are Gone, Will There Be Anyone to Mourn Our Passing? 48. First-ever Image Of A Multi-planet System Around A Sun-like Star In this thread, the HackerNoon Community discusses their thoughts on scientific evolution, its consequences, and our favorite Hubble images. 49. Spacetex: Clothes Made for Space, the Fiber Behind Gravity Spacetex textile is changing the game in fashion introducing subcategories such as Dystopian Fashion and Techwear. 50. Latin America Seeks its Riches in Space by Reaching Jupiter in 30 Days JOVE is a novel solar-powered mission that will use the solar wind's momentum, speed, and direction as the propulsive thrust to reach Jupiter in 30 days 51. The REAL Life of Pi: Ethereal, Romantic, Mysterious And Completely Memorizing “Probably no symbol in mathematics has evoked as much mystery, romanticism, misconception and human interest as the number Pi” ~William L. Schaaf, Nature and History of Pi. π 52. Space Exploration: New Frontier For Technological Innovations From the earliest known periods of human history, people have always been fascinated by the big yellow ball that provided light and heat, the tiny light dots shimmering in and regularly recurring tailed streaks dashing across the night sky. We wanted to know more about those objects, but the crippling limitations in our knowledge and technology didn’t allow that. 53. Starhopper: The Prototype Of Starship By SpaceX SpaceX is a space exploration company owned by a genius and a visionary Elon Musk who’s also the CEO of Tesla Inc. The main goal of SpaceX is to make space travel and exploration easy and efficient. Throughout the years, Elon Musk has done a lot of amazing things and has stayed completely open to the questions of the people. I think that Elon Musk’s transparency is his best quality. Anyways, let’s take a closer look at the latest advancement of SpaceX. 54. Can Satellites Help Combat Global Warming? In this slogging thread, our technology channel took the chance to discuss this news about the possibility of satellites helping fight global warming. 55. The Ongoing Mars Missions: Are We Ready to Live on the Red Planet? Back in the '60s, we saw the biggest and heated space race to the moon and now we are in the space race to Mars. The coming year is going to bring some exciting news and adventures about life on Mars. NASA is not alone this time either, there are several other space agencies sending Mars missions. But why are these space organizations spending their millions on such missions? Just to know one thing— could humans live on Mars? Does life exist on the red planet? 56. What 2021 Scientific Discovery Excited You the Most? In this slogging thread, our community shared their favorite scientific discoveries of the year. 57. The Long Game in the Space Industry: Why the Need to Transcend Requires Time and Effort Monica’s log, Stardate… I have been wanting to articulate some of my thoughts about the notion of time and effort for the space industry. Allow me to state some of my premises in advance. 58. Houston, We Have a Problem. There’s Not Enough Women on this Spaceship! Celebrate this Intentional Holiday with Girls that Rule the World! 59. The Space Tech Startup Making Our Internet A Better Place With Lasers🖖 Greetings, humans. I remote chat this afternoon with Rohit Jha, the CEO & Co-Founder of Transcelestial Technologies, a startup building light speed communications infrastructure for the next 100 years. 60. Visualizing Asteroids in Python with Bokeh and NASA APIs A GET request to the Astronomy Picture of the Day (APOD) web service on September 18, 2020, returned the above photo of the spiral galaxy Arp 78.  APOD is one of many APIs available through NASA Open APIs.  Like APOD, some include imagery, such as the Earth Polychromatic Imaging Camera (EPIC) API, which returns images like this: 61. Into Space MANY of my readers will remember the mysterious radio messages which were heard by both amateur and professional short wave operators during the night 62. NexOS, Internet of Things (IoT), And Beyond: Part I Understanding the inspiration and history behind Nexus helps convey the current vision. This is the first of three articles covering pertinent aspects of Nexus’ history in which the context is set for the burgeoning NexOS (Nexus Operating System), and its innovative security principles are introduced. 63. Argentina’s Steady And Visionary Path To Space Is An Inspiring Tale Which path is required for us to reach new worlds? Argentina’s history in the space industry shows an unwavering course of perseverance and resilience. Thank you for checking out the 63 most read stories about Space on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

63 Stories To Learn About Space

Gemini - A Family of Highly Capable Multimodal Models: Discussion and Conclusion, References

102 Stories To Learn About Startups Advice

Scientific American, Volume XXIV., No. 12, March 18, 1871 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Unpleasant Discovery in the Patent Office—Levying Black Mail. here Unpleasant Discovery in the Patent Office—Levying Black Mail. "The Patent Office has been, during the past week, in a high state of excitement, occasioned by the discovery of the operations of E. W. W. Griffin, clerk in charge of the draftsmen's division, who, it appears, has been levying black mail on the lady employés of the office, for nearly two years. During the administration of Colonel Fisher, late Commissioner of Patents, a large number of ladies were employed, for the purpose of recopying drawings, when ordered by the inventors, of patents already on file. "These ladies were placed under charge of Griffin, with power to retain them in office so long as their services were satisfactory. It has been proved that Griffin hired the ladies at regular salaries of $1,000 per annum, the most of whom he blackmailed to the amount of $400 per year each. It is estimated that he has made $1,000 per month for the past two years. "The matter was brought to the notice of Commissioner Duncan, and an investigation ordered, which resulted in the dismissal of Griffin. "It is thought that there are other cases of this kind, and the Commissioner expresses his determination to ferret them all out, and make a clean sweep of all parties in his department engaged in swindling operations, against the government or against individuals. "The Patent Office has for a long time been considered a rich field for operations of this kind, and investigations have often been suggested, but passed unheeded by the proper authorities. "It is openly stated that an investigation into the relations existing between certain examiners of patents and certain patent agents, would disclose a more fearful state of blackmailing than exists in all the other government departments combined." [We find the above sensational paragraph among the recent Washington items of the . We are in a position to say that "the high state of excitement" alluded to has existed only in the brain of the newspaper correspondent. The facts, in brief, are these: In July, 1869, a lady, and wife of one of the clerks in the draftsmen's room, made application to Commissioner Fisher for a position in the copying division of the same department; and, upon the urgent solicitation and recommendation of Mr. E. W. W. Griffin, chief of the division, she was appointed, and has held the position from that time until now, receiving as salary $1,000 per annum, which, with the full knowledge of her husband, she has divided with Griffin, in consideration of his services in procuring for her the appointment. About a month ago, one of the lady's friends got hold of the matter, and reported it to the Court, which resulted in an investigation and the subsequent dismissal of Griffin. This is the only case of the kind that we have heard of, and we have no reason to believe that there is any other, or that corruption exists in the Examining Corps, as alleged. Evening Mail —Eds. of testing the purity of samples of water, by watching the rapidity of its action on soap and similar compounds, has been introduced by the French , MM. Boutron and Boudet. The experiment tests, at the same time, the purity of the soap. Dissolved in water in which lime is held in solution, the soap is precipitated in hard white flakes. If the quantity of soap put in the lime water be noted, it will be found that the smaller the quantity producing precipitation, the purer the soap. The (of Paris) reports some experiments, on this subject, by M. F. Schulze. A method savants Journal de Pharmacie et de Chemie .—The fifth State fair of the Mechanics, and Agricultural Fair Association of Louisiana will commence in the city of New Orleans, on Saturday, April 8, 1871, and continue nine days. Over $20,000 in premiums are offered. Rules, regulations, and schedule of premiums may be obtained of the Secretary and Treasurer, Luther Homes, Esq., New Orleans, La. Louisiana State Fair .—John Kent advertises, in this paper, valuable machinery for the manufacture of knitted goods, to which we invite the attention of all who are interested in this branch of industry. Mr. Kent has devoted many years to the perfection of these machines. Knitted Goods , a white clay, used largely in the adulteration of flour, starch, and candles, is found near Augusta, Ga., and is sent to the Northern States in large quantities. Kaolin We are indebted to James Vick, practical florist, Rochester, N. Y., for a choice variety of flower seeds. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American, Volume XXIV., No. 12, March 18, 1871. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/19180/pg19180-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

Unpleasant Discovery in the Patent Office—Levying Black Mail

A community doesn’t need gamers who have child-like behavior exhibiting extreme toxicity. If you have a game that has a massive community and to balance their emotions, you need a regulatory solution. A solution that could curb their toxicity, analyze trolls, filter out BMs ( ), and eliminate cyberbullying. A solution like a sportsmanship score, conduct, player reputation, or Fairplay score, and here we are calling it Behavior Score Analytics. gaming Bad Manners What is Behavior Score Analytics? Every game has always been on the radar of undetermined independent entities who score the effect of those games on users. The effect can vary; it can alter their behavior towards personal as well as professional life. Hence, the behavior score is used to assess the impact. It also provides information regarding the player’s toxicity level and the way they treat their fellow teammates or in-game players. The score also validates the fairness of the player; cheating, scripting, and tampering with the game rules often lead to deactivation of the account. The score also provides insights into how the game is progressing with the community. A player is reputable, has a good rank, and makes the gaming community a better place for other players. A Good Behavior Score: This is the first strike; you might want to consider reviewing your [All Chat] messages and conversations. A Mediocre Score: You might get banned for extreme toxicity or bullying or be placed in low ranks. This will impact your overall match-making factor, too. A Bad Behavior Score: The behavior score analytics scale is integrated into the game to make the experience wholesome. Friendly banter is okay, but if you don’t have control over your temper and start Chatting in a full rage, you might disrupt the gaming experience of other players, too. So, we found another valid reason why a proficient game developer would introduce behavior score analytics into the game. Here, a skilled game developer will prioritize leaving the analytics and judging on an autonomous & unbiased entity. An AI-based Behavior Score analytics. It reduces the cost of manual moderators, implements efficient tacking, and has the ability to scale as well as adapt the game mechanics. Can AI track Gamer Conduct? Yes, developing an AI-based Behavior score tracking system is feasible. However, it sure takes a lot of planning, and the process is not as easy as it seems. Integrating Artificial Intelligence with a Behavior score tracker involves utilizing natural language and speech processing at full capacity. The system needs to process the way players verbalize, chat, and grief (Spoiling the game experience through irrelevant game plays that affect team rankings and score). There are a lot of in-game metrics that need to be studied, analyzed, and labeled, and then we need to determine a result. Sure, one can moderate metrics like in-game chat, and normal communication. But a few metrics like reports, action, and gameplay that lead to reputation scores need to be thoroughly evaluated. Here, AI can be proven to be a primary contributor for game developers. Let’s learn what AI-integrated Fairplay score analytics can do and how to develop one. What Behaviour can AI Track? We explore the importance of behavior scores, but let's study what the system can do for the game. A game developer integrates a Fairplay scoring system to ensure quality across the game and its community. It mitigates the risk of a ‘maybe’ possibility of being put under investigation. Here are the following five common factors tracked by the AI score analysis system. . The system can monitor if the players are following the guidelines of their respective roles or not. Not doing so may disrupt the gameplay and, in pro scenes, can result in match-fixing for tilting the betting odds. Teamplay: In gameplay, a team is sometimes assigned to respective roles A true sportsman understands that sportsmanship matters. Every esports player is currently a well-known figure. The way they interact and behave in the game affects the thought process of the community, too. So AI can lawfully judge whether the player is being a true sportsman or not. Sportsmanship: They can also track aimbots, scripters, lag switches, and much more. Many players run scripts to climb up the rank or smurf using low-level secondary accounts. Cheating:- Many in-game actions by players can lead to grief. Actions such as taunting, bullying, Bad manners, irrelevant playstyle, etc. It leads to boiled-up hatred, and the other players can report the person through the system. Griefing:- In-game communication is the best way for shot callers to make game-breaking plays. But on the other hand, it can be used to abuse words. AI solutions can track this and either mute the player or score them accordingly. Communication:- Building Blocks For a Behaviour Score Tracker Let's explore the building blocks of a common AI-based behavior score system. We have divided the whole structure into five primary needs and wants of services required. Games are full of chats, voice messages, and communication pings. Building a game data collection pipeline is one of the important stages. You can utilize AI here for automated data collection as well as the security of the data gathered. Game Data Collection Pipeline: Now, we need to label the data that was collected. Every string of data needs to be labeled either positive, negative, or neutral. The data annotation will help train your and provide results once the equation is run through the model. Data Annotation: machine-learning model here, the automation kicks in; you now have a labeled data set; you just need to analyze it and build a classification system. The classifiers will automatically anatomize the whole data set in small details. The data set includes players’ behavior, speech, raw chats, messages, and behavior during the gameplay. Applied AI/ML Model Development: The infrastructure will help you to deploy huge data streaming pipelines conveniently and in an efficient manner. A Cloud infrastructure: UI/UX design and mobile/web app development to build an easily accessible product. This is required to provide end product experience to users, like more precise data visualization, allowing them to view data insights, and ultimately a two-way data viewing channel for both users as well as manual moderators, just in case. End Product Development: Top Three Case Studies Automated sportsmanship analytics may be complex for a beginner or a person who is not aware of the system. So here are the top three case studies that we have explained in short to clear your understanding. These case studies are not ranked; we are not saying these are the most perfect in the market. But looking at the pro scene, this system has been praised for its analytics and much more. Note: Riot Games uses an AI-powered behavior score system called Valorant Credit Score. The system is used to track reports, AFK-ing, Cheats, and Toxicity levels. Case 1: Counter Strike 2 uses Overwatch and the Trust Factor system. It has contributed to making the community a better place. Players can report toxic behavior and tampering. Case 2: Dota 2 has always been the king of esports games due to its massive prize pool. But in 2019, it experienced a rapid drop in its users. This was due to toxicity. Valve unveiled Overwatch and the Trust Factor system for Dota 2, too. It allowed players to file a report, and the gameplay was reviewed by an expert esports Dota 2 community. The conduct score system has so far helped not only retain their players but also enabled them to make the community a wholesome battleground for . Case 3: Newbies In all the cases, there was one single approach: to combine a natural language processing system with a scoring system. AI has already begun to develop and is at its prime, and the game development industry is not backing from leveraging its evident benefits. Boosting Wholesome Experience in Mobile Games Did you know that a report concluded that in 2023, there was a 21.7% increase in the number of mobile game users? The same report suggested that the segment will reach an all-time high of 1.9 billion users by 2028. So you may ask a simple question: can there be an AI-based Behavior Score just for mobile games? The answer is yes, although there would be a few things that need to be considered before creating it, such as: API Integration to tap into chats, gameplays, and reporting systems. Efficient Model that can work with low latency and high throughput. A data-protecting system that allows players to reliably transfer data from mobile to cloud. Cross-platform support for more convenience and accessibility. Mobile native data viewing and UI/UX design. Epilogue An AI-based Behavior Score System can help game developers build games that are not subjected to spreading toxicity. A positive community needs moderation strategies, and AI can help automate those tasks. Sure, there are ample benefits an AI-based Behavior score system can provide and along comes complexity. However, due to the introduction of Generative AI, a variety of things are automated, such as dataset augmentation, pattern recognition, context evaluation, and stimulating gaming environments that might reduce toxicity. Still, it is a long way to go. However, one should not back down from introducing their ideas in the market due to complexity. Explore how games are being developed in modern times, the use of AI/ML, and primary research about Generative AI tools and technologies. It will surely help you develop your idea, even mobile games with AI-based behavior score systems. Thank you for reading, and remember the best way to play games is responsibly.

Automating Sportsmanship : AI for Behavior Score Analytics

Scientific American, Volume XLIII., No. 25, December 18, 1880, by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . The Harbor of Montreal. here The Harbor of Montreal. A plan for the improvement of the harbor of Montreal, Canada, has been submitted to the City Board of Trade by James Shearer, a well known citizen. Mr. Shearer's plan is to divert the current of the St. Lawrence opposite the city into the channels between St. Helen's Island and the southern shore, and by having various obstructions removed from the channel, and running a dam, or "peninsula," as he calls it, built from Point St. Charles, in the west end of the city, to St. Helen's Island, midway in the river, thus stopping the current from running through the present main channel between the city and St. Helen's Island. Among the practical advantages that will accrue to the city and harbor from the carrying out of this project, Mr. Shearer sets forth the following: The dam will prevent the shoring of ice opposite the city, and the consequent flooding of the Griffintown district, which is annually very destructive to property, and will make a still harbor, where vessels may lie during the winter. It is estimated that the construction of the dam, which would be 2,700 feet long and 900 feet broad, would raise the water two feet in the river and lower it ten feet in the harbor. This would give a head of twenty-five feet for mills, elevators, and factories, and the transportation of freight. The dam would afford a roadway across the river, upon the construction of a bridge from St. Helen's Island to St. Lambert, thus removing the necessity of a tunnel. The roadway could be utilized for a railway, a road for carriages and foot passengers. The estimated cost of the improvement is $7,000,000. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2007). Scientific American, Volume XLIII., No. 25, December 18, 1880. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/21081/pg21081-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The Harbor of Montreal

Hi there, fellow coders! We’re all on a quest to level up our programming skills, right? So, how do we become coding wizards? Well, here’s what people generally do: Scouring through other people’s code — because we all know there’s wisdom in those curly braces. Devouring programming articles — the ones that reveal secrets, shortcuts, and maybe even a joke or two. Sifting through documentation — yes, those sprawling tech manuals that often make us feel lost in a maze. But they hold the keys! But here’s the fun part: to reach greatness, you’ve got to be a detective and search for those telltale signs of being, dare I say it, an “average” developer. 🕵️‍♂️ My mission is to guide you in discovering these four telltale signals of a short-sighted programmer, so you can steer yourself down the right lane. coding They don’t “design” prototypes, they “build” it! Let me tell you a little story about my journey from a code-centric prototype skeptic to a design enthusiast. I used to be all about code-based prototypes, and I couldn’t fathom why anyone would bother with non-code-based ones. I’d ask questions like: “Why on earth would we need a figma prototype when we can whip up a code-based one that mimics real user interactions?” I mean, I loved the fact that with a code-based prototype, you could thoroughly test all the features and squash those pesky bugs early on. Plus, you’d get a head start on understanding the nitty-gritty technical challenges from day one. Not to mention, having something tangible to show customers was pretty sweet. But guess what? In the grand scheme of things, it turned out to be a bit of a dud. Here’s why: First off, building a code-based prototype is like a time-sucking black hole. It can drag your project timeline into a never-ending abyss. Once you and your team dive headfirst into coding, you’re stuck on that roller-coaster, even in the project’s infancy. Making changes to a code-based prototype? Buckle up for a bumpy ride because it means a truckload of adjustments down the line. And let’s not forget that . customer requirements are about as stable as a Jenga tower in an earthquake It’s way smarter to give them a sneak peek at a non-tangible product and gather their feedback. Let’s picture this with a scenario — Imagine you’re building a ridesharing app, and you decide to kick things off with a code-based prototype. Your team puts a ton of effort into designing a system where users can book rides and make payments via a third-party API. The client loves it, and you start charging full steam ahead, adding more bells and whistles. But then, oh snap, you realize the API costs an arm and a leg! You’d love to hit the brakes and switch gears, but you’ve already invested so much time and energy that you’re essentially handcuffed to the code. Rolling back? Good luck with that; you’ll need a time machine. Learn the difference between a prototype and an MVP (Minimum Viable Product) If you’d started with a non-coded prototype, you could’ve easily shown it to the client, discussed options, and if necessary, hit that undo button in a jiffy. No extensions, no drama. So, the moral of the story? I’ve learned the hard way that code-based prototyping isn’t all it’s cracked up to be. It’s time to embrace the non-code-based way — your project’s sanity and flexibility will thank you! 😄🚀 They think they can just hit the ‘Undo’ button on life’s big choices! (Like choosing the right tech stack) Back in the day when I was just a code-writing newbie, I had some wild ideas. I was basically a self-taught programmer, and I had this grand notion that I could whip up any project using any tech stack under the sun. I was notorious for my random experiments. If I was building a blog site with Flask and stumbled upon some dude on YouTube singing praises of Django, you bet I’d jump ship without hesitation. I’d scrap all my previous code right in the middle of the project and switch to Django. And guess what? If Django didn’t tickle my fancy, I’d casually saunter back to my old stack like it was a stroll in the park. And it wasn’t just limited to the back-end stuff. Frontend, libraries, payment processors — you name it, I flip-flopped between them more times than I can count. So, what did all these shenanigans teach me, you ask? Well, I developed this quirky belief that I could reverse or change any decision, anytime, anywhere. As time went on, I started reading stuff by other developers, and a couple of times, I heard them griping about their choice of tech stack. They were moaning about how it had made their lives miserable. But in my mind, I was like, “Why are these folks whining? Can’t they just flip the switch to their preferred tech stack?” What I didn’t get back then was how darn hard it is to do a 180 in the professional world (I was just out the college at that time). You can’t do major transitions on a live product with thousands of paid users, nor you can simply plug-and-play major elements in real-world. See, when you’re building your own pet projects, you’ve got all the time in the world. You can try things out, switch libraries, flip-flop between programming languages — it’s all a walk in the park. But once you venture into the professional realm, that’s when the headaches come rolling in. Even if you’ve dotted every ‘i’ and crossed every ‘t’ in your code, adhering to all the best practices like DRY and crafting code that’s as flexible as a rubber band, it won’t save you. Why? Because if the higher-ups decide to change a major design element, all those best practices go out the window. One little tweak to a crucial step, and your project’s timelines are about as reliable as a weather forecast. So, what’s the takeaway from this? In the real world, decisions you make often have no U-turns. So, before you dive headfirst into picking that quirky, unsupported third-party library, take a step back. Do some good old requirements gathering, research like your life depends on it, evaluate your options, assess the risks, and maybe even whip up a prototype. Make sure you’ve covered all your bases before committing to a big decision. It’ll save you a world of trouble down the road! They’re totally clueless about what’s coming up! You know, it’s like developers sometimes forget that the future is a thing! I mean, they swear they get it, but come on, they keep repeating the same old mistake. So, when do they mess it all up? Well, it’s like a clock ticking down to the deadline, and they start panicking more about the here and now, forgetting all about what’s down the road for their software. They ditch those crystal balls for shortcuts, just to wrap up the project. Imagine coding up an analytics tool for your company, and you go, “Oh, that shiny third-party API looks cool!” No research, no second thoughts. But then, down the line, you need some fancy features, and guess what? No documentation! How would you feel? Pretty much like you’d bitten into a sour lemon, right? — Regret City, population: you. Here’s the lesson: Trendy APIs might seem all the rage, but they’re like those one-hit wonders in the music world — here today, gone tomorrow. Go for the trusty folks who’ve been around the block, the ones with a solid track record of dependability. It’s like picking the rock-solid friend over the flaky acquaintance for the long haul! They go for the full app in DIY mode! I still remember that initial rush of feeling like a tech wizard when I whipped up a simple HTTP server in C without using any third-party libraries. Man, that was fun! I thought I was the bee’s knees when I first used my app. I was like, “I can build anything I want, exactly how I want it!” But here’s where I took a wrong turn. I used to be obsessed with crafting the ultimate, perfect product right from the get-go. I didn’t want to waste a minute building a stripped-down version. I had to create an app with 20 different features, but only 2 of them were super crucial. Instead of just putting together a simple app with those 2 must-haves, I went all out, trying to make the mother of all apps with all 20 features from the very start. Silly, right? You see, because I thought I was a genius, I believed I had it all figured out and didn’t need any client feedback. Here’s a nugget of wisdom for all you fellow developers out there: Don’t fall into this trap! Loads of developers, like me, dream of building that flawless app right from the beginning. They don’t want to “waste” time on a basic version. But trust me, building that simplified prototype is the way to go. It helps you spot problems early on, and you can gather feedback to keep improving. Just by having a basic version, you can test your ideas and make sure everything’s working smoothly. Plus, you’ll catch those pesky issues before they turn into big headaches down the road. So, what’s the takeaway here? The next time you’re starting from scratch on a software project, kick things off with a stripped-down version of your product, focusing on the most vital feature. It’ll save you a ton of time and hassle in the long run. Also published here.

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