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A Guide to Outsourcing Without Compromising Data Quality In order for data science teams to outsource annotation to a managed workforce provider — also known as a Business Process Outsourcer (BPO) — they must first have the tools and infrastructure to store and manage their training data. Data management tools and infrastructure should support R&D product management teams, outsourced labeling teams, and internal labeling and review teams working together in a single centralized place with fully transparent oversight. Scaling with Subject Matter Expertise There is a direct relationship between the volume of your training data and the size of your annotation team. The alternative to scaling your annotation workforce through outsourcing is hiring an internal team of labelers. While this is an expensive option, it is sometimes the only option. For example, scaling sensitive training data, such as medical data with HIPAA protection, might require a solely internal labeling workforce. Continuing with this example, medical data, such as CT scans, would need to be labeled by radiologists who have the necessary medical expertise to properly interpret the data. The concern with outsourcing labeling work requiring subject matter expertise is that a BPO will not be able to provide specialized labelers. While there is good reason to be skeptical about outsourcing complex or niche datasets, BPOs cover a surprisingly wide spectrum of subject matter expertise and with a little bit of research, you might find one that offers a specialized annotation service capable of labeling your dataset at a fraction of the cost it would take to hire an internal team. Grant Osborne, Chief Technology Officer at , a comprehensive esports community platform powered by AI, describes his decision-making process behind using Labelbox’s outsourcing feature to scale annotations within the competitive gaming industry. Gamurs is developing an AI coach for professional video game players. The AI coach will help to improve gamer performance by learning from similar examples in which players are underperforming and suggest ways to enhance the gamer’s performance. Grant originally considered crowdsourcing gamers from their large social media following to label their favorite games of choice. At first, he looked into a number of popular crowdsourcing tools but quickly rejected this option because their revenue generation comes from annotation. Gamurs “These tools charge for storage based on the number of bounding boxes. And since we will have millions of labels, this pricing structure is impractical.” He then considered building a cheap in-house tool and hiring an internal team of labelers, until he spoke with Brian Rieger, Co-founder and Chief Operating Officer at Labelbox. Gamurs needed a platform for uploading and regulating images of multiple games with object detection. In contrast to other commercial labeling tools, Labelbox’s pricing structure is based on a three-tier system: Free, Business, and Enterprise. The subscription tiers are categorized by number of ML projects and dataset size. These tiers vary in price and access to certain platform features. “My favorite part about Labelbox is the ease of the API. Having a developer focused API makes it effortless to productionize models.” Dota2 Annotations on Labelbox (photo: Gamurs) “We needed a machine learning pipeline solution and Labelbox was it!” — Grant Osborne, CTO at GAMURS Unsurprisingly, Grant was initially dubious about outsourcing specialized gaming actions on Dota2 or League of Legend to a BPO. “We wanted to have an internal labeling team because the computer actions are complicated. How are we going to have an external company used to labeling simple objects, like stop signs and trees, label our games? However, Labelbox’s BPO partners told us to just send over a manual and they’d handle getting a dedicated annotation team up to speed.”  “Labelbox recommended two BPOs that would best fit our needs and said there were more if we were interested. The BPOs estimated that it would take ~3–4 weeks to get everyone completely trained. While this estimation was a bit optimistic for how complicated the material is, they were able to finish the training cycle in ~4–5 weeks.” Despite the drastically different cost quotes from the two BPOs (with one at 1.5–2 cents per bounding box and the other at 10–12 cents per bounding box), Gamurs still decided to use a mixture of both BPOs with a 20 person labeling team from the first and a 10 person labeling team from the second. League of Legends Annotations on Labelbox (photo: Gamurs) “We will probably do a combination of BPOs based on their strengths per game. We will get them to do consensus and if one BPO is better at quality assurance but slower at labeling, we will use them to cross review the other team’s work.” Scaling with Data Quality The inverse misconception of outsourcing subject matter expertise is believing that all human labelers are equal when it comes to annotating an extremely simple dataset. This perspective often downplays the importance of data quality in labeling. Read the section to learn how training a deep convolutional object detection model to identify something as simple as a pumpkin is actually much more complex than you might guess. Even with simple labeling tasks, to ensure data quality, you must be able to oversee the consistency and accuracy of labels across annotators and over time.  Labeling at scale without compromising data quality requires transparency throughout your labeling pipeline. Teams of data scientists who are outsourcing on locally run in-house tools often send data to several different annotation services where labeling happens locally, sometimes in a variety of countries, and the data scientists must rely on these labelers to send the file via email or to do uploading acrobatics via Dropbox.  Consequentially, the data becomes fragmented, disorganized, and difficult to manage, leaving it vulnerable to problems in data security, data quality, and data management. In order to monitor labeling accuracy and consistency of outsourcing services in real time, companies, like switch from managing their annotation workforce on a homegrown tool to managing it through Labelbox. is best in the world for integrating your in-house labeling and review teams with your outsourcing team in one centralized place. What’s a Pumpkin? SomaDetect Labelbox Not all Labelers are Equal Factors that differentiate outsourcing goes far beyond only the subject matter expertise it services. Labelbox has hand selected the top BPO firms based on the following criteria: Pricing transparency Quality customer service Diversity in company size, regions of service, range of skills, and styles of engagement We spoke with Michael Wang, Computer Vision Engineer at Companion Labs, who spoke to us about his experience outsourcing on Labelbox with one of our recommended BPO partners. He explained why outsourcing with a dedicated team of labelers, as opposed to crowdsourcing random human labelers, produces higher quality training data. “Connecting directly with a dedicated team of outsourced labelers helps you and the clients figure out how to label the project and labelers get better over time. With random labelers, you have to start the learning curve from scratch every time. Dedicated teams of labelers come to understand your project and when you explain something it gets communicated across the entire team.” — Michael Wang Before choosing Labelbox, Companion Labs had compared Labelbox to a leading competitor by trying out both labeling service APIs in terms of quality metrics, time, and effort to label their project. Michael said that Labelbox has a higher quality outsourcing pool than the well-known competitor who crowdsources.  When asked how he chose who to work with amongst Labelbox’s partner BPOs, he explained that Labelbox provided two recommendations, which he evaluated both on quality and cost metrics. “Both providers were pretty amazing in terms of quality so choosing came down to the cost.” Outsource on Labelbox Managed workforce services are often an instrumental part of making an AI project successful. Therefore, we at Labelbox want to enable managed workforce providers to render their services in as frictionless a way as possible. With Labelbox, teams of data scientists, annotators, and product managers can transparently manage small projects and experiments to super large projects all on a single platform. Our focus is to make our customers as successful as they can be at their AI projects. Our customers are businesses of all sizes building and operating AI. We have worked with a lot of managed workforce providers and it is clear to us that the best providers stand out from the rest in the service they provide and the customer-centric nature of their business. We have hand selected BPO partners so that our customers can have high-quality labeling services rendered directly inside of their Labelbox projects.  On Labelbox your internal and outsourced labelers can work together on a labeling project. It’s so cohesive that there’s literally no seam between the two! seamlessly An Effortless Two-step Process Contact one of our Workforce Partners listed . here Share your Project with them by adding their “Firm Provider ID” (Provided by the Workforce Partner). That’s really it! Your Project will show up as a shared Project in the Workforce Partner’s Labelbox account where they will be able to add and manage their own labelers in your project. They will have access to annotate, review annotations, and manage their labelers. The best part is that your internal team will be able to monitor their performance with complete transparency. For more information . check out our docs Get Started with Labelbox Visit to explore for free or about an enterprise solution for your business. www.labelbox.com Labelbox speak to one of our team members Originally published at medium.com on December 13, 2018.

How to Scale Training Data

is a powerful technique for solving optimization problems that can be divided into smaller sub-problems. The main idea of dynamic programming is to avoid recomputing the same sub-problems over and over again, by storing and reusing their solutions. This way, dynamic programming can reduce the time and space complexity of recursive algorithms and often find the optimal solution to a problem. Dynamic programming In this article, we will explore some real-world examples and applications of dynamic programming, and see how it can be used to solve various kinds of problems in different domains. Knapsack Problem The knapsack problem is a classic example of dynamic programming. The problem is as follows: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight does not exceed a given limit and the total value is as large as possible. This problem can be solved by using a two-dimensional array to store the optimal value for each sub-problem, defined by the number of items considered and the remaining capacity of the knapsack. At each step, we can either include or exclude the current item and choose the option that maximizes the value. The final answer is the value at the bottom-right corner of the array. The knapsack problem has many practical applications, such as packing a suitcase, selecting investments, allocating resources, etc. All Pair Shortest Path Another common problem that can be solved by dynamic programming is finding the shortest path between any two nodes in a weighted graph. This problem is known as the all pair shortest path problem, and it can be solved by using algorithms such as Floyd-Warshall or Bellman-Ford. These algorithms use a three-dimensional array to store the shortest distance between any pair of nodes for each intermediate node considered. At each step, they update the distance by comparing the current distance with the distance obtained by going through the intermediate node. The final answer is the distance matrix at the last iteration. The all pair shortest path problem has many applications in network analysis, routing, navigation, social network analysis, etc. Seam Carving Seam carving is an interesting application of dynamic programming in image processing. The problem requires you to resize an image without distorting its important features, such as faces, objects, or text. This can be done by removing or adding pixels along seams, which are paths of low energy in the image. To find the optimal seams to remove or add, we can use dynamic programming to compute the cumulative energy of each pixel in the image, based on its gradient and its neighbors. Then, we can find the seam with the lowest energy by tracing back from the bottom to the top of the image. We can repeat this process until we reach the desired size. Seam carving can be used to create content-aware image resizing, cropping, retargeting, etc. Machine Learning and Genomics Dynamic programming can also be used to solve problems in and , such as sequence alignment, hidden Markov models, and phylogenetic trees. machine learning genomics Sequence alignment is the process of finding similarities between two or more sequences of symbols, such as DNA or protein sequences. This can help us understand their evolutionary relationships, functional roles, or structural properties. Dynamic programming can be used to find optimal alignments between sequences by scoring their matches and mismatches according to some criteria. Hidden Markov models are probabilistic models that describe sequences of events or observations that depend on some hidden states. They can be used to model complex phenomena such as speech recognition, natural language processing, bioinformatics, etc. Dynamic programming can be used to find the most likely sequence of hidden states given a sequence of observations by using algorithms such as Viterbi or Forward-Backward. Phylogenetic trees are graphical representations of evolutionary relationships among organisms or genes. They can help us infer their common ancestors, divergence times, or evolutionary events. Dynamic programming can be used to construct optimal phylogenetic trees from sequence data by using algorithms such as Fitch or Sankoff. Cryptography Dynamic programming can also be used to solve problems in cryptography, which is the science of secure communication. Cryptography involves techniques such as encryption, decryption, digital signatures, authentication, etc. Encryption is the process of turning readable information into unreadable information that can only be accessed with an encryption key. Decryption is the reverse process of turning unreadable information back into readable information with the same or a different key. Digital signatures are methods of verifying the authenticity and integrity of a message or document. Authentication is the process of verifying the identity of a sender or receiver. Dynamic programming can be used to implement various cryptographic algorithms, such as dynamic key cryptography, code-based cryptography, and dynamic programming-based cryptography. Dynamic key cryptography is a technique that uses dynamic keys to encrypt and decrypt messages. Dynamic keys are keys that change over time or according to some criteria. This makes them more secure and resistant to attacks than static keys. Dynamic key cryptography can be implemented using dynamic programming to generate and update the keys. Code-based cryptography is a technique that uses error-correcting codes to encrypt and decrypt messages. Error-correcting codes are codes that can detect and correct errors in transmission. Code-based cryptography is considered to be quantum-resistant, which means it can withstand attacks from quantum computers. Code-based cryptography can be implemented using dynamic programming to encode and decode the messages. Dynamic programming-based cryptography is a technique that uses dynamic programming algorithms to encrypt and decrypt messages. Dynamic programming algorithms are algorithms that solve optimization problems by breaking them into smaller subproblems. Dynamic programming-based cryptography can use various dynamic programming algorithms, such as knapsack, shortest path, or seam carving, to perform encryption and decryption. Conclusion Dynamic programming is a useful technique for solving problems that have overlapping sub-problems and optimal substructure. By storing and reusing sub-problem solutions, dynamic programming can improve the efficiency and optimality of recursive algorithms. Dynamic programming has many real-world examples and applications in various domains, such as combinatorial optimization, graph theory, image processing, machine learning, genomics, and cryptography. Sources: The complete beginners guide to dynamic programming - Stack Overflow Blog Dynamic Programming: Examples, Common Problems, and Solutions - MUO Real-world dynamic programming: seam carving - Medium Dynamic Programming: Applications In Machine Learning and Genomics - edX Dynamic Programming for Machine Learning - Towards Data Science Dynamic key cryptography and applications - Monash University The lead image for this article was generated by HackerNoon's AI Image Generator via the prompt "A computer screen with a running program"

Real-world Use Cases of Dynamic Programming

Calling All Writers: Learn What the Opt-Out Writing Contest is All About From The Āut Labs' Team

Heyo, Hacker! is designed by our friends at Āut Labs with themes and ideas for you to enter the Opt Out Writing contest. This writing prompt Click here to write with this template. See the contest announcement . Learn how to enter the contest . here here Theme 1: . Opt out of a System that doesn’t represent you #autonomy: : Explore the critical role of autonomy in decentralized systems like DAOs. Consider focusing on how Āut’s mission and products (i.e.: Nova, ĀutID, ĀutOS, …) enhance this. You can tell us about Roman’s , Greek’s , French or some role-based, [dys/u]topian society that is yet to come. Autonomy in Decentralized Systems, Collectives and DAOs triumvirates poleis communes - : Remember the “ ” in the Berlin of the 90ies? We love that vibe. Consider the intersection of autonomy in art, technology, and activist reforms - highlighting innovative approaches based on autonomy of one or multiple parties. As well as how these parties can play together to take down a censoring, centralized, self-absorbed Moloch. Autonomy in Art, Technology, and Activism hacker labs : Tell us a story on how a “ ” may look like. Are we aiming towards a dystopian, whole-state surveillance, or towards the highest level of individual autonomy and collective productivity that humankind has ever seen? Anything worse? Anything in between? Reshape the future workplace and work culture, especially imagining a world where decentralized organizations actually made it. Autonomy in the Workplace workplace of the future : . Is different for DeFi degens vs. artists & writers vs. political scientists & philosophers vs. governance vs. devs & mathematicians? Feel free to tackle them all at once, tell us a story about one of them - or create a role-based governance model that is going to take the future generations by storm. Role-specific Autonomy 50 shades of Autonomy autonomy : Square and simple. What is , isn't it a paradox in terms, and what does that even mean? Yeah, all that jazz. You can take a mathematical angle, invent new game-theorical rules of the game, or just make up a story that even for a second lets us suspend our disbeliefs. Collective Autonomy Collective Autonomy #identity: : What is identity in the digital space? Is it a mere reflection of what we are offline, or is it an augmented version of ourselves? Is there a “minimum viable tech stack” that can be combined to create verifiable individuals? This is an open prompt - feel free to take it from a technical or philosophical standpoint. And be provocative - we aim for non-trivial answers only on how digital technologies enable new forms of identity, personal expression and verification. Identity in the Digital Space : That’s an obvious one. How identity evolved over the centuries. Did we “mature” as a society? Did technology change what we are as individuals? Are humans different in their [self-awareness; proprioception; way to perceive others] or we did nothing but taking a long stroll from Stone Age to Technocracy? The History of Identity : we talk DAOs, distributed nations, on-chain agencies. But what are individuals within groups? Is collective intelligence a “flattening model” that blurs individuality within collectives, or it turns each individual actor into a needed, recognizable tile of the puzzle? And what is the threshold between individual and collective identity? This is a difficult one - new models, visual graphs, and brand-new, DAO-shaking processes are encouraged. Collective Identity : from Metaverses and NFTs, to basic PGP and SSIDs. How can an ID be as unstoppable, and uncensorable on one side, as it is credible, and reliable on the other? Please, be as geeky as needs be - use your tech-knowledge and understanding as an act of civil disobedience. On-chain Identities : This is our Sci-fi prompt. Tell us stories. Speculate on how identity will evolve in decentralized societies. On how they will impact individuality. For this prompt you can share your tech journal, tell us personal identity narratives, or even invent on-chain personas and breed them to NFT perpetual life. Whatever works. The Evolution of Identity in Decentralized Societies #selfsovereignty: : What is -sovereignty? Why it matters? “ ” is already a long, difficult word per se - so why did we even feel the need to add the prefix “ ” there? This is all about the inalienable individuals’ right to privacy and selective disclosure. Give us self-sovereignty straight, or explore it in a specific context. The Essence of Self-Sovereignty self Sovereignty self- : Provide real-world examples or case studies where self-sovereignty is effectively implemented. Can’t find any? Even better. Make one up, and let’s make it happen together. Self-Sovereignty in Action : This is a big one. As the Anarchist proverb goes, . But what are the borders of this personal freedom? Should self-sovereignty self-enforce in decentralized social/community contracts? Or we should somehow “hardwire” a sort of collective ethos beforehand, into the decentralized smart contracts that will govern us all? Balancing Self-Sovereignty and Collective Responsibility one can only be free if everyone else is free : Think of DeFi credit score, think of UBI. Is a self-sovereign, verifiable ID enough to automate the individual and collective distribution of wealth? Or we still need/want/expect “watchmen” to supervise that all goes smooth - and to potentially deem liable if something goes wrong? Self-Sovereignty in Financial Systems : Should we really be limited by old-world concepts such as “1 person : 1 Identity/vote/seat”? Or meritocracy means that we should be able to enforce a self-sovereign right to multiplicity in the digital space, as long as we can handle our multifaceted selves? To Sybil or not to Sybil Open Prompts: : The old, best writing advise: write about what you know. From literature, to robotics, to the legal system - write about one of the contest topics in relation to a specific field you are deeply knowledgeable or passionate about. [#autonomy; #identity; #selfsovereignty] in [insert field] This is a quote that we like, from J.P. Proudhon. To be governed is to be watched, inspected, spied upon, directed, law-driven, numbered, regulated, enrolled, indoctrinated, preached at, controlled, checked, estimated, valued, censured, commanded, by creatures who have neither the right nor the wisdom nor the virtue to do so. To be governed is to be at every operation, at every transaction noted, registered, counted, taxed, stamped, measured, numbered, assessed, licensed, authorized, admonished, prevented, forbidden, reformed, corrected, punished. It is, under pretext of public utility, and in the name of the general interest, to be placed under contribution, drilled, fleeced, exploited, monopolized, extorted from, squeezed, hoaxed, robbed; then, at the slightest resistance, the first word of complaint, to be repressed, fined, vilified, harassed, hunted down, abused, clubbed, disarmed, bound, choked, imprisoned, judged, condemned, shot, deported, sacrificed, sold, betrayed; and to crown all, mocked, ridiculed, derided, outraged, dishonored. That is government; that is its justice; that is its morality. , - Pierre-Joseph Proudhon The General Idea of the Revolution Explore it in the key that you like, adherent to one of the three main themes. Or just use it as an inspiration, and write about whatever you want :) Click here to write with this template.

Aut Labs Story Template: Opt Out of a System that Doesn’t Represent You

অট ল্যাবস স্টোরি টেমপ্লেট: এমন একটি সিস্টেম থেকে অপ্ট আউট করুন যা আপনাকে প্রতিনিধিত্ব করে না

Aut Labs-Story-Vorlage: Melden Sie sich von einem System ab, das Sie nicht repräsentiert

Plantilla de historia de Aut Labs: optar por no participar en un sistema que no lo representa

Modèle d'histoire Aut Labs : désinscription d'un système qui ne vous représente pas

ऑट लैब्स स्टोरी टेम्प्लेट: उस सिस्टम से ऑप्ट आउट करें जो आपका प्रतिनिधित्व नहीं करता है

Aut Labs ストーリー テンプレート: あなたを代表しないシステムからオプトアウトする

Aut Labs 스토리 템플릿: 귀하를 대표하지 않는 시스템에서 탈퇴

Modelo de história do Aut Labs: desative um sistema que não representa você

Шаблон истории Aut Labs: Откажитесь от системы, которая не представляет вас

Aut Labs Hikaye Şablonu: Sizi Temsil Etmeyen Bir Sistemden Vazgeçin

Mẫu câu chuyện của Aut Labs: Chọn không tham gia hệ thống không đại diện cho bạn

自动实验室故事模板：选择退出不代表您的系统

Today I’m going to tell you about the Ryder Ripps Bored Ape Yacht Club… Remember, in the , I promised I would write a separate piece about it? previous story about the Bored Ape Yacht Club Well, here it is! The timing seemed perfect since the trial happened last week. So let’s dive in. Origin Story From the previous issue, you already know the high-level story of the Bored Apes Yacht Club - but what the hell is Ryder Ripps Bored Ape Yacht Club (RR BAYC)? You may be wondering. Here is how it all started. In May 2022, conceptual artist Ryder Ripps took a picture of the Bored Ape that owned and used as his profile picture on Twitter and minted it as a new NFT on Foundation. He then linked his wallet to his Twitter account and used that as his new profile picture. Twitter, in its turn, showed a hexagon around the image, which proved that it’s an NFT that the account holder (Ryder) owns. j1mmy.eth NFT I could not find the exact public dialogue between j1mmy.eth and Ryder, but I recall that  j1mmy.eth was not happy at all. The conversation between them and the Twitter crowd provoked thoughts and brought up important topics such as NFTs, IP rights, ownership, provenance, etc. And within this context, below is the tweet that started it all There were many people tweeting and asking to get their RR BAYC based on their chosen Bored Ape image. Ryder Ripps himself was minting the RR BAYC apes one by one on Foundation, and soon it became a trending collection on the platform. If I am not mistaken, at one point, Yuga Labs had sent a DMCA letter requesting the Foundation to take the collection down. It was taken down for a day, but after an investigation was brought back up. Everyone who was purchasing RR BAYC had to agree to the terms below. A copycat? Many simplified the matter and, due to the same imagery used (later even the media while covering the topic), simply labeled the RR BAYC collection a copycat. As you can see from the terms, Ryder meant to for educational purposes, as protest and satirical commentary. re-conceptualize the BAYC imagery And everyone was informed that it was a new mint and not an NFT from the original Bored Ape Yacht Club collection. It is hard to deny, though, that the collection did what Ryder intended it to do. Educational You cannot copy an NFT. It would be safe to say that there were many people in the space who had the wrong perception of what an NFT actually was. Many really thought they were buying, holding, and trading the image (jpeg). This is exactly why some had that ignorant “right-click save” counter-argument. What they didn’t realize was that when they bought the NFT, they bought the token, not the image. And although RR BAYC NFT was pointing to the same image of the respective BAYC ape, it was a completely new NFT under a different smart contract. Protest Please note that the accusations about Yuga Labs being a Nazi brand had not yet gained traction, but they were already around. Ryder had launched at the beginning of 2022, and different Twitter Spaces were debating the matter. https://gordongoner.com/ So to many at this point, minting a RR BAYC was a form of protest. Appropriation Art RR BAYC may be looked at as appropriation art too. What is appropriation art? Appropriation in art and art history refers to the practice of artists using pre-existing objects or images in their art with little transformation of the original. Appropriation art raises questions of originality, authenticity, and authorship. Below is just one example More examples are mentioned in this tweet. https://twitter.com/SirRonHale/status/1687072588692889601?s=20&embedable=true And yes, you may argue that in the RR BAYC case, it’s pointing to the same BAYC original image… but remember - the NFT is not about the image but provenance, right? Anyway, let’s see what happened next Seems that at some point, the demand became so high that Ryder could no longer mint them manually. So he teamed up with Pauly (Jeremy Cahen) and a few others to launch a website where people could buy/mint them. I already told you in the previous story that the Youtuber called BORED APE NAZI CLUB at the time the 2022 was taking place. Philion published his video NFT NYC The video blew up, and I think everyone in the NFT space watched it(+ some more since it got 2M views so far). The video mentioned the RR BAYC collection and brought the attention of more people to it. So the demand kept growing… Yuga’s move At first, the most powerful NFT company that gave birth to BAYC: Yuga Labs, ignored the matter, probably hoping that it would never gain traction and be forgotten with time. But not only the video kept gaining views, but also the crypto and mass media picked up the topic, so with each day, more and more people were coming across the accusations and the RR BAYC collection as a result. So they reached a point where ignoring it further was no longer an option. That’s when Gordon Gomer published labeling the accusations “bullshit” but addressing them nevertheless. A letter from the Founders Trying to recall those times, I don’t remember the Bored Ape community being as loyal and united, supporting the brand as Ryder Ripps and Pauly’s supporters were. The latter was way more loud, bold, and passionate compared to the Bored Ape holders. I personally think that if it was the other way around, things would die out and eventually be forgotten, and this story would simply stop here… But no… we’re still halfway there. Yuga Labs sued Ryder Ripps, Pauly (Jeremy Cahen), and DOES 1-10 in June 2022. Before, they were saying that accusations were “bullshit” and the accusers were just trolls. Now a 4 billion company was suing them. And yes, I get it - all these accusations certainly had a very negative impact on the brand's reputation… but wait - it looks like it is not a defamation case at all! If you are as ignorant in legal matters as I am, you may be wondering - who the hell is DOES 1-10? Looked into court files, and here is who else Yuga Labs is suing besides Ryder and Jeremy: Don’t wanna bore you with too many legal details, but below are just a few segments of what Yuga Labs’ complaints consist of to give you a better context, so you can follow the story along. In response to the Bored Ape Yacht Club’s popularity, Defendant Ryder Ripps, a self-proclaimed “conceptual artist,” recently began trolling Yuga Labs and scamming consumers into purchasing RR/BAYC NFTs by misusing Yuga Labs’ trademarks. He seeks to devalue the Bored Ape NFTs by flooding the NFT market with his own copycat NFT collection using the original Bored Ape Yacht Club images and calling his NFTs “RR/BAYC” NFTs. Brazenly, he promotes and sells these RR/BAYC NFTs using the very same trademarks that Yuga Labs uses to promote and sell authentic Bored Ape Yacht Club NFTs. He also markets these copycat NFTs as falsely equivalent to an authentic Bored Ape Yacht Club NFT. He then goes on to use Yuga Labs’ marks to promote his coming “Ape Market” NFT marketplace, which requires a person to purchase one of his infringing NFTs to join the Ape Market. This is no mere monkey business. It is a deliberate effort to harm Yuga Labs at the expense of consumers by sowing confusion about whether these RR/BAYC NFTs are in some way sponsored, affiliated, or connected to Yuga Labs’ official Bored Ape Yacht Club, in violation of the Lanham Act and related state law. Yuga Labs brings this action against Ripps and others involved in perpetrating his scam to dispel the confusion he has caused in the marketplace, to protect the goodwill in authentic Bored Ape NFTs and the Bored Ape Yacht Club, to protect members of the NFT community from being deceived into thinking they are purchasing a highly coveted Bored Ape NFT, and to protect the general public from deceptive commercialization or use of RR/BAYC NFTs that would lead consumers to believe those NFTs are official Bored Ape NFTs. Ripps claims his actions are “satire,” yet he conveniently rakes in millions in ill-gotten profit from sales of the RR/BAYC NFTs using Yuga Labs’ marks to make those sales. Copying is not satire, it is theft. And lying to consumers is not conceptual art, it is deception. Ripps, Cahen, and Does 1-5’s website (https://rrbayc.com) claims that minting exact replicas of Yuga Labs’ Bored Ape NFTs and reselling them at a profit is “satire.” In reality, this is part of a longstanding harassment campaign against Yuga Labs and an attempt to devalue the price of authentic Bored Ape NFTs. At the same time, Ripps, Cahen, and Does 1-5 stand to make millions of dollars by tricking consumers into buying these fake Bored Ape NFTs. Indeed, on information and belief, Ripps has made well over $5 million through this scheme of pumping and dumping fake NFTs. There is also a part specifically for all those who have bought RR BAYC too… Defendants Does 6-10 have joined Ripps, Cahen, and Does 1-5 in acting to devalue authentic Bored Ape NFTs through their participation in social media in promoting the RR/BAYC NFTs while knowing them to be fake. Their specific actions will be alleged when and if their identities are ascertained. Will leave in case you’d like to dive into it deeper. the link to all public documents here There are tons of documents and evidence in there. In January 2023, Yuga filed a complaint against Thomas Lehman, focusing on his role in coding and developing the RR BAYC contract and the rrbayc.com site. In February, they reached a settlement (source: ). Coindesk I guess we won’t know what they had agreed on though. In April 2023, Yuga Labs won summary judgment. But the court decided that any damages would be calculated and determined during the trial. The trial And here we are, just a week after the trial. The trial was open to the public, and Pauly encouraged their supporters to show up in a tweet mentioning it a few times on Twitter Spaces too. https://twitter.com/Pauly0x/status/1684566734181920768?s=20&embedable=true There was a bit of citizen journalism going on, so many were following the developments in real-time, reading the tweets, and watching videos from the breaks. Here are both parties arriving at the court: When I started researching this story, I reached out to the Twitter audience to get more information and details. As a result, I personally spoke to 10+ people who were at the trial to find out more details and write this part. All of them were there to support Ryder and Jeremy. They all discovered RR BAYC at different times (from the 1st day, after following Pauly through Pepe, after watching the video, etc.), but all were united by their beliefs. People had traveled from Washington, Miami, and Arizona to be there in person and show their support. Here are just a few of them below, explaining why they decided to be there. This guy flew from Miami. And he also brought his framed RR BAYC with him to the trial. People I spoke to thought everyone from the Yuga Labs side was paid to be there - i.e., mostly from their legal team, hired experts, etc. and no one from the public came to support them. I reached out to Yuga Labs and did not get a response, so unfortunately, there will be no way of presenting their side of the story here. Most of the people I spoke with were on the same page when they were sharing their impressions and observations. I tried to summarize them below: Ryder Ripps did not get a chance to speak. He was asked 1 question only. Being the “hero of the story,” it felt strange to me… When I asked Ryder’s mother: Helene Verin, who was there too, why she thinks that was, she responded: It's obvious; Ryder was so articulate in his deposition, they didn't want him to explain his protest. Jeremy, though, was questioned for 30-40 minutes, and he was very calm and confident. Greg Solano (one of Yuga Lab's co-founders) admitted that the theme of their brand is “scatological” in nature and that Bored Ape Yacht Club is a luxury brand. Quoting one of the supporters below (a sentiment/impression I got from several in different phrasing) I was shocked that Nicole Munoiz (x CEO of Yuga Labs) didn’t even know her own company’s terms . The way certain YUGA witnessed lied on the stand and then we’re quickly reminded of their lies via their deposition was insane. I can’t believe it. It was embarrassing. They really shamed themselves that day. Yuga Labs brought around 13 boxes of printed evidence There were some laughs and giggles during Yuga Labs’ testimony Yuga Labs have spent tons of money (around $600k?) to hire experts to prove that people were confused and bought RR BAYC thinking they were buying BAYC The story is not over yet, and it’s hard to predict what would the decision about the damages be. I believe that the law will find its way. I believe that things will be reconciled. Reconciled because the main business of Yuga Labs is illegitimate. They promise you “IP” — intellectual property if you own one of these NFTs and there is no boundaries of how that intellectual property can be used. I think that’s the most fascinating thing in all of this. Yuga’s examples of IP are poop videos and penises on a bathroom wall. Everybody else, whom Yuga Labs celebrates is using their IP to make marijuana products, kids toys, clothing, pillows, socks, anything you could think of… So in what world is there a guideline? The spectrum of how you can use your IP is wide. If you want to utilize your IP to make criticisms of the company, why can’t you? (a witness from Ryder’s side at trial) _ @hWonderofWorld The rabbit hole with this story seems too deep, and this story just scratched the surface. Meanwhile, it feels like we are living at times when memes are used as “serious” evidence in court, and people keep meme-ing anyway. That was all for this week's Rebels! Disclaimer: I am not a lawyer and qualified in legal matters, so all I have in this story is what I managed to research and comprehend: feel free to correct if needed. I also have not owned and don’t own RR/BAYC at the moment. Also published . here

Yuga Labs Sues Ryder Ripps, Jeremy Cahen, and DOES 1-10: This is Not Monkey Business

A Content-Rich Q&A Session - Star Japanese Web3 Fund, Meteorite Labs, Uncovers How to Penetrate and Integrate into the Japanese Market Hello everyone, it's a pleasure to engage in a discussion about the Japanese market with you. Today, our conversation will focus on the nuances of the Japanese Web3 market, particularly in relation to project operations. I'm delighted to introduce our esteemed guest, who is deeply involved in the Japanese Web3 market. Umi possesses significant industry experience in Japan and is a highly regarded Web3 professional. This dialogue will allow us all to gain a deeper understanding of the Japanese market and provide insights that may prove helpful for project operators seeking to enter this market. Firstly, I'd like to invite Umi to introduce herself and answer the inaugural question of this session: : HOST From your personal experiences living and working on projects in Japan, could you identify some unique features and trends within the Japanese Web3 market? How do these aspects influence the operation of projects? Hello everyone, I'm Umi. I'm the BD Lead of Meteorite Labs based in Japan. Meteorite Labs is not just a foundation, but also functions as an incubator. As an early-stage Web3 investment fund, our portfolio boasts an impressive line-up, including projects like Galaxy, Fusionist, and Stepn, all of which we had invested in at an early stage and introduced to Japan. : UMI Addressing your question about , two characteristics come to mind: . Japan has one of the highest levels of customer loyalty and purchasing power worldwide. Projects like Stepn and Fusionist, which I mentioned earlier, have been remarkably successful, gaining favor with platforms like Binance. Interestingly, during the early operational phase of the Stepn project, nearly half of its 800 users were Japanese. Even now, as the project has grown considerably, . what makes the Japanese market distinctive loyalty and purchasing power the Japanese still make up 20%-30% of its user base Why is this so? One possible explanation lies in the structure of Japanese households. Unlike Chinese families, which often consist of a single child, Japanese families typically have three to four children, in addition to parents. This means that if one family member begins using a service like Stepn, they are likely to share it with the rest of their family. It's not uncommon for entire families to engage with the platform, perhaps buying multiple pairs of shoes. This trend speaks volumes about the strong purchasing power inherent in the Japanese market. Take , for instance, our involvement was not just in the form of investment; we also assisted them with strategic planning for marketing in Japan. Leveraging our extensive experience in the Japanese market, Meteorite Labs was able to craft custom strategies for their venture into this region. After these strategies were implemented, . This has led us to believe that trust is crucial in the Japanese market. Once the consumers trust and know you, and find your project interesting and engaging, they'll remain loyal for a long time. Fusionist the company revealed that 30% of its user base is Japanese Recently, we invested in a game project: Mahjong Meta. We plan to continue aiding their expansion into the Japanese market, using our operational experience in the region. We'll open a brick-and-mortar mahjong parlor in Shibuya, which will serve as a gateway from Web2 to Web3, embedding the concept in the minds of Japanese users. We also have an example involving a . Our founder had previously assisted FTX Japan in cementing its foothold in the Japanese market. In its initial six months, FTX Japan didn't make a profit—it was purely an investment stage that required extensive market cultivation, . Hence, loyalty and purchasing power are distinct traits of the Japanese market. cryptocurrency exchange finding ways to establish trust and stimulate Japanese Users’ purchasing power Considering the user characteristics of the Japanese market you just mentioned, while there is a significant number of crypto users with considerable purchasing power, engaging these users presents its challenges. What are some effective strategies for customer acquisition in the Japanese market? How can we increase Japanese users' understanding of, and participation in, Web3 projects? : HOST From an operational standpoint, for example, with Stepn, Meteorite Labs has conducted numerous . These events were quite straightforward, allowing real users of Stepn to gather and form an organic community. The idea is not to have the project party exert significant effort in event planning but to let the community naturally converge, fueling user motivation. : UMI ground-level real-world events The social structure in Japan allows for a variety of tribes and communities, . This is a defining characteristic of society. During my university days in Japan, there were many community activities. Individuals often sought their sense of belonging and self-identity by participating in these communities and organizations. This approach holds for Stepn and our upcoming project, Mahjong Meta. We drive users to spontaneously form communities via various offline activities, thereby amplifying the brand's influence. fostering a sense of belonging for individuals For foreign projects entering Japan, . For instance, there's a renowned company called Bandai Namco in Japan, holding many famous IPs. We maintain a close collaboration with several well-known Japanese funds, such as Emoote and MZfund. Therefore, when we identify promising early-stage projects or projects we've previously invested in, Meteorite Labs can introduce them to these leading fund teams. These funds can then offer unique resources, such as recommending tailored activities, thus giving projects an opportunity to accurately identify their user base and engage more directly with users in the real world. partnering with local big corporations or notable investors is an excellent strategy It's widely known that, due to language habits and social-cultural differences, brand implantation in the Japanese market can be challenging—it's a relatively closed market. : HOST What's the most effective strategy for Web3 projects to establish brand awareness and promote projects in the Japanese market? How can they forge close connections and collaborations with local Japanese communities and homegrown projects? When a foreign project aims to penetrate the Japanese market, . Ideally, community moderators or core members should be Japanese, or at least, they should be fluent in Japanese. This approach helps foster a strong sense of camaraderie. Peace and safety are core values in Japan, which is why it's crucial. : UMI it is essential to establish a favorable and familiar impression Another key factor is the . It's vital to deeply understand their user base, the content they focus on, and their overall influence. To illustrate, there was a project that engaged a KOL named KazMax, known for negative content, during its promotional activities in Japan. This resulted in substantial harm to the project's brand in the early stages of its entry into the Japanese market. This underscores the importance of discerning the type of KOL during the selection process. comprehensive vetting of your Key Opinion Leader (KOL) In Japan, multiple small groups are formed by various KOLs, all supporting each other within different communities. Hence, if you engage a KOL and things become somewhat awkward, other high-quality KOLs might be reluctant to promote your project. This has happened in real life. . Consequently, discerning the abilities of KOLs is extremely important when promoting in the Japanese market For project developers, identifying the right KOL becomes a major challenge. Recognizing this, Meteorite Labs has invested in the Aki Network. On the surface, . It uses numerous indicators to assess an influencer's core influence. The platform not only measures the interaction data between influencers and users but also evaluates the derivative interactions that the influencer generates and the volume of referral data. This holistic approach assesses an influencer's account quality. All these precise records are maintained on the Aki platform, enabling project developers to understand their true capabilities as well as those of the influencers they collaborate with. Aki Network might seem like a tool for an event planning platform, but it differentiates itself by emphasizing the influencer's impact Mature project developers attach great importance to this aspect. Whether it's about entering the Japanese market or other international markets, you might collaborate with a famous KOL who has hundreds of thousands of fans, only to realize that the attention they generate is not as significant as anticipated. . Therefore, for projects looking to penetrate the Japanese market and establish close connections with KOLs, they can use tools like Aki Network to discern KOL's capabilities, thus saving cognitive costs. The Aki Network reveals this hidden information, allowing users and project developers to access this crucial information When dealing with cultural differences in the Japanese market, what challenges have your projects encountered? How have you addressed these challenges and successfully integrated into the local culture? : HOST Honestly, . Integrating into the Japanese market means investing time, building relationships, making friends, and fostering trust. Once trust is established, users will reveal many truths. However, this . Also, having Japanese team members or those fluent in Japanese who can connect deeply with people is beneficial. The majority of the Meteorite Labs team comprises Chinese who have lived in Japan for over a decade, so there are minimal cultural differences. : UMI it requires patience trust-building process takes time Meteorite Labs' founder, Melody, has many years of experience in this field. Before moving into investment, she helped many projects get listed on Japanese exchanges. For instance, she orchestrated IOST's listing on CoinCheck, marking the first overseas listing. She also has experience with exchanges and venture capital, giving her a comprehensive and multidimensional perspective of the Japanese market. As we've guided numerous projects into the Japanese market, we've identified several rules to follow. . This characteristic extends from the Web2 to Web3 era. . This is because our approach extends beyond just interacting with Key Opinion Leaders (KOLs) and fostering their trust and loyalty; it's also about helping the mainstream users to gradually accept and embrace the project. In this field, Meteorite Labs brings extensive experience and a rich array of resources to the table. Also, the Aki Network, as mentioned earlier, can serve as an effective and streamlined tool for ventures looking to infiltrate and broaden their reach within the Japanese market. Should anyone harbor an interest in Japanese local funds or community resources and desire to delve deeper into these topics, I extend an open invitation for contact and communication. The core of Japanese culture values quality, rejects impulsiveness, and embodies the spirit of a craftsman As a result, projects that lean towards hasty operations or a short-term, money-oriented approach may not find an easy fit within the Japanese market About Meteorite Labs Meteorite Labs is a fundamental research-driven crypto fund with extensive experience and connections in Asia, particularly Japan. Its multidisciplinary team combines expertise in investment, marketing, mathematics, data analysis, arts, game industry, and law. Meteorite Labs invests in venture and liquid opportunities within the blockchain sector through intensive research, investigation, and data analytics. We actively evaluate blockchain projects and ecosystems, with a focus on those that instill positive values in the web3-based world economy and experience, as well as the bridges between them. About Aki Network Aki Network is the first Web3 growth stack to track real promotion performances of crypto influencers with on-chain data-driven products. Since its launch in July 2022, Aki Network has been growing rapidly, collaborating with 200+ campaigns while connecting them with 2400+ network influencers and 310k+ community members via 303k+ successful user referrals. Aki Network's approach to data-driven influencer marketing, combined with its strong network of influencers and community members, makes it an indispensable asset for businesses looking to grow in the Web3 space. In-Person Contact Telegram： BD Director Meteorite Labs Founder | @Umiii_xh @melodysyz This story was distributed as a release by web3.com under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author

Unlocking the Japanese Market: Insights from Star Web3 Fund, Meteorite Labs 

Desbloqueo del mercado japonés: perspectivas de Star Web3 Fund, Meteorite Labs

Déverrouiller le marché japonais : perspectives du fonds Star Web3, Meteorite Labs

जापानी बाज़ार को खोलना: स्टार वेब3 फंड, उल्कापिंड लैब्स से अंतर्दृष्टि

日本市場の開拓: Star Web3 Fund、Meteorite Labs からの洞察

Desbloqueando o mercado japonês: insights do Star Web3 Fund, Meteorite Labs

Mở khóa thị trường Nhật Bản: Thông tin chi tiết từ Quỹ Star Web3, Phòng thí nghiệm thiên thạch

解锁日本市场：Star Web3 Fund、Meteorite Labs 的见解

Metamorphosis Commenced: Network States v0.01

মেটামরফোসিস শুরু হয়েছে: নেটওয়ার্ক স্টেটস v0.01

Beginn der Metamorphose: Netzwerkzustände v0.01

Metamorfosis comenzada: Estados de la red v0.01

La métamorphose a commencé : États du réseau v0.01

मेटामोर्फोसिस शुरू हुआ: नेटवर्क स्टेट्स v0.01

変態開始: ネットワーク状態 v0.01

변형 시작됨: 네트워크 상태 v0.01

Metamorfose iniciada: Estados de rede v0.01

Метаморфоза началась: Состояния сети v0.01

Metamorfoz Başladı: Ağ Durumları v0.01

Bắt đầu biến thái: Trạng thái mạng v0.01

蜕变开始：网络状态 v0.01

The contemporary discourse on generative Artificial Intelligence (AI) presents a nuanced and dualistic narrative of technological development. I will delve into contrasting perspectives surrounding the current state and future of generative AI, juxtaposing the pervasive sentiments of disillusionment against the sustained advancements in the field. Notably, despite apparent stagnation in some sectors and declining public interest, significant strides in AI technology and applications continue to emerge. This analysis provides a nuanced examination of the cycle of hype, stabilization, and potential revolutionary impact of generative AI, comparing it with historical technological disruptions such as the printing press, electricity, and the internet. Through a balanced review of both setbacks and breakthroughs in the AI landscape, I aim to discern whether generative AI is merely experiencing a temporary lull or if it signifies a broader technological revolution. By critically assessing the evidence and forecasting future trends, the article also explores the implications of this technology on societal norms and industry practices, ultimately questioning the revolutionary potential of generative AI amidst ongoing challenges and evolving expectations. Economic Performance and Market Valuations Recent data suggest that the economic outcomes related to generative AI have not aligned with prior expectations. For instance, despite significant investments in hardware, such as the $50 billion spent on Nvidia equipment, the return, in terms of revenue, has been relatively modest, amounting to only $3 billion (The Wall Street Journal). Additionally, there is a notable stagnation in visits to AI-focused websites (Exponential View), and venture capital firm Sequoia has highlighted the overvaluation of AI startups, suggesting a disconnect between market valuations and underlying economic realities (The Information). Industry Challenges and Strategic Adjustments Several high-profile AI startups have experienced difficulties, signaling potential instability within the sector. For example, InflectionAI has been effectively disbanded, with Microsoft acquiring its assets, including the expertise of former CEO Mustafa Suleyman (TechCrunch). Moreover, StabilityAI faces uncertain prospects following leadership controversies (Forbes). Additionally, the broader enterprise adoption of AI technologies is hampered by concerns over security and ethical implications (Diginomica). Public Perception and Technological Engagement While the initial public enthusiasm for AI technologies like ChatGPT has waned, a subset of users, particularly software developers, continue to find value in these tools (Pew Research Center). This contrasts with the broader perception that AI tools serve more as novelties rather than practical aids in productivity (The Register). Innovative Developments and Future Prospects Despite these challenges, the development of AI technologies continues at a rapid pace. New models like Claude 3 from Anthropic are setting benchmarks in AI capabilities (Anthropic). The field also anticipates the arrival of advanced models such as OpenAI's GPT-5, signaling ongoing innovation and potential market recovery (Business Insider). Historical Perspective on Generative AI Development Tyler Cowen, in his analysis, proposes that the current state of AI reflects a natural progression seen in other revolutionary technologies. Drawing parallels to the adoption of the printing press, electricity, and the internet, Cowen suggests that the lifecycle of transformative technologies typically transitions through phases of hype, stabilization, and eventual widespread utility. This pattern, he argues, is evident in the current trajectory of generative AI technologies (Bloomberg). Cowen articulates that while the initial excitement surrounding generative AI has diminished—a phase characterized by inflated expectations and speculative investments—the underlying advancements in technology continue to progress significantly. This 'silent lull' is not a regression but a recalibration of expectations as the technology matures and integrates more deeply into various sectors. Generative AI, despite facing skepticism regarding its immediate impacts, mirrors the developmental paths of its historical counterparts. Notably, the internet, post-dot-com bubble, and the gradual integration of electricity into industrial processes both experienced periods of underwhelming performance followed by significant, long-term contributions to economic and social structures. Recent developments in AI technology further support Cowen's thesis. OpenAI's enhancement of enterprise services and the advancement of models like Google's GPT-4 competitor illustrate ongoing innovation within the field (ZDNet, Google). Moreover, the rapid progression of open-source AI models, although less visible to the casual user, underscores a robust, underlying growth in AI capabilities that continues to push the boundaries of what these technologies can achieve (Archive). The Path Forward Despite the optimism expressed by some industry leaders, there are notable challenges and setbacks that temper the enthusiastic projections about AI. Issues such as the slower-than-anticipated adoption rates in enterprises and the mixed results of new AI products like Google Gemini Advanced highlight the complex reality facing AI development (Diginomica, The Algorithmic Bridge). The question remains whether generative AI will indeed follow the transformative paths of its predecessors or diverge due to unique challenges and societal dynamics. The industry's ability to navigate these challenges, coupled with ongoing technical advancements, will likely determine the trajectory of AI's impact on society. Concluding Thoughts Generative AI's journey is marked by cycles of hype and recalibration, similar to earlier technologies. While immediate outcomes may seem underwhelming, the continued development and integration of AI into various sectors may very well underpin the next wave of significant technological and societal transformations. As with historical innovations, the true measure of AI's impact will likely be observed in hindsight, shaped by a complex interplay of technological capabilities, market forces, societal acceptance, and regulatory environments. References "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d
"Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620
"AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal
"Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/
"Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/
Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg
OpenAI introduces business version of ChatGPT - ZDNet
Challenges in AI adoption within enterprises - Diginomica
Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge The contemporary discourse on generative Artificial Intelligence (AI) presents a nuanced and dualistic narrative of technological development. I will delve into contrasting perspectives surrounding the current state and future of generative AI, juxtaposing the pervasive sentiments of disillusionment against the sustained advancements in the field. Notably, despite apparent stagnation in some sectors and declining public interest, significant strides in AI technology and applications continue to emerge. This analysis provides a nuanced examination of the cycle of hype, stabilization, and potential revolutionary impact of generative AI, comparing it with historical technological disruptions such as the printing press, electricity, and the internet. Through a balanced review of both setbacks and breakthroughs in the AI landscape, I aim to discern whether generative AI is merely experiencing a temporary lull or if it signifies a broader technological revolution. By critically assessing the evidence and forecasting future trends, the article also explores the implications of this technology on societal norms and industry practices, ultimately questioning the revolutionary potential of generative AI amidst ongoing challenges and evolving expectations. Economic Performance and Market Valuations Economic Performance and Market Valuations Recent data suggest that the economic outcomes related to generative AI have not aligned with prior expectations. For instance, despite significant investments in hardware, such as the $50 billion spent on Nvidia equipment, the return, in terms of revenue, has been relatively modest, amounting to only $3 billion ( The Wall Street Journal ). Additionally, there is a notable stagnation in visits to AI-focused websites ( Exponential View ), and venture capital firm Sequoia has highlighted the overvaluation of AI startups, suggesting a disconnect between market valuations and underlying economic realities ( The Information ). The Wall Street Journal Exponential View The Information Industry Challenges and Strategic Adjustments Industry Challenges and Strategic Adjustments Several high-profile AI startups have experienced difficulties, signaling potential instability within the sector. For example, InflectionAI has been effectively disbanded, with Microsoft acquiring its assets, including the expertise of former CEO Mustafa Suleyman ( TechCrunch ). Moreover, StabilityAI faces uncertain prospects following leadership controversies ( Forbes ). Additionally, the broader enterprise adoption of AI technologies is hampered by concerns over security and ethical implications ( Diginomica ). TechCrunch Forbes Diginomica Public Perception and Technological Engagement Public Perception and Technological Engagement While the initial public enthusiasm for AI technologies like ChatGPT has waned, a subset of users, particularly software developers, continue to find value in these tools ( Pew Research Center ). This contrasts with the broader perception that AI tools serve more as novelties rather than practical aids in productivity ( The Register ). Pew Research Center The Register Innovative Developments and Future Prospects Innovative Developments and Future Prospects Despite these challenges, the development of AI technologies continues at a rapid pace. New models like Claude 3 from Anthropic are setting benchmarks in AI capabilities ( Anthropic ). The field also anticipates the arrival of advanced models such as OpenAI's GPT-5, signaling ongoing innovation and potential market recovery ( Business Insider ). Anthropic Business Insider Historical Perspective on Generative AI Development Tyler Cowen, in his analysis, proposes that the current state of AI reflects a natural progression seen in other revolutionary technologies. Drawing parallels to the adoption of the printing press, electricity, and the internet, Cowen suggests that the lifecycle of transformative technologies typically transitions through phases of hype, stabilization, and eventual widespread utility. This pattern, he argues, is evident in the current trajectory of generative AI technologies ( Bloomberg ). Bloomberg Cowen articulates that while the initial excitement surrounding generative AI has diminished—a phase characterized by inflated expectations and speculative investments—the underlying advancements in technology continue to progress significantly. This 'silent lull' is not a regression but a recalibration of expectations as the technology matures and integrates more deeply into various sectors. Generative AI, despite facing skepticism regarding its immediate impacts, mirrors the developmental paths of its historical counterparts. Notably, the internet, post-dot-com bubble, and the gradual integration of electricity into industrial processes both experienced periods of underwhelming performance followed by significant, long-term contributions to economic and social structures. Recent developments in AI technology further support Cowen's thesis. OpenAI's enhancement of enterprise services and the advancement of models like Google's GPT-4 competitor illustrate ongoing innovation within the field ( ZDNet , Google ). Moreover, the rapid progression of open-source AI models, although less visible to the casual user, underscores a robust, underlying growth in AI capabilities that continues to push the boundaries of what these technologies can achieve ( Archive ). ZDNet Google Archive The Path Forward The Path Forward Despite the optimism expressed by some industry leaders, there are notable challenges and setbacks that temper the enthusiastic projections about AI. Issues such as the slower-than-anticipated adoption rates in enterprises and the mixed results of new AI products like Google Gemini Advanced highlight the complex reality facing AI development ( Diginomica , The Algorithmic Bridge ). Diginomica The Algorithmic Bridge The question remains whether generative AI will indeed follow the transformative paths of its predecessors or diverge due to unique challenges and societal dynamics. The industry's ability to navigate these challenges, coupled with ongoing technical advancements, will likely determine the trajectory of AI's impact on society. Concluding Thoughts Concluding Thoughts Generative AI's journey is marked by cycles of hype and recalibration, similar to earlier technologies. While immediate outcomes may seem underwhelming, the continued development and integration of AI into various sectors may very well underpin the next wave of significant technological and societal transformations. As with historical innovations, the true measure of AI's impact will likely be observed in hindsight, shaped by a complex interplay of technological capabilities, market forces, societal acceptance, and regulatory environments. References "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d "Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620 "AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal "Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ "Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg OpenAI introduces business version of ChatGPT - ZDNet Challenges in AI adoption within enterprises - Diginomica Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d "Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620 https://substack.com/@exponentialview/note/c-52677620 "AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal "Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ "Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg Bloomberg OpenAI introduces business version of ChatGPT - ZDNet ZDNet Challenges in AI adoption within enterprises - Diginomica Diginomica Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge The Algorithmic Bridge

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