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Lima labs - Crunchbase Company Profile & Funding

Lima Labs is a leading African AI company recognized at TechCrunch for our approach to helping growers reduce their CO2 emissions while increasing their profitability. What&#x27;s our secret 🤫 Help growers better match their supply and demand... How? 1. 🍏 Clean infield data collection: We ...

Lima Labs | LinkedIn

Information on valuation, funding, cap tables, investors, and executives for Lima Labs. Use the PitchBook Platform to explore the full profile.

Lima Labs Company Profile: Valuation & Investors | PitchBook

Lima Labs is a Kenyan-based artificial intelligence (AI) technology company that provides Kenyan farmers with a machine vision system making their farms smarter and more predictable.

Engineer deploys AI to make Kenyan farms smarter - Business Daily

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Lima Labs LLC in Trumbull, CT | Company Information & Reviews

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Lima Labs Careers | AngelList Talent

The Lima laboratory studies mechanisms underlying RNA processing as well as post-translational protein modification by ubiquitin-like proteins.

The Christopher Lima Lab | Sloan Kettering Institute

Life without sex and reproduction would not only be less interesting, it would be impossible. Yet, despite its importance for the existence of the species, unlike feeding, it is not actually necessary for the survival of the individual. Still, nature developed “ways” to ensure animals do ...

Lima Lab | Neuroethology Lab

Startup incubated at IIT Madras. We offer Courses, Training &amp; Workshops on emerging technologies such as Robotics, Embedded Systems, Internet of Things (IoT), Data Science &amp; Machine Learning.

Lema Labs | Incubated at IIT Madras Incubation Cell

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The Lima Lab’s research is concentrated on the development and application of imaging and technology to address scientific and clinical problems involving the heart and vascular system. Specifically, our research is focused on developing magnetic resonance imaging (MRI) contrast techniques ...

Lima Lab | Johns Hopkins Medicine

Saving farmers time and money with AI powered computer vision.

About Lima Labs - Agriculture company in Kenya

Lima turns commercial farms into data-driven, predictable, demand-based producers.

Lima Labs

This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Mathias-Felipe de-Lima-Santos, Faculty of Humanities, University of Amsterdam, Institute of Science and Technology, Federal University of São Paulo; (2) Wilson Ceron, Institute of Science and Technology, Federal University of São Paulo. Table of Links Abstract & Introduction Data and Methods Results Discussion and Conclusions Funding and References Funding This project was partially funded by the University of Amsterdam’s RPA Human(e) AI and by the European Union’s Horizon 2020 research and innovation programs No 951911 (AI4Media). References (1) Sunstein, C. R. #Republic: Divided Democracy in the Age of Social Media; Princeton University Press: Princeton, New Jersey, 2017. (2) Garimella, K.; De Francisci Morales, G.; Gionis, A.; Mathioudakis, M. Political Discourse on Social Media. 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Disinformation Echo-Chambers on Facebook: Funding and References

In 2021, hosted the first-ever awards!! HackerNoon Startup of the Year The goal of this campaign was to give recognition to the hardworking startups who pulled through the pandemic -- growing and thriving (despite all of the challenges). More than 44,000 startups were nominated all across the globe! They were selected from over 4,553 cities, with a total number of * cough * “4 billion” votes. Insane, right? To see who is a winner in each respective city, visit and pick a city. The name at the top of the list is the winner. (Awards, with compromised reviews, are under review.) startups.hackernoon.com The will announce the winners per region in their respective cities. Startups Winners Announcement Series Apparently, South America startups did incredibly well in that regard. With so many, until now, uncrowned jewels, it’s time we present to you... * drumroll* 🥳 The South America Startups of the Year Winners! Santiago, Chile Chile is known for being the most stable country to do business in Latin America, ranking 13th in The Economist’s Business Environment Index. Moreover, according to the Global Innovation Index, Chile ranks first in Latin America for innovation and is recognised as Chilean Silicon Valley with Santiago being the central city. The winner is…. QCObjects It is the 1st world class open-source framework made in Latin-America. São Paulo, Brazil And the winner of Brazil’s vibrant financial center is... Innvo Digital Their mission is to create the best ecosystem for a technology professional to work and undertake while sharing it with our customers and society. São Carlos The absolute leader of Sao Carlos seems to be: Predify Predify is an online software for optimizing pricing proccess and improving profits with AI and Big Data Analytics. Belo Horizonte, Brazil With a more than noble goal, Belo Horizone’s winner is: CM Tecnologia CM Tecnologia is an online scheduling system for healthcare providers in Brazil. Porto Alegre, Brazil With the focus on data protection, Porto Alegre, Brazil’s winner is…. Privacy Tools Privacy compliance platform, based on AI/Blockchain, which helps global companies to keep compliant with the data protection requirements. Brasil, Brazil With the focus on EdTech, Brasil is bringing us: Awari Awari is a YC-W21 company focusing on education for the Tech Industry. The company is growing at a fast pace and has gathered experts from all leading tech companies into a full education experience to prepare the next cohort of tech talent. Quito The capital of Ecuador, and also the closest capital to the actual equator, as the winner brings us: Agrodemanda The most comprehensive agricultural directory in Ecuador. Rio De Janeiro, Brazil Rio de Janeiro has more than 300 startups and is ranked 3rd in Brazil in terms of startup ecosystem development. The city is famous for the startups in the spheres of education, energy & environment and foodtech. Their winner is…. Bybrand Bybrand is the simplest way to save time and avoid frustration when managing your employee's email signatures. Buenos Aires, Argentina Buenos Aires, Argentina is not only the cosmopolitan capital with a vibrant history. It’s also Latin America’s most important port. Which makes their winner actually a very logical choice. Please meet: Liftit Liftit is the leading technology platform to automate and execute last-mile truck deliveries across Latin America. Curitiba, Brazil With a more noble mission and sustainability in mind, Curitiba, Brazil, as the winner brings us... Discrepante is the marketplace for a more human and sustainable economy Discrepante.com Florianópolis, Brazil Would you really be surprised one of the Brazil’s winners is related to football training? We neither. Please meet... Fútbol Fit Club Football FitClub® is a fitness training firm that gives fitness training to improve like a professional football player. Medellín, Colombia And the first Colombian Startup Winner is is a data intelligence solution powered by a high quality team. Meet... LogComex Market intelligence for international trade in Latin America Montevideo, Uruguay The host of inaugural FIFA world cup of 1930 comes through when it comes to innovation even in 2021. I’d like to introduce you to: Drop Technologies First electronic hand antiperspirant device Lima, Peru Lima, Peru, has in 2021 delivered some amazing results when it comes to blockchain technology. Their winner is very well deserved: RSK Labs RSK is the first open-source smart contract platform São Carlos Do Pinhal Well this is a unique case. The absolute unanimous winner of São Carlos Do Pinhal is: brain4care brain4care solution enables monitoring intracranial compliance noninvasively anywhere Blumenau, Brazil We’re sensing a theme here. Another stellar EdTech winner is coming from Blumenau, Brazil. Please meet... Uniasselvi Uniasselvi is a Brazilian distance-learning company that offers more than 60 undergraduate and postgraduate courses, in person and distance. Bogotá, Colombia Startups of Bogotá, Colombia definitely showed they’re not to be underestimated. With a very noble mission, let me introduce you to: Risü Risü is an online platform that links online consumption to donation to social institutions. Campina, Brazil If there’s one typo of business we’d single out as taking the biggest hit out of the pandemic, it would have to be small businesses. Thankfully, the winner of Campina, Brazil, operates with small businesses in mind Superlógica Tecnologias Ltda. Superlogica is a management system company created for small service businesses. Cerqueira César, Brazil Swooping half the points from the entire City, this year’s winners of Cerqueira César are InfoPrice INFOPRICE is a business intelligence company focused on physical retail pricing. Governador Valadares, Brazil The same can be said for the winners here. Let’s hear it for: Grupo KPG Saas, Payment, Manufacture, Pharmaceutical, E-commerce, Marketplace, Logistics Caxias Do Sul Known for wine making and Italian cultural influence, Caxias Do Sul brings as an interesting winner. Studio 360 Studio 360 is a proptech focused on easing the purchase experience for real state companies, brokers, and costumers. Sorocaba From Sorocaba, we have an interesting concept coming. Looking forward to seeing it further develop. Let’s meet: Quinto Quinto is a social network that represents the collective opinion of society—to help democracy evolve through technology Viña Del Mar To be a venue-oriented business and survive through the pandemic definitely deserves some recognition. In the name of that, let’s meet: SonicPollen SonicPollen, based in Chile, is a web-based booking platform that connects bands with venues and organizers. Lages Learn more about high-growth startups in Lages, South America. and the winner is…. Qualiall Qualiall develops technologies for training in operational processes such as work security, equipment maintenance, and more. Córdoba, Argentina Another gem from Argentina brings us unique agricultural solutions. Please meet: Kilimo Kilimo is a Big Data solution for water management in agriculture. São José Dos Campos, Brazil Another great agricultural solution comes this time from Brasil. Meet São José Dos Campos Startup winner: TerraMagna TerraMagna is a fintech company that focuses on risk mitigation for agribusinesses. São Leopoldo, Brazil Event-oriented businesses that have survived in the previous years should definitely bottle their perseverance and start selling it. One of those is definitely this winner: Wedy Wedy offers a one-stop-social marketplace for weddings. Pelotas, Brazil Medical scheduling platforms are definitely something we need to see more of. So glad Pelotos winner comes from this particular niche. Fácil Consulta Fácil Consulta is a booking platform that allows people to schedule an appointment with a Specialist Physician in their area. Santa Maria Could you believe how versatile the startups of South America are when we are only now coming across a game development studio? Let’s meet them Imgnation Studios Imgnation Studios is a game development studio that focuses on virtual reality. Asunción, Paraguay A FinTech solution coming from Paraguay. Meet Asunción Startup of the Year winner Vision Banco Vision Banco is a solid and growing financial institution serving the financial needs of the micro, small and medium enterprises. Caracas Venezualan food delivery app that seemed to have your heart. Meet Caracas Startup of the Year winner Yummy Inc. First Food Delivery App in Venezuela Recife A suitable combo between gaming and education, Recife Startup of the Year winner brings revolutionary solutions. Let’s meet them. Joy Street Joy Street offers develops video games focused on educational needs. Rosario, Argentina The winner of Rosario Startup of the Year award for 2021 is... Gbot Gbot is an autonomous robot that controls weeds without using agrochemicals. We also collect data in fields and generate precision maps. Vila Olímpia, Brazil The winner of Vila Olímpia Startup of the Year award for 2021 is... Seekr Seekr operates in the Information Technology sector, providing tools for managing and monitoring of brands. Barueri The winner of Barueri Startup of the Year award for 2021 is.... Glic Brazilian mhealth (web/app) platform for diabetes management Brasília The winner of Brasília Startup of the Year award for 2021 is... Ticies Ticies is a social network that helps people plan where to go with their friends, relatives and acquaintances, in all cities of the world. Juiz De Fora The winner of Juiz De Fora Startup of the Year award for 2021 is... Qranio Qranio is a gamified mobile learning platform for enterprises that rewards learning and stimulates users to engage with educational content. La Paz The winner of La Paz Startup of the Year award for 2021 is... Jukumari Advice 360 photo based market place for responsible tour operators Temuco The winner of Temuco Startup of the Year award for 2021 is... GoFeels GoFeels is the first independent hospitality network in the world. We promote collaborative work among hotels around the world. Vitacura The winner of Vitacura Startup of the Year award for 2021 is... MeatMe MeatMe delivers meats and accessories to have a culinary experience. Barranquilla The winner of Barranquilla Startup of the Year award for 2021 is... Mandaos Mandaos is a digital platform that connects companies and people with a network of independent messengers Ceará The winner of Ceará Startup of the Year award for 2021 is... Caroá Caroá is a cooperative that sells 34 varieties of vegetables, organic fruits, and vegetables. Chapecó The winner of Chapecó Startup of the Year award for 2021 is... HortiAgro HortiAgro is a seed and fertilizer market. Chile Chico The winner of Chile Chico Startup of the Year award for 2021 is... Gleengo Gleengo connects children with their favorite toys, through a tiny device and an application based on text-to-voice. Goiânia The winner of Goiânia Startup of the Year award for 2021 is... Auvo Auvo is an external teams management software. Itá The winner of Itá Startup of the Year award for 2021 is... TISSUELAB Tissuelab is a research and development center focused on biotechnology, and systems for reconstructive musculoskeletal surgery. Jardim Paulista The winner of Jardim Paulista Startup of the Year award for 2021 is... DiviCom DiviCom is a digital video networking company that designs, integrates, and markets complete systems. João Pessoa The winner of João Pessoa Startup of the Year award for 2021 is... YupiPlay YupiPlay develops and offers an educational gaming platform. La Reina The winner of La Reina Startup of the Year award for 2021 is... INTI-TECH INTI-TECH is the fastest growing renewable energy in Chile and the world's leading unconventional source. Leme The winner of Leme Startup of the Year award for 2021 is... EcoStart EcoStart focuses on manufacturing sustainable electric bicycles, fans, and accessories. Loja The winner of Loja Startup of the Year award for 2021 is... Enerwi Corporation Keeping people connected and secured through wireless charging novel solutions Manizales The winner of Manizales Startup of the Year award for 2021 is... Porter Metrics Porter Metrics has developed an automated solution for generating social media reports in minutes. Nova Lima The winner of Nova Lima Startup of the Year award for 2021 is... Biomimetic Solutions Biomimetic Solutions is an innovative tissue engineering company. Paraná The winner of Paraná Startup of the Year award for 2021 is... Laura Laura is a provider of artificial intelligence and predictive analytics platform for hospitala and clinics to prevent damage & reduce costs. Salvador The winner of Salvador Startup of the Year award for 2021 is... Sanar Sanar is a platform that focuses on being the doctor's guide and support, offering specialized content that helps in their development. Santa Catarina The winner of Santa Catarina Startup of the Year award for 2021 is... DrPOCKET Sunchales The winner of Sunchales Startup of the Year award for 2021 is... Eolo Pharma Eolo Pharma focuses on developing drugs targeting the molecular and cellular basis of inflammation-related diseases Valparaiso The winner of Valparaiso Startup of the Year award for 2021 is... Invitta Invitta transforms plastic waste into a high-performance construction material for manufacturing sustainable urban furniture. Vila Velha The winner of Vila Velha Startup of the Year award for 2021 is... OneGrid OneGrid is a developer of hardware and software solutions focused on energy management. Indaiatuba The winner of Indaiatuba Startup of the Year award for 2021 is... DWUL Energy Renewable Energy Campinas, Brazil The winner of Campinas Startup of the Year award for 2021 is... Ativy Ativy is an IT company specialized in cloud computing, data centers, IT outsourcing, service desk, and IT management. Las Condes, Chile The winner of Las Condes Startup of the Year award for 2021 is... # MuvPass Subscription services that allows it's users unlimited access to fitness classes in the best gyms and studios in Latin America. Pinheiros, Brazil The winner of Pinheiros Startup of the Year award for 2021 is... GuiaBolso GuiaBolso is a personal finance platform that empowers people to take control of financial well-being. Rio, Brazil The winner of Rio Startup of the Year award for 2021 is... EmCasa EmCasa is a vertically-integrated platform that helps customers buy and sell a home in Latin America, starting in Brazil. Guayaquil The winner of Guayaquil Startup of the Year award for 2021 is... Sabroso Online platform for LatAm's enterprises to order low-cost meals Jundiaí The winner of Jundiaí Startup of the Year award for 2021 is... Sintecsys Sintecsys offers a fast and effective detection, reducing losses and costs with fire brigades. Minas Gerais The winner of Minas Gerais Startup of the Year award for 2021 is... Rizoflora Biotechnology Rizoflora Biotechnology is a producer of biological product designed for nematodes control. São Caetano Do Sul The winner of São Caetano Do Sul Startup of the Year award for 2021 is... Wevo 1 iPaaS in Latam - Enabling companies to be truly digital companies with APIs, systems and data integrated into a single platform Canoas The winner of Canoas Startup of the Year award for 2021 is... ContaÁgil ContaÁgil facilitates and reduces bureaucracy in accounting routines of companies. Chile The winner of Chile Startup of the Year award for 2021 is... Unight Unight is the future of nightlife social media. Israelândia The winner of Israelândia Startup of the Year award for 2021 is... Matchpool Matchpool is a platform that creates human connections. La Plata The winner of La Plata Startup of the Year award for 2021 is... Pixivus Pixivus offers a community-based application that enables its users to collect, store, and share pictures of events. Novo Hamburgo The winner of Novo Hamburgo Startup of the Year award for 2021 is... Devorando Devorando offers an online food ordering system and menus available in restaurants based in Brazil. Pernambuco The winner of Pernambuco Startup of the Year award for 2021 is... Redu Redu is a distant learning platform which is built on a social networking structure. Providencia The winner of Providencia Startup of the Year award for 2021 is... # TrainFES TrainFES is a medical Devices for the rehabilitation of people with paralysis. Ribeirão Prêto The winner of Ribeirão Prêto Startup of the Year award for 2021 is... AllyHub Ally is a sales distribution channel technology that connects Schools and Service Providers with Education Agencies. Santa Cruz De La Sierra The winner of Santa Cruz De La Sierra Startup of the Year award for 2021 is... Mobi Latam Mobi Latam is a clean energy startup that focuses on transportation systems based on electric mobility. Santana De Parnaíba The winner of Santana De Parnaíba Startup of the Year award for 2021 is... MercadoLivre.com is an e-commerce technology company providing solutions to individuals and companies buying, selling, and more online. MercandoLivre.com More Information If you’re a winner, please answer ! If you’re a reader, participant, just a curious individual, consider answering one of our interviews . this interview here Read the FAQs about or . Startups here here To see all of the winners you may visit , pick any city and view the name that appears at the top. this site If you’re interested in partnering with us, we invite you to look through some of these or reach out to our business department. unique sponsorship options Perhaps creating your very own tickles your fancy or maybe you have a whole new idea for how we can partner! writing contest Thank you to all of our sponsors! We truly appreciate your contribution to the tech world and thus the future! The Startups Awards are sponsored by: , , , , , , , , , , Blockster Brex FreeCodeCamp LaunchDarkly Coil Udacity Udemy Vercel Asia Pacific Transgender Network Bybit Everscale Network This post was written/compiled by Shreya Kundu and Katarina Andrejević! If you have any questions or concerns or would like to report a discrepancy please email ellen@hackernoon.com.

Meet the Winners of Startups in South America

The world’s most independent tech publication, —where hackers start their afternoons, just partnered with to present : The Tech Industry's Greenest Awards. Hacker Noon Stream.io the inaugural Noonies 2019 "The Noonies! It’s time to vote on what matters in tech. Year after year these will serve as the definitive, international and somewhat democratic acknowledgement of all the best and worst people and/or products in technology today," someone overheard CEO David Smooke saying in an All-Hands meeting on Zoom recently. Divided across Hacker Noon’s three editorial categories— , , and , the first annual #Noonies aims to be a public recognition of both the contributing writers, community members, and readers who make Hacker Noon the best place for tech professionals to publish; as well as a great forum for all of us to up and/or downvote the brands, products and apps we use to build things every day. General Technology Crypto and Blockchain Software Development Scroll down for the full list of 50 # awards and 300+ nominees > to upvote your favourites! Noonies click through You can until August 16th, so go ahead and set a reminder to exercise your daily right to declare the best and worst of the world's technology industry. VOTE EVERY DAY FROM TODAY For the first week of voting, public award nominations remain open. Please note, your custom nominations are subject to review before being added. All Noonies 2019 Award Winners will be announced on August 21st. — #NOONIES 2019 GENERAL TECH AWARD NOMINEES Best Tech News Source Twitter Hacker News Reddit Developer News (freeCodeCamp) WIRED TechCrunch MIT Technology Review Product Hunt TechLoaf recode TLDR The World's Most Productive Remote Team GitLab InVision Basecamp Doist Automattic Buffer Zapier Knack Harvest Niteo Best Use of Tech for Good UpEffect CYCLE.LAND Nexus Labs Ethical Angel CryptoCare GIVALYTICS Kindred The Bait & Switch Award Medium's Paywall Upwork Apple's Butterfly Switch Keyboards Facebook's Libra Most Exciting Startup She.VC Everipedia Superhuman Food Alliance Hacker of the Year Pedro Lima Arthur Tkachenko Nirav Thomas galyna Mister Fahrenheit Betty Product Manager of the Year Lenny Rachitsky Marija Cvjetkovic Suketu Patel Vindhya C Abhishek Sharma John Cutler Dan Fedirko Josh Ben-David Claudio Cossio Alex Mitchell Antonio van der Weel Pramod Chandrayan Nancy Wang Timoté Geimer Momčilo Dakić Contributing Writer of the Year Cassie Kozyrkov Andreas Sandre Arthur Tkachenko Aditi Bhatnagar sudhanshu kumar Noam Levenson Technology Writer of the Year Ashan Fernando Arthur Tkachenko James Dargan Riz Virk Amanda Woo Chris Herd Chris Castiglione AI Writer of the Year Daniel Jeffries Akash Deep Tony Aubé Adrien Book Matt Swayne Cassie Kozyrkov Shreya Amin Most Over-Hyped Technology AI Docker GraphQL Meteor Cybersecurity Writer of the Year Han Yoon Mark Nadal Daniel Jeffries Alice Henshaw Drew Rossow Aaron Gershwin Best AMA (ask-me-anything) award Carlos Domingo Muneeb Ali Taylor Monahan Jean-Loïck Michaux (JLO) Jeff Atwood Courtland Allen Alicia Ferratusco Mike Kalomeni Paul Foley Shamir Karkal Richard Garcia & Michael Ambrosino Erik Zhang Social Network of the Year Twitter Instagram (by Facebook) Reddit Youtube WhatsApp (by Facebook) QQ Qzone Facebook Pinterest Messenger (by Facebook) WeChat AllSocial Cake Strava Most Valuable Chatbot Framework Watson Assistant Rasa Chatbots by PubNub Vergic Bold360 (by LogMeIn) Microsoft Bot Framework Wit.AI Rulai LivePerson Dialogflow (by Google) PandoraBots Botpress BotKit ChatterBot Messenger API (by Facebook) Enterprise Chatbot by Inbenta Ada 20 Under 20 Awards [ ] open nominations! White Hat of the Year [ ] open nominations! 60 Over 60 Awards [ ] open nominations! — #NOONIES 2019 CRYPTO / BLOCKCHAIN AWARD NOMINEES Most Hardcore Bitcoin Maximalist Hodlonaut Pierre Rochard Trace Mayer Francis Pouliot Jimmy Song Adam Back Giacomo Zucco Beautyon Tuur Demeester Vortex Adam Meister Tone Vays Gabriel D Vine Most crypto-friendly Jurisdiction Award Malta I'm an Institutional Investor. Jurisdictions are an artificial construct, Man. The Zug, Switzerland Estonia Belarus Crypto-Name Drop of the Year Eminem's Kamikaze Album Silicon Valley's story arc Forbes' coverage of Bitcoin Second-Best Crypto Publication on Earth John McAfee's Twitter Feed cointelegraph Coindesk CCN Tokenpost Crypto-Buzzword of the Year Bitcoin Maximalist DeFi Buidl Crypto-Winter Defining Crypto-Moment of the Year Facebook Announces Libra Binance gets Hacked CCN blames Google and has a shutdown scare Crypto-Exchanges start conducting 10+ IEOs daily Crypto-Dud of the Year Civil Sparkster The All-About-PR Award VeID aELF Best Blockchain Award Bitcoin Ethereum EOS Stellar* NEO ZCash Monero Blockchain of the Year Award Bitcoin Ethereum Monero EOS ZCash NEO Stellar* Hyperledger Variants The best crypto magazine Cointelegraph Coindesk CryptoCoinNews CryptoSlate Best crypto analysts Muhrad Mahmudov Willy woo Plan B Tone Vays The Zero Factor Authentication Award for Achievement un Security MountGox Bitfinex Poloniex Binance Best Crypto Rap Song EDCON 2019 - Vitalik Rap Bitcoin Rap Gucci Gang - HODL Gang I am still on Coinbase - CoinDaddy Team Hodl - Lambo Land The best bitcoin Shiller Anthony Pompliano John McAffee (Good Old John) Jack Dorsey Mark Zuckenberg (with Libra) Bryan Kelly (CNBC) Donald Trump The Cutest Crypto Kitty Lilbubthemagicalspacecat SirMeowsalot Felono The Best White Paper Bitcoin Ethereum Stellar EOS Blockstack Most Mind-blowing Bitcoin Story "Bitcoin’s Biggest Hack In History: 184.4 Billion Bitcoin from Thin Air; Satoshi Hard Forks, Saves Bitcoin," by Charlie Shrem "Why the Price of Bitcoin Doesn't Matter," by Beautyon "What Will Bitcoin Look Like in Twenty Years?" by Dan Jeffries "Bitcoin Miners Beware: Invalid Blocks Need Not Apply," by StopAndDecrypt "The Great Bitcoin Scaling Debate — A Timeline," by Daniel Morgan "Why Bitcoin is not trustless" by Haseeb Qureshi #CryptoTwitter's MVP @hodlonaut @BullyEsq @aantonop PeterMcCormack CryptoCobain @PirateBeachbum @VitalikButerin @TimDraper @haydentiff @iam_preethi @muneeb @brian_armstrong The Shitcoin Award [ ] open nominations! —SOFTWARE DEVELOPMENT AWARDS NOMINEES #NOONIES 2019 Developer Tool Buzz of Year GraphQL React Hooks GatsbyJS Zeit Nuxt.js Prisma Next.js Apollo CMS You Can't Live Without Wordpress Netlify CMS Ghost Squarespace Wix Medium Strikingly Weebly Joomla TYPO3 Personal Developer Blog of the Year Overreacted David Walsh Coding Horror Daring Fireball (John Gruber) Paul Jarvis Best Developer on Twitter @dan_abramov @iamdevloper @mxstbr (Max Stoiber) @addyosmani @mpjme (FunFunFunction) @jensimmons @jasonfried @codinghorror (Jeff Atwood) @no_fear_inc Best JAMstack React Serverless Framework Smashing Magazine freecodecamp.org Lodash SEOmonitor Impossible Foods NYC Pride 2019 The State of European Tech Airbnb Engineering & Data Science Stream Best Dev Podcast Syntax.fm Developer Tea The Laracasts Snippets The Changelog Shop Talk Show The Bike Shed The Undefined Podcast Top Dev Teacher Wes Bos Scott Tolinski Brian Holt Maximilian Schwarzmüller Kyle Simpson (YDKJS) Jeffrey Way Will Sentance Sarah Drasner Brad Traversy Kent Dodds Tyler McGinnis Dan Abramov Gregg Pollack Nick Pettit Bianca Gandolfo Shirley Wu Todd Motto Ben Awad Best Open Source Project VS Code React Vue.js Styled Components npm Tensorflow Font Awesome Kubernetes Atom Webpack faceswap Best Dev Community Github Dev.to Freecodecamp Stack Overflow Hacker News Product Hunt WIP Stack Share Best Open Startup Nomadlist Gumroad Ghost Insomnia Convertkit Baremetrics Hubstaff Upscribe Simple Analytics Notable No-Code App Tim Ferriss Dreamline Calculator Freelance Calculator Seedform Most Promising Fintech Braintree Acorns GoCardless n26 Robinhood Revolut Razorpay You can until August 16th, so go ahead and set a reminder to exercise your daily right to declare the best and worst of the world's technology industry. The winners will be announced on August 21st. VOTE EVERY DAY FROM TODAY The Noonies are made possible by Stream . Stream’s simple, powerful APIs for scalable feeds and chat are used by some of the largest and most popular apps.

Hacker Noon Awards: #Noonies 2019—Full Nominees List

In light of the recent initiatives to implement changes to Bitcoin’s protocol, the present signatories — representing the main exchanges, companies, service providers, and hundreds of thousands of users in the region, hereby collectively denominated as the “Brazilian and Argentinian communities” — wish to voice their deepest concerns over the upcoming November hardfork as mandated by the so-called New York Agreement (“NYA”), also known as SegWit2x (“S2X”). As enthusiasts, entrepreneurs, developers, businessmen, it is our belief we all share the same goal of making Bitcoin succeed and fulfill its huge potential as a disruptive technology, allowing for greater financial freedom, monetary sovereignty and empowerment to each and every individual around the world. We also value Bitcoin’s technological breakthrough for applications well beyond money and borderless payments. But regardless of the use cases, a secure and reliable is paramount. blockchain We do believe the NYA signatories have the best of intentions in attempting to improve Bitcoin’s protocol, and we also recognize the invaluable service historically provided by the companies and the talented individuals associated with S2X. We profoundly disagree, however, with the means chosen to carry out such a plan. And therein lie all the discord, controversy, feverish debates, and even resentment for some actors. What follows is a non-exhaustive list of the main reasons why the Brazilian and Argentinian communities deem SegWit2x an ill-advised and unwarranted pursuit: the NYA narrative framed the situation as a scaling gridlock that needed be solved, thus an agreement between relevant actors (developers, miners, exchanges, payment processors) was sought after. But the very nature of an “agreement” between a few parties in a decentralized consensus protocol can be interpreted as an aggression against the network. Bitcoin’s governance model is certainly not perfect, nonetheless it is far from dysfunctional. If a proposed change lacks adherence, status quo remains. That is a strength. Difficulty in changing the protocol — especially when affecting the consensus layer — really is a feature to be commended. BIP stands for Bitcoin Improvement Proposal, there is no Bitcoin Improvement Agreement for the simple reason that users cannot and should not be coerced into adopting unwanted changes to the protocol. As a community, we should strive to propose, educate, and convince. Overriding the governance mechanisms through closed agreements does not foster unity. 1) An agreement, instead of a proposal: from the onset, there was a clear deficiency of transparency and clarity from the leading S2X’s developers. Countless cases of interested parties being barred from freely subscribing to the mailing list, or accessing the slack channel, were verified. That cannot be considered open participation. Although this has somewhat been resolved, it contributed to confusion and suspicion**,** resulting in many parties simply distrusting or not believing SegWit2x true intentions. In the end, we are left wondering if NYA is genuinely about Bitcoin scaling or simply a subterfuge for a “governance takeover”, if the latter was even possible. Moreover, participation was encouraged only on the basis of obedience to a pre-agreed upon decision. If the technical and security merits of a “2mb hardfork in 3 months” are not permitted to be discussed, participating seems a sterile exercise. 2) Lack of development and objective transparency: : it has been frequently stated that SegWit2x represented a compromise. Immediate activation of SegWit (BIP141), as many users desired (by conservative measures over 70% of full nodes were already running SegWit ready software by then), and an increase in base blocksize limit to 2mb, as desired by miners and in accordance with an alleged agreement made during the Hong Kong Scaling Conference — though such an agreement was nothing more than a few developers promising to do research and make an open code proposal. A compromise in a decentralized consensus protocol poses a grave problem as it shows little regard for the technical consequences on the whole network. Changes impacting the consensus layer should not be adopted based on accords simply because some participants (be it miners, or merchants, or developers) are insisting on them. It is immensely difficult to make the case this isn’t a politically motivated change, one which has little to do with enhancements of the network. If Bitcoin’s protocol can be altered by the sheer pressure of select participants, it means decentralized consensus has failed. It means Bitcoin cannot and will not withstand even greater attacks in the future. To assert that S2X, if successful, sets a bad precedent is a gross understatement. 3) Political compromise, instead of technical upgrade technological as a decentralized free open-source software, changes to bitcoin’s protocol cannot be forced upon users of the network. As previously argued, had the proponents of S2X merely proposed a change, engaged in open and truthful debate, the divisive situation could have been avoided in its entirety. If upgrades are in fact needed, let us build consensus around them. 4) Consensus imposition, instead of consensus building: this was perhaps one of the most controversial stances by the S2X developing team. The outright refusal, followed by persistent reluctance, to implement strong replay protection gave a sense of recklessness to the entire community. It seems, at times, that S2X aims at deliberately causing disruption in the expectation users will capitulate and end up upgrading to its incompatible implementation. This posture undermines S2X’s own credibility as a legitimate attempt to improve the protocol. 5) Replay protection and unnecessary disruption: trust is an emergent property where multiple parties must act in strict conformity to the rules or risk consensus failure. Consensus is achieved by: i) full nodes independently validating transactions, ii) miners aggregating transactions into a block and producing a proof of work, iii) full nodes verifying miners’ blocks, and iv) full nodes selecting the longest valid chain. Seeking majority hashpower as a means to demonstrate consensus is pointless. Miners provide an essential service to the network, but they do not determine consensus. Mining does not define what the rules are. Full nodes enforce rules and defend the network against arbitrary changes by rejecting invalid transactions or blocks. If miners did have the sole power of affecting protocol changes at their own discretion, Bitcoin wouldn’t be a robust and secure network. 6) Emphasis on mining to the detriment of users: hardforking, by definition, means breaking backwards compatibility. Hardforking without consensus guarantees a chain split. For a network worth billions of dollars being used by millions of users, allowing for sufficient planning, testing, and preparation should be a self-imposed best practice. Unfortunately, S2X’s implementation (btc1 core) adopted a hasty timeline for activating a hardfork, risking leaving a significant portion of users adrift. Additionally, the so-called “quiet period” before the date of activation makes S2X all the more worrying. We would have preferred to see the risk of a chain split being mitigated by open and intensive testing instead. Downplaying backwards compatibility and security issues makes us extremely uneasy about running btc1 core software. 7) Impatience over prudence: we obviously prefer low fees to high fees, faster confirmations than longer confirmations, but simply raising base blocksize limit to 2mb now is a partial solution at best. As acknowledged by the very proponents of S2X, even 2mb is considered already insufficient and further increases should be implemented soon. If that is the case, does S2X plan on hardforking every 3 or 6 or 12 months? Congestion in the network is not a fundamentally technical problem to Bitcoin’s protocol. It certainly prevents some use cases in the short term, but does not imperil the network’s functionality and utility. We believe preserving Bitcoin’s censorship-resistant properties should be a top priority in protocol development. 8) A non-solution to a perceived problem: the chances of a chain split overburden exchanges, payment processors, and wallet services that must plan, prepare, and support a new coin in the event of a permanent split, encumbering these third-parties with potential liabilities should they refrain from doing so. Furthermore, it causes network turmoil by requiring participants to take extra precautions prior to the fork to safeguard wallets and by exposing users to possible loss of funds. Averting disorder in the network should be a prime concern in protocol upgrades, it is unfortunate to realize S2X might accomplish the very opposite. Lastly, uncertainty originated from S2X tends to reverberate negatively in the markets affecting asset prices across cryptocurrencies in general. 9) Externalizing risks, network and market turmoil and potential liabilities: it seems that miners have been misled into signing to a promise that overwhelming agreement in the network would be achieved. But since this is clearly not the case, if miners do run btc1 core, they endanger their operations by mining a chain the majority of users will invalidate. A more prudent approach would have been to recommend miners to “execute a hardfork if the signs of consensus in the network are unequivocal”, but never “do hardfork at all costs”. 10) Misleading miners: unfortunately, companies we do admire and have business with have released misleading statements regarding S2X inadvertently withholding crucial information from its users about what is really at play in the network. Everyone is free to choose the software they want to run, but customers should be rightfully informed if its service provider is adopting an incompatible implementation and what the risks are. 11) Misleading statements by some proponents: We believe sooner or later upgrades to the protocol will necessitate a hardfork. With due planning and preparation the network can smoothly coordinate to effectuate such changes with minimal chances of chain split and disruption. That, however, requires time, education and testing. Governance in a free open-source software is a complex business and some parties become frustrated by the lack of agility or ability to upgrade the protocol. Roadmaps, promises, and compromises are innocuous in a decentralized consensus network where no entity or group of actors can unilaterally dictate and enforce rules at will. We are all part of consensus. For all the reasons above, the Brazilian and Argentinian Bitcoin communities stand in opposition to SegWit2x. We consider any potential benefit arising from a hardfork as per the NYA is not worth the risks. Therefore, we urge its proponents to discontinue this endeavor and reengage the community towards a healthy and collaborative process for improving Bitcoin’s protocol. Signatories From Brazil: Bitcoin Brasil (Facebook group with 65K members, public poll shows results of more than 97% support in 720 respondents) Bit.One Bitsendal (Bitwage in Brazil) Blinktrade Blockchain Hub Braziliex CoinBR Coinkite, Opendime Criptomoedasfacil.com FoxBit ITS Rio MercadoBitcoin NegocieCoins OriginalMy Star Labs SuM Law TradeBit Walltime From Argentina: laBITconf (Latin American Bitcoin & Blockchain Conference) ONG Bitcoin Argentina Bitcoin Argentina Meetup group Bitcoin Argentina forum (public poll shows results of more than 99% support in ~350 respondents) EspacioBitcoin From Spain: Meetup Bitcoin Madrid Individual Signatories (many more to be included soon): Alex Bráz Alexandre Ferraz Alexandre Leite André Baptista André Ramos Arthur Campos Edilson Osorio Jr. Fabiano Dias Fabro Steibel (Diretor Executivo do ITS Rio) Felipe D’avila Felipe Micaroni Lalli Fernando Cesar Fernando Ulrich Gabriel Aleixo Geraldo Bastos Helena Margarido Hygoor Jorge Cruz Freire Jéssica Lima Jhonatas Wesly Joana Santos João Dias João Paulo Mayall Joeldo Holanda José Wilker Marco Agner Marcelo Henrique Sáez Quiñónez Marcelo Zola Zanotim Mathias Negrão Kux Murilo Valadares Nelson Lowenhaupt Junior Paulo Aragão Rafael Motta Rafael Nogueirol Renan Kruger Renato Nunes Renato Oliveira Santos Rocelo Lopes Rodini Netto Rodolfo Novak Rodrigo Cassio Rodrigo Saraiva Marinho Rodrigo Souza Rubens Neistein Safiri Felix Thiago Cesar Úrsula Vergilio Victor Hugo Guimarães Costa Vitor Augusto Pedrozo Dias Wendel Smith

Why the Brazilian and Argentinian Bitcoin communities oppose SegWit2x

today announced their plans to expand into Virtual Reality (VR) and Game Content (AIGC). Building upon their GameFi expertise, BinaryX has reportedly entered into agreements with their VR and AIGC partners, AiGC Labs, to develop a groundbreaking new GameFi genre of AI-based VR games. BinaryX Artificial Intelligence First AI-Powered Virtual Reality Game on the Metaverse According to the team, BinaryX is preparing for the launch of the first-ever VR game which heavily features both VR and AIGC in collaboration with AiGC Labs. The team has not released the full details of the game yet, but has hinted that the game will be set in a character-rich universe, inspired by heroes and characters from East Asian folklore. This comes just after Apple’s official reveal of their VR headset, Apple Vision Pro, during the Worldwide Developers Conference event on June 5. Using ChatGPT and GameGPT for Game Design The team revealed that they have been experimenting with ChatGPT and GameGPT to generate engaging gameplay, and characters and build compelling narratives for their games. The AI models helped the team to explore and refine ideas for world-building as well, including ideas for environmental layout, challenges, and level design. Besides the AI-powered VR game in collaboration with AiGC Labs, BinaryX has also been working on a separate AI-powered game that will be released sometime this year. "We are incredibly excited to unveil our latest venture into VR and AIGC technologies," said Rudy, Head of Growth at BinaryX. "This is a significant milestone for our companies as we continue to push the boundaries of innovation in the Web3 gaming industry. Together with our partners, our team has poured talent and dedication into creating a game that will redefine the gaming experience and captivate players like never before. We’re excited to reveal the game to our players soon." The game is currently still under development and more details about the official release will be shared on their social media. This story was distributed as a release by Chainwire under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author About BinaryX BinaryX is a GameFi and IGO platform, and the force behind popular blockchain games such as CyberChess, CyberDragon, and CyberLand. These games run on the BNB Chain. Aside from developing games, BinaryX has now evolved into a full-fledged GameFi platform by offering services, giving game developers the opportunity to launch their GameFi projects on their platform, and for users to get early access to innovative new games. Initial Game Offering (IGO) As one of the top 10 projects on the BNB Chain, BinaryX has a vast community of more than 100k coin holders and 30K monthly active wallets. It is also one of the top few metaverse projects by trading volume on the BNB chain, with more than 200 million in market cap. BinaryX also has a token, $BNX, that has consistently demonstrated strong performance despite the bear market. For more details and information about BinaryX, please visit | | | | Official website Medium Discord Telegram Twitter Check out BinaryX's games on their and on website YouTube Contact: marketing@binaryx.pro

BinaryX and AiGC Labs Set to Launch AI-Powered VR Game on Metaverse

BinaryX y AiGC Labs se preparan para lanzar un juego de realidad virtual impulsado por IA en Metaverse

BinaryX et AiGC Labs s'apprêtent à lancer un jeu VR alimenté par l'IA sur Metaverse

बाइनरीएक्स और एआईजीसी लैब्स मेटावर्स पर एआई-पावर्ड वीआर गेम लॉन्च करने के लिए तैयार हैं

BinaryX と AiGC Labs がメタバース上で AI 搭載 VR ゲームを開始予定

BinaryX e AiGC Labs preparam-se para lançar um jogo de realidade virtual baseado em IA no Metaverse

Phòng thí nghiệm BinaryX và AiGC được thiết lập để khởi chạy trò chơi VR do AI cung cấp trên Metaverse

BinaryX 和 AiGC Labs 将在元界推出 AI 驱动的 VR 游戏

Authors:
(1) Renan F. F. da Silva, Institute of Computing, University of Campinas;
(2) Yulle G. F. Borges, Institute of Computing, University of Campinas;
(3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. 9 Conclusion Our approaches were quite effective, enabling us to find solutions very close to the optimal solution, even in instances with many items. These results are partly due to the excellent quality of the solutions given by Two-by-Two, which efficiently handles color constraints. Another positive factors are our neighborhoods, which are efficient in quality and time complexity. Lastly, Gilmore and Gomory Formulation has a strong relaxation for the BPP, and this property may extend to CBPP. For a strong relaxation, the values for the optimal fractional and integer solutions are very close, so the patterns used by relaxation probably belong to integer solutions of high quality. Therefore, this is an excellent method to find a good set of patterns for the initial build of GRASP. Acknowledgements This project was supported by the S˜ao Paulo Research Foundation (FAPESP) grants #2015/11937-9 and #2020/06511-0; and the Brazilian National Council For Scientific and Technological Development (CNPq) grants #144257/2019-0, #311039/2020-0 and #425340/2016 3. Declarations Conflict of interest All authors declare that they have no conflicts of interest. References [1] Alsarhan H, Chia D, Christman A, et al (2016) A two-pass algorithm for unordered colored bin packing. Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School pp 1–10 [2] Balogh J, B´ek´esi J, Dosa G, et al (2013) Black and white bin packing. In: Erlebach T, Persiano G (eds) Approximation and Online Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 131–144, https://doi.org/10.1007/978-3-642-38016-7_12 [3] Balogh J, B´ek´esi J, D´osa G, et al (2015) Offline black and white bin packing. Theoretical Computer Science 596:92–101. https://doi.org/10.1016/j.tcs.2015.06.045 [4] Belov G, Scheithauer G (2006) A branch-and-cut-and-price algorithm for one-dimensional stock cutting and two-dimensional two-stage cutting. European Journal of Operational Research 171(1):85–106. https://doi.org/10.1016/j.ejor.2004.08.036 [5] B¨ohm M, Sgall J, Vesel´y P (2015) Online colored bin packing. In: Bampis E, Svensson O (eds) Approximation and Online Algorithms. Springer International Publishing, Cham, pp 35–46, https://doi.org/10.1007/978-3-319-18263-6_4 [6] B¨ohm M, D´osa G, Epstein L, et al (2018) Colored bin packing: Online algorithms and lower bounds. Algorithmica 80(1):155–184. https://doi.org/10.1007/s00453-016-0248-2 [7] Borges Y, Schouery R (2020) Modelos pseudo polinomiais para o problema do empacotamento colorido. In: Anais do V Encontro de Teoria da Computa¸c˜ao, pp 37–40, https://doi.org/ 10.5753/etc.2020.11084, (In Portuguese) [8] Borges YGF, Schouery RCS, Miyazawa FK (2023) Mathematical models and exact algorithms for the colored bin packing problem. 2305.15291 [9] Brand˜ao F, Pedroso JP (2016) Bin packing and related problems: General arc-flow formulation with graph compression. Computers & Operations Research 69:56–67. https://doi.org/10. 1016/j.cor.2015.11.009 [10] Buljubaˇsi´c M, Vasquez M (2016) Consistent neighborhood search for one-dimensional bin packing and two-dimensional vector packing. Computers & Operations Research 76:12–21. https://doi.org/10.1016/j.cor.2016.06.009 [11] Carvalho JMVd (1999) Exact solution of bin-packing problems using column generation and branch-and-bound. Annals of Operations Research 86(0):629–659. https://doi.org/10. 1023/A:1018952112615 [12] Castelli M, Vanneschi L (2014) A hybrid harmony search algorithm with variable neighbourhood search for the bin-packing problem. 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) pp 1–6. https://doi.org/10.1109/NaBIC.2014. 6921849 [13] Chen J, Han X, Bein W, et al (2015) Black and white bin packing revisited. In: Lu Z, Kim D, Wu W, et al (eds) Combinatorial Optimization and Applications. Springer International Publishing, Cham, pp 45–59, https://doi.org/10.1007/978-3-319-26626-8_4 [14] Delorme M, Iori M (2020) Enhanced pseudo-polynomial formulations for bin packing and cutting stock problems. INFORMS Journal on Computing 32(1):101–119. https://doi.org/ 10.1287/ijoc.2018.0880 [15] Delorme M, Iori M, Martello S (2018) Bpplib: a library for bin packing and cutting stock problems. Optimization Letters 12(2):235–250. https://doi.org/10.1007/s11590-017-1192-z [16] Demˇsar J (2006) Statistical comparisons of classifiers over multiple data sets. The Journal of Machine learning research 7:1–30 [17] D´osa G, Epstein L (2014) Colorful bin packing. In: Ravi R, Gørtz IL (eds) Algorithm Theory – SWAT 2014. Springer International Publishing, Cham, pp 170–181, https://doi.org/10. 1007/978-3-319-08404-6_15 [18] Feo TA, Resende MG (1989) A probabilistic heuristic for a computationally difficult set covering problem. Operations Research Letters 8(2):67–71. https://doi.org/https://doi.org/ 10.1016/0167-6377(89)90002-3 [19] Fleszar K, Hindi KS (2002) New heuristics for one-dimensional bin-packing. Computers & Operations Research 29(7):821–839. https://doi.org/10.1016/S0305-0548(00)00082-4 [20] Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32(200):675–701. https: //doi.org/10.1080/01621459.1937.10503522 [21] Gilmore PC, Gomory RE (1961) A linear programming approach to the cutting-stock problem. Operations Research 9(6):849–859. https://doi.org/10.1287/opre.29.6.1092 [22] Gonz´alez-San-Mart´ın J, Cruz-Reyes L, G´omez-Santill´an C, et al (2023) Comparative Study of Heuristics for the One-Dimensional Bin Packing Problem, Springer Nature Switzerland, Cham, pp 293–305. https://doi.org/10.1007/978-3-031-28999-6_19 [23] Gupta JND, Ho JC (1999) A new heuristic algorithm for the one-dimensional binpacking problem. Production Planning & Control 10(6):598–603. https://doi.org/10.1080/ 095372899232894 [24] Iman RL, Davenport JM (1980) Approximations of the critical region of the fbietkan statistic. Communications in Statistics - Theory and Methods 9(6):571–595. https://doi.org/10. 1080/03610928008827904 [25] Karp RM (1972) Reducibility among Combinatorial Problems, Springer US, Boston, MA, pp 85–103. https://doi.org/10.1007/978-1-4684-2001-2_9 [26] de Lima VL, Iori M, Miyazawa FK (2022) Exact solution of network flow models with strong relaxations. Mathematical Programming pp 1–34. https://doi.org/10.1007/ s10107-022-01785-9 [27] Loh KH, Golden B, Wasil E (2008) Solving the one-dimensional bin packing problem with a weight annealing heuristic. Computers & Operations Research 35(7):2283–2291. https:// doi.org/10.1016/j.cor.2006.10.021 [28] Mladenovi´c N, Hansen P (1997) Variable neighborhood search. Computers & Operations Research 24(11):1097–1100. https://doi.org/10.1016/S0305-0548(97)00031-2 [29] Nemenyi PB (1963) Distribution-free multiple comparisons. PhD thesis, Princeton University [30] Pessoa A, Sadykov R, Uchoa E, et al (2020) A generic exact solver for vehicle routing and related problems. Mathematical Programming 183(1):483–523. https://doi.org/10.1007/ s10107-020-01523-z [31] Vance PH (1998) Branch-and-price algorithms for the one-dimensional cutting stock problem. Computational Optimization and Applications 9(3):211–228. https://doi.org/10.1023/A: 1018346107246 [32] Wei L, Luo Z, Baldacci R, et al (2020) A new branch-and-price-and-cut algorithm for onedimensional bin-packing problems. INFORMS Journal on Computing 32(2):428–443. https://doi.org/10.1287/ijoc.2018.0867 This paper is available on arxiv under CC 4.0 license. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. 9 Conclusion Our approaches were quite effective, enabling us to find solutions very close to the optimal solution, even in instances with many items. These results are partly due to the excellent quality of the solutions given by Two-by-Two, which efficiently handles color constraints. Another positive factors are our neighborhoods, which are efficient in quality and time complexity. Lastly, Gilmore and Gomory Formulation has a strong relaxation for the BPP, and this property may extend to CBPP. For a strong relaxation, the values for the optimal fractional and integer solutions are very close, so the patterns used by relaxation probably belong to integer solutions of high quality. Therefore, this is an excellent method to find a good set of patterns for the initial build of GRASP. Acknowledgements This project was supported by the S˜ao Paulo Research Foundation (FAPESP) grants #2015/11937-9 and #2020/06511-0; and the Brazilian National Council For Scientific and Technological Development (CNPq) grants #144257/2019-0, #311039/2020-0 and #425340/2016 3. Acknowledgements Declarations Conflict of interest All authors declare that they have no conflicts of interest. Conflict of interest References [1] Alsarhan H, Chia D, Christman A, et al (2016) A two-pass algorithm for unordered colored bin packing. Proceedings of the 9th International Conference on Discrete Optimization and Operations Research and Scientific School pp 1–10 [2] Balogh J, B´ek´esi J, Dosa G, et al (2013) Black and white bin packing. In: Erlebach T, Persiano G (eds) Approximation and Online Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 131–144, https://doi.org/10.1007/978-3-642-38016-7_12 [3] Balogh J, B´ek´esi J, D´osa G, et al (2015) Offline black and white bin packing. Theoretical Computer Science 596:92–101. https://doi.org/10.1016/j.tcs.2015.06.045 [4] Belov G, Scheithauer G (2006) A branch-and-cut-and-price algorithm for one-dimensional stock cutting and two-dimensional two-stage cutting. European Journal of Operational Research 171(1):85–106. https://doi.org/10.1016/j.ejor.2004.08.036 [5] B¨ohm M, Sgall J, Vesel´y P (2015) Online colored bin packing. In: Bampis E, Svensson O (eds) Approximation and Online Algorithms. Springer International Publishing, Cham, pp 35–46, https://doi.org/10.1007/978-3-319-18263-6_4 [6] B¨ohm M, D´osa G, Epstein L, et al (2018) Colored bin packing: Online algorithms and lower bounds. Algorithmica 80(1):155–184. https://doi.org/10.1007/s00453-016-0248-2 [7] Borges Y, Schouery R (2020) Modelos pseudo polinomiais para o problema do empacotamento colorido. In: Anais do V Encontro de Teoria da Computa¸c˜ao, pp 37–40, https://doi.org/ 10.5753/etc.2020.11084, (In Portuguese) [8] Borges YGF, Schouery RCS, Miyazawa FK (2023) Mathematical models and exact algorithms for the colored bin packing problem. 2305.15291 [9] Brand˜ao F, Pedroso JP (2016) Bin packing and related problems: General arc-flow formulation with graph compression. Computers & Operations Research 69:56–67. https://doi.org/10. 1016/j.cor.2015.11.009 [10] Buljubaˇsi´c M, Vasquez M (2016) Consistent neighborhood search for one-dimensional bin packing and two-dimensional vector packing. Computers & Operations Research 76:12–21. https://doi.org/10.1016/j.cor.2016.06.009 [11] Carvalho JMVd (1999) Exact solution of bin-packing problems using column generation and branch-and-bound. Annals of Operations Research 86(0):629–659. https://doi.org/10. 1023/A:1018952112615 [12] Castelli M, Vanneschi L (2014) A hybrid harmony search algorithm with variable neighbourhood search for the bin-packing problem. 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) pp 1–6. https://doi.org/10.1109/NaBIC.2014. 6921849 [13] Chen J, Han X, Bein W, et al (2015) Black and white bin packing revisited. In: Lu Z, Kim D, Wu W, et al (eds) Combinatorial Optimization and Applications. Springer International Publishing, Cham, pp 45–59, https://doi.org/10.1007/978-3-319-26626-8_4 [14] Delorme M, Iori M (2020) Enhanced pseudo-polynomial formulations for bin packing and cutting stock problems. INFORMS Journal on Computing 32(1):101–119. https://doi.org/ 10.1287/ijoc.2018.0880 [15] Delorme M, Iori M, Martello S (2018) Bpplib: a library for bin packing and cutting stock problems. Optimization Letters 12(2):235–250. https://doi.org/10.1007/s11590-017-1192-z [16] Demˇsar J (2006) Statistical comparisons of classifiers over multiple data sets. The Journal of Machine learning research 7:1–30 [17] D´osa G, Epstein L (2014) Colorful bin packing. In: Ravi R, Gørtz IL (eds) Algorithm Theory – SWAT 2014. Springer International Publishing, Cham, pp 170–181, https://doi.org/10. 1007/978-3-319-08404-6_15 [18] Feo TA, Resende MG (1989) A probabilistic heuristic for a computationally difficult set covering problem. Operations Research Letters 8(2):67–71. https://doi.org/https://doi.org/ 10.1016/0167-6377(89)90002-3 [19] Fleszar K, Hindi KS (2002) New heuristics for one-dimensional bin-packing. Computers & Operations Research 29(7):821–839. https://doi.org/10.1016/S0305-0548(00)00082-4 [20] Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32(200):675–701. https: //doi.org/10.1080/01621459.1937.10503522 [21] Gilmore PC, Gomory RE (1961) A linear programming approach to the cutting-stock problem. Operations Research 9(6):849–859. https://doi.org/10.1287/opre.29.6.1092 [22] Gonz´alez-San-Mart´ın J, Cruz-Reyes L, G´omez-Santill´an C, et al (2023) Comparative Study of Heuristics for the One-Dimensional Bin Packing Problem, Springer Nature Switzerland, Cham, pp 293–305. https://doi.org/10.1007/978-3-031-28999-6_19 [23] Gupta JND, Ho JC (1999) A new heuristic algorithm for the one-dimensional binpacking problem. Production Planning & Control 10(6):598–603. https://doi.org/10.1080/ 095372899232894 [24] Iman RL, Davenport JM (1980) Approximations of the critical region of the fbietkan statistic. Communications in Statistics - Theory and Methods 9(6):571–595. https://doi.org/10. 1080/03610928008827904 [25] Karp RM (1972) Reducibility among Combinatorial Problems, Springer US, Boston, MA, pp 85–103. https://doi.org/10.1007/978-1-4684-2001-2_9 [26] de Lima VL, Iori M, Miyazawa FK (2022) Exact solution of network flow models with strong relaxations. Mathematical Programming pp 1–34. https://doi.org/10.1007/ s10107-022-01785-9 [27] Loh KH, Golden B, Wasil E (2008) Solving the one-dimensional bin packing problem with a weight annealing heuristic. Computers & Operations Research 35(7):2283–2291. https:// doi.org/10.1016/j.cor.2006.10.021 [28] Mladenovi´c N, Hansen P (1997) Variable neighborhood search. Computers & Operations Research 24(11):1097–1100. https://doi.org/10.1016/S0305-0548(97)00031-2 [29] Nemenyi PB (1963) Distribution-free multiple comparisons. PhD thesis, Princeton University [30] Pessoa A, Sadykov R, Uchoa E, et al (2020) A generic exact solver for vehicle routing and related problems. Mathematical Programming 183(1):483–523. https://doi.org/10.1007/ s10107-020-01523-z [31] Vance PH (1998) Branch-and-price algorithms for the one-dimensional cutting stock problem. Computational Optimization and Applications 9(3):211–228. https://doi.org/10.1023/A: 1018346107246 [32] Wei L, Luo Z, Baldacci R, et al (2020) A new branch-and-price-and-cut algorithm for onedimensional bin-packing problems. INFORMS Journal on Computing 32(2):428–443. https://doi.org/10.1287/ijoc.2018.0867 This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Fast Neighborhood Search Heuristics for the Colorful Bin Packing Problem: Conclusion and References

Authors:
(1) Renan F. F. da Silva, Institute of Computing, University of Campinas;
(2) Yulle G. F. Borges, Institute of Computing, University of Campinas;
(3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. Abstract The Colorful Bin Packing Problem (CBPP) is a generalization of the Bin Packing Problem (BPP). The CBPP consists of packing a set of items, each with a weight and a color, in bins of limited capacity, minimizing the number of used bins and satisfying the constraint that two items of the same color cannot be packed side by side in the same bin. In this article, we proposed an adaptation of BPP heuristics and new heuristics for the CBPP. Moreover, we propose a set of fast neighborhood search algorithms for CBPP. These neighborhoods are applied in a meta-heuristic approach based on the Variable Neighborhood Search (VNS) and a matheuristic approach that mixes linear programming with the meta-heuristics VNS and Greedy Randomized Adaptive Search (GRASP). The results indicate that our matheuristic is superior to VNS and that both approaches can find near-optimal solutions for a large number instances, even for instances with many items. Keywords: Cutting; Packing; Meta-heuristic; Matheuristic; Neighborhood Search 1 Introduction In the Bin Packing Problem (BPP), there is a set of items and an unlimited set of bins of equal capacity. The objective is to allocate the items in bins, respecting their capacities and minimizing the number of used bins. A generalization of BPP is the Colorful Bin Packing Problem (CBPP), where each item also has a color, and there is an additional constraint that two items of the same color cannot be packed side by side in the same bin. The CBPP was proposed independently by B¨ohm et al [5] and D´osa and Epstein [17], being studied in these articles only from the point of view of online algorithms and approximation algorithms. In particular, B¨ohm et al. show that the adaptations of the BPP classic algorithms First Fit, Best Fit, and Worst Fit for the CBPP have unbounded approximation ratios. Moreover, the authors prove that any online algorithm has an asymptotic competitive ratio of at least 2.5 and show an (absolute) 3.5-competitive algorithm. Also, some years before these works, Balogh et al [2] introduced the Black and White Bin Packing Problem (BWBPP), a particular case of CBPP with only two colors. Just like Balogh et al [2], the following works Chen et al [13], Balogh et al [3], and B¨ohm et al [6] studied approximation algorithms for online and offline versions of BWBPP and CBPP. An exact and linear algorithm for CBPP was proposed by Alsarhan et al [1] for the particular case where all items have zero weight. Later, Borges and Schouery [7], Borges et al [8] proposed four exact algorithms for the CBPP. The first two are pseudo-polynomial formulations based on Arc Flow Formulation for the BPP proposed by Carvalho [11]. On the other hand, the last two are set-partition formulations solved by the VRPSolver framework proposed by Pessoa et al [30]. Balogh et al [2] presents two applications for CBPP. The first one is in packing problems of twodimensional objects of similar widths that must be packed alternately. For example, consider the contents of information and advertisement on video-content sharing portals (like YouTube) and Social Media, which should fit under each other due to the tiny display of smartphones. Thus, the maximum content that fits in one screen is the bin capacity, the content height is the item size, the information contents have the color white, and advertisement contents have the color black. The second application is commercial breaks on radio or TV, where commercials of different lengths and genres must be scheduled for commercial blocks. In this case, the length of the commercial blocks represents the bin capacity, and the commercial duration is the item size. Two commercials of the same genre have the same color to prohibit them from being transmitted in sequence. The CBPP is an NP-hard problem since it is a generalization of BPP (Karp [25]). For dealing with NP-hard problems, in addition to the exact algorithm approach, another interesting approach is heuristic algorithms, in particular, the meta-heuristic approach, which commonly finds high-quality solutions in reasonable computational time. In this article, we study CBPP using meta-heuristic and matheuristic approaches, and, as far as we know, it is the first study in the literature to use this approach. Next, we present a literature review of heuristic approaches to BPP and present our contribution to CBPP. 1.1 Literature Review Many authors have studied BPP and its variants in the literature, using much as exact algorithms as meta-heuristic algorithms. Next, we present a review of the best-known algorithms for BPP and its generalization called the Cutting Stock Problem (CSP). Also, we introduce the main studies that utilize the VNS in the BPP. The BPP exact algorithms are based on two main formulation types: the formulation of Gilmore and Gomory [21] and the Arc Flow Formulation of Carvalho [11]. Other works that use Gilmore and Gomory Formulation are Vance [31], Belov and Scheithauer [4], and Wei et al [32]. On the other hand, for the arc flow, there are the following works Brand˜ao and Pedroso [9], Delorme and Iori [14], and de Lima et al [26]. Conversely, in the heuristic algorithm approach, Fleszar and Hindi [19] study the Variable Neighborhood Search (VNS) meta-heuristic applied to BPP. In this work, the authors use a variation of the heuristic called Minimum Bin Slack, proposed by Gupta and Ho [23] as an initial solution for VNS. This combination proved to be quite powerful and is able to find the optimal solution in 1329 of the 1370 instances evaluated. Sequentially, Loh et al [27] use the Weight Annealing meta-heuristic in the BPP, which finds optimal solutions in all instances used by Fleszar and Hindi. Castelli and Vanneschi [12] propose a BPP heuristic called BPHS, which is used as the initial solution of the VNS. Despite promising results, this combination has shown a lower performance than two previous studies. Finally, Gonz´alez-San-Mart´ın et al [22] presents a comparative study among nineteen heuristic algorithms proposed in the last two decades. The best algorithm in the study was the Consistent Neighborhood Search (CNS) introduced by Buljubaˇsi´c and Vasquez [10], which solved 99.81% of the studied instances. 1.2 Our Contributions In this article, we study the CBPP using five initial construction heuristics. The first two are adaptations of heuristics of the BPP called Best Fit Decreasing and Minimum Bin Slack. The last three are heuristics proposed by us called Good Ordering, Hard BFD, and Two-by-Two. In sequence, we present a meta-heuristic approach for CBPP using the VNS, which uses the previous heuristics to build the initial solution. Lastly, we propose a new matheuristic that mixes linear programming with the meta-heuristics VNS and Greedy Randomized Adaptive Search (GRASP). Our results show that our approaches can find near-optimal solutions for instances of up to 104 items in seconds. In particular, for all instances studied of up to 2 × 103 items and with the known optimal solution, our approaches, in 60 seconds, find solutions that use at most one extra bin than an optimal solution. The article is organized as follows. In Section 2, we present a formal definition for CBPP. Next, in Section 3, we present some convenient notations and prove a proposition that provides easy handling of color constraints. In Section 4, we propose an Auxiliary Algorithm, which we use as a subroutine in some of our algorithms. The initial heuristics, the VNS, and the matheuristic are introduced, respectively, in Sections 5, 6, and 7. Finally, the computational results and conclusion are present in Sections 8 and 9. This paper is available on arxiv under CC 4.0 license. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. Authors: (1) Renan F. F. da Silva, Institute of Computing, University of Campinas; (2) Yulle G. F. Borges, Institute of Computing, University of Campinas; (3) Rafael C. S. Schouery, Institute of Computing, University of Campinas. Abstract The Colorful Bin Packing Problem (CBPP) is a generalization of the Bin Packing Problem (BPP). The CBPP consists of packing a set of items, each with a weight and a color, in bins of limited capacity, minimizing the number of used bins and satisfying the constraint that two items of the same color cannot be packed side by side in the same bin. In this article, we proposed an adaptation of BPP heuristics and new heuristics for the CBPP. Moreover, we propose a set of fast neighborhood search algorithms for CBPP. These neighborhoods are applied in a meta-heuristic approach based on the Variable Neighborhood Search (VNS) and a matheuristic approach that mixes linear programming with the meta-heuristics VNS and Greedy Randomized Adaptive Search (GRASP). The results indicate that our matheuristic is superior to VNS and that both approaches can find near-optimal solutions for a large number instances, even for instances with many items. Keywords: Cutting; Packing; Meta-heuristic; Matheuristic; Neighborhood Search Keywords: 1 Introduction In the Bin Packing Problem (BPP), there is a set of items and an unlimited set of bins of equal capacity. The objective is to allocate the items in bins, respecting their capacities and minimizing the number of used bins. A generalization of BPP is the Colorful Bin Packing Problem (CBPP), where each item also has a color, and there is an additional constraint that two items of the same color cannot be packed side by side in the same bin. The CBPP was proposed independently by B¨ohm et al [5] and D´osa and Epstein [17], being studied in these articles only from the point of view of online algorithms and approximation algorithms. In particular, B¨ohm et al. show that the adaptations of the BPP classic algorithms First Fit, Best Fit, and Worst Fit for the CBPP have unbounded approximation ratios. Moreover, the authors prove that any online algorithm has an asymptotic competitive ratio of at least 2.5 and show an (absolute) 3.5-competitive algorithm. Also, some years before these works, Balogh et al [2] introduced the Black and White Bin Packing Problem (BWBPP), a particular case of CBPP with only two colors. Just like Balogh et al [2], the following works Chen et al [13], Balogh et al [3], and B¨ohm et al [6] studied approximation algorithms for online and offline versions of BWBPP and CBPP. An exact and linear algorithm for CBPP was proposed by Alsarhan et al [1] for the particular case where all items have zero weight. Later, Borges and Schouery [7], Borges et al [8] proposed four exact algorithms for the CBPP. The first two are pseudo-polynomial formulations based on Arc Flow Formulation for the BPP proposed by Carvalho [11]. On the other hand, the last two are set-partition formulations solved by the VRPSolver framework proposed by Pessoa et al [30]. Balogh et al [2] presents two applications for CBPP. The first one is in packing problems of twodimensional objects of similar widths that must be packed alternately. For example, consider the contents of information and advertisement on video-content sharing portals (like YouTube) and Social Media, which should fit under each other due to the tiny display of smartphones. Thus, the maximum content that fits in one screen is the bin capacity, the content height is the item size, the information contents have the color white, and advertisement contents have the color black. The second application is commercial breaks on radio or TV, where commercials of different lengths and genres must be scheduled for commercial blocks. In this case, the length of the commercial blocks represents the bin capacity, and the commercial duration is the item size. Two commercials of the same genre have the same color to prohibit them from being transmitted in sequence. The CBPP is an NP-hard problem since it is a generalization of BPP (Karp [25]). For dealing with NP-hard problems, in addition to the exact algorithm approach, another interesting approach is heuristic algorithms, in particular, the meta-heuristic approach, which commonly finds high-quality solutions in reasonable computational time. In this article, we study CBPP using meta-heuristic and matheuristic approaches, and, as far as we know, it is the first study in the literature to use this approach. Next, we present a literature review of heuristic approaches to BPP and present our contribution to CBPP. 1.1 Literature Review Many authors have studied BPP and its variants in the literature, using much as exact algorithms as meta-heuristic algorithms. Next, we present a review of the best-known algorithms for BPP and its generalization called the Cutting Stock Problem (CSP). Also, we introduce the main studies that utilize the VNS in the BPP. The BPP exact algorithms are based on two main formulation types: the formulation of Gilmore and Gomory [21] and the Arc Flow Formulation of Carvalho [11]. Other works that use Gilmore and Gomory Formulation are Vance [31], Belov and Scheithauer [4], and Wei et al [32]. On the other hand, for the arc flow, there are the following works Brand˜ao and Pedroso [9], Delorme and Iori [14], and de Lima et al [26]. Conversely, in the heuristic algorithm approach, Fleszar and Hindi [19] study the Variable Neighborhood Search (VNS) meta-heuristic applied to BPP. In this work, the authors use a variation of the heuristic called Minimum Bin Slack, proposed by Gupta and Ho [23] as an initial solution for VNS. This combination proved to be quite powerful and is able to find the optimal solution in 1329 of the 1370 instances evaluated. Sequentially, Loh et al [27] use the Weight Annealing meta-heuristic in the BPP, which finds optimal solutions in all instances used by Fleszar and Hindi. Castelli and Vanneschi [12] propose a BPP heuristic called BPHS, which is used as the initial solution of the VNS. Despite promising results, this combination has shown a lower performance than two previous studies. Finally, Gonz´alez-San-Mart´ın et al [22] presents a comparative study among nineteen heuristic algorithms proposed in the last two decades. The best algorithm in the study was the Consistent Neighborhood Search (CNS) introduced by Buljubaˇsi´c and Vasquez [10], which solved 99.81% of the studied instances. 1.2 Our Contributions In this article, we study the CBPP using five initial construction heuristics. The first two are adaptations of heuristics of the BPP called Best Fit Decreasing and Minimum Bin Slack. The last three are heuristics proposed by us called Good Ordering, Hard BFD, and Two-by-Two. In sequence, we present a meta-heuristic approach for CBPP using the VNS, which uses the previous heuristics to build the initial solution. Lastly, we propose a new matheuristic that mixes linear programming with the meta-heuristics VNS and Greedy Randomized Adaptive Search (GRASP). Our results show that our approaches can find near-optimal solutions for instances of up to 104 items in seconds. In particular, for all instances studied of up to 2 × 103 items and with the known optimal solution, our approaches, in 60 seconds, find solutions that use at most one extra bin than an optimal solution. The article is organized as follows. In Section 2, we present a formal definition for CBPP. Next, in Section 3, we present some convenient notations and prove a proposition that provides easy handling of color constraints. In Section 4, we propose an Auxiliary Algorithm, which we use as a subroutine in some of our algorithms. The initial heuristics, the VNS, and the matheuristic are introduced, respectively, in Sections 5, 6, and 7. Finally, the computational results and conclusion are present in Sections 8 and 9. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Fast Neighborhood Search Heuristics for the Colorful Bin Packing Problem

Masa Network's Groundbreaking Integration with LayerZero In a time when data is the new gold, the quest for ways to preserve personal information while simultaneously improving its utility in the quickly developing artificial intelligence business has led in the development of unique solutions, at a rapid speed! This is because the industry is seeing tremendous expansion. As a result of the announcement of a strategic collaboration with LayerZero, Masa Network has emerged as a potential competitor among these, so establishing a distinct territory within the ecosystem of blockchain technology and artificial intelligence. By combining the cutting-edge encryption technology of Masa Network with the powerful data processing capabilities of LayerZero, this cooperation promises to bring about a novel approach to the protection and utilisation of personal data. As a result of the integration of these two strong platforms, users are now able to take advantage of the benefits of increased privacy and security without having to sacrifice the effectiveness and speed with which data is processed. This partnership, which is an important step towards shaping the future, will have a significant impact on personal data management in the digital era. As Masa Network establishes a connection with LayerZero in order to fuel its cross-chain AI Data Network, the implications for data privacy, the development of artificial intelligence, and blockchain technology are profound and far-reaching. A Closer Look at Masa and LayerZero's Integration With the upcoming launch of the MASA token and Network Mainnet, Masa wants to redefine data ownership. Users' digital footprints and social graphs are encrypted and stored in Zero-Knowledge Soulbound Tokens (zkSBTs) data lockers, empowering individuals to share and monetize their data securely - this model not only enhances privacy but also fuels the decentralized AI economy! Users earning MASA tokens as their data powers AI developments! Calenthia Mei, Co-founder of Masa, encapsulates this vision, stating, "Masa is thrilled to be integrating with LayerZero Labs, which has become the industry standard for interoperability. Masa wants to empower users to own, share, and earn from their data, no matter which blockchain network their data is on. With LayerZero’s support, we are excited to be cross-chain and interoperable from the very beginning.” The Impact and Future Prospects While Masa Network is getting ready to debut, it is indisputable that it has the ability to shake up the existing data and artificial intelligence landscapes. With more than 1.4 million distinct wallets and more than 37 million proprietary data points, Masa is at the forefront of providing individualised training data that prioritises clients' privacy. Using this treasure trove, developers may train artificial intelligence models, which will allow them to create services that are both personalised and inventive while maintaining data privacy. Simon Baksys, VP of Business Development at LayerZero, reflects on the collaboration's significance: "We are excited to collaborate with Masa to enhance privacy and innovation in AI development. The integration of LayerZero infrastructure with Masa's ecosystem will enable accelerated development of personalized AI applications while ensuring user data remains private and secure.” Masa Network and LayerZero are not only building a platform, but also the plans for how personal data will be used and protected in the future. We are on the verge of a new era in data protection and use. The road ahead will bring not only new technologies, but also new ideas about who owns data, privacy, and AI's hidden potential. The Market and Emerging Trends An unprecedented amount of personal data has been accumulated as a result of the advent of the digital era, which has raised worries over privacy and the monopolisation of information by large technology companies. During the same time period, the sectors of artificial intelligence (AI) and blockchain are both enjoying significant development, where for the purpose of training more complicated artificial intelligence models, developers are asking for access to vast datasets that are in compliance with established privacy standards. Masa Network's attempts to develop an interoperable network that spans different blockchains in order to create an artificial intelligence data marketplace serve as a timely fix for these difficulties. A marketplace for artificial intelligence data is being created. Masa makes sure that communication is constant across a variety of different blockchain platforms by using the interoperability protocol that LayerZero created. The Ethereum and Binance Smart Chain platforms are among these platforms, and there are plans to extend to include Polygon, Base, Celo, and other sites that are relevant to the cryptocurrency industry. Don’t forget to like and share the story! This author is an independent contributor publishing via our brand-as-author program. Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure:

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