Tangle is a relatively recent distributed ledger technology (DLT), which is specially designed for IoT (Internet of Things) applications. The blockchain technology which is used for the Bitcoin cryptocurrency, relies upon the concept of rewarding the mining node whose newly created block is appended to the chain of blocks. This concept is not feasible in the realm of IoT technology. This is true because: If the Bitcoin blockchain technology is used, then the required transaction fees may turn out to be higher than the value of the IoT transaction itself. IoT networks require higher transaction processing rate than cryptocurrencies. Recall from the chapter on blockchain-throughput of this Volume (Volume 2: Engineering Principles), that the blockchains which support Bitcoin-like applications have a very low transaction processing rate. Further, nodes in the IoT network may or may not have high computational power.
This presentation will demonstrate using WebAssembly for audio plugins outside the web browser. Specifically, the showcase is a WebAssembly binary used as a synthesizer plugin in a commercial, desktop based Digital Audio Workstation software such as Garage Band or Logic. In addition there will be a proposal and demonstration of a commercial model for distributing and controlling access and ownership to these WebAssembly audio plugins, by storing them on the NEAR blockchain and binding them to Non-Fungible-Tokens ( NFTs ).
Recent years have seen great improvements in zero-knowledge proofs (ZKPs). Among them, zero-knowledge SNARKs are notable for their compact and efficiently-verifiable proofs, but suffer from high prover costs. Wu et al. (Usenix Security 2018) proposed to distribute the proving task across multiple machines, and achieved significant improvements in proving time. However, existing distributed ZKP systems still have quasi-linear prover cost, and may incur a communication cost that is linear in circuit size. In this paper, we introduce HyperPianist. Inspired by the state-of-the-art distributed ZKP system Pianist (Liu et al., S&P 2024) and the multivariate proof system HyperPlonk (Chen et al., EUROCRYPT 2023), we design a distributed multivariate polynomial interactive oracle proof (PIOP) system with a linear-time prover cost and logarithmic communication cost. Unlike Pianist, HyperPianist incurs no extra overhead in prover time or communication when applied to general (non-data-parallel) circuits. To instantiate the PIOP system, we adapt two additively-homomorphic multivariate polynomial commitment schemes, multivariate KZG (Papamanthou et al., TCC 2013) and Dory (Lee et al., TCC 2021), into the distributed setting, and get HyperPianistKand HyperPianistDrespectively. Both systems have linear prover complexity and logarithmic communication cost; furthermore, HyperPianistDrequires no trusted setup. We also propose HyperPianist+, incorporating an optimized lookup argument based on Lasso (Setty et al., EUROCRYPT 2024) with lower prover cost. Experiments demonstrate HyperPianistKand HyperPianistDachieve speedups of 63.1x and 40.2x over HyperPlonk with 32 distributed machines. Compared to Pianist, HyperPianistKcan be 2.9x and 4.6x as fast and HyperPianistDcan be 2.4x and 3.8x as fast, on vanilla gates and custom gates respectively. With layered circuits, HyperPianistKis up to 5.9x as fast on custom gates, and HyperPianistDachieves a 4.7x speedup.
This paper examines the hesitancy of Australian musicians towards embracing the music non-fungible token (NFT) as a commodity. Drawing on the concepts of cultural autonomy and the digital disruptive sublime, the study argues that the overtly economic nature of NFTs challenges the ideology of creative independence in the hegemonic ‘indie’ music scene. Through interviews with nine Australian musicians who participated in our project, the research finds a cautious curiosity towards the technology, with technical barriers and a perceived cultural disconnect between the NFT ‘community’ and traditional music scenes contributing to hesitation. The paper concludes that attempts to engineer disruption in the music industry through web3/blockchain technology have thus far failed to attract sustained interest from musicians, as the cultural norms and practices associated with NFTs do not align with the values of the existing indie music ecosystem. The findings highlight the difficulties in planning and engineering cultural change within the music industry.
This chapter delves into the future of the complex and evolving world of non-fungible tokens (NFTs), focusing on their potential to drive mass adoption of blockchain technology. Beginning with some historical context, the chapter explores the rapid growth of NFTs in the digital art and collectibles space, most notably during the speculative boom in 2021–2022 and the subsequent crash. The chapter then investigates how NFTs might expand beyond these initial use cases. It describes major developments in technology, business models, and financial infrastructure that will support further evolution of NFTs. Using real-world examples, the chapter then discusses emerging categories of NFT use cases, such as tokenization of physical assets, ticketing, and digital identity. It concludes by emphasizing that the true mass adoption of NFTs will occur when the technology becomes invisible and the primary draw becomes the value of use cases, not the novelty of NFTs themselves. While one should be skeptical about specific predictions for massive NFT adoption, this chapter shows that the capabilities NFTs provide are poised to add value in a wide variety of contexts.
Parallel Computing and Optimization Techniques
Music Technology and Sound Studies
Physical Unclonable Functions (PUFs) and Hardware Security
This chapter introduces two new concepts: ‘Decentralized Creative Networks’ and ‘Performative Transactions’. Decentralized Creative Networks are envisioned as blockchain-based post-human social networks, in which artists and AI agents develop and transact composable artistic processes, transparently building upon each other’s interoperable contributions. These processes are shared in Decentralized Creative Networks like social media posts. Artists can use them to shape their artistic work, by making it dependent on the execution of processes created by other artists and AI agents (for instance to compose music, to execute live performances of an artistic work, or to generate non-fungible tokens). Performative Transaction is a kind of transaction specific to these networks. It is executed by a smart contract, the code of which specifies both the artistic process and the terms of referencing it by other processes. To ensure interoperability, artistic processes in the system are composed as recursive patterns of transformations in a framework inspired by the Transformational Theory of David Lewin and Machine Learning’s feature engineering. When interlinked Performative Transactions are executed, smart contracts carry out all referenced musical transformations contributing to the musical result. They also automatically distribute any financial receivables to the creators of all referenced artistic processes. Furthermore, the integration of Artificial Intelligence within Decentralized Creative Networks is discussed, suggesting a collaborative framework where human and AI agents interact, actively shaping the artistic network. These interactions are further elucidated on the examples of music composition, performance, analysis, and sound synthesis, demonstrating the versatility of Performative Transactions for musical use cases. While recognizing the potential of Decentralized Creative Networks, the chapter acknowledges current challenges for their development. Overcoming these challenges could significantly impact how art is created, shared, and experienced in the digital era.
In recent years, increased access to sophisticated tools in the domains of artificial intelligence (AI) and decentralized computation (in particular blockchain-enabled technologies) is leading to significant developments in the landscape of digital art. In the creative experiments of artists, designers, and technologists, such developments are evident, for example, in a focus on generative processes (e.g., AI-enabled text-to-image generation) and on the production of unique digital artifacts (such as blockchain-enabled non-fungible tokens, or NFTs). For now, the bulk of creative experimentation and theoretical reflection appears to have taken place in an occularcentric mode, and with a primary focus on visual, non-time-based artforms. Drawing on this existing discourse, in this chapter I will begin to explore some opportunities that emerging AI and blockchain technologies represent for new compositional practices, performance, collaboration, and distribution of music and sound-based aesthetic artifacts. Throughout this discussion, the underlying focus is on the shifting contours of creative agency effected by AI and blockchain technologies. With this focus in mind, key concerns include the following: How can creative agency be encoded in AI-augmented and blockchain-enabled musical objects? What are the implications of this ‘becoming-agential’ for questions related to authorship and ownership? It will not be possible to provide conclusive answers to these questions here. Instead, my aim in this chapter is to stake the relevance and importance of the questions raised by outlining underlying concerns and perspectives. In the following sections, this is done first by offering detailed contextualization, and subsequently by discussing an ongoing multimodal art project that is of great relevance to the concerns outlined above.
Blockchain and Web3 technologies were originally understood in a narrowly financial context, associated with cryptocurrencies such as Bitcoin. Non-fungible tokens, or NFTs, have put music (and other creative economy use cases such as art and gaming) center stage. Yet there remains a widespread misconception that speculative investments in cryptocurrencies and NFTs are the be-all and end-all of Web3. This chapter examines the potential impact of blockchain technology on the music industry from a more holistic perspective. Specifically, its contribution lies in proposing four lenses through which we can view Web3 music: financial, social, environmental and experiential. By examining the value of tokens – fungible as well as non-fungible – in terms that go beyond short-term price fluctuations, I hope to deepen our understanding of cultural value in Web3 and beyond.
Non-fungible tokens (NFTs) are digital assets that provide unique ownership and authenticity of digital media such as art, music, and collectibles.NFT Marketplace is a blockchain-based platform that enables the creation, trading, and collecting of NFTs.The platform leverages blockchain technology to ensure the authenticity and ownership of NFTs, providing a secure and transparent way to transact digital assets.In this major project report, we explore the NFT Marketplace and its underlying blockchain technology.We provide an overview of the platform's features, including the ability to tokenize any digital asset, create customizable smart contracts, and sell NFTs with low fees and instant trades.We also discuss the advantages and disadvantages of the platform, including its ease of use, potential for fraud, and scalability challenges.The Non-Fungible Tokens (NFTs) have revolutionized the digital realm, redefining the concept of ownership and trade of unique digital assets.NFTs represent one-of-a-kind tokens, each verifiably and indelibly linked to a specific digital or physical asset, encompassing diverse forms of content, including video, audio, and images.These unique tokens have paved the way for creators to monetize their digital creations while providing collectors with an innovative means to invest, trade, and showcase their multimedia NFT collections.Central to the NFT ecosystem are NFT marketplaces, digital platforms designed to facilitate the creation, sale, and management of NFTs in various multimedia formats.These marketplaces have proliferated, providing creators with the means to mint NFTs, buyers with the opportunity to acquire them, and collectors with platforms to curate and trade their diverse NFT portfolios.We explore the multifaceted world of NFT marketplaces, focusing on their pivotal role in the creation, sale, and management of video, audio, and image NFTs.We analyze the economic implications, including pricing strategies and royalties, while addressing environmental sustainability concerns associated with NFTs.Challenges and opportunities encountered within this dynamic ecosystem are critically examined, including scalability, intellectual property rights, and the emergence of decentralized NFT marketplaces.Through in-depth case studies, we offer insights into the unique features and innovative approaches adopted by leading NFT marketplaces, shedding light on the transformative potential of this digital metaverse.This report serves as a valuable resource for those seeking a comprehensive understanding of NFT marketplaces catering to video, audio, and image NFTs, emphasizing the profound impact these tokens have on the creation, trade, and experience of digital content across various media formats.Navigating this dynamic digital frontier necessitates a nuanced perspective, and our survey aims to provide a holistic view of this rapidly evolving landscape.
In recent years, the music industry has advanced a lot in technology and provided listeners with easy access to music via digital platforms. The internet has re-organized the value chain and accelerated processes with the evolution of streaming services. Associated issues include copyright protection and royalty distribution. By looking at the music business’s appropriation organization, it very well may be seen that the internet web-based stages have empowered buyers to access music easily, but however has introduced a level of mediation among specialists and the users, creating a wasteful eminence installment framework. The motivation behind this chapter is to identify blockchain applications that would draw in the disintermediation of the business, enabling artists to gain additional benefits from their music. This chapter details the impact of blockchain on the music business and various innovations to make this music appropriation framework safer and more reliable.
Digital arts have gained an unprecedented level of popularity with the emergence of non-fungible tokens (NFTs). NFTs are cryptographic assets that are stored on blockchain networks and represent a digital certificate of ownership that cannot be forged. NFTs can be incorporated into a smart contract which allows the owner to benefit from a future sale percentage. While digital art producers can benefit immensely with NFTs, their production is time consuming. Therefore, this paper explores the possibility of using generative adversarial networks (GANs) for automatic generation of digital arts. GANs are deep learning architectures that are widely and effectively used for synthesis of audio, images, and video contents. However, their application to NFT arts have been limited. In this paper, a GAN-based architecture is implemented and evaluated for novel NFT-style digital arts generation. Results from the qualitative case study indicate that the generated artworks are comparable to the real samples in terms of being interesting and inspiring and they were judged to be more innovative than real samples.
Open access
3 source records
Generative Adversarial Networks and Image Synthesis
Recently, NFT (Non-Fungible Token) is emerging. It is applied in many areas especially in the digital art. In this article, the concept of NFT, its players in the market, minting and operations, applications, notable NFT artwork, and some controversial outstanding issues will be discussed.
Cultural Heritage Materials Analysis
Additive Manufacturing and 3D Printing Technologies
To explore the automatic computer composition, investigate the copyright protection and management of digital music, and expand the application of deep learning and blockchain technologies in the generation of digital music works, piano composition was taken as a sample. First, through the elaboration of the neural network methods based on deep learning, the Recurrent Neural Network (RNN), Long-Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) networks were introduced, and the deep learning-based GRU-RNN automatic composition model was constructed. Second, the blockchain technology was analyzed and expressed, and the problems in the traditional copyright protection and management of digital music were analyzed. The three aspects, i.e., ownership, right of use, and right protection, were fully considered, and the blockchain technology was integrated into the copyright protection and management of digital music. Finally, the manual analysis evaluation and pause analysis were selected as the indicators to analyze and characterize the music composition quality of the GRU-RNN model, as well as analyzing the development of the digital music market integrated with blockchain technology. The results show that the GRU-RNN model shows satisfactory effects in manual analysis evaluation or in the pause analysis of the passage. The deep learning method has great potential for application in automatic computer composition of digital music; the integration of blockchain technology has played a promotive role in the expansion and popularization of the digital music market. However, in the meantime, it still faces some technical and policy challenges. The results have a positive effect on promoting the development and application of deep learning methods and blockchain technology in digital music.
In order to explore the application of deep learning algorithms in arrangement and composition, and the role of blockchain in the protection of digital music copyright, a monophonic melody composition model based on the deep generative adversarial networks (DCGANs) is constructed firstly, and the composition performance of the model is analyzed using hymn as input sample in this study. Later, the multi-instrument co-arrangement (MICA) model based on the multi-task learning is proposed, and the composition performance is analyzed by taking the actual music as an input sample. Finally, the improved practical byzantine fault tolerance (IPBFT) algorithm is proposed, and a digital music copyright protection system is designed based on the blockchain in this study. The results indicate that the accuracies constructed DCGANs model in predicting the Soprano and Alto voice melody are higher than those of the DeepBatch model by 2.29% and 3.32%, respectively. The performance on the harmony score, note accuracy, Levenshtein similarity (LS), notes distribution mean square error, and empty as well as the convergence speed of the constructed MICA model are better than those of other models. The average transaction per second (TPS) value of the proposed IPBFT algorithm in the real digital music copyright protection system is 3469, which is superior to other blockchain technologies. Finally, the digital music copyright protection system is achieved, the error rate of completing the request is 0% in the state of many users operating concurrently, and a high TPS value can be guaranteed. In short, the DCGANs and MICA models pointed out in this study can be used in the composition of monophonic melodies and complex melodies, and the digital music copyright protection system based on the blockchain has excellent performance in practical applications.
Open access
Generative Adversarial Networks and Image Synthesis