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01Synergy

01synergy

Table of Links Abstract and 1 Introduction 2 Background & Problem Statement 2.1 How can we use MLLMs for Diffusion Synthesis that Synergizes both sides? 3 DreamLLM 3.1 End-to-End Interleaved generative Pretraining (I-GPT) 3.2 Model Training 4 Experiments and 4.1 Multimodal Comprehension 4.2 Text-Conditional Image Synthesis 4.3 Multimodal Joint Creation & Comprehension 5 Discussions 5.1 Synergy between creation & Comprehension? 5. 2 What is learned by DreamLLM? 6 Related Works 7 Conclusions and References A Additional Experiments B Additional Qualitative Examples C Implementation Details D Additional Related Works E Limitations, Failure Cases & Future Works 5 DISCUSSIONS 5.1 SYNERGY BETWEEN CREATION & COMPREHENSION? To elucidate the synergy between multimodal creation and comprehension, we make the comparison among three methods with DREAMLLM architecture, each utilizing identical training data yet differing in their learning objectives: a) the Creation-only baseline, focused solely on text/document-conditional image synthesis; b) the Comprehension-only baseline, dedicated to word generation exclusively; c) the Joint-learning method, which is the default setting of DREAMLLM learning both image and language modeling. Qualitative Analysis In Fig. 4, we compare answers to some examplar VQA tasks from comprehension-only and joint learning modules, respectively. It can be seen that: i) The joint-learning method exhibits superior multimodal comprehension, particularly in identifying subject relationships and attributes like object size. ii) In multimodal comprehension scenarios involving multiple image inputs, the joint-learning approach demonstrates enhanced precision. This improved performance is a natural outcome of I-GPT pretraining, allowing better modeling of multimodal correlations in various interleaved documents Multimodal In-Context Generation Multimodal in-context generation is a critical emerging capability for MLLMs (Bommasani et al., 2021; Alayrac et al., 2022). While significant strides have been made in in-context visual question answering, in-context image synthesis remains relatively lacking in exploration. The multimodal context-conditional image synthesis capabilities of DREAMLLM, as demonstrated in Fig. 5, offer promising insights into this domain. Tasks such as in-context image edition, subject-driven image generation, and compositional generation, however, pose significant challenges in a zero-shot setting, particularly without downstream fine-tuning as in DreamBooth (Ruiz et al., 2023) or attention modification techniques as in Prompt2Prompt (Hertz et al., 2023). Despite these hurdles, Fig. 5 illustrates DREAMLLM’s ability to generate images conditioned on the provided image context. This capability suggests promising potential for DREAMLLM in maintaining subject, identity, and semantic context, thereby paving a new way for resolving these complex tasks. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors:
(1) Runpei Dong, Xi’an Jiaotong University and Internship at MEGVII;
(2) Chunrui Han, MEGVII Technology;
(3) Yuang Peng, Tsinghua University and Internship at MEGVII;
(4) Zekun Qi, Xi’an Jiaotong University and Internship at MEGVII;
(5) Zheng Ge, MEGVII Technology;
(6) Jinrong Yang, HUST and Internship at MEGVII;
(7) Liang Zhao, MEGVII Technology;
(8) Jianjian Sun, MEGVII Technology;
(9) Hongyu Zhou, MEGVII Technology;
(10) Haoran Wei, MEGVII Technology;
(11) Xiangwen Kong, MEGVII Technology;
(12) Xiangyu Zhang, MEGVII Technology and a Project leader;
(13) Kaisheng Ma, Tsinghua University and a Corresponding author;
(14) Li Yi, Tsinghua University, a Corresponding authors and Project leader. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background & Problem Statement 2 Background & Problem Statement 2.1 How can we use MLLMs for Diffusion Synthesis that Synergizes both sides? 2.1 How can we use MLLMs for Diffusion Synthesis that Synergizes both sides? 3 DreamLLM 3 DreamLLM 3.1 End-to-End Interleaved generative Pretraining (I-GPT) 3.1 End-to-End Interleaved generative Pretraining (I-GPT) 3.2 Model Training 3.2 Model Training 4 Experiments and 4.1 Multimodal Comprehension 4 Experiments and 4.1 Multimodal Comprehension 4.2 Text-Conditional Image Synthesis 4.2 Text-Conditional Image Synthesis 4.3 Multimodal Joint Creation & Comprehension 4.3 Multimodal Joint Creation & Comprehension 5 Discussions 5.1 Synergy between creation & Comprehension? 5.1 Synergy between creation & Comprehension? 5. 2 What is learned by DreamLLM? 5. 2 What is learned by DreamLLM? 6 Related Works 6 Related Works 7 Conclusions and References 7 Conclusions and References A Additional Experiments A Additional Experiments B Additional Qualitative Examples B Additional Qualitative Examples C Implementation Details C Implementation Details D Additional Related Works D Additional Related Works E Limitations, Failure Cases & Future Works E Limitations, Failure Cases & Future Works 5 DISCUSSIONS 5.1 SYNERGY BETWEEN CREATION & COMPREHENSION? To elucidate the synergy between multimodal creation and comprehension, we make the comparison among three methods with DREAMLLM architecture, each utilizing identical training data yet differing in their learning objectives: a) the Creation-only baseline, focused solely on text/document-conditional image synthesis; b) the Comprehension-only baseline, dedicated to word generation exclusively; c) the Joint-learning method, which is the default setting of DREAMLLM learning both image and language modeling. Qualitative Analysis In Fig. 4, we compare answers to some examplar VQA tasks from comprehension-only and joint learning modules, respectively. It can be seen that: i) The joint-learning method exhibits superior multimodal comprehension, particularly in identifying subject relationships and attributes like object size. ii) In multimodal comprehension scenarios involving multiple image inputs, the joint-learning approach demonstrates enhanced precision. This improved performance is a natural outcome of I-GPT pretraining, allowing better modeling of multimodal correlations in various interleaved documents Qualitative Analysis Multimodal In-Context Generation Multimodal in-context generation is a critical emerging capability for MLLMs (Bommasani et al., 2021; Alayrac et al., 2022). While significant strides have been made in in-context visual question answering, in-context image synthesis remains relatively lacking in exploration. The multimodal context-conditional image synthesis capabilities of DREAMLLM, as demonstrated in Fig. 5, offer promising insights into this domain. Tasks such as in-context image edition, subject-driven image generation, and compositional generation, however, pose significant challenges in a zero-shot setting, particularly without downstream fine-tuning as in DreamBooth (Ruiz et al., 2023) or attention modification techniques as in Prompt2Prompt (Hertz et al., 2023). Despite these hurdles, Fig. 5 illustrates DREAMLLM’s ability to generate images conditioned on the provided image context. This capability suggests promising potential for DREAMLLM in maintaining subject, identity, and semantic context, thereby paving a new way for resolving these complex tasks. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv Authors: (1) Runpei Dong, Xi’an Jiaotong University and Internship at MEGVII; (2) Chunrui Han, MEGVII Technology; (3) Yuang Peng, Tsinghua University and Internship at MEGVII; (4) Zekun Qi, Xi’an Jiaotong University and Internship at MEGVII; (5) Zheng Ge, MEGVII Technology; (6) Jinrong Yang, HUST and Internship at MEGVII; (7) Liang Zhao, MEGVII Technology; (8) Jianjian Sun, MEGVII Technology; (9) Hongyu Zhou, MEGVII Technology; (10) Haoran Wei, MEGVII Technology; (11) Xiangwen Kong, MEGVII Technology; (12) Xiangyu Zhang, MEGVII Technology and a Project leader; (13) Kaisheng Ma, Tsinghua University and a Corresponding author; (14) Li Yi, Tsinghua University, a Corresponding authors and Project leader. Authors: Authors: (1) Runpei Dong, Xi’an Jiaotong University and Internship at MEGVII; (2) Chunrui Han, MEGVII Technology; (3) Yuang Peng, Tsinghua University and Internship at MEGVII; (4) Zekun Qi, Xi’an Jiaotong University and Internship at MEGVII; (5) Zheng Ge, MEGVII Technology; (6) Jinrong Yang, HUST and Internship at MEGVII; (7) Liang Zhao, MEGVII Technology; (8) Jianjian Sun, MEGVII Technology; (9) Hongyu Zhou, MEGVII Technology; (10) Haoran Wei, MEGVII Technology; (11) Xiangwen Kong, MEGVII Technology; (12) Xiangyu Zhang, MEGVII Technology and a Project leader; (13) Kaisheng Ma, Tsinghua University and a Corresponding author; (14) Li Yi, Tsinghua University, a Corresponding authors and Project leader.

What Is the Synergy Between Creation & Comprehension? What You Need to Know

Quantum Computing and AI: A Revolution in Technological Synergy

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Digital Synergy: How the Merger of AI and Blockchain Will Play Out

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Hey there, digital creators! Let's talk about something exciting and a bit mind-blowing - AI’s role in web development. Now, before you imagine robots stealing our jobs, that's not our focus here. We're diving into how AI is shaking things up in the best way possible. Think about it: isn’t it cool when tedious tasks get handled by smart tools, or when you get insights that make your design just ? That’s the kind of stuff AI is bringing to the table. But it’s not all sunshine and rainbows. We’ve got to tackle the tough parts too, like what it means for our online privacy or the skills we need to keep up with the AI wave. pop So, stick around! We’re about to take a rollercoaster ride through the ups and downs of AI in our world. And who knows? You might get the itch to give these AI tools a whirl in your next project. Current State of AI in Web Development Alright, let’s get down to business and talk about where we’re at with AI in web development. It's not just sci-fi stuff anymore; AI is here, and it’s making some noise. First off, we've got AI making our lives easier with things like code completion. You know when you're typing, and the perfect piece of code just pops up like it read your mind? That’s all thanks to AI’s language processing, learning from tons of code it’s analyzed. It’s like having a buddy who’s seen it all and gives you insider tips. Then there are the design assistants. These aren't your typical “clippy” helpers; they're advanced tools that suggest design elements, layouts, and even color schemes. Imagine getting real-time feedback about your design choices, almost like a co-designer who’s really into data and trends. But wait, there's more! AI is also our sidekick for testing and debugging. It can automatically spot bugs, and point out what’s off, and some tools can even fix issues on the fly. So, those long nights squinting at lines of code? They might just be a thing of the past. And we can't forget the chatbots. AI-powered chatbots on websites are getting so smart that sometimes it’s hard to tell you’re not chatting with a real person. They’re handling customer questions, guiding users through sites, and providing help 24/7. So, that’s the snapshot of our AI world right now. It’s like having a new set of superpowers, but instead of a cape, we’ve got algorithms and machine learning. And this is just the beginning — there’s a lot more on the horizon! Benefits of Integrating AI Into Web Development Now, let's chat about the good stuff — the real cherry-on-top moments that AI brings to our web development game. We’re not just talking about making things faster or easier (though, there’s plenty of that); it’s about upping the ante across the board. : Remember the days of repetitive coding tasks that felt like a never-ending loop? AI’s cutting that down in a big way. With smart automation, we’re freeing up loads of time. That means we can focus on the cool stuff, like innovation and creativity. It’s like having a personal assistant who handles the grunt work while we brainstorm the next big thing. Saving Time Like a Pro : AI lets us give users the VIP treatment with ultra-personalized experiences. Based on user behavior and preferences, AI tweaks websites in real-time to resonate with visitors. It’s like being a mind reader who can tailor your site to what users want, sometimes even before they know it! Hello, Personalization! : Ever been on a website and felt like it just ? That’s AI at work. Smart recommendations, intuitive navigation, and interactive elements make users feel at home. It’s about crafting experiences that are not just user-friendly but user-adoring. Making Websites Smarter gets you : With AI, we’re not just making sites for some; we’re making them for everyone. AI tools can automatically adjust your website for visually impaired users, translate languages on the fly, and much more. It’s about knocking down barriers and rolling out the red carpet for all. Ace Accessibility : In a world where online threats are like plot twists in a spy movie, AI is our secret weapon. It monitors patterns, fights off hacking attempts, and keeps data locked down tight. Think of it as your website’s personal bodyguard. Boosting Security : AI doesn’t just go with its gut; it’s all about the data. It helps analyze how your site’s doing, providing insights and reports that are gold for making improvements. It’s like having a coach who gives you play-by-play feedback on your game. Analyzing Performance So, there you have it. Integrating AI isn’t a nice-to-have; it’s a game-changer. It’s like your website is cruising on a highway, and AI is the turbo boost taking it to new speeds. And the best part? We’re just scratching the surface! Challenges and Considerations Alright, friends, it's time to get real. Integrating AI into web development isn't a walk in the park. It's more like a hike — super rewarding but with some uphill battles. Let's unpack the not-so-pretty side of our AI journey. : Here’s the deal: AI is fantastic for automation, but can it be creative? Sure, it can suggest designs based on data, but what about that human touch, that spark of genius? There’s a fine line between helpful suggestions and stifling creativity. We’ve got to find the balance. Creativity vs. Automation : Getting on the AI train isn’t so simple. There’s a bunch to learn, and guess what? AI is always evolving. It’s like trying to catch a moving train sometimes. So, we’ve got to invest time in learning and keeping up-to-date, which can be pretty daunting. The Learning Curve : With great data comes great responsibility. AI needs heaps of data to function, but handling that data? Big challenge! We’re talking about security risks, privacy concerns, and ethical dilemmas. It’s a whole thing, and we’ve got to navigate it carefully. Data Privacy : Let’s talk cash. Implementing AI can mean fancy tools and new resources. It’s not always cheap, and for many, budget is a big deal. Weighing the costs versus the benefits is a must-do exercise. Cost Implications : Here’s a tricky one. AI tools are super helpful, but leaning on them too much? Risky business. We might get comfy and stop pushing the boundaries, or worse, lose our problem-solving edge. Keeping our skills sharp while embracing AI is the tightrope we walk. Overdependence : AI’s not just about tech; it’s about people. Creating echo chambers, influencing decisions, cultural sensitivity in design — there’s a lot of power here, and wielding it wisely is non-negotiable. We’re not just developers; we’re guardians of ethical web space. Ethical Quandaries Phew! That’s a lot, right? But knowing the challenges means we’re prepared, and being prepared is half the battle won. It’s about embracing AI but staying woke — understanding the risks, asking the tough questions, and keeping it real. Onward, trailblazers! Case Studies/Real-World Applications Let's take a break from the hypothetical and dive into the real world where AI isn't just a concept; it's a practical tool reshaping how we build the web. We're not naming specific companies (they're out there, and you've probably encountered a few!), but here are some scenarios where AI made a noticeable difference. AI-Powered Personalization in E-Commerce: Imagine an online shopping experience that feels like everything was picked just for you. That's AI working behind the scenes, analyzing user behavior, and making real-time suggestions. It's not just about showing you more of what you like, but also surprising you with things you love but haven't discovered yet. For e-commerce, this means happier customers and, of course, better sales. Automated Quality Assurance Saves the Day: Here's a toast to the end of sleepless nights before a product launch! With AI-driven testing tools, identifying and fixing bugs doesn't have to be a manual marathon anymore. These tools are like an extra pair of eyes that never get tired, scanning every nook and cranny of the code, ensuring everything's in top shape for the big day. Breaking Language Barriers: Expanding your website's reach globally? AI's got your back, offering smart translation that goes beyond words and dives into cultural context. It's not just "Hello" and "Hola"; it's about making every user feel like the content speaks directly to them, no matter where they are. Championing Web Accessibility: AI isn't just about business; it's also about making the web a place for everyone. With smart accessibility features, websites can now be more usable for people with disabilities. Think of dynamic font size adjustments, color contrast settings, and screen reader optimizations. It's the web saying, "Welcome, this place is for you too." The Unsung Heroes of Cybersecurity: In the ongoing battle against cyber threats, AI is the silent guardian watching over websites. It learns from patterns, anticipates risks, and takes action before threats materialize. For website owners, it's peace of mind; for users, it's a promise of safety. These aren't just success stories; they're proof that AI is here, making a difference. It's exciting, it's evolving, and it's very much real. So, the next time you're impressed by a website feature, there might just be AI magic working behind the curtain! Preparing for an AI-Driven Future As we ride this wave of digital evolution, one thing's clear: AI isn't just a fleeting trend; it's the future knocking on our door. So, how do we, as web developers, prep for this AI-driven scene? It's all about adaptability, continuous learning, and a dash of curiosity. : AI’s changing the game, folks. We’ve got to keep our skills fresh and our knowledge up-to-date. Dive into AI-related resources, join webinars, take courses, or even tinker with AI tools on your projects. Stay curious, stay hungry. Never Stop Learning : Let’s face it, stepping out of our comfort zones can be daunting, but that’s where growth happens. Don’t shy away from projects that push you into the AI realm. Be the one who’s eager to experiment and adapt. Embrace the Change : With great power comes great responsibility, right? As we wield AI’s capabilities, it’s crucial to keep the ethical implications in mind. That means respecting user data, valuing privacy, and ensuring transparency. It’s not just about what we can do, but what we should do. Ethics Matter : No one’s alone in this. Being part of a community means sharing insights, learning from others, and maybe even collaborating on projects. Let’s not forget, even with AI, the human touch is what makes the difference. Community and Collaboration Preparing for an AI-driven future isn’t about predicting it perfectly; it’s about being ready to ride the wave, adapt, and make the most of it when it comes. Conclusion: So, there we have it! We’ve journeyed through the AI landscape in web development, uncovered its potential, and even peered into the future. What’s apparent is that AI is more than just code; it’s a tool that amplifies our human capabilities. It’s not here to take over but to elevate. As we embrace AI, we’re not just coding websites; we’re crafting experiences, solving real-world problems, and maybe, just maybe, making the world a little better. So, to all the web developers out there: let’s welcome AI into our toolkit, explore with gusto, create with empathy, and above all, let’s pioneer responsibly into this exciting digital frontier! Remember, the future isn’t written in stone; it’s coded one line at a time. And with AI in our corner, who knows what incredible chapters we’ll pen next?

Embracing the Future: The Unexplored Synergy of AI in Web Development

Machine learning models that can understand and generate both images and text have seen rapid progress recently. But how can we get these "multimodal" models to synergize and mutually boost their abilities in comprehending and creating visual and textual content? That's the key question tackled in an interesting from Anthropic, Tsinghua University, Xi'an Jiaotong University, and MEGVII Technology. new paper Why This Matters Multimodal models could be transformative for how we interact with AI systems. Imagine asking your personal assistant to not just describe a concept but also generate or edit an image to illustrate it. Or searching for media on the internet by describing it instead of keywords. Enabling fluid joint understanding and generation of vision and language is a stepping stone toward more natural and intuitive human-AI interaction. The Technical Stuff The authors propose , a novel framework for training large multimodal language models (MLLMs) that can both understand and generate images and text. DREAMLLM Here are the key elements: Uses for image generation, which creates images by gradually refining random noise into the desired output. This avoids compressing images into discrete tokens that lose details. diffusion models Images are generated by - getting a pretrained diffusion model like Stable Diffusion to guide the training instead of trying to reproduce its internal representations. This prevents information loss. score distillation Trains the model to generate with both text and images, modeling all possible combinations of conditioned outputs. This unified approach allows full learning synergy. free-form interleaved documents Introduces " " - learnable embeddings that extract multimodal semantics from the MLLM to condition image generation, avoiding tampering with its core output space. dream queries Experiments show SOTA results on common multimodal benchmarks, significantly outperforming other MLLMs. DREAMLLM also demonstrates promising zero-shot capabilities in conditional image generation, compositional image editing, and generating coherent interleaved content from prompts. The Significance in Plain English This work moves us closer to AI assistants who can truly understand and generate both visual and textual information. Key takeaways: By training on free-form documents, DREAMLLM learns real-world patterns of interleaving text and images. This helps it develop a joint understanding of vision and language. Modeling images as pixels instead of discrete tokens preserves visual details. The dream queries act as an interpreter between modalities. Not forcing the model to match CLIP's image representations avoids bottlenecks and allows full knowledge transfer between modalities. Strong zero-shot performance shows the model develops a robust general intelligence spanning both images and text. Capabilities like conditional image editing hint at future applications in quickly generating customized visual content. Of course, we're still far from human-level intelligence. There are concerns about bias, safety, and misuse of generative models. But frameworks like DREAMLLM point the way towards more capable and cooperative AI assistants in the future. The key insight is that jointly training generative abilities in both images and text leads to superior understanding and creativity overall. As AI continues crossing modalities, finding synergies between perception, reasoning, and creation will pave the path ahead. Also published . here

Unlocking Synergy: Advancements in Training Multimodal Language Models for Vision and Text

The and UST. collapse of Terra Luna The bankruptcy of Three Arrows Capital and Celsius Network. The . FTX scam The arrival of the regulator. The cryptocurrency market continues to feel shaky, putting pressure on the entire industry. Quite recently, people’s focus has shifted to Artificial Intelligence. However, blockchain remains one of the most promising and important technologies that will literally change everything around us. Web3, Blockchain, and Tokenization , one of the world’s leading IT research companies, identifies three distinct trends for the near future: , and , each of which is a critical factor for emerging technologies. A new study by Gartner Web3 Blockchain, Tokenization Moreover, the report anticipates the emergence of that not only benefits people and society but can also increase transparency and privacy. It is no secret that for AI to be effective and useful, it must be developed in an open-source way. It is also self-explanatory that AI needs data and data needs AI, but current interaction models are not harmonized and do not encourage this symbiosis. Human-centered AI One of the leading companies in the AI market – – despite having openness in its name, is already facing lawsuits for alleged copyright infringement. Training AI for specific use cases requires a data set that is often not available externally, and solving this problem requires a fundamentally new incentive model. There is no doubt that we can build this model by applying Web3 thinking. For example, AI can get traceable access to the data through tokenization, and the owner, in turn, should be entitled to royalties for the authorship of the data. OpenAI If you take a look at the orange area of the diagram, then you will see that Gartner places there, meaning that this technology is already knocking on the door. This cutting-edge technology implies moving computational activity from a central server to the periphery, meaning that model training takes place alongside the data rather than the other way around, but it will require a blockchain infrastructure for security and privacy. Edge AI Edge AI can be used in a variety of industries, including healthcare, transportation and energy. In medicine, for example, Edge AI can be leveraged to analyze patients’ medical data to determine the most effective treatment methods; in transport, Edge AI can help optimize vehicle routes, reduce waiting times at stops and improve road safety; in the energy sector, Edge AI can be exploited to optimize power plants and reduce energy costs. One of the key advantages of Edge AI is that it can operate in real-time, allowing it to react quickly to changes in the environment and make instant decisions based on the data it receives. Another vital aspect is . By tokenizing data access, AI model training companies will be able to create local computing environments where the data is stored. Model owners will then be able to train models on sensitive data for non-trivial use cases, and data owners will receive a premium for authorship without worrying about data security and privacy, as access to the algorithm can be formalized as a smart contract that only trains, but does not upload the data externally. The openness of the smart contract allows it to be audited, removing the issue of trust in the blockchain infrastructure. Tokenization Now, I would kindly ask you to look at the top left of the diagram, where what we call ‘ ’ is located. At the moment, this is a pressing issue for public acceptance of AI, as the models are often created and used by large technology companies. In order to develop the technology, we need to focus on how the data is accessed and who ultimately benefits from the development of the models. Overall, addressing transparency and privacy in AI requires an integrated approach that includes the use of open standards, data protection methodologies, and mechanisms to control the use of models. Revolutionary approaches such as data tokenization and blockchain-based AI, writing business logic into a smart contract, will all contribute to transparency in the technology, as well as saving money by transferring learning algorithms to data. Transparency and Privacy Balancing the Risks for Further AI Development , another influential global research firm, notes that in order to benefit from generative AI, companies need to manage risk, increase reliability, and address potential intellectual property complexities. Forrester One solution is , which is implemented on blockchain and with Decentralized Digital Identity zero-knowledge proof. Zero-knowledge proof is a technique that allows one party (the prover) to prove to another party (the verifier) that a statement is true, without revealing any additional information. As a rule, this technique is used when confidential information needs to be verified without giving access to it. As well as protecting intellectual property, this solution will eventually help replace identity documents with more advanced tokenized alternatives. For example, it is possible to provide proof of age without providing an exact age. At the same time, a more distant prospect is the emergence of – a concept based on blockchain technology to create a decentralized network where information is not controlled by centralized organizations. Instead, data is stored on users’ computers and transferred between them through the network. In Web3, there is no single control center and all transactions are carried out through smart contracts stored on the blockchain. Some of the crucial advantages of Web3 are: Web3 – the lack of a single control center means that data and transactions cannot be modified or deleted without the consent of all participants in the network. Decentralization – the use of blockchain provides a high level of data security by storing information in encrypted form and allowing transactions to be verified. Security – smart contracts automate tasks and processes, making data easier to work with and faster to process. Automation – web3 opens up new opportunities to create game-changing products and services that can be used in various fields such as finance, healthcare, education, etc. Innovation However, at the moment, there are key technical challenges hindering Web3 from being finally released, including scaling and security, identity and key management, as well as privacy. Additionally, there is , articulated by , proposing a set of three main issues that developers encounter when building blockchains: the blockchain trilemma Vitalik Buterin – the network should operate without verification by specific participants so that you can join it as a node using an ordinary computer. Decentralization – the network must be able to withstand a potential 51% attack, where one or a group of nodes take over most of the network, allowing them to alter transaction chains. Security – the ability to increase the number of transactions processed per unit of time. Scalability There is an inevitable trade-off in this trilemma, but to avoid it, the solutions based on large blockchains are applied, most notably on and . Transactions on the underlying network can be expensive and slow, but the usage of Layer2 technologies enables developers to collect transactions off-net and pass them to the main blockchain, increasing the number of transactions passing through a single blockchain and reducing fees by spreading them across all the collected transactions for that block. Layer2 Bitcoin Ethereum Achieving all three aspects is considered by some in the business to be an impossible task that will never be accomplished, at least not soon. However, some ambitious developers still hold on to the notion that blockchain networks are capable of including all three of these features and more. is one instance of a cryptocurrency project that claims to be resolving the blockchain trilemma. Algorand Emergence of New Economic Sectors One of the world’s leading accountancy firms, , explores the value that blockchain will add to the global economy by 2030: it estimates that more than 40 million jobs will be improved, and the overall impact of blockchain on the global economy is estimated at US$1.76 trillion. PwC The PwC report also features the top five applications of blockchain: (potential boost to global GDP by 2030: US$962bn) – improving consumer safety in the supply chain, as well as confidence in the authenticity and origin of goods, e.g. pharmaceuticals. Provenance (US$433bn) – reducing costs and speeding up transactions, improving financial accessibility, and optimizing cross-border payments. Payments and Financial Instruments (US$224bn) – freedom from labor-intensive and inefficient paper-based record-keeping systems that are easily breached. Identity (US$73bn) – improving the flow of commercial agreements and flagging any disputes. Contracts and Dispute Resolution (US$54bn) – Prevent customers from leaving loyalty programs by consolidating programs and transferring scores between different systems, and increasing the liquidity of subscription products through tokenization. Customer Engagement Conclusion In conclusion, the duumvirate of blockchain and Artificial Intelligence is an incredibly powerful tool for creating more secure, efficient, and transparent systems. Their combination can improve data quality, speed up information processing and increase automation. However, in order to maximize their impact, it is necessary to consider all aspects of the interaction of these technologies and develop effective strategies for their application in different areas of activity. Blockchain technology is definitely not easy to use, but it has been modernized in recent years, and with the advent of Artificial Intelligence, it is becoming more customizable and useful at both government and grassroots levels than ever before.

The Digital Duumvirate: Exploring a Potential Synergy Between Blockchain Technology and AI

Blockchain and artificial intelligence (AI) are two of the most exciting and rapidly developing technologies that are heralding the digital revolution. When divided, the two refurbish the way we interact, work, and live with each other. When merged, the sky's the limit on the solutions they provide in different sectors, from finance to medicine, supply chains, academic research, computation technologies, and much more. The goal of the Blockchain-AI merger is the creation of powerful solutions that alleviate some of the challenges we face as a digital society. Explored below, in no particular order, are some leading projects that exploit the properties of blockchain technologies (decentralisation, immutability, smart contracts, etc.) and AI (simulation of human intelligence, exemplary problem-solving skills, learning from the data provided to get exponentially smarter over time.) to build the next generation of Blockchain-AI systems. Promising Blockchain-AI Projects: An Overview of their Innovative Use Cases The synergy between blockchain tech and AI creates innovative solutions across different industries. Let us dive into the benefits of this integration and their impact on the future of business and society - we will do this by highlighting the key players and organisations leading the way in this field. DeepBrain Chain - Blockchain-AI for Computation This is a decentralised AI computing platform that supplies processing power to companies looking to develop AI technologies. The main use cases of the platform lie within blockchain, artificial intelligence, cloud games, visual rendering, biopharmaceuticals, and semiconductor simulation. Companies leverage the functionality of DeepBrain Chain to attain highly cost-effective GPU computing power. AIWork - Blockchain-AI in Video Content Dubbed the 'Open Network for Artificial Intelligence,' AIWork is powered by blockchain tech to help facilitate a marketplace of crowdsourced AI human experts that create, verify, and validate AI data sets that make AI smarter in the video content realm. The project's main use case is the refurbishing of the content safety index for video content viewers, enabling programmatic determination of content suitability based on a numeric filter criteria. Their upcoming Open Video Search Engine will offer a transparent and ubiquitous index and search engine for online video curated and maintained by the community. By doing so, content distributors, publishers, and advertisers will achieve broad adoption and network effects of the video content they publish. Erasure - Blockchain-AI in Finance Erasure is Numerai's prediction marketplace that leverages AI’s data learning capabilities and blockchain's decentralised nature for financial predictions. The Erasure Protocol does not rely on speculative tech, and through it, data scientists and other participants can buy and sell their predictions based on data sets. The goal is to create a more efficient market for financial data - a market operating on both AI and a blockchain network that enjoys security, transparency, and immutability to the transactions and data. doc.ai - Blockchain-AI in Medicine This decentralised, blockchain-based platform aids in medical data analysis and prediction by leveraging the potential behind artificial intelligence (AI) and machine learning (ML) to enable patients better understand their health and make more informed decisions. Doc.ai's primary use case is the provision of personalised and accurate healthcare information to its users. ML enables the platform to analyse large amounts of data (encrypted and stored to the blockchain) and generate insights and predictions tailored to an individual user's current status and health history. The platform also provides researchers and healthcare organisations with access to large datasets needed in medical research. Data contributed by its users can be used to advance scientific understanding of various health conditions, develop new treatments, and improve medical outcomes. Intuition Fabric - Blockchain for AI Algorithms The Intuition Fabric brings the development and deployment of machine learning (ML) and artificial intelligence (AI) models to our fingertips. Blockchain technology is a key contributing factor towards the collaboration between businesses, developers, and data scientists. The platform's main use case is the provision of powerful AI and ML resources to businesses without the need for technical expertise or extensive infrastructure. By bringing AI and ML closer to those that need it, organisations can enjoy improved decision making, enhanced customer experiences, and optimised processes. Also, when data scientists and developers collaborate, the Blockchain-AI industry will experience accelerated development rates, driving innovation in a range of industries. The Future of Blockchain & AI Blockchain-AI is still in its early stages, with more evolution and expansion expected in the field - overall, the future of Blockchain-AI is exciting. For the upcoming Blockchain-AI projects that are struggling to establish a foothold in the field, the best way forward is having a strong vision and execution strategy, with a focus on innovation and solving real-world problems. Borrowing a leaf from the projects explored earlier, we can deduce that newcomers need to have: Collaborative ecosystems Open-source approaches Strong technical expertise A clear use case and value proposition A Strong governance structure Compliance with regulatory frameworks The intersection of blockchain and AI has birthed innovative solutions that could transform a wide range of industries. Blockchain-AI has the potential to unlock new opportunities for social impact, collaboration, and innovation. The power of this synergy goes beyond the standalone Blockchain and AI features by creating more secure, transparent, and efficient solutions that address some of the most pressing challenges facing our society today.

Unlocking the Power of Synergy: Leading Blockchain-AI Projects and Their Use Cases

The metaverse Yet another sci-fi phenomenon in the tech world and the spaces of crypto, gaming, and art — the metaverse is the futuristic concept that refers to a persistent simulated online digital universe that mimics the real world. On the tech side, to provide an immersive experience for its users, the metaverse combines multiple elements, including such integral components as VR, AR, MR, and blockchain, along with social media concepts. Coined in the early 1990s by American science fiction writer Neal Stephenson in his novel , the term ‘metaverse’ originally described a virtual world in the imagined future where VR goggle-wearing users inhabit 3D avatars and buy and sell virtual real estate on a planet-encircling market. Snow Crash Today it is considered more as a future iteration of the internet that creates a shared 3D virtual space, an environment that enriches users’ interaction while they perform online the activities that they do in everyday life, whatever they are — working or shopping, playing games, or socializing together. The metaverse concept has been a buzzword and one of the hottest trends, especially after Facebook’s announcement that it was rebranding to Meta, and giant companies like Microsoft, Google, and Sony dived into the metaverse with their unique platforms or started investing. Currently, there are plenty of metaverses out there, for example, the popular virtual world Decentraland, the Pokemon-inspired play-to-earn metaverse game Axie Infinity, and the digital gaming platform The Sandbox. While a single, united metaverse with unified online infrastructure and real-time events is likely a way off, the developments that may lead to its creation are already here. Advantages of the metaverse The most notable one is that the metaverse , connecting the world and negating physical distance. It brings some kind of equality. The metaverse acts as a neutral space where everyone can meet as equals to some extent. destroys geographic barriers On top of that, the metaverse , mainly for business and educational institutions. With the benefits of 3D virtual worlds and engaging seamless experiences, social interactions and events are way more immersive. Keep in mind, that since the raging pandemic grasped the world in its clutches in 2020, individuals and organizations recognized the value of remote or distance interactive meetings, working, and learning in event of restrictions. So today it makes sense. has the potential to bring innovations in communication Another metaverse advantage . The metaverse economy can serve as the ideal platform for exchanges of digital assets with real economic value. Cryptocurrency and NFTs play crucial roles here through blockchain technology providing decentralization, transparency, and trust. Due to them, the metaverse provides the right grounds for innovative advancements in DeFi, GameFi, and tokenization of content. focuses on the creation of a separate virtual economy Also, the metaverse brings up beyond Web2, along with establishing its role in marketing. new opportunities for expanding branding and social media A late 2021 Statista survey of global internet users that overcoming obstacles that prevented them from doing something in real life was perceived as the biggest benefit of the metaverse. Enhancing creativity and imagination was ranked second with 37 percent of respondents claiming this as a benefit. The metaverse also holds promise for upskilling, education, and exploring new career opportunities. found Cons of the metaverse However, despite the apparent advantages, as always, there are two sides to every coin. It is difficult not to pay attention to and other sorts of illegal activities that are already disrupting the existing extremely vulnerable digital space. cyber security crime, fraud, Sybil attacks and identity theft , The statistics insane numbers — around 1 in 15 people become victims of identity fraud. And in 2022 identity theft scenarios are increasing drastically. There were 5.7 million reports of identity theft and fraud in the US only last year, up from 4.7 million in 2020. With a $500 median loss, the cost to victims is growing as society becomes more digitally dependent. show One of the reasons why security threats remain is that people store, contribute, and share a lot of personal information (PII) and sensitive data online. Events like the that exposed 700 million user records confirmes that, shaking the digitized world to the bone over and again. LinkedIn breach One of the most significant security risks in the digital space is the one that is associated with social networks. Users can never be 100% sure that you interact with the exact person they want to connect with — or with a real person altogether. In the metaverse, with the proliferation of avatars and lack of moderation, communication with the right individual may become even more challenging. In addition, in the metaverse where people will enter more networks via various tools like VR goggles, mobile devices, and various services, the risk of fraudulence or device thievery is much higher. has always been a concern in the digital space, with people unaware of their data being collected and sold. The main agenda for criticism is the fact that major players like Meta are leading the charge towards the new metaverse. Considering their previous history with privacy concerns of their users, that doesn’t simply fade away. The metaverse can lead to new issues in privacy for individuals as well as institutions. Privacy Other concerns around the metaverse are related to Thus, as a realistic 3D universe the metaverse blurs the gap between real and virtual worlds. Similar to gaming, addiction becomes a significant issue. There is a bigger addiction risk with the metaverse, since users are fully immersed in a virtual world, and while they are in the metaverse they easily lose track of time. mental health issues, addiction, and loss of connection with the physical world. Needless to say, while a secondary issue the metaverse remains, as for those who are not into tech or don’t belong to the crypto community, joining it is still problematic. Overcoming this flaw is important because without it the metaverse phenomenon will hardly reach mass adoption. UX issue Biometrics Biometrics as a technology for identifying a person based on the measurement and statistical analysis of its unique physical or behavioral characteristics is a phenomenon of high importance in modern society. It is a key to anchoring digital identity and the most suitable means of authenticating individuals in a reliable and fast way. Overall face shape, fingerprints, palm print, hand geometry, iris recognition, DNA, dental records, and even more subtle metrics like heartbeats or odor — modern technology can measure extremely complex inputs to find identity matches or verify identity. And experts argue that growth trends in mobile identity verification and remote onboarding will be sustained due to the recent pandemic spread which leads to the e-passport and health-passport markets explosion. Merits and demerits Biometrics provides numerous benefits. Thus, biometric technology is comparatively less time-consuming, dependable, user-friendly, and hard to falsify. However, there are some risks associated with biometric authentication. The main issues here are . security and privacy concerns In the last decades, major tech companies like have been constantly working on seamless user experiences without a hitch, bypassing the problems with login credentials. At the same time, users get used to trusting big tech to manage and collect their biometric data. These privacy concerns are multiplied by the fact that biometric data is regarded as highly sensitive since it may be linked to a single person. Apple Another major tech company patents captures users’ behavioral biometrics data. Specifically, pupil movements, body poses, and crumpled noses, which Meta would use to make digital avatars realistically animated. The patents by The Financial Times, according to their article Meta also intends to use biometric data to provide hyper-targeted advertising and sponsored content. Meta were reviewed What’s more, the company says it has created a new tool, , that will enable someone in Horizon, Meta’s metaverse, to import and create digital objects and features using only their voice. The voice assistant may not include a biometric authentication feature, but would rapidly accumulate a database of speech data, if successful. And an AI model for chatting with virtual assistants, something called Project , aims to enable natural conversations between assistants and people. Meta engineers also are working on software to all written languages and, separately, a universal speech translator for instant spoken-word translation. BuilderBot CAIRaoke translate Yet nothing is said about . biometric privacy at Meta Furthermore, even though biometric scanners are persistently improving in terms of quality, they can still create when an authorized user is not identified or authenticated, as well as false positives when an unauthorized person is recognized and authenticated. false negatives The most noteworthy merits and demerits of biometric identification are listed in the table above. In a nutshell, on the one hand, biometrics is , as well as , and remains a constant , on the other. and secure, flexible, affordable, trustable , and costly complex subject to attacks Q&A Before the world will dive headlong into the metaverse, the following questions need to be answered: How to protect your biometric data from malicious collection or theft? How to make sure that nobody else embodies your identity or metaverse avatar? How to ensure that you are not manipulated, and the person or company you interact with virtually is who you think they are? How to simplify the entrance to the metaverse and its UX for non-tech savvy users? Blockchain and biometrics are the answers, coming to the rescue here. Web3 and its backbone — have the potential to solve security issues and the need to trust personal data to major corporations when it comes to biometrics. blockchain Decentralization and transparency are the key concepts in Web3, that strive to increase the level of trust between the network’s participants, in the scenario when there is no third party controlling it. To minimize the risk of fraud, the metaverse operator shouldn’t have complete control over the biometric identity information and user data. The chosen identity authentication system could work with blockchain technology to help people stay in control of their personal data and how they are used. The blockchain would keep personal data under a user’s control because it cannot be changed once it’s on the public ledger. The service would just check against the blockchain whether the data user is genuine. This so-called self-sovereign identity attempts to solve the problem of providing personal info to service providers without risking data misusage. Linked with blockchain and protocols like zero-knowledge proofs are phenomena that are designed to bring privacy to the metaverse. encryption Precise, reliable, and handy can help protect metaverse users’ identities and the identities of others. Face recognition with liveness detection and iris scans are some of the most reliable biometric modalities. Regular biometric checks ensure that the metaverse user’s device such as VR goggles has not switched for another person. The system can have additional verification mechanisms, for example, through geolocation data. If the goggles are out of the usual space, further verification may be required. The idea is to validate a person’s authorized access with a combination of , such as a second software device, as seen in two-step verification. biometric identity verification biometrics and other authentication elements Furthermore, Biometrics is platform-agnostic, therefore users can leverage biometric verification for customer verification processes on all their devices — phones, goggles, or browsers. This makes biometrics very convenient when used for various gadgets. Compared with passwords, biometric authentication is faster and more seamless. With it, metaverse visitors have their biometric data at hand all the time, and it can’t be forgotten or lost. . biometrics enhances user experience On top of that, the appearance of items and agents metaverse users are interacting with can be adapted to their preferences based on data that they have shared. For example, eye tracking data can provide pupil dilation and gaze fixation data in response to visual stimuli, motion data can provide proxemic behavior and body language cues, and physiological data like EEG and skin conductance can provide levels of emotional activation. Additionally, facial tracking can also provide a window into an emotional response. These nonverbal cues can be fed into clever ML and AI algorithms to create personalized, idealized interactions. Blockchain and biometrics merge could have many pros for the metaverse. Blockchain technology biometric systems with some desirable characteristics such as immutability, accountability, availability, and universal access. Additionally, the integration of biometric technology is very beneficial for blockchain-based metaverses too, as it could significantly improve the current distributed digital identity schemes. In this case, an authentication protocol based on biometrics could significantly raise the current security level. could provide The merge: Web3 + biometrics Humanode is the world’s first blockchain project that utilizes a consensus mechanism based on crypto-biometric identification, to realize its goal of one human = one node = one vote network that brings Sybil resistance and innovative governance models to economics as a whole, and the crypto industry, in particular, using biometric technology. Humanode Humanode’s direct biometric API allows metaverses and other Dapps to integrate and enable unique online identities. Utilizing biometrics as one of its core technologies, Humanode creates the decentralized biometric identification layer that is not only used on the native Humanode platform but can be used in the metaverse. Due to s liveness detection technology, these biometric identifications ensure that the right person enters the metaverse and that he is a unique and real human being. FaceTec’ Humanode biometric identifications are likely to be tied in as an option for metaverse visitors’ identification in form of a wallet’s browser extension or as a full-fledged app. They will provide a simple way to interact with the metaverse and offer the most user-friendly interface for non-techy users. By only scanning their face, they will effortlessly access the metaverse, buy and sell tokens there, and sign transactions most accurately and securely. It is known that the collection of biometric data raises privacy concerns about the ultimate use of this information. The Humanode team is working on it. Besides biometrics and blockchain technologies in the broad sense, the project utilizes which is based on a stack of various disciplines and technologies such as cybersecurity, encryption, liveness detection, and zero-knowledge proofs. Once a user logs in to the Humanode, the 1 to n search and matching operation happens in an encrypted space, and because it is zero-knowledge based, the only piece of information that is searched for and is given out is if that user is a registered user or not. crypto-biometrics Avarta s biometric technology plays a critical role in another ambitious crypto project. In this case, the company’s partner is Singapore-based , a startup that is working to build an identity platform tailored to the DeFi and metaverse spaces. FaceTec’ Avarta Avarta aims is to establish a trust scoring system based on aggregated wallet data collected from multiple blockchain platforms while empowering end users with the ability to control what information they share with trusted third parties when seeking to gain access to regulated platforms or whitelists. Avarta is also looking to leverage geofencing and device scoring for its identity platform and has patented what it calls a “Dynamic PIN Lock” system. IriTech & IBCT In July 2022, with the Institute of Blockchain Technology (IBCT) to strengthen security for metaverse applications. The result is the Decentralized Identity Data Hub (DIDH) that runs on the blockchain. In practice, the joint offering will replace legacy security solutions like PINs with more secure iris biometrics for those using hardware wallets. Those wallets often give the owner no recourse if they forget their PIN, whereas the IriTech offering will allow owners to retrieve their secret backup seed with an iris recognition scan. In doing so, it will give owners a way to recover their accounts without exposing them to the security risk associated with any knowledge-based authenticator. IriTech teamed up The iris scan for the joint solution will be carried out with IriTech’s , which comes with liveness detection and is compatible with mobile devices. The goal, according to the two companies, is to give people more control over their personal information, in a manner that adheres to the principles of Self-Sovereign Identity (SSI). Data that is stored with the iris tech could theoretically be used for a variety of applications, ranging from healthcare and financial services to virtual and augmented reality. IriTech since its tech can be deployed alongside the iris tracker in a headset. IriKey technology expects VR and AR to be especially popular use cases Conclusion Both blockchain and biometrics technologies can mutually benefit each other and the metaverse, especially when combining them. Although the unified metaverse is still in its infancy, from all the above discussion, it is clear that biometrics alongside blockchain has the potential to make metaverse identity management decentralized, secure, private, simplified, and seamless, metamorphosing the landscape and accelerating adoption. Also Published Here

Metaverse and Biometrics' Synergy - Vol 1

Freelancing is probably one of the main pillars of the modern economy. It would be difficult to get our job or task done if it’s not for on-demand services platforms and freelancers. This helps us to manage time and resources efficiently and achieve goals that seem plausible before. But everything isn’t going inflow in the freelancing industry. Whether we see it from freelancers’ perspective or the other way around. Freelancer faces job insecurity and poor rewards. According to a , those who prefer freelancing over a proper job earn less than their counterparts. Uber in 2014, claimed that cab drivers in NYC earn a handsome amount of $ . But according to a found that an average Uber driver earns more or less $14 per hour including the tips received. report from Deloitte 91,000 annually recent survey from Ridester Yet with all these difficulties, the gig economy is growing at a rapid pace. On the other hand, clients face difficulties in finding skilled professionals for their tasks. Often the freelancers they hire couldn’t produce satisfying results or lack skills and professional knowledge. Both the freelancers and clients have had several issues with the quality of user experience during their journey on different freelancing platforms, it seems more obvious that a change or technological disruption is needed to address these issues. Issues with freelancing platforms While one solution is simply not to use freelancing platforms, this solves certain problems but creates new ones altogether. Here are some major problems that freelancers and clients face today. Too many spams and fake job posts On major freelancing platforms such as Upwork and Fiverr, clients are allowed to post jobs without paying anything. While freelancers working on these platforms have to go under some scrutiny to reduce the number of spam and fake posts. There are possibilities that the project listed is legit but the threat of spam remains unchanged and results in the wasted time for freelancers. Clients on the other side of the aisle feel that most of the freelancers didn’t get the job done at the time. So fake and spammy jobs create difficulties for both clients and freelancers. Contract dispute resolution support isn’t available While there is a common misconception, on both sides, that freelancing platform provides a contract dispute resolution. The clients assume that their money is secure with the freelance platform and freelancers are always threatened that if the client rejects their work their rating will be down despite delivering quality work. Oftentimes, freelancers either don’t receive any of the funds from escrow or only receive a portion. Meanwhile, the clients are always in tension, if they are handling their work to the right person who will deliver it according to their expectations. Adding to these difficulties, freelancers have to pass different tests to achieve a higher level and ratings. What problems do AI and Blockchain solve in freelancing? While these problems exist with almost every freelancing website, artificial intelligence, and blockchain technology, which has been enhancing the working capabilities of different industries through innovations and efficient solutions. Industries like finance, agriculture, marketing all have been benefited from these technologies. Artificial intelligence and machine learning are changing the way we bank and blockchain is adding safety to the financial sector. Countries are even looking to use blockchain technology for secure and democratized voting. Similarly, these two technologies can assist skilled professionals and businessmen to connect with each other without any threat. Even though freelancing platforms are a good way to find remote work and hire talent but still the presence of a middleman remains. Blockchain’s decentralized system and unhackable security make . Businesses could hire talent directly without any extra third party charges. it perfect technology for the freelancing marketplace Freelancers will have the opportunity to build a profile that is saved and is available with them every time. This way both clients and freelance can easily connect to each other and make the deal without having any difficulties and trust issues. Blockchain technology brought about a revolution that will no doubt be felt up until the next century and beyond. Due to the level 6 encryption of blockchain technology, it remains one of the safest and most anonymous means of storage. is one such startup with smart contracts that adds more security to both clients and skilled professionals prospects. Similarly, that has a decentralized global operating system with infinite processing power, Netcoincapital is trying to take a step in designing and building a new generation of processors. The processors that the company is studying, will turn each of the home devices into a supercomputer. Intelligent Hero Netcoin Capital a blockchain-based platform AI engineers are innovating their own solutions for the betterment of the freelance marketplaces. The technology helps freelancers in better project management and finding the right job matching their skills. Smart AI algorithms allow freelancers to better target their pitches and secure jobs. While freelancing itself helped AI and blockchain startups and ideas to grow, these technologies hold the potential to return the favor by solving the problems that freelancers and clients have to go through. It can also make it easy for every skilled person to freelance by adding transparency.

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