Indonesian multinational telecommunications conglomerate Telkom Indonesia, and South Korean telecommunications giant KT Corp have signed a memorandum of understanding (MoU) to collaborate on a smart city project in what will soon be the country’s new capital,

Telkom Indonesia and KT announce MoU for Indonesian smart city project

Major 5G services market participants include AT&T, Inc., BT Group plc, China Mobile Ltd., China Telecom Corporation Ltd., Bharti Airtel Ltd., NTT Docomo, KT Corp., Saudi Telecom Company, Vodafone Group,

5G Services Market to exceed $1 Tn by 2032, Says Global Market Insights Inc.

South Korean telecommunications giant KT Corp. announced Wednesday that it has secured a partnership with Telkom Indonesia, pushing development for the smart city project in Indonesia’s new capital, Nusantara.

KT, Telkom join hands for Indonesia smart city project

South Korea's leading mobile carrier KT Corp. said Wednesday it has signed an initial agreement with Indonesia's state-owned telecommunications network Telkom Indonesia to cooperate for a smart city project in the Southeast Asian country's new capital.

KT signs MOU for smart city project in Indonesia's new capital

South Korean telecommunications giant KT Corp. on Tuesday unveiled Mi:dm, a customizable large language model aimed at corporate clients looking to develop their own advanced AI services in the booming field of generative AI technologies.

KT unveils large language model Mi:dm for corporate customization

KT unveiled its hyperscale AI platform Mi:dm and will expand its AI business in business-to-business (B2B) markets at a time when increasing numbers of organizations are considering adopting the emerging technologies to improve efficiency and productivity,

KT launches hyperscale AI platform Mi:dm

KT launches hyperscale AI Mi:dm

SEOUL, Oct. 31 (Yonhap) -- South Korea's leading mobile carrier KT Corp. on Tuesday unveiled its large artificial intelligence (AI) model, Mi:dm, in a bid to expand its AI business to the manufacturing, financial, education and public sectors, as well as the global market.

(LEAD) KT launches 200 bln-parameter large AI model Mi:dm

South Korean network operator KT Corp. has teamed up with LG Electronics and Corning to develop reconfigurable intelligent surface (RIS) technology that can be used in multiple candidate 6G radio frequencies; backhaul equipment specialist Ceragon Networks ...

What’s up with… KT, Ceragon, Vodafone

Advanced Micro Devices (AMD) and Korean telco KT are among the investors of Moreh, which builds an AI software tool that optimizes and creates AI models.

AMD and Korean telco KT back AI software developer Moreh in $22M Series B

KT CORPORATION

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Authors:
(1) Hoon Kim, Beeble AI, and contributed equally to this work;
(2) Minje Jang, Beeble AI, and contributed equally to this work;
(3) Wonjun Yoon, Beeble AI, and contributed equally to this work;
(4) Jisoo Lee, Beeble AI, and contributed equally to this work;
(5) Donghyun Na, Beeble AI, and contributed equally to this work;
(6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 9 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction
2. Related Work
3. SwitchLight and 3.1. Preliminaries
3.2. Problem Formulation
3.3. Architecture
3.4. Objectives
4. Multi-Masked Autoencoder Pre-training
5. Data
6. Experiments
7. Conclusion Appendix A. Implementation Details
B. User Study Interface
C. Video Demonstration
D. Additional Qualitative Results & References 6. Experiments This section details our experimental results. We begin with a comparative evaluation of our method against state-ofthe-art approaches using the OLAT dataset. We also employ images from the FFHQ–test [25] for user studies. For qualitative analysis, we utilize copyright-free portrait images from Pexels [1]. Additionally, we conduct ablation studies to validate the efficacy of our pre-training framework and architectural design choice. Subsequently, we detail the additional features and conclude by discussing its limitations. Our evaluation uses the OLAT test set, comprising 35 subjects and 11 lighting environments, ensuring no overlap with the train set. Evaluation metrics. We employ several key metrics for evaluating the prediction accuracy; Mean Absolute Error (MAE), Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM) and Learned Perceptual Image Patch Similarity (LPIPS). While these metrics offer valuable quantitative insights, they do not fully capture the subtleties of visual quality enhancement. Therefore, we emphasize the importance of qualitative evaluations to gain a comprehensive understanding of model performance. Baselines. We compared our approach with three state-of-the-art baselines: Single Image Portrait Relighting (SIPR) [45], which uses a single neural network for relighting; Total Relight (TR) [34], employing multiple neural networks that incorporate the Phong reflectance model; and Lumos [52], a TR adaptation for synthetic datasets. Due to the lack of publicly available code or model from these methods, we either integrated their techniques into our framework or requested the original authors to process our inputs with their models and share the results. Quantitative Comparisons. The results in Table. 1 shows our method outperforming SIPR and TR baselines, demonstrating the significance of incorporating advanced rendering physics and reflectance models. The transition from SIPR to TR emphasizes the value of physics-based design, while the shift from TR to our approach underscores the importance of transitioning from the empirical Phong model to the more accurate Cook-Torrance model. Additionally, pretraining contributes to further enhancements, as evidenced by the improved image details, depicted in Fig 6. Qualitative Comparisons. Our relighting method exhibits several key advantages over previous approaches, as showcased in Fig. 7. It effectively harmonizes light direction and softness, avoiding harsh highlights and inaccurate lighting that are commonly observed in other methods. A notable strength of our approach lies in its ability to capture highfrequency details like specular highlights and hard shadows. Additionally, as shown in the second row, it preserves facial details and identity, ensuring high fidelity to the subject’s original features and mitigating common distortions seen in previous approaches. Moreover, our approach excels in handling skin tones, producing natural and accurate results under various lighting conditions. This is clearly demonstrated in the fourth row, where our method contrasts sharply with the over-saturated or pale tones from previous methods. Finally, the nuanced treatment of hair is highlighted in the sixth row, where our approach maintains luster and detail, unlike the flattened effect typical in other methods. More qualitative results are available in our supplementary video demonstration. User Study. We conducted a human subjective test to evaluate the visual quality of relighitng results, summarized in Table. 2. In each test case, workers were presented with an input image and an environment map. They were asked to compare the relighting results from three methods–Ours, Lumos, and TR–based on three criteria: 1) consistency of lighting with the environment map, 2) preservation of facial details, and 3) maintenance of the original identity. To ensure unbiased evaluations, the order of the methods presented was randomized. To aid in understanding the concept of consistent lighting, relit balls were displayed alongside the images. The study included a total of 256 images, consisting of 32 portraits each illuminated with 8 different HDRIs. Each worker was tasked with selecting the best image for each specific criterion, randomly assessing 30 samples. A total of 47 workers participated in the study. The results indicate a strong preference for our results over the baseline methods across all evaluated metrics. Ablation Studies. We analyze our two major design choices in Table. 3: the MMAE pre-training framework and DiffuseNet. The MMAE, which integrates dynamic masking with generative objectives, outperforms MAE. This superiority is mainly due to the incorporation of challenging masks and global coherence objectives, enabling the model to learn richer features during pre-training. Furthermore, our method of predicting diffuse render demonstrates superiority over direct albedo prediction. Firstly, we see it simplifies the learning process, as predicting diffuse render is more closely related to the original image. Secondly, our approach effectively distinguishes between the influences of illumination (diffuse shading) and surface properties (diffuse render). This distinction is crucial for accurately modeling the intrinsic color of surfaces, as it enables independent and precise evaluation of each element (see Eqn. 9). In contrast, methods that predict albedo directly often struggle to differentiate between these factors, leading to significant inaccuracies in color constancy, as shown in Fig. 8. Applications. We present two applications using predicted intrinsics in Fig. 9. First, real-time PBR via Cook-Torrance components in Three.js graphics library. Second, switching the lighting environment between the source and reference images. Further details are in the supplementary video. Limitations. We identified a few failure cases in Fig. 10. First, our model struggles with neutralizing strong shadows, which leads to inaccurate facial geometry and residual shadow artifacts in both albedo and relit images. Incorporating shadow augmentation techniques [16, 54] during training could mitigate this issue. Second, the model incorrectly interprets reflective surfaces, such as sunglasses, as opaque objects in the normal image. This error prevents the model from properly removing reflective highlights in the albedo and relit images. Lastly, the model inaccurately predicts the albedo for face paint. Implementing a semantic mask [52] to distinguish different semantic regions separately from the skin could help resolving these issues. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Authors: Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 9 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 9 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 9 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 9 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.3. Architecture 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 5. Data 6. Experiments 7. Conclusion Abstract and 1. Introduction Abstract and 1. Introduction 2. Related Work 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.2. Problem Formulation 3.3. Architecture 3.3. Architecture 3.4. Objectives 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 4. Multi-Masked Autoencoder Pre-training 5. Data 5. Data 6. Experiments 6. Experiments 7. Conclusion 7. Conclusion Appendix A. Implementation Details B. User Study Interface C. Video Demonstration D. Additional Qualitative Results & References A. Implementation Details A. Implementation Details B. User Study Interface B. User Study Interface C. Video Demonstration C. Video Demonstration D. Additional Qualitative Results & References D. Additional Qualitative Results & References 6. Experiments This section details our experimental results. We begin with a comparative evaluation of our method against state-ofthe-art approaches using the OLAT dataset. We also employ images from the FFHQ–test [25] for user studies. For qualitative analysis, we utilize copyright-free portrait images from Pexels [1]. Additionally, we conduct ablation studies to validate the efficacy of our pre-training framework and architectural design choice. Subsequently, we detail the additional features and conclude by discussing its limitations. Our evaluation uses the OLAT test set, comprising 35 subjects and 11 lighting environments, ensuring no overlap with the train set. Evaluation metrics. We employ several key metrics for evaluating the prediction accuracy; Mean Absolute Error ( MAE ), Mean Squared Error ( MSE ), Structural Similarity Index Measure ( SSIM ) and Learned Perceptual Image Patch Similarity ( LPIPS ). While these metrics offer valuable quantitative insights, they do not fully capture the subtleties of visual quality enhancement. Therefore, we emphasize the importance of qualitative evaluations to gain a comprehensive understanding of model performance. Evaluation metrics. MAE MSE SSIM LPIPS Baselines . We compared our approach with three state-of-the-art baselines: Single Image Portrait Relighting ( SIPR ) [45], which uses a single neural network for relighting; Total Relight ( TR ) [34], employing multiple neural networks that incorporate the Phong reflectance model; and Lumos [52], a TR adaptation for synthetic datasets. Due to the lack of publicly available code or model from these methods, we either integrated their techniques into our framework or requested the original authors to process our inputs with their models and share the results. Baselines SIPR TR Lumos Quantitative Comparisons. The results in Table. 1 shows our method outperforming SIPR and TR baselines, demonstrating the significance of incorporating advanced rendering physics and reflectance models. The transition from SIPR to TR emphasizes the value of physics-based design, while the shift from TR to our approach underscores the importance of transitioning from the empirical Phong model to the more accurate Cook-Torrance model. Additionally, pretraining contributes to further enhancements, as evidenced by the improved image details, depicted in Fig 6. Quantitative Comparisons. Qualitative Comparisons. Our relighting method exhibits several key advantages over previous approaches, as showcased in Fig. 7. It effectively harmonizes light direction and softness, avoiding harsh highlights and inaccurate lighting that are commonly observed in other methods. A notable strength of our approach lies in its ability to capture highfrequency details like specular highlights and hard shadows. Additionally, as shown in the second row, it preserves facial details and identity, ensuring high fidelity to the subject’s original features and mitigating common distortions seen in previous approaches. Moreover, our approach excels in handling skin tones, producing natural and accurate results under various lighting conditions. This is clearly demonstrated in the fourth row, where our method contrasts sharply with the over-saturated or pale tones from previous methods. Finally, the nuanced treatment of hair is highlighted in the sixth row, where our approach maintains luster and detail, unlike the flattened effect typical in other methods. More qualitative results are available in our supplementary video demonstration. Qualitative Comparisons. User Study. We conducted a human subjective test to evaluate the visual quality of relighitng results, summarized in Table. 2. In each test case, workers were presented with an input image and an environment map. They were asked to compare the relighting results from three methods–Ours, Lumos, and TR–based on three criteria: 1) consistency of lighting with the environment map, 2) preservation of facial details, and 3) maintenance of the original identity. To ensure unbiased evaluations, the order of the methods presented was randomized. To aid in understanding the concept of consistent lighting, relit balls were displayed alongside the images. The study included a total of 256 images, consisting of 32 portraits each illuminated with 8 different HDRIs. Each worker was tasked with selecting the best image for each specific criterion, randomly assessing 30 samples. A total of 47 workers participated in the study. The results indicate a strong preference for our results over the baseline methods across all evaluated metrics. User Study. Ablation Studies. We analyze our two major design choices in Table. 3: the MMAE pre-training framework and DiffuseNet. The MMAE, which integrates dynamic masking with generative objectives, outperforms MAE. This superiority is mainly due to the incorporation of challenging masks and global coherence objectives, enabling the model to learn richer features during pre-training. Furthermore, our method of predicting diffuse render demonstrates superiority over direct albedo prediction. Firstly, we see it simplifies the learning process, as predicting diffuse render is more closely related to the original image. Secondly, our approach effectively distinguishes between the influences of illumination (diffuse shading) and surface properties (diffuse render). This distinction is crucial for accurately modeling the intrinsic color of surfaces, as it enables independent and precise evaluation of each element (see Eqn. 9). In contrast, methods that predict albedo directly often struggle to differentiate between these factors, leading to significant inaccuracies in color constancy, as shown in Fig. 8. Ablation Studies. Applications . We present two applications using predicted intrinsics in Fig. 9. First, real-time PBR via Cook-Torrance Applications components in Three.js graphics library. Second, switching the lighting environment between the source and reference images. Further details are in the supplementary video. Limitations . We identified a few failure cases in Fig. 10. First, our model struggles with neutralizing strong shadows, which leads to inaccurate facial geometry and residual shadow artifacts in both albedo and relit images. Incorporating shadow augmentation techniques [16, 54] during training could mitigate this issue. Second, the model incorrectly interprets reflective surfaces, such as sunglasses, as opaque objects in the normal image. This error prevents the model from properly removing reflective highlights in the albedo and relit images. Lastly, the model inaccurately predicts the albedo for face paint. Implementing a semantic mask [52] to distinguish different semantic regions separately from the skin could help resolving these issues. Limitations This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv

Researchers Asked 47 People to Judge AI-Enhanced Portraits—Here’s What They Chose

I am a big advocate of open-source startups. Over the next year, you will see many more of them. You take an existing product and open-source it. I built a social media scheduling tool (many exist in the market) and created an open-source version. This is Postiz, an open-source social media scheduling tool. And of course, if you could help me with a star, it would be amazing. The thing about the source It's open-source, and everybody can come and take your code, so what's the catch? Open source is a community; when you start to push your product, thousands of developers will fork and clone it and help you on your journey. It will bring massive exposure to your product. So far, the Postiz docker has been downloaded 26k times. On the other hand, everybody can be a competitor and use your open-source solution instead of paying you, and you have to live with this. Some licenses can save you, such as apache-2 or Agpl-3. It means that people can't compete with you without open-sourcing your code and giving you credit, but it doesn't prevent commercial use. Support is harder Having an open-source repository (with docker and all) will attract many self-hosters and require much support.So far, 3-5 tickets from Coolify, Portainer, and Unraid are received daily. This is only the start; I am sure there will be more deployment platforms soon. Make sure you give other contributors the respect they deserve. They will help you tremendously with support. Revenue is uncertain If there is one thing developers are known for, it is not to pay for stuff if it's not needed. We were born with this gene, I guess 😂 So don't expect developers to pay you. They'll host you on Raspberry Pi or a $5 Coolify server. It's important to know this. The goal of the contributors is: Help you to build the product
Help you with exposure
Build a fun and active community where everybody can grow I can't tell you how often I have seen a contributor tagging me on some X post about Postiz. Or some top trending open-source article. Enterprise It depends on your product, but some enterprises can use only self-hosted solutions and will pay you for your support and custom implementation. This is super important because that's something only open-source solutions can offer. Play with the suitable license There are no secrets. Monetized open-source (COSS) is sometimes misused in the wrong ways, for example: Adding dual licensing to the open-source, so when you use the code, you use the enterprise version and need to figure out how to remove it from the code base.
Adding non open-source license. You can put something like BSL, but it is not counted as "open-source," and fewer people see your solution as attractive. You would need to refer to your solution as self-hosted instead.
Holding out on SSO - having SSO for enterprise is only considered a destructive pattern. I have discovered lately that you can find many websites like SSO.tax because SSO is a security thing. SSO can still be commercialized, but it's better to take a stand like Tailscale, which limits seats or enterprise providers.
Be a part of the community; don't talk like "We. " Say "I" and connect with your audience; nobody likes communicating with a corporation. Go open-source. For me, it's the only way to build Please help me out with a star. It would be awesome ❤️https://github.com/gitroomhq/postiz-app I am a big advocate of open-source startups. Over the next year, you will see many more of them. You take an existing product and open-source it. I built a social media scheduling tool (many exist in the market) and created an open-source version. This is Postiz , an open-source social media scheduling tool. Postiz Postiz And of course, if you could help me with a star, it would be amazing. The thing about the source It's open-source, and everybody can come and take your code, so what's the catch? Open source is a community; when you start to push your product, thousands of developers will fork and clone it and help you on your journey. It will bring massive exposure to your product. So far, the Postiz docker has been downloaded 26k times. On the other hand, everybody can be a competitor and use your open-source solution instead of paying you, and you have to live with this. Some licenses can save you, such as apache-2 or Agpl-3. It means that people can't compete with you without open-sourcing your code and giving you credit, but it doesn't prevent commercial use. Support is harder Having an open-source repository (with docker and all) will attract many self-hosters and require much support. So far, 3-5 tickets from Coolify, Portainer, and Unraid are received daily. This is only the start; I am sure there will be more deployment platforms soon. Make sure you give other contributors the respect they deserve. They will help you tremendously with support. Revenue is uncertain If there is one thing developers are known for, it is not to pay for stuff if it's not needed. We were born with this gene, I guess 😂 So don't expect developers to pay you. They'll host you on Raspberry Pi or a $5 Coolify server. It's important to know this. The goal of the contributors is: Help you to build the product Help you with exposure Build a fun and active community where everybody can grow Help you to build the product Help you with exposure Build a fun and active community where everybody can grow I can't tell you how often I have seen a contributor tagging me on some X post about Postiz. Or some top trending open-source article. Enterprise It depends on your product, but some enterprises can use only self-hosted solutions and will pay you for your support and custom implementation. This is super important because that's something only open-source solutions can offer. Play with the suitable license There are no secrets. Monetized open-source (COSS) is sometimes misused in the wrong ways, for example: Adding dual licensing to the open-source, so when you use the code, you use the enterprise version and need to figure out how to remove it from the code base. Adding non open-source license. You can put something like BSL, but it is not counted as "open-source," and fewer people see your solution as attractive. You would need to refer to your solution as self-hosted instead. Holding out on SSO - having SSO for enterprise is only considered a destructive pattern. I have discovered lately that you can find many websites like SSO.tax because SSO is a security thing. SSO can still be commercialized, but it's better to take a stand like Tailscale, which limits seats or enterprise providers. Be a part of the community; don't talk like "We. " Say "I" and connect with your audience; nobody likes communicating with a corporation. Adding dual licensing to the open-source, so when you use the code, you use the enterprise version and need to figure out how to remove it from the code base. Adding non open-source license. You can put something like BSL, but it is not counted as "open-source," and fewer people see your solution as attractive. You would need to refer to your solution as self-hosted instead. Holding out on SSO - having SSO for enterprise is only considered a destructive pattern. I have discovered lately that you can find many websites like SSO.tax because SSO is a security thing. SSO can still be commercialized, but it's better to take a stand like Tailscale , which limits seats or enterprise providers. SSO.tax SSO.tax Tailscale Tailscale Be a part of the community; don't talk like "We. " Say "I" and connect with your audience; nobody likes communicating with a corporation. Go open-source. For me, it's the only way to build Please help me out with a star. It would be awesome ❤️ https://github.com/gitroomhq/postiz-app https://github.com/gitroomhq/postiz-app https://github.com/gitroomhq/postiz-app

How I Made $700 a Month With My Open-source Scheduling Tool

كيف تمكنت من ربح 700 دولار شهريًا باستخدام أداة الجدولة مفتوحة المصدر الخاصة بي

Как направих $700 на месец с моя инструмент за планиране с отворен код

Cómo gané $700 al mes con mi herramienta de programación de código abierto

Kuinka tienasin 700 dollaria kuukaudessa avoimen lähdekoodin aikataulutyökalullani

Como gañei 700 dólares ao mes coa miña ferramenta de programación de código aberto

איך הרווחתי 700 $ לחודש עם כלי התזמון שלי בקוד פתוח

Kijan mwen te fè $700 pa mwa ak zouti ouvè pou pwogramasyon mwen an

Bagaimana Saya Menghasilkan $700 Sebulan Dengan Alat Penjadwalan Open-source Saya

オープンソースのスケジュール管理ツールで月に700ドル稼いだ方法

របៀបដែលខ្ញុំរកបាន 700 ដុល្លារក្នុងមួយខែជាមួយនឹងឧបករណ៍កំណត់ពេលវេលាប្រភពបើកចំហរបស់ខ្ញុំ

我如何利用开源调度工具每月赚取 700 美元

For more than a decade, the world of crypto has represented the leading edge of both technology and finance. But from the outside, there's no shortage of people that — or even subversive. And it's those defenders of the status quo who've been the most resistant to the many benefits that crypto has to offer. view it as disruptive But despite all of that institutional resistance, crypto's relentless march forward continues. With each passing day, more and more ideas, concepts, and technologies are crossing over out of the crypto realm and into the business world writ large. And the latest example of that is the decentralized autonomous organization (DAO). First developed to help manage crypto projects in a decentralized way, DAOs are in the wider business community. And their rise is prompting some to wonder: can they eventually come to replace corporate boards as the primary mechanism for corporate governance? Here's a look at how that might happen and what's standing in the way. beginning to gain traction The Basics of a DAO To understand why DAOs are getting some serious attention from mainstream businesses, you must first answer the question: in the first place? And without getting too deeply into the technical details, the answer to that question is simple. what is a DAO A DAO is a blockchain-based system of smart contracts that allows large groups of individuals to participate in and have a say in a crypto project. Most DAOs use crypto tokens to perform a handful of functions necessary for the proper operation and development of the project they control. In a DAO, the most basic form of token functionality is access provisioning. In other words, owners of a specified number of the token have access to the DAO and its features. The second function is governance. In that case, tokens function as voting shares, giving the holder a proportional say in how the project proceeds. And the third function is compensation. In a DAO, it's common for tokens to accrue to participants who do work needed for the project to progress. A DAO as a Form of Corporate Governance At first glance, it would appear that DAOs would be a natural fit in a corporate governance role. But only at first glance. The reason for that is simple: corporations aren't democracies. In a typical corporate management structure, there's a distinct stratification between the people calling the shots and the shareholders. The former is ordinarily comprised of a board of directors. And the latter typically only gets to vote on who those directors are and other high-level governance decisions. They have almost no say over the day-to-day operations of the business they own a part of. But the average DAO doesn't work that way. In a DAO, it's most common for every token holder to have voting rights commensurate with their holdings. No single user has more of a say than the others unless they've got more assets at stake in the DAO. And there's no board of directors, per se. All of the decision-making is done by the group, and the majority wins. But there's nothing that says a DAO has to operate that way. It's technically feasible to set up a DAO that emulates a conventional corporate governance structure. And operating a business in that way has some merit. It's one of the reasons that business heavyweights like Mark Cuban of the DAO model of late. And at the same time, some heavyweight investors are doing everything they can to of what's predicted to be an explosion of DAO activity in the months and years ahead. have sung the praises get in on the ground floor So What's Stopping DAOs From Crossing Over? The primary factor limiting DAOs from making serious headway in the corporate governance space is a lack of regulatory certainty. Put simply, there isn't enough of a legal structure surrounding governance by DAO for any major business to use one for that purpose. It's a similar problem to the one that continues to in the US and beyond. hamper Bitcoin adoption Whereas individuals might ignore the uncertainty and take the plunge into crypto, corporations — with investors to answer to — will not. That means it's unlikely that we'll see any corporation of note explore the use of a DAO for governance anytime soon. But that doesn't mean we won't see it at all. The reason is that there's been some recent activity on the regulatory front regarding DAOs. Wyoming — which is as crypto-friendly as it gets — recently enacted a law giving DAOs . That may soon make the state into something of a proving ground for using DAOs in corporate governance. And if there's some success there, it's not all that farfetched to expect that additional states or federal regulators might look to emulate Wyoming's legal approach. similar legal standing to LLCs The Bottom Line So, to answer the question posed at the beginning of this article, yes, DAOs may one day come to replace corporate boards as the primary form of corporate governance structures. But that day's certainly not today, or likely even close. As with most other disruptive changes in the business world, no business is going to want to test out a new form of governance unless there are some legal ground rules in place to guide them and help them avoid liability. And it's going to take time for regulators to agree upon those rules and codify them. The bottom line, though, is that crypto's recent past offers some clues as to what to expect, here. After all, it wasn't that long ago that mainstream financial commentators agreed that crypto itself was little more than a tech-fueled Ponzi scheme. And today, it looks likely that we're going to see a sooner rather than later. government-issued crypto dollar So, as DAOs continue to prove themselves as a trustworthy governance solution within the crypto realm, keep a close eye on Wyoming. It may soon yield the prototype of a DAO-managed corporation. And when it does — you can bet that it won't be the last time you see one of its kind.

DAOs Could One Day Be The Primary Mechanism for Corporate Governance

In the earliest days of the Internet, pioneering businesses didn't have too many options to get their companies online. At the time (the mid to late 1990s), web hosting options were minimal. You could either turn to a shared hosting plan offered by a fledgling web hosting firm or foot the bill for an expensive colocation arrangement within a datacenter and operate your own server. If you're old enough to remember those days, you'd also know that everything about the process was difficult. Web servers were new, tough to maintain, and didn't allow you to do much. Just serving static pages was enough of a challenge – and heaven help you if you were trying to offer video streaming (major points to anyone who can remember running for that purpose). Xing's Streamworks on an SGI O2 In the years since, web hosting services have become a dime-a-dozen. Today's businesses have myriad options to choose from, and even the cheapest hosting plans make the hosting services of yesteryear look archaic by comparison. Now, businesses have a new problem: figuring out what kind of web hosting will suit their needs. To help, here's an overview of the common types of web hosting available today, and what they're good for. Shared Hosting The oldest and most common form of web hosting available is shared hosting. As the name implies, it involves leasing space on a web server that's shared by hundreds or thousands of other businesses. It is still the primary offering of most major operating today. It's also a category where you can find countless combinations of features on offer. The most important ones to evaluate are: web hosting providers – Many shared hosting packages now come with unlimited storage, but some come with a fixed amount of space and charge for more in increments. Storage Space – Again, some shared hosting offers unlimited bandwidth, but limits on throughput speeds. Others do the exact opposite, offering unlimited speed for a certain amount of traffic per month. Bandwidth – The average shared hosting plan promises a total uptime of 98%. That refers to the percentage of time a hosted site will be reachable by the outside world. Uptime – Most shared web hosting packages come with the option of installing common preconfigured apps (like WordPress, Joomla, cPanel, etc.). They also tend to come with bonus offers (like free advertising credits on Google or Facebook). Apps and Bonuses For the most part, shared hosting packages are well suited for sites that don't expect heavy traffic, and don't require any complex custom server configurations. They also tend to be the least expensive option, making them ideal for some small businesses. They are not suited for mission-critical applications, as they break down under high demand. Managed WordPress Hosting Although it is, by definition, another form of shared web hosting, it only seemed proper to give managed WordPress hosting its own section. It's a form of shared hosting where the provider configures and maintains a WordPress instance that a business can customize as its own site. WordPress is the most popular and most widely-used content management system on the internet, now operating today. For that reason, managed WordPress hosting is a popular option, especially among small businesses that lack the internal expertise to handle the technical side of maintaining the system. powering 35.9% of all websites Virtual Private Servers (VPS) The next step up from shared web hosting solutions is known as a . Like shared hosting, it involves multiple sites sharing the same hardware, but there are key differences that make it a superior option. The first is that VPS solutions guarantee a set amount of resources to each hosted website. virtual private server That means that a sudden traffic surge on one site won't cripple the others, and the server software acts to containerize the processes associated with each. It's kind of like having your own (admittedly low-end) server hardware, without the big ongoing expenses. Cloud Hosting In more than a few ways, cloud hosting is the next evolution of shared web hosting. The major difference is that with cloud hosting, the workload of each website is distributed among multiple servers that could be operating in multiple locations. Unlike standard shared hosting, each part of a website's backend needs may be handled by different hardware. Storage in one place, compute power in another, and databases still elsewhere. Cloud hosting is the new option of choice for a wide variety of web hosting needs since it leverages the economy of scale to drive down costs. It also makes it possible to add or remove hosting resources as business needs change. It's such a booming business that today's biggest tech companies operate cloud services, including , , and , which make up a good portion of each company's revenue. Amazon Web Services Microsoft's Azure Platform Google Cloud Dedicated Servers The last and most expensive and complex hosting option is to run your own web servers. It used to be a very common practice among midsized to large enterprises because it meant having total control over every aspect of the business's hosting environment. Today, only very large companies tend to utilize dedicated servers, and even then, only for highly complex customized applications that would be impractical to move elsewhere. Most big corporations have already moved their web properties onto cloud hosting platforms, and the few that haven't should be following suit in the near future. Still, for businesses that need absolute physical and software control of their web hosting – a dedicated server is still a viable option. The Host With the Most As you can see, there are now web hosting options to suit every type of need and every type of budget. Right now, the vast majority of businesses begin to build their online presence using some version of shared hosting (which they shouldn't, by the way – they're too limiting) and upgrade and relocate their sites as they grow. Interestingly, more and more small businesses are starting to skip over all of the other available options and are moving straight to cloud hosting, which is where the industry as a whole seems to be moving anyway. In the future, most of these hosting solutions are probably going to be absorbed into today's cloud providers, taking us back to a time when choosing a web hosting option was simple. The good news is that this time, that one option won't require you to learn to operate obscure software and hardware to keep everything working – and in that respect, we've come quite a long way in a short time. And thank goodness for that. Images licensed via contributor's Adobe Stock account by Cybrain, mehaniq41, meenkulathiamma, and momius.

Businesses Have Countless Web Hosting Options: Here's What They Are

For the past 40 years, the undisputed home of the global technology industry has been Silicon Valley, which is the home of some of today's biggest and best-known tech corporations. It was the birthplace of the integrated circuit, the microprocessor, the hard disk drive, and even the internet itself. In recent years, however, a growing slice of the industry has been fanning out across the United States, and even growing in far-off nations. Internationally, the big new kid on the technology block is China, whose technology market has of late. It isn't the only major technology hub that's sprung up in the world, however. In fact, there's another thriving technology hub that's building a strong bilateral innovation pipeline with tech firms here in the US. I'm speaking, of course, about Israel, which has become a major player in global technology and is fueling growth on both sides of the Atlantic. Here's a deeper look at the technology ties that have been growing between the US and Israel, and how one man, in particular, is working to expand them through a growing network of Israeli startups and innovators looking to penetrate the US market. grown by leaps and bounds A Vibrant and Booming Technology Economy Although the technology industry in Israel has been gaining worldwide renown lately, it's hardly new. Its roots date back to the early 1960s, with the emergence of companies like ECI Telecom and Elron into the global market. Since then, the technology sector there has become one of the most innovative in the world, attracting billions of dollars in venture capital and fostering some of the highest rates of startup activity anywhere. Of course, while Israel did well in building a high-tech industry within its borders, it also needed markets for the tech products it produced. They found just what they were looking for in the US, both through direct sales as well as activity by US companies like Berkshire Hathaway, Google, and others. Today, however, that relationship is poised to grow even stronger, due in large part to the efforts of one man working to bring Israeli startups straight to American shores. a flood of acquisition An Israeli Tech Hub in Florida For Israeli startups, the traditional path to the US market has been through acquisition by a US firm or strategic partnerships within the industry here. Now, Ron Kimhi, who represents the (FIBA), is changing all that by offering Israeli startups a direct route into the US market by connecting them with the resources they need to gain a foothold stateside, and more specifically, in the burgeoning Tampa Bay, Florida technology scene. Florida-Israel Business Accelerator The first hurdle he had to clear, however, was in convincing Israeli founders that Tampa Bay would make for fertile ground for their US expansion plans. He recalled the early days by saying "Getting the founders to believe that there is something interesting happening in of all places, Tampa, Florida, was my biggest challenge." Still, the effort started to pay some handsome dividends in short order. Beginning with a mission to expand participation in the FIBA program from around 20 startups to at least 60, Kimhi set to work connecting with as many Israeli founders and startups as he could find that had an interest in the American market. What he found was an overwhelming appetite in the booming Israeli tech sector for a direct means of entry to the US. After over 1500 calls and emails in his first month of work, an astounding 99 firms had joined the program. Says Kimhi of the process, "When I started, many people said I was insane, but after iterating on our value proposition messaging a few times, I found the winning formula and reached that figure" But that was only the beginning. An Exchange of Minds In service of making sure that the connection between the US and Israeli tech industries is truly bilateral, Kimhi has also worked to export some of the brightest minds in the US tech field to work directly for startups in Israel. That effort came through the Birthright Israel Excel initiative, which selects 40 technology students that hail from the most prestigious universities here in the US for internships throughout the Israeli technology sector. For Israel, such a talent pipeline couldn't come at a better time. That's because the rapid growth of the industry there has created that might act as a check on future growth if not addressed. That's another part of the reason that so many Israeli tech startups are so eager to find homes in the US market, where resources and skilled labor are more plentiful. a high-skill labor shortage A Natural Symbiosis As the relationship between the US and Israeli technology sectors continues to grow and prosper, it's offering opportunities for businesses on both sides. For US firms, it promises a continued flow of innovation and new partnerships to feed what has become the biggest and most influential part of the national economy. For Israeli firms, it offers room to grow beyond their borders and some welcome relief from the current labor situation they face at home. Together, they make a formidable high-tech pair that should have the wherewithal to continue to dominate the global technology economy for years to come, even in the face of rising Chinese influence. Given how much the two sides have already prospered together, there's little doubt that the best is yet to come. Photo Credits via the contributor's Adobe Stock License by comzeal, natanaelginting, and itchaznong.

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