Litespace is a SaaS platform solving the challenges of the hybrid workplace. By providing smart office scheduling, event recommendations, and analytics, litespace empowers businesses to foster a thriving company culture and boost employee productivity. Join us to elevate your hybrid workplace and bridge the gap between hybrid policies and employee needs.

litespace

As a Developer Relations professional, I spend a pretty large amount of my time writing, organizing, and collecting content for publication to our blog. This is at a degree where it is necessary to have a solid project management system to keep everything in order. Having recently been a student as well, I know firsthand how important it is to allow for easy collaboration in drafting content, making edits, suggestions, and sharing simple to make it less of a chore to contribute. It all broke one day when I was getting fed up with the solution I was working on, thinking to myself, there must be something better. We live in an extremely innovative time of technology, surely there must be a startup that solves my needs. So I went on a hunt to try and test out a bunch of different content collaboration solutions I found from sources like Google, Quora, AlternativeTo, the DevRel community, and more to see if I could find that perfect solution, and maybe help some other people decide at the same time. The Requirements At we collect content from a variety of people in multiple different media, but at the end of the day we want to keep everything centralized and consistent when possible. is handled in the backend using , so when considering options for content management it was critical that it played well enough with Wordpress, to avoid as much manual intervention as possible. Because of this, there were a few "must haves" for the platforms to consider: Dolby.io Our blog Wordpress 1. Exceptional handling of code blocks and inline code This is a developer blog after all, so there needs to be proper ways to share code. Ideally this will contain proper syntax highlighting for languages used, and has good copy-paste ability. 2. Commenting and editing is simple As this is a collaboration platform, we want the collaboration tools to be robust. Being able to comment on sections of text or the whole document should be easy, with a bonus for tools like "Suggest Edits" for inline changes. 3. Intuitive project management tools With the scale of posts written over time and the large number of contributors, keeping track of the status and metadata of posts within the same system they are written in is a huge benefit. This helps managers figure out the status of the content, and see what is missing from a glance, and automatically populates based on the original edit. 4. Able to handle multiple users editing at the same time We don't want collisions to happen if two people are editing at the same time, as that can result in a lot of lost work and wasted time. Ideally this will be a living document that updates automatically. 5. Image and other media handling not tied to their servers As the content will all be copied into Wordpress, we want to ensure media doesn't copy the internal reference instead of the base file. Otherwise it can look fine for people connected to the company network, but not to the public, which is a tricky thing to troubleshoot when not anticipating it. 6. Cross-platform We have team members on multiple different platforms who should all be able to contribute. The best solution for this is a web app, where it can easily be connected to a SSO solution. Nice to Haves There are a few other bonus points that can help separate the good from the great that I considered: Low price or a free tier that fits our needs Version history management Markdown based editor as either a default or an option alongside a rich-text editor Have a free trial so I can test it without needing to pay Immediate Outs With these rules, some popular tools were immediately thrown out and will not be discussed in further length. , , and all do not have great code block handling, and were taken out of consideration. Google Docs Office 365 Box Notes Tools like are enticing for purely technical teams, especially with their feature, but we work with a mixture of backgrounds that make these products too high a barrier of entry. This doesn't stop GitHub of being a good part of the workflow for linking code samples and Gists. GitHub Projects Similarly, cloud based Markdown editors such as , , and among others are not great choices for those who don't have Markdown experience, plus are a bit more barebones than desired for project management. The same applies for LaTex collaboration software like . HedgeDoc StackEdit HackMD Draft Overleaf Apps like are MacOS only, which doesn't work for team members on Windows or other platforms. Slick Products I trialed In no particular order, here are the products I tried out, and my thoughts on how they worked for . Keep in mind that just because something might not be a good fit for our workflows doesn't mean it isn't perfect for yours. us 1. Confluence Confluence is a tool that a vast majority of people who have worked in tech in the last 15 years are familiar with, due to it being a part of the Atlassian ecosystem, where Jira has been a centerpiece of modern tech workflows. I've used Confluence in every single job I've worked at for this reason, and I tend to have a love/hate relationship with it. It's an extremely powerful tool that allows massive customization of the spaces it has, links very well with itself and Jira, and provides third-party extension support for workflows that it doesn't support out of the box. However, it feels dated with the implementation of a lot of these benefits, where just because the option is there doesn't mean that the option was elegantly designed. For example, code blocks are supported, but require you specifically use a code block macro that is its own container instead of living with the other in-line text. It also uses its own markup syntax, which makes taking existing Markdown that you may already have not as simple as copy-pasting it into the platform. Other small quirks like it needing to host every file you upload to it, having a functional, yet quirky way of dealing with simultaneous edits, and the typical Atlassian sentiments many tech workers know make it a compromise. We use Confluence already at , and I imagine many of you reading this are also using this tool right now, so the price is already right. The best way to sum up my feelings of Confluence are "if it ain't broke, don't fix it", which fits some team's philosophies better than others, make of that as you will. Dolby.io 2. Notion Notion is the relatively new big hitter coming to the block with a recent surge in users that has slowly started taking up the startup scene. Notion is what I would describe as the Atlassian suite if it was made with modern tech design, and it shows from the visual aesthetic to the technical decisions made. However, instead of separating the company into multiple products, it is all grouped in one workspace, where you can link tables, docs, kanban boards, and more together seamlessly and it frankly feels elegant. Notion uses Markdown as its text processor, though instead of keeping the raw text, it automatically interprets it to make the lives of writers a bit easier, though not as intuitive as a traditional rich-text editor. If text is highlighted, it brings up the command palette, though this isn't the most intuitive behavior for new users. I would say it is similar to Slack's editor, which makes sense due to the high user base. Overall I was a big fan of Notion, and its growth tends to support my sentiment, as I see more and more companies start using Notion as their main platform for nearly everything. There were issues in image copying to Wordpress, but this was unfortunately fairly standard across most platforms. I will note that I have had server issues in the past with Notion with issues like slowness to not being able to access my documents, though I have not experienced it in recent tests of the platform, and can likely attribute this to its growing pains. 3. Quip Quip is Salesforce's option in the content collaboration space with a heavy focus on live discussions, with chat, edits, and its integration with Salesforce being its key marketing points. I've used Quip outside of this test in reviewing content from third parties, and found it to be fine, but nothing out of the ordinary in terms of capabilities. While it was able to match these claims in experience, overall it really does seem like this is built for sales teams, not content creation, where a lot of the project management assumes heavy Salesforce use, whom I imagine are the target customers for this product. 4. Dropbox Paper Unlike its major competitors in Google Docs and Box Notes, Dropbox Paper has native support for code blocks, which was a huge boon in its usability for technical content. It's another Markdown-based editor with rich-text interpretation, not unlike Notion's offering. It still has commenting support and version history built-in (including comment history) which makes it great as a living document solution. This is where the benefits dwindle though, as its project management capabilities are virtually non-existent, being a cloud-storage solution first. Additionally, it played strangely with Wordpress, where linespaces were not kept and code blocks weren't recognized properly. If your team is already using Dropbox as the storage provider, this is an option for consideration, though I wouldn't suggest it except for the most basic of needs. 5. Coda Upon asking my fellow DevRel community which tools they enjoyed using, Coda was one that was brought up a few times, but with the caveat that it was "highly technical" and more like a Smartsheet or Airtable than a collaboration document solution. I agree with this take, where instead of the previous couple feeling more like a document-centric solution, this one felt like more of a project management solution, where content wasn't managed as well as Notion or Confluence. To be fair, this is not Coda's intent with the platform, instead directly making the statement , where they encourage you to use Coda as the publishing platform. Coda itself looks like a super promising and interesting tool for an alternative blogging process. Docs are the new blogs 6. Slab With Slab, we return back to the "content-first" sub-category of solutions where we have another Markdown-based editor with a few bells and whistles added for ease of use. Some of these include a content map that helps visualize the assortment of categories your documents live in, templating, and robust commenting solutions. Once again, project management is limited, though they have built-in integrations with Jira and Miro among others that imply that it isn't meant to be that and you should be using tools dedicated to that workflow for that purpose. 7. Walling Walling is another project management based solutions which takes advantage of a "grid-like" workspace for organizing content between "walls" while using Markdown as the editor. This makes keeping information like publishing metadata and checklists very pleasant to work with, as they have their own dedicated space instead of needing to format your document in a way that has them live inline with the actual content. Despite these features, there isn't a great tabling solution, and there isn't a great way to link to other posts in the workspace. It also didn't really feel like it was built for collaboration, as commenting isn't a super intuitive process at all. 8. Whimsical Whimsical is all about keeping all content in an organized, central place. They center around five main types of content: docs, flowcharts, wireframes, mind maps, and sticky notes that can all be embedded within another. However, it felt more catered towards a creative organization rather than a robust project management feature, as I couldn't find a distinct way to properly create a workflow that autopopulated content when a new document was made. The benefits of small things like live cursors and linking content within content were useful. It also had the added benefit of working well with Wordpress, where images were not directly copied, but an image upload object was created in its stead, ensuring that you uploaded a proper copy of the image. 9. ClickUp ClickUp have been advertising heavily lately, with banners all over San Francisco, and when I tried it there was a lot going for it. ClickUp has spaces dedicated for both "Spaces", or your tables of project management based content, and "Docs", which uses a Markdown based editor and organizes and shares your content. The spaces section reminded me a lot of Airtable with a bit more stuff going on, letting you expand each entry to see the editing history, to do list, attachments, and all, really solidifying itself as a proper "entry" of work to be done. The docs had useful tools like attributing authors and having ample version history. As a major bonus, content copied itself super well into Wordpress, which is a major time save in not needing to reformat every piece of content posted. Issues however started to appear once I tried mixing the spaces with the docs. Oddly, they didn't play super well together, where there was no great way to link a new doc as an entry into a specific space the same way you can with Notion and Confluence. You can paste the docs content into a space entry, or link a doc to an entry as an attachment that links to the doc, but I found no way to automate this process. This meant every single new doc I wanted to make also required me to make a new entry in the space I was recording the status on, and manually modify the metadata in the space each time the doc was updated. I was close to being satisfied with ClickUp as my "Goldilocks" solution for my issues, but it just barely missed the mark for being something worth migrating to. It feels like they were trying so hard to replace a large number of competitors that they missed some of the nuances that made their competitors stand out. I am optimistic that as they grow, some of these missing features are implemented into the platform. Final thoughts After my time trialing with all of these platforms (and unsubscribing from all of their mailing lists...), it helped me sort out what exactly was best for me in a content collaboration app, and where my biases landed. Clearly these solutions have their own strengths and weaknesses, and all have a very solid number of customers that use them daily. If I had to choose my favorite today (October 2021), was my overall winner, where if I was starting completely from scratch, Notion filled the majority of my needs and had a good user experience that I was excited to work in. It was easy to organize, edit, collaborate, and more in a way that facilitated as many automated processes as possible. Notion However, I am not starting from scratch, and there are tradeoffs to migrating interfaces. So for that reason, we have decided to stick with Confluence, as all of our content is already there, we already pay for it, and it doesn't require our team members to sign up for a new account anywhere. A bit anti-climactic, but none of the solutions we found offered enough more than Confluence to be worth the resource investment to migrate. As a reminder, these solutions were only tested on how well they played with Wordpress. While Wordpress is still extremely popular, there are so many other growing and out there like , , and that might play better with some of these applications than others. Especially given Wordpress' tendency to be a bit dated on how it plays with more modern content solutions. popular CMS solutions Sanity Strapi Contentful I suggest taking advantage of the free trials these platforms provide, though I hope this rundown provided some good context of what pros and cons each have to see if there is a good fit for your team. Remember that what my teams needs are might not be reflected in yours, and these products are all actively being worked on. Missing features can be added, and beloved features can be sunset. I'd love to hear what solutions you are using in the comments and see if there are any promising contenders I may have missed! Also published here.

The Best Content Collaboration Solutions for Content Production

What is Opside? is a decentralized ZK-RaaS ( ) platform as well as a PoW (Proof of Work) network that facilitates ZKP (Zero-Knowledge Proof) mining. It employs a hybrid consensus mechanism combining PoS and PoW. This platform offers a unique feature for Web3 developers, namely, the ability to generate zkEVM application chains with a single click. The multitude of ZK-Rollups brings about a substantial need for computational power, creating a beneficial mining environment for global miners. Opside ZK-Rollup as a Service The notion of L2 is widely recognized in scalability solutions. However, L2 doesn't adequately manage diverse types of hardware resources such as data availability, ZKP computational power, or packaging nodes. Furthermore, operating an L2, especially a ZK-Rollup, requires considerable hardware maintenance costs and a high level of technical proficiency, which can be off-putting for many developers. To address these challenges, Opside introduced the ZK-RaaS concept. This service allows developers to launch their zkEVM chains within a minute, without needing detailed knowledge about ZK or chain nodes. Opside also introduced the ZK-PoW concept, inviting miners to participate in maintaining zkEVM and calculating ZKPs. Opside's objective is to simplify ZK-Rollup usage and promote its wider adoption, thus facilitating the large-scale deployment of zkEVM-based application chains. Developers can deploy their ZK-Rollup (zkEVM) across multiple chains with a single click. For miners, Opside serves as a multi-chain PoW protocol, supporting ZK mining and generating zero-knowledge proofs for ZK-Rollups across various public chains. ZK-RaaS ZK-RaaS (ZK-Rollup as a Service) provides a one-click ZK-Rollup generation service to all users. Opside offers a general ZK-Rollup launchpad, enabling developers to effortlessly deploy different types of ZK-Rollups onto different base chains. These base chains include Ethereum, Opside chain, BNB chain, Polygon PoS, and other public chains. Types of ZK-Rollup (zkEVM) encompass zkSync, Polygon zkEVM, Scroll, StarkNet, and other zkEVMs, as well as other varieties of ZK-Rollups. Opside deploys a Rollup System Contract (RSC) on each base chain to manage the lifecycle of Rollups on that chain, including registration, suspension, and withdrawal. By leasing a Rollup slot with a certain number of IDE (Opside native tokens), developers can own a ZK-Rollup. The idea of a Rollup slot is comparable to a slot in Polkadot or an application chain in Cosmos. However, Cosmos' application chain requires maintaining its own consensus layer and cross-chain bridge, presenting substantial security risks. Conversely, ZK-Rollup applies ZK technology, mathematically ensuring the shared consensus and data availability layer between Rollup and the base chain. This method is more secure, more decentralized, and incurs lower maintenance costs. Upon leasing a Rollup slot, developers gain an independent execution environment, where they can own a unique ZK-Rollup chain. Developers can fully control the ZK-Rollup, and customize its economic model, including the selection of gas tokens. They can freely adjust gas fees, even to zero, thereby exempting users from paying any fees. Developers are not burdened with any hardware costs. All hardware resources, such as data availability, sequencer, and ZKP computing power, are decentralized and provided by the Opside ZK-PoW cloud. Moreover, native cross-rollup communication can be implemented among different ZK-Rollups on the same base chain. It is a message communication mechanism enabling an address on one rollup to directly interact with a contract on another rollup. This feature significantly addresses the fragmentation of user assets and enhances interoperability between applications. Opside ZK-PoW Cloud Compared to OP-Rollup, ZK-Rollup has several advantages including enhanced security, trustless operations, and faster withdrawal speeds. A key technological difference is that ZK-Rollup requires robust ZKP computational power to generate zero-knowledge proofs.\ Opside's Multi-chain ZK-PoW Mechanism The multi-chain ZK-PoW mechanism of Opside ZK-PoW Cloud will be deployed on multiple chains including, but not limited to, Ethereum, BNB Chain, Polygon PoS, and Opside Chain itself. With the design of Opside, developers can deploy ZK-Rollups on these different base chains. As the technology of ZK-Rollup matures, we may see hundreds or even thousands of ZK-Rollups, leading to a significant demand for ZKP computational power. After the transition from Ethereum PoW to PoS, many Ethereum mining machines lost their application scenarios. The value of these machines, in terms of capital scale, is around 12 billion USD, with many currently idle. With the large-scale implementation of ZK-Rollup, the generation of ZKP requires a lot of hardware and mining machines, such as CPUs, GPUs, and FPGAs, to provide computational capacity. Opside uses the ZK-PoW mechanism to incentivize miners to provide ZKP computational power, thereby offering comprehensive hardware infrastructure for ZK-Rollup. This is one of the core ideas of Opside. All participants, including users, developers, and miners, can benefit from this Opside economic model. Two-step submission mechanism for ZKP verification To encourage more miners to participate in ZKP calculation tasks simultaneously, Opside has proposed a two-step submission mechanism for ZKP verification. The share of PoW rewards for a ZKP will be distributed to the effective ZKP submitter, the miner, according to certain rules. : Within a specified timeframe for a certain sequence, multiple miners can participate in the computation of zero-knowledge proof. After each miner calculates the proof, they don't submit the original proof directly but compute the proofhash of (proof/address) and submit this proofhash to the contract. Submit proofhash : After the timeframe ends, the miner submits the original proof and verifies it against the previously submitted proofhash. Miners who pass this verification receive PoW rewards, with the reward quantity distributed according to the miner's stake. Please refer to for further details. Submit ZKP ZKP's Two-Step Submission Algorithm Optimized ZKP Generation Algorithm When Rollup's smart contract verifies the ZKP, if the original proof is submitted, it could potentially incite on-chain attacks. To avert such attacks, ZK-Rollup often performs additional operations to obscure the original proof data. Opside's innovative two-step submission algorithm for ZKP leverages a "submit first, verify later" approach, circumventing unnecessary aggregate computations for proof and address. Moreover, in some open-source zkEVMs, ZKP calculation and submission occur sequentially. This can become a bottleneck when ZK-Rollup submits a large number of sequences, as miners can't compute multiple ZKPs concurrently. Opside's two-step submission algorithm enables parallel computation and sequential submission of ZKP, allowing miners to perform multiple ZKP generation tasks simultaneously and significantly enhancing ZKP generation efficiency. The Opside team also enhanced the ZKP recursive aggregation algorithm, markedly improving machine resource utilization in the cluster and further accelerating ZKP computations. Stress tests in practical environments showed that miners using a machine cluster of 20 units (each with a 128-core CPU and 1TB RAM) sustained a transaction rate of 27.8 TPS for approximately 40 minutes. Under similar conditions, Opside managed to slash the average transaction confirmation time from roughly 5-6 minutes to about 3 minutes, enhancing the ZKP generation efficiency by about 80%. With the participation of more ZK-Rollups and miners, the demand and supply scale of the ZKP computational power market will continue to expand, making the efficiency improvements offered by Opside's PoW algorithm increasingly noticeable. Opside Chain The Opside Chain, as one of the base chains, not only supports the Opside ZK-PoW Cloud but also offers further optimizations for ZK-Rollup. These include the use of precompiled contracts for accelerated ZKP verification, data sharding support, and the adoption of a PoS consensus based on ETH 2.0. Future support will also be extended to EIP-4844, DankSharding, and other full-shard solutions, potentially reducing Rollup gas costs to near zero. Ethereum currently stands as the world's largest decentralized network, boasting over half a million nodes. These nodes offer significant decentralization and, looking to the future, are set to provide tremendous data availability thanks to data-sharding technology. Inspired by Ethereum, Opside Chain has chosen to enhance the PoS consensus derived from ETH 2.0. We predict that Opside Chain will have an impressive network of over 100,000 nodes. When considering Rollup, the question arises of how to decentralize the sequencer further instead of relying on a singular node for centralized packaging. A practical approach is allowing Opside Chain's block proposers to also propose blocks for the Rollup Layer, effectively separating the roles of builder and proposer. The builder is supported by a permissionless P2P network, while the proposer leans on Opside Chain's block proposer. This methodology eliminates the availability risk of a single node while maintaining resistance to Miner Extractable Value (MEV) and censorship. Consequently, Opside Chain presents a standardized decentralized sequencer mechanism, with its block proposers also proposing blocks for the Rollup. In this way, ZK-Rollup not only inherits security from the higher layer but also its degree of decentralization. Opside Chain introduces a mixed consensus model involving PoS and PoW: In the Opside chain: PoS: Opside plans to adopt and modify Ethereum 2.0's PoS algorithm. It allows anyone holding Opside tokens to become a validator, who can then receive block rewards and gas fees within the Opside chain. In the Rollup layer: PoS (Sequencer): Validators propose blocks in both the Opside Chain and the Rollup Layer (i.e., data batches). Hence, they also serve as sequencers in the Rollup Layer, where they can earn gas fees from transactions. PoW (Prover): Any individual with sufficient computational power for ZKP calculations can become a prover in the Rollup Layer. Under PoW rules, provers generate zk-proofs from the Rollup Layer blocks submitted by the sequencer. Drawing a comparison, a ZK-Rollup is akin to a computer, with the hard drive represented by the data availability offered by PoS and the CPU mirrored by the computational power granted by PoW. Opside Chain's task is to strike a balance between PoS and PoW, enabling all parties to maximize their contribution and benefits, thereby enhancing the performance and user experience of a large-scale ZK-Rollups network. Supply and Demand of IDE Tokens Regarding the supply and demand of tokens, Opside tokens (IDE) will be minted as PoS and PoW rewards, catering to Validators and Miners, respectively. During the Pre-Alpha test net phase, the block reward ratio of PoS to PoW is temporarily set at 1:2. In the future, this ratio will dynamically adjust based on the network's ZKP computational power supply-demand relationship. PoS rewards As previously stated, Opside Chain employs an enhanced PoS consensus based on ETH 2.0. To act as a Validator, users must deposit a certain amount of IDE tokens into a deposit contract and operate three separate software modules: an execution client, a consensus client, and a Validator. These Validators oversee the validation of new blocks circulated across the network and occasionally generate and propagate new blocks themselves. If a Validator is found to be dishonest or inactive, their staked IDE will be forfeited as punishment. Under the PoS mechanism, Opside Chain maintains a fixed rate of block production. The timeframe is subdivided into slots, each lasting 12 seconds, and epochs, composed of 32 slots. Within each slot, a validator is selected at random to propose a new block. This validator is tasked with creating and broadcasting the new block to the rest of the network. Likewise, a committee of validators is chosen randomly during each slot, whose collective votes confirm the validity of the proposed block. For a detailed understanding of this mechanism, kindly refer to the . PoS consensus model of Ethereum For the Alpha testnet phase, Opside Chain is set to incorporate . This introduces Data Availability Sampling (DAS), a tool used to ensure that transaction data from ZK-Rollup is available after execution, without overburdening any single node. In practice, each validator will randomly pull transaction data from the blob to verify its presence. The same method can also ensure that all data from block producers is accessible to secure light clients. In line with , only block builders are required to process the entire block, while other validators will employ data availability sampling for validation. EIP-4844 the Proposer-Builder Separation (PBS) principle Please note, Opside Chain may vary on specific parameters; the latest values can be accessed in the code repository. Broadly speaking, staking encourages individual participation in network protection, thus fostering decentralization. Validator nodes can be run on regular laptop computers. Some delegation staking pools even permit staking activities for users who do not hold a sufficient quantity of IDE tokens. PoW rewards Based on the ZK-Rollup launchpad provided by Opside, developers can choose to have their own ZK-Rollup on a base chain. To support the massive hardware resources required by numerous ZK-Rollups, Opside offers a unified ZKP computation market, encouraging miners (or provers) to generate ZKP for these ZK-Rollups. This is the ZK-PoW mechanism of Opside. Single Rollup Sequence Reward Allocation ZK-PoW is a multi-chain protocol, meaning that PoW rewards will be distributed across various base chains including Ethereum, Opside Chain, BNB Chain, and Polygon PoS. The number of PoW rewards for each base chain depends on the number of registered Rollup slots, ZKP workload, etc. For each base chain, within a block, each Rollup can only submit one sequence (which can include multiple blocks of the Rollup). Each sequence will equally share the PoW rewards of the current block. This means, for example, if there are four Rollups submitting sequences within a block on the base chain, the PoW rewards will be divided into four parts, with each sequence receiving one-fourth of the block's PoW rewards. Of course, some blocks might not have any Rollup submitting a sequence, so the actual inflation of PoW may be lower than expected. In the future, each sequence will have workload estimates based on the corresponding ZK-Rollup type, the number of Rollup transactions, gas usage, etc., to price different sequences differently. Prover's Staking and Penalties To prevent malicious behavior related to provers, provers are required to register in a specific system contract and stake tokens. Provers are free to participate in the PoW mining of one or more Rollups. Provers need to stake a certain amount of IDE in the system contract for each Rollup they wish to participate in. If the current stake is below the threshold, they are not allowed to submit ZKP for that Rollup. The rewards earned by provers for submitting ZKP will be distributed based on the proportion of stakes, thereby preventing malicious behavior of provers submitting ZKP multiple times. Provers will be penalized differently for the following actions: If a prover submits an incorrect hash. If no ZKP passes verification, then all provers who have submitted a hash will be penalized. The confiscated Opside tokens will be burned. For more details and considerations on the two-step submission mechanism for ZKP, please refer to the official documentation. The specific figures for prover stakes and penalties may change in the future. Developers Leasing Rollup Slots On each base chain, Opside will deploy the ZK-PoW protocol. Developers can register a Rollup slot with a single click through the ZK-Rollup launchpad, thereby creating their own ZK-Rollup. All hardware resources for this ZK-Rollup are provided by the decentralized Opside network. Developers need to pay for the rental of the Rollup slot, and this portion of the rent will be directly burned. In addition to a fixed amount of rent, developers can also provide additional ZKP subsidies for their ZK-Rollup to encourage miners to provide computational power. The specific rules and parameters for rent and subsidies can be found in the official documentation or the code repository. Governance and Development The functions and performance of the Opside network will continue to evolve over time. Here are a few examples of higher priorities: Adjust the reward distribution ratio of PoS and PoW dynamically based on the supply and demand relationship of ZKP computational power in the entire network. Validator's data sharding and data availability sampling will provide more abundant storage space for the entire Rollup Layer, accommodating a more ZK-Rollup ecosystem. Separation of the Rollup proposer and builder allows the Rollup layer to use Opside chain's validator as the block proposer, inheriting decentralization from the previous layer. The optimization of miners' staking and slashing mechanisms encourage miners to provide continuous and stable ZKP computational power. Application developers subsidize the ZKP generation of their Rollups to incentivize miners to provide computational power. Workload estimates based on ZK-Rollup type, number of Rollup transactions, gas usage, etc., to establish a personalized pricing mechanism for Rollup batches. These improvements will significantly enhance the utility of the Opside network, thereby promoting the long-term development and prosperity of ZK-Rollup as a Service. After the launch of the Opside mainnet, an Opside DAO will be established, which includes a reasonable process and mechanism to jointly determine the future of the network. All updates to the parameters and mechanisms of the Opside mainnet will be determined through the Opside DAO. It is important to emphasize that Opside is a co-constructed economy and evolves over time. Future improvements will be detailed in DAO proposals, explaining how these plans benefit the long-term interests of the Opside economy and each participant category. As the network develops, it is crucial to build an economy that can operate independently and robustly without the need for a large number of tools and subsidies.

Opside Litepaper V2 Released: Introducing a Multi-chain ZK-PoW Mechanism

Lanzamiento de Opside Litepaper V2: Presentación de un mecanismo ZK-PoW de múltiples cadenas

Publication d'Opside Litepaper V2 : Présentation d'un mécanisme ZK-PoW multichaîne

ऑपोजिट लाइटपेपर V2 जारी: एक मल्टी-चेन ZK-PoW तंत्र का परिचय

Opside Litepaper V2 リリース: マルチチェーン ZK-PoW メカニズムの導入

Lançamento do Opside Litepaper V2: Apresentando um mecanismo ZK-PoW de várias cadeias

Đã phát hành Opside Litepaper V2: Giới thiệu Cơ chế ZK-PoW đa chuỗi

Opside Litepaper V2 发布：引入多链 ZK-PoW 机制

As crypto evolves from Ether → Plasma → Matter, the material transmutation must be flawless. We hope this critique helps us get there. At , we’ve been big fans of Mattereum ever since pulled us by the scruff of the neck and told us that “for years, has been talking about CleanApp-type services.” CleanApp Foundation Cryptech Vinay Gupta For a while now, we’ve also been stressing that crypto needs to take a concerted turn towards material cryptonomics . Our reasoning is simple: (1) (& always will dwarf digital assets because people eat fructose & cellulose apples, not silicone apples); (2) developing . the material economy dwarfs digital assets a crypto-material-economy is vital to offset the clear systemic threats posed by crypto-finance We’ve been researching and trying to understand Mattereum’s plan to put physical assets on chain. In addition to , Mattereum’s recently-published “litepaper” (summary whitepaper) — offers a great introduction to one of today’s most audacious plans to bridge the crypto and physical realms. ( !) Mattereum’s website Hat tip to BookLocal for sharing the best insights from DevCon4 The point of this article is to give some initial thoughts on the litepaper, with the express disclaimer that everything here is meant as constructive critique. We have nothing but the utmost respect for the project. we want to give the project the same treatment has gotten from its best critics. That’s why our whitepaper What is Mattereum? For context, let’s start with a screenshot from . Mattereum’s website Here’s what we notice straight off the bat: . What does Mattereum actually do? In our read, Mattereum will serve as a legal layer between a core blockchain (such as Ethereum 4.8.1) and different end-user-oriented blockchain applications. Mattereum is a LegalTech project We’ll get deeper into the shortly. how For now, it’s important to take a moment to appreciate how of the bullet points above is a legal form and/or legal relation. each one Mattereum seeks to crypto-legalize physical assets, and physically-enforce digital legal decrees. Mattereum = LegalTech Please note, we’re not sure whether our characterization of Mattereum as LegalTech squares with how Mattereum describes Mattereum. The project description is far more ambitious (and ambiguous) in scope than our description, so of course, you should read all of these materials for yourself. But in our view, LegalTech is nothing to shirk from. In a way, all of crypto is a big LegalTech enterprise thus far. Even CryptoKitties is in the midst of a massive IP turf war. Crypto projects that acknowledge crypto’s legal genesis blocks (and the imprint of those blocks on the conceptual architecture of crypto) will thrive. Those that continue to labor under the anxiety of legal intervention will eventually have to give way or fold. Mattereum is wisely adopting the path of greatest adoption, which means greater integration with existing legal processes. Kudos. That’s a smart strategy. What’s most remarkable about Mattereum is that it’s orders of magnitude more legalistic than even projects like . At scale, the two may well evolve into fierce competitors (Mattereum as Amazon; OpenLaw as EBay). Like Amazon & EBay (or Westlaw & LexisNexis, for that matter), Mattereum, OpenLaw and other LegalTech players will find plenty of ways to complement one another. OpenLaw The key viability (market-potential and feasibility) question is whether all stakeholders will coalesce around the hyperutility proposition of transaction-level crypto-legal interoperability. To us, the potential gains for all sides are so vast that it’s a no-brainer. But crypto is a very tribal place, so who knows what will happen. Where Is Mattereum? In terms of blockchain development layers, here’s how Mattereum sees itself: In reality, the little red lines need to go to many more boxes. For instance, it’s not clear why Mattereum is saying it won’t be involved in credit management, since the most immediately obvious use-case for Mattereum is collateralization and asset-tracking. Mattereum says as much in its litepaper: As Mattereum extends its services into developing economies, the benefits of collateralizing movable property will become extremely important because it fuels economic growth. And credit management collateralization. When debtors will ask Coinbase to refinance the 3rd equity line of credit on their bicycle, what Coinbase wants to know is: (1) where the moveable collateral is right now; (2) what other collateral can be added to the collateral portfolio to secure the loan that Coinbase will desperately want to approve. is The same is true for advertising. In a Mattereum future of fractional asset ownership, subjective emotional ties to assets like cars and apartments are weakened. Owners will be even more incentivized to monetize their assets in novel ways. So apartments rented out through can have entire walls serve as digital billboards; refrigerators within those apartments can serve as chain-verified market survey mechanisms. So long as everyone consents to the transactional chains, it’s easy to see retailers like Ikea or Amazon demo-ing product lines within short-term apartment rentals. BookLocal If you’re renting a car for a day, and can get a 25%, 50% or higher discount for plastering magnetic placards on your rental (placards that you can remove before you arrive at your destination) — and the ad placements can be securely verified, then . advertisement rights become some of the most valuable property rights in all of crypto It’s not clear why Mattereum limits its own scope. The two examples above — blockchain short-term apartment rentals & car rentals — are plucked directly from the litepaper. We observe in the way Kik/Kinit talk about Kin. the same paradox Who knows; maybe understatement is a new crypto trend. Mattereum Math-ereum The way that Mattereum describes its approach to smart property is essentially assigning a digital identity to the maximum number of physical assets, and then apportioning rights of access to the property by, say, time (like time-sharing). Additionally, Mattereum introduces age-old property law forms — such as the divide between possessory interests, reversionary interests, and titular interests (without using the legal jargon, thankfully). Here’s how the litepaper describes it: An automated custodian becomes an asset’s legal owner and registrar, maintaining the authoritative register of interests in the asset. This enables the unbundling of [1] legal ownership, [2] financial beneficial interest, and [3] possession or use of the asset. Unbundling suggests fractional ownership — the registrar owns 1/3 of the property; the user owns 1/3 of the property; and a financial institution owns 1/3 of the “financial beneficial interest.” In reality, the first thing that the financial institution will do with its “financial beneficial interest” is somehow encumber that financial beneficial interest, whether through existing derivative structures, or through some as-yet-uninvented bit of FinTech wizardry. It’s not just financiers who will try to fragment their stakes in an apartment or car to squeeze more value out of them: owners and users of the property have every incentive to do the same thing. Instead of , what emerges looks more like : fractional ownership fractal ownership Mathematically and biologically, the fractal is an exceedingly elegant and efficient form. To the extent something like can be coded, seems intuitively reasonable: by permitting property cell division into smaller and smaller blocks, the system gives each resulting block the highest likelihood of finding most efficient use. smart property fractal ownership So, returning to the apartment-sharing example from the litepaper, we can imagine the emergence of extremely diverse micro-property markets, with firms paying small amounts to do product placement on micro-property-surfaces (example: displaying a classic Coke bottle or a framed photo of a local bar in a prominent place). Perhaps the reason fractal ownership is not addressed is the fear that it would complicate enforcement of property rights. But enforcement is already complicated by the myriad permutations of “smart property” x “smart contract” rights anticipated by Mattereum. How Are Rights Enforced? This is the biggest conceptual and operational weakness in the paper. Given that enforcement is the fulcrum on which “smart property” v. “smart contract” will perform their balancing act, it’s a big deal. Mattereum knows it’s a big deal. Here’s how the litepaper opens: What if code really did have the force of law behind it? The litepaper states the problem perfectly: today’s crypto legal instruments lack clearly articulated and well-theorized enforcement mechanisms (our restatement of the paper’s core thesis). But the litepaper’s proposed solutions restate the problem, rather than solving it. Here’s how the litepaper claims to solve off-chain enforcement of on-chain arbitral awards: (1) ; (2) (“removing the legal obstacles between an arbitrator making an award and the successful counterparty actually receiving compensation.”). dispute minimization disintermediation The way that Mattereum claims to accomplish #2 is by introducing a novel legal form: (3) an . automated custodian An automated custodian is the perfect legal counterparty to a smart contract. An automated custodian becomes an asset’s legal owner and registrar, maintaining the authoritative register of interests in the asset. Unfortunately, the litepaper does not explain how the automated custodian — a bot whose job is to maintain a micro-title registry — will actually do en-force-ment. Here’s the litepaper again: Being the asset’s legal owner, the registrar [a bot] is in the strongest position to enforce these constitutional requirements in respect of the asset. But the only way a bot can en-force any legal requirements (constitutional or contractual or property) is if the bot has legitimate law en-force-ment authority in the physical realm. That implies RoboCops. Short of RoboCop en-force-ment, Mattereum cannot and should not describe its processes as automated enforcement in the physical realm. If Mattereum means to actualize Szabo’s original “smart property” plans of self-repossessing cars (#autorepoauto) and self-locking apartments, then it must say so and open these important governance and policy questions to public debate. Right now, the litepaper claims that the Mattereum protocol will allow the deployment of “a simple API for the control of off-chain assets.” But as its own graphic makes clear, the actual mechanism of control is not physical control, but actually just another layer of legal rights — (1) transfer rights; (2) collateral rights; (3) IP license rights; (4) insurance rights. In the event of a dispute concerning these rights, arbitration, adjudication, and enforcement would be done off-chain. If parties want to arbitrate, then Mattereum would presumably integrate with an arbitration provider like OpenCourt, providing somewhat greater on-chain control. But at the end of the day, actual en-force-ment would be done in a non-Mattereum enforcement forum. Smart Stradivarius The litepaper uses the example of a rare Stradivarius violin (worth $9m). Mattereum claims that this violin will be the first that it turns into smart property. The violin is then used to illustrate several aspects of the Mattereum protocol. The litepaper gives several examples of what can be done with the violin, including automated registrar oversight with respect to given custodial instructions. So if the property owners & contract parties wanted to specify that the violin be used in “6 concerts in 3 countries over the course of a year,” the suggestion is that this violin would be used in “6 concerts in 3 countries over the course of a year.” But the key question is — ? How will Mattereum enforce these property+contract hybrid rights? Again, the only conceivable way that this could be done autonomously is if the automated custodian is a robot who is programmed to deliver the violin to each of the 6 concert venues and then bring the violin back to a secure vault somewhere. But even in that scenario, what happens if the violinist at the 5th concert returns a fake? What happens if she refuses to return the violin to the robot? how The key point is that “smart contract” self-enforcement is illusory. It’s an oxymoron. Mattereum elides this problem through two means: (1) by not using self-enforcement terminology ( !); (2) by inventing a third party property law mechanism — the — that will do the enforcement. thankfully automated custodian But that just kicks the can down the road. The automated custodian cannot do enforcement. It is not a law en-force-ment body. “Smart Contracts” v. “Legal Contracts” Even though we’re thrilled to see a major blockchain project consciously move away from “self-enforcement” terminology, Mattereum’s legal architecture is still underdeveloped. The clearest illustration of this is the continuing reliance on “smart contract” terminology despite principled argumentation and clear countervailing trends. against this usage These are not semantic choices, aesthetic considerations, or “opinions.” At this caliber, continued misuse of Legalese after clear corrective signals leads to only one outcome: further conceptual fragmentation and confusion. When Mattereum writes that its “infrastructure [turns] smart contracts into legal contracts that can be efficiently enforced all over the world,” Mattereum’s contrastive frameworks only make matters worse. There’s no conceptual divide in law between “smart contracts” and “legal contracts,” just like there’s no conceptual divide between “legal contracts” and “contracts.” Adding the adjectival “legal” is unnecessarily redundant. A contract is, by definition, a legal form. No clear trade usage attaches to the term “smart contract” or to the term “legal contract.” On the contrary, crypto discourse has far too much inaccurate equivalence between different genres of “smart contract” and variously “self-enforcing” legal contracts. Here’s the actual answer to how “smart contracts” are turned into “legal contracts” — The resounding “maybe” is a far cry from claims that Mattereum contracts “can be efficiently enforced all over the world.” The best thought exercise for moving away from efficient enforcement and getting closer to maybe is to return to the Stradivarius and to imagine a complex provenance dispute -or- a hybrid contract + property + tort dispute arising from damage to the violin occasioned by an angry violinst protesting the onchainization of art, or whatever. It doesn’t matter how clear the chain of title may seem now; in a large stake dispute, it’s impossible to contain the parties to on-chain dispute resolution mechanisms — irrespective of their prior consent to on-chain arbitration. Underneath Mattereum’s Hood Here’s our theory on the actual inner workings of Mattereum’s . automated custodian Mattereum’s automated custodian seems to be a clandestine way of converting a property law form (such as a bailment) into a contract form. Mattereum is doing this type of legal alchemy in order to (property law is quintessentially local; contract law is far more cosmopolitan, with robust international legal mechanisms for enforcement of arbitration awards). internationalize & harmonize property law Conveying property to a centralized or decentralized registrar is an attempt to contract-ize a given asset (to change its legal essence from a property form to a contract form). Despite best efforts to do this (with advice of great lawyers), any claim of ease of enforcement, ease of implementation, and/or easy efficiency gains must be very closely scrutinized. Next Steps We close with several questions and requests for clarification. The Mattereum website states: “Where contracting parties have agreed that their obligations will be secured against registered assets, registrars will recognise and enforce an arbitration award directly against the assets.” Q: What is Mattereum’s preferred arbitration mechanism? In our understanding, the decision to on-chain a Stradivarius is motivated by a desire to chose a high-profile asset with an indisputable provenance. Q: Are you open to prototyping Mattereum with other asset classes, but where title is unclear, and provenance can be disputed ? Thank you to the Mattereum team for blazing a new path forward in the evolution of the broader global blockchain project. Your litepaper’s innovative suggestion to marketize carbon and pollution data is a major milestone in blockchain history. We applaud it wholeheartedly. We see Mattereum’s full potential as custodian protocol of a similar but broader physical asset class: a blockchain embodiment of Open AR Cloud. We’d be honored to share our ideas for integrating blockchain processes with physical assets to unlock entirely new transactional spaces.

Mattereum Litepaper {Pros & Cons}

Python Bokeh is one of the best Python packages for data visualization. Today, we are going to see some Python Bokeh Examples. I have also provided the Python Bokeh project source code on GitHub. Learn this easy visualization tool and add it to your Python stack. What is Python Bokeh? Python is a data visualization tool, or we can also say Python Bokeh is used to plot various types of graphs. There are various other graph plotting libraries like matplotlib, but Python Bokeh graphs are dynamic in nature, which means you can interact with the generated graph. See the below examples… Bokeh Installation 💻: Python Bokeh can be easily installed using PIP. You can install the Python Bokeh easily by running the command: pip install bokeh Now everything is ready, let’s go through the examples 🏃‍♂️… 1. LinePlot from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="{LinePlot Python Bokeh Example")
p.line(x, y, line_width=2)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 2. Scatter Plot from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Scatter Plot Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=10, color="navy", alpha=0.5)
output_notebook()
show(p) 3. Bar Chart from bokeh.plotting import figure, show, output_notebook
categories = ["A", "B", "C", "D", "E"]
values = [10, 15, 8, 12, 6]
p = figure(x_range=categories, title="Bar Chart Python Bokeh Example by PratikPathak.com")
p.vbar(x=categories, top=values, width=0.9)
output_notebook()
show(p) 4. Histogram from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.normal(0, 1, 1000)
p = figure(title="Histogram Python Bokeh Example by PratikPathak.com")
p.hist(data, bins=30, color="navy", alpha=0.5)
output_notebook()
show(p) 5. Pie Chart from bokeh.plotting import figure, show, output_notebook
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
p = figure(title="Pie Chart Python Bokeh Example by PratikPathak.com")
p.wedge(x=0, y=0, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_label=labels)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 6. Time Series Plot from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Time Series Plot Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p) 7. Linked Brushing from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
source = ColumnDataSource(data=dict(x1=x1, y1=y1, x2=x2, y2=y2))
p1 = figure(title="Scatter Plot 1")
p1.circle('x1', 'y1', source=source)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle('x2', 'y2', source=source)
output_notebook()
show(p1, p2) 8. Hover Tooltips from bokeh.plotting import figure, show, output_notebook
from bokeh.models import HoverTool
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Hover Tooltips Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p) 9. Annotations from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Arrow, VectorRenderer, Label
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Annotations Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
arrow = Arrow(x_start=2, y_start=4, x_end=3, y_end=5, line_width=2, line_color="red")
label = Label(x=3, y=6, text="This is a label", render_mode='css', border_line_color='black', border_line_alpha=1.0, background_fill_color='white', background_fill_alpha=0.5)
p.add_layout(arrow)
p.add_layout(label)
output_notebook()
show(p) 10. Custom Glyphs from bokeh.plotting import figure, show, output_notebook
from bokeh.models.glyphs import Asterisk
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Custom Glyphs Python Bokeh Example by PratikPathak.com")
p.add_glyph(x, y, Asterisk(size=20, line_color="red", fill_color="yellow"))
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 11. Gridlines and Axes from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Gridlines and Axes Python Bokeh Example by PratikPathak.com", x_range=(0, 6), y_range=(0, 8))
p.grid.grid_line_color = "grey"
p.grid.grid_line_dash = [6, 4]
p.xaxis.axis_label = "X-axis"
p.yaxis.axis_label = "Y-axis"
p.line(x, y, line_width=2)
output_notebook()
show(p) 12. Legend from bokeh.plotting import figure, show, output_notebook
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p = figure(title="Legend Python Bokeh Example by PratikPathak.com")
p.line(x1, y1, line_width=2, color="red", legend_label="Line 1")
p.line(x2, y2, line_width=2, color="blue", legend_label="Line 2")
p.legend.location = "top_left"
output_notebook()
show(p) 13. Categorical Plots from bokeh.plotting import figure, show, output_notebook
fruits = ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"]
counts = [5, 3, 4, 2, 4, 6]
p = figure(x_range=fruits, title="Categorical Plots Python Bokeh Example by PratikPathak.com")
p.vbar(x=fruits, top=counts, width=0.9)
p.xaxis.axis_label = "Fruit"
p.yaxis.axis_label = "Count"
p.xaxis.axis_label_text_font_size = "12pt"
p.yaxis.axis_label_text_font_size = "12pt"
output_notebook()
show(p) 14. Subplots from bokeh.plotting import figure, show, output_notebook
from bokeh.layouts import gridplot
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com")
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
grid = gridplot([[p1, p2]], plot_width=400, plot_height=400)
output_notebook()
show(grid) 15. Interactive Plots from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool
import numpy as np
x = np.random.random(1000)
y = np.random.random(1000)
source = ColumnDataSource(data=dict(x=x, y=y))
p = figure(title="Interactive Plots Python Bokeh Example by PratikPathak.com", tools="hover,box_select")
p.circle('x', 'y', source=source, size=3, color="navy", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 16. Linked Panning and Zooming from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com", x_range=Range1d(0, 6), y_range=Range1d(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2) 17. Linked Axis Ranges from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1", x_range=(0, 6), y_range=(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2) 18. DateTime Axis from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Datetime Axis Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p) 19. Heatmap from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.rand(10, 10)
p = figure(title="Heatmap Python Bokeh Example by PratikPathak.com")
p.image(image=[data], x=0, y=0, dw=10, dh=10, palette="Viridis256")
output_notebook()
show(p) 20. Streamgraph from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
import numpy as np
# Generate some sample data
x = np.linspace(0, 10, 100)
y1 = np.cumsum(np.random.randn(100))
y2 = np.cumsum(np.random.randn(100))
y3 = np.cumsum(np.random.randn(100))
y4 = np.cumsum(np.random.randn(100))
y5 = np.cumsum(np.random.randn(100))
source = ColumnDataSource(data=dict(x=x, y1=y1, y2=y2, y3=y3, y4=y4, y5=y5))
p = figure(title="Streamgraph Python Bokeh Example by PratikPathak.com")
p.area(x='x', y1='y1', y2='y2', y3='y3', y4='y4', y5='y5', source=source, line_color=None)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 21. Polar Plot from bokeh.plotting import figure, show, output_notebook
import numpy as np
r = np.linspace(0.1, 1, 10)
theta = np.linspace(0, 2*np.pi, 10)
p = figure(title="Polar Plot Python Bokeh Example by PratikPathak.com", plot_width=600, plot_height=600, x_range=(-1.2, 1.2), y_range=(-1.2, 1.2), toolbar_location=None)
p.polar(r, theta, color="navy", alpha=0.5, line_width=2)
output_notebook()
show(p) 22. Donut Chart from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
source = ColumnDataSource(data=dict(labels=labels, values=values))
p = figure(title="Donut Chart Python Bokeh Example by PratikPathak.com", x_range=labels)
p.wedge(x=0, y=1, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_field="labels")
p.wedge(x=0, y=1, inner_radius=0.3, outer_radius=0.4, start_angle=0.6, end_angle=2.6, color="white")
p.axis.visible = False
p.grid.grid_line_color = None
output_notebook()
show(p) 23. Treemap from bokeh.plotting import figure, show, output_notebook
from bokeh.models import TreemapRenderer, ColumnDataSource
import pandas as pd

# Sample data
data = pd.DataFrame({
    'label': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
    'parent': ['', 'A', 'A', 'B', 'B', 'C', 'C', 'D'],
    'value': [10, 5, 4, 3, 2, 1, 1, 1]
})

source = ColumnDataSource(data)
p = figure(title="Treemap Python Bokeh Example by PratikPathak.com")
treemap = TreemapRenderer(
    source=source,
    label='label',
    parent='parent',
    value='value',
    color_discrete_sequence=["#e6550d", "#3182bd", "#31a354", "#756bb1", "#636363", "#9e9ac8", "#de2d26", "#fd8d3c"],
)
p.add_layout(treemap)
output_notebook()
show(p) If you get any error, make sure you have installed Python pandas by using the “pip install pandas” command 24. Network Plot from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, NodesAndLinkedEdges
import networkx as nx

# Sample data
nodes = ['A', 'B', 'C', 'D', 'E', 'F']
edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('B', 'E'), ('C', 'F')]
G = nx.Graph()
G.add_nodes_from(nodes)
G.add_edges_from(edges)

node_positions = nx.spring_layout(G)
node_x = [node_positions[node][0] for node in G.nodes()]
node_y = [node_positions[node][1] for node in G.nodes()]
node_color = ['red', 'green', 'blue', 'yellow', 'purple', 'orange']

source = ColumnDataSource(data=dict(
    x=node_x,
    y=node_y,
    color=node_color,
    node=nodes
))

p = figure(title="Network Plot Python Bokeh Example by PratikPathak.com", x_range=(-1.1, 1.1), y_range=(-1.1, 1.1))
p.add_tools(HoverTool(tooltips=[("Node", "@node")]))
p.circle('x', 'y', size=15, color='color', source=source)

edge_x = []
edge_y = []
for start, end in edges:
    x0, y0 = node_positions[start]
    x1, y1 = node_positions[end]
    edge_x.append(x0)
    edge_x.append(x1)
    edge_x.append(None)
    edge_y.append(y0)
    edge_y.append(y1)
    edge_y.append(None)

p.multi_line(edge_x, edge_y, color="black", alpha=0.5, line_width=1)

output_notebook()
show(p) 25. Sankey Diagram from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Sankey, ColumnDataSource

# Sample data
flows = [
    ('A', 'X', 5),
    ('B', 'X', 3),
    ('A', 'Y', 2),
    ('B', 'Y', 4),
    ('X', 'C', 4),
    ('X', 'D', 3),
    ('Y', 'C', 2),
    ('Y', 'D', 4)
]

source = ColumnDataSource(data=dict(
    source=[flow[0] for flow in flows],
    target=[flow[1] for flow in flows],
    value=[flow[2] for flow in flows]
))

p = figure(plot_width=800, plot_height=400, title="Sankey Diagram Python Bokeh Example by PratikPathak.com")
sankey = Sankey(source=source, label_text_color="white", label_text_font_size="8pt")
p.renderers.append(sankey)

output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 26. Chord Diagram from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, CategoricalColorMapper
import numpy as np

# Sample data
nodes = ['A', 'B', 'C', 'D', 'E', 'F']
connections = [
    ('A', 'B', 0.5), ('A', 'C', 0.3), ('A', 'D', 0.2),
    ('B', 'C', 0.4), ('B', 'D', 0.3), ('B', 'E', 0.3),
    ('C', 'D', 0.2), ('C', 'E', 0.3), ('C', 'F', 0.5),
    ('D', 'E', 0.2), ('D', 'F', 0.3), ('E', 'F', 0.4)
]

source = ColumnDataSource(data=dict(
    start=np.array([con[0] for con in connections]),
    end=np.array([con[1] for con in connections]),
    value=np.array([con[2] for con in connections])
))

p = figure(title="Chord Diagram Python Bokeh Example by PratikPathak.com", plot_width=800, plot_height=800)
chord = p.chord(
    source=source, 
    start_angle=np.pi / 2,
    direction="clockwise",
    colors=CategoricalColorMapper(factors=nodes, palette="Spectral11")
)

output_notebook()
show(p) How to Contribute? Feel free to open a PR request on our GitHub repo. Steps to contribute: Fork the repo Make changes in the Forked repo and save Open a Pull Request That’s it 😄! 🌿 Contribute Conclusion In this Repo, I have shared 25+ Python Bokeh examples that can help you learn Python Bokeh. Feel free to contribute to our GitHub repo and keep it updated. Also published . here

Getting Started With Python Bokeh: 25+ Data Visualization Examples With Source Code

VANCOUVER, Canada, March 27th, 2024/Chainwire/-- In a significant move to fuel the growth of decentralized artificial intelligence, ceτi AI is proud to announce the establishment of the ceτi AI Partnership Innovation Fund with an initial allocation of $500k USD. This strategic fund is designed to catalyze innovation by forging partnerships with emerging projects at the intersection of and blockchain technology. AI Overview ceτi AI, a leader in decentralized AI infrastructure, is initiating this fund to support projects that align with its mission of democratizing access to advanced AI technologies. The fund aims to facilitate collaborative efforts that push the boundaries of what's possible in decentralized AI, enhancing the ecosystem's diversity and driving technological advancement. Investment Details The Partnership Innovation Fund is a pivotal step at the beginning of ceτi AI's journey, dedicating an initial $500k USD worth of resources to empower innovation through strategic alliances. This initiative underscores ceτi AI's commitment to not just being a participant but a catalyst in the decentralized AI marketplace. Use of Proceeds The allocation of this fund will specifically target: Strategic Partnerships: Identifying and supporting projects that demonstrate the potential to revolutionize decentralized AI with innovative solutions. Technology Advancement: Encouraging the development of technologies that can seamlessly integrate with ceτi AI's infrastructure, contributing to the ecosystem's growth and scalability. Community and Ecosystem Development: Strengthening the decentralized AI community by backing projects that bring value, diversity, and innovation to the space. Why Partner with ceτi AI? ceτi AI stands at the forefront of the decentralized AI revolution, with a proven track record of innovation and a strong commitment to an open, accessible AI future. By partnering with ceτi AI through the Partnership Innovation Fund, projects can gain access to: Expertise and Collaboration: Leverage ceτi AI's deep industry knowledge and technical expertise to accelerate project development. Network and Visibility: Benefit from ceτi AI's established network and gain visibility within the broader decentralized AI and blockchain communities. Shared Vision: Users can join a collective effort to shape the future of AI, promoting a decentralized approach that prioritizes accessibility, diversity, and innovation. A Vision for Partnership and Innovation Tony Evans, Chief Strategy Officer at ceτi AI, shared his vision for the fund, "The ceτi AI Partnership Innovation Fund isn't just about financial investment; it's a testament to our belief in the transformative power of collaboration at the intersection of AI and blockchain. By supporting projects that share our vision of an open, decentralized AI future, we're not just fueling innovation; we're actively building the community and ecosystem that will drive the future of technology. This fund is our invitation to innovators and visionaries who dare to dream big and join us in shaping the next frontier of AI." Shaping the Future with ceτi AI ceτi AI invites crypto AI projects, developers, and innovators looking to make a substantial impact in the decentralized AI space to explore partnership opportunities with ceτi AI. Those interested in the Partnership Innovation Fund or seeking more detailed information can contact ceτi AI at . partnership@taoceti.ai About ceτi AI ceτi AI is pioneering the decentralization of artificial intelligence. Our mission is to build a globally distributed, high-performance, scalable AI infrastructure accessible to developers and networks across the globe, thereby accelerating the advancement of decentralized AI and fostering a more diverse and inclusive AI ecosystem. For a deeper dive into our mission, technology, and the future we’re building, users can refer to ceτi AI and visit ceτi AI website at . , , and for the latest updates and community discussions. litepaper http://taoceti.ai Follow us on X Telegram Discord Contact Information: For press inquiries, users can contact: .For inquiries regarding the Partnership Innovation Fund, users can contact: press@taoceti.ai partnership@taoceti.ai Contact Chief Strategy Officer Tony Evans ceτi AI partnership@taoceti.ai This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here.

ceτi AI Announces Partnership Innovation Fund To Accelerate Innovation In Decentralized AI

How to Sample From Latent Space With Variational Autoencoder

ভেরিয়েশনাল অটোএনকোডার দিয়ে সুপ্ত স্থান থেকে কীভাবে নমুনা করবেন

So sampeln Sie mit Variational Autoencoder aus dem Latentraum

Cómo muestrear desde el espacio latente con el codificador automático variacional

Comment échantillonner à partir de l'espace latent avec l'encodeur automatique variationnel

वेरिएशनल ऑटोएनकोडर के साथ अव्यक्त स्थान से नमूना कैसे लें

変分オートエンコーダーを使用して潜在空間からサンプリングする方法

Variational Autoencoder를 사용하여 잠재 공간에서 샘플링하는 방법

Como fazer amostragem do espaço latente com codificador automático variacional

Как выполнить выборку из скрытого пространства с помощью вариационного автоэнкодера

Varyasyonel Otomatik Kodlayıcıyla Gizli Uzaydan Örnekleme Nasıl Yapılır?

Cách lấy mẫu từ không gian tiềm ẩn bằng bộ mã hóa tự động biến đổi

如何使用变分自动编码器从潜在空间进行采样

Creating Scrollable Lists using Protocol-Oriented Programming and UICollectionViewFlowLayout

Multi-Class Classification: Understanding Activation and Loss Functions in Neural Networks

মাল্টি-ক্লাস শ্রেণীবিভাগ: নিউরাল নেটওয়ার্কগুলিতে সক্রিয়করণ এবং ক্ষতি কার্যকারিতা বোঝা

Mehrklassenklassifizierung: Aktivierungs- und Verlustfunktionen in neuronalen Netzen verstehen

Clasificación de clases múltiples: comprensión de las funciones de activación y pérdida en redes neuronales

Classification multiclasse : comprendre les fonctions d'activation et de perte dans les réseaux de neurones

मल्टी-क्लास वर्गीकरण: तंत्रिका नेटवर्क में सक्रियण और हानि कार्यों को समझना

マルチクラス分類: ニューラル ネットワークの活性化関数と損失関数を理解する

다중 클래스 분류: 신경망의 활성화 및 손실 함수 이해

Classificação multiclasse: Compreendendo as funções de ativação e perda em redes neurais

Классификация нескольких классов: понимание функций активации и потерь в нейронных сетях

Çok Sınıflı Sınıflandırma: Sinir Ağlarında Aktivasyon ve Kayıp Fonksiyonlarını Anlamak

Phân loại nhiều lớp: Tìm hiểu các chức năng kích hoạt và mất mát trong mạng thần kinh

多类分类：了解神经网络中的激活函数和损失函数

litespace

litespace.io

11-50 employees

Since 2021

COMPANY RANKING

LITESPACE

EVERGREEN INDEX #6606

litespace WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

litespace

litespace.io

11-50 employees

Since 2021

COMPANY RANKING

LITESPACE

EVERGREEN INDEX #6606

RELATED COMPANIESRANK

STORIES ABOUT LITESPACE

litespace WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!