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Automation is the best answer to controlling cloud costs, especially if you work with modern solutions like containers and Kubernetes. But automated optimization solutions come in different forms: they focus on automating different cost-saving tactics and give you various levels of visibility and control. Here’s a comparison of two automation solutions available to teams that work with Kubernetes: CAST AI and Spot.io. Keep on reading to find out which one supports your use cases better. – Full-Service Cloud-Native Platform CAST AI – Automated Spot Instance Use Spot.io Created by industry veterans, CAST AI is a comprehensive cloud automation platform for environments. Companies across e-commerce and ad tech are using CAST AI to . Automation features include spot instances, autoscaling up & down, and AI VM type selection. optimizing Kubernetes save from 50% to even 90% on their cloud bills Developed by NetApp, is a cloud cost management solution that focuses on optimizing cloud infrastructure costs with spot instance automation. Using machine learning and analytics algorithms, helps teams to get spot capacity for their workloads automatically, cutting costs and ensuring high availability. Spot.io Spot.io CAST AI vs. – Quick Feature Comparison Spot.io Feature CAST AI 🥇 Spot.io Supported platforms AWS ✅ ✅ Google Cloud ✅ ✅ Microsoft Azure ✅ ✅ Cost visibility Detailed cluster cost breakdown ✅ ✅ Automated cost forecasting ✅ ✖ Cost view across multi-cloud ✅ ✖ Real-time alerting functionality ✖ (coming soon) ✅ Kubernetes cost optimization and automation Rightsizing Recommendations, for instance, types and sizes ✅ ✅ Automated rightsizing via AI-driven instance selection ✅ ✖ Multi-shape cluster construction ✅ ✖ Autoscaling ✅ ✅ Automated pod scaling parameters ✅ ✅ Horizontal pod autoscaling ✅ ✅ Node autoscaling ✅ ✅ Cluster scheduling ✅ ✅ Automatic bin packing ✅ ✅ Spot Instance automation ✅ ✅ Full multi-cloud optimization ✅ ✖ Detailed Feature Comparison of and CAST AI Spot.io Cost visibility and monitoring Cost optimization and automation Spot instance automation Full multi-cloud optimization Security Pricing 1. Cost visibility and monitoring Cluster cost breakdown & forecasting In , you get a cost breakdown at the project, cluster, namespace, and deployment level. Teams can analyze costs down to individual microservices and then generate a detailed forecast of their cluster costs for better planning. CAST AI uses universal metrics that work with all supported cloud service providers. CAST AI The platform also comes with a cost allocation feature that works per cluster and per node. A feature for ongoing cloud cost reporting is also in the near-future pipeline since the CAST AI team plans to expand cost dimensions beyond compute – such as control plane, network, egress, storage, and others. breaks down the infrastructure costs of clusters and offers insights into each of the layers. Costs are broken down into namespaces and individual workloads within every namespace, with the option to filter them according to your container labels and annotations. For each workload, Spot.io displays compute and storage costs. Spot.io Users can use this data to analyze the application costs, perform chargebacks without extensive resource tagging, and estimate future cloud spend. Cost View Across Multi-cloud Many companies use more than one cloud service today. Allocating costs in a multi-cloud context is challenging, but equips teams with insights for addressing that. Its full multi-cloud functionality comes with visibility via universal metrics from Grafana and Kibana that can be used for any supported cloud service providers. CAST AI currently doesn’t support multi-cloud functionality or visibility across its solutions for containerized applications. Spot.io 2. Cost Optimization and Automation Rightsizing uses AI to choose the best instance types and sizes that meet an application’s requirements but still help teams save cloud costs. Whenever a cluster needs extra nodes, the AI-driven instance selection algorithm selects instances that achieve maximum performance at a minimum cost. Your team doesn’t have to lift a finger because it all happens automatically. CAST AI The platform also comes with multi-shape cluster construction, since choosing the same instance shape for every node in a cluster may easily lead to overprovisioning. That’s why CAST AI delivers an optimized mix of different instance types adapted to an application’s requirements. offers a handy Right-Sizing recommendation mechanism. The tool monitors workload utilization in real-time to provide you with recommendations for adjusting the resource requirements of workloads when they start consuming significantly more or fewer resources than requested. Spot.io The solution provides recommendations per container and summarizes them for the entire workload to enable easier visualization at a high level and faster implementation. Autoscaling Horizontal Pod Autoscaling and Node Autoscaling automates pod scaling parameters to help teams avoid overprovisioning their infrastructures. The platform also includes a Horizontal Pod Autoscaler, which uses business metrics to generate the optimal number of required pod instances. The feature then scales the replica count of your pods up and down, scaling to zero and removing all pods if there’s no work to be done. CAST AI CAST AI also ensures that the number of nodes in use matches the application’s requirements at all times, scaling nodes up and down automatically. continuously checks for unschedulable pods, and if it finds one, it scales up to make sure that all the pods have a place to run. The solution also removes nodes automatically when all pods running on the node can be moved to other nodes in the cluster. To optimize costs, Spot.io prioritizes downscaling the least utilized nodes. Spot.io Cluster Scheduling and Termination automatically pauses and resumes clusters created within the platform to help teams avoid paying for resources they’re not using. CAST AI makes sure that all that pods and nodes are terminated in a case of scale-down or instance replacement. Spot.io Automatic Bin Packing Kubernetes presents a cost challenge to teams because it distributes applications within a cluster evenly, with no attention paid to how cost-effective this setup is. changes the default pod scheduling behavior and uses automated bin-packing to achieve maximum savings in line with your settings. Fewer nodes translate to lower costs. CAST AI uses bin-packing algorithms as well. When the tool identifies instances where workloads may be distributed across the cluster, it triggers a scale-down to drain and terminate the instance. Spot.io 3. Spot Instance Automation Spot Instances can result in dramatic savings of up to 90% off the On-Demand pricing. But there’s a catch – the cloud provider can pull the plug anytime. That’s why automation is so critical for effective spot instance use. makes sure that the replacement of spot instances that were interrupted is fully automated. This means that teams don’t have to worry about their workloads not finding a place to run. The platform is always on the lookout for better instance alternatives and provisions in a split-second to guarantee high availability. CAST AI allows users to run their clusters on spot instances without the need to provision or scale instances. The tool also takes care of bin packing containers on spot instances to optimize their use even further. Spot.io 4. Full Multi-Cloud Optimization As more and more companies use multiple cloud services to access best-in-class services and prevent disasters, the need to monitor, manage, and optimize costs across providers is greater than ever. CAST AI meets this need by offering you the option to set up multi-cloud clusters using a number of : multi-cloud features – CAST AI replicates applications and data across multiple cloud services. If one fails, others keep your workloads afloat, guaranteeing business continuity. Active-Active Multi-Cloud – the platform distributes traffic evenly across all the participating clouds, always choosing the endpoints that are up and healthy. Global Server Load Balancing – CAST AI makes cost allocation across cloud services easier thanks to universal metrics from Grafana and Kibana. Multi-cloud visibility doesn’t support the multi-cloud functionality at the moment. Spot.io 5. Security Since both automation solutions work directly with the cloud infrastructure, their security is essential. Created by cybersecurity experts, offers a number of security features such as encryption at rest/in transit, secrets management, network security, logging, visibility, and more. The platform also comes with automatic patching and upgrades to VMs and Kubernetes to eliminate the chance of errors in your clusters. Additionally, CAST AI doesn’t access any environment variables that are considered sensitive such as secrets, passwords, tokens, etc. CAST AI is ISO-certified and well underway to obtaining SOC 2 certification. CAST AI encrypts account data within the browser and re-encrypts it with a secure algorithm when it reaches its servers. The tool doesn’t store any private keys, passwords, or authentication tokens – authentication is based on the IAM Cross-Account Role & External ID. Spot.io 6. Pricing offers a free Savings report you can run to check whether you could save up on your cloud bill. The analyzes your setup and generates actionable recommendations. You can implement them manually or turn automated cost optimization features – in that case; you can choose between two plans: Growth and Enterprise. CAST AI read-only agent CAST AI offers guaranteed savings of at least 50%. offers a free trial, after which users can choose from two different pricing models: Pay-as-you-Go without the annual commitment and Subscription that comes with a commitment but opens the doors to more discounts and priority support. Spot.io Summary Both Spot.io and CAST AI are great automation solutions for reducing cloud costs and facilitating processes like cost monitoring, management, and optimization. Using spot instances is a smart method for reducing the cloud bill, but it’s just part of the picture. By – for example, ones purchased within an AWS Savings Plan – you can drive your cloud bill down even more. rightsizing other instances While Spot.io offers recommendations, CAST AI does the job for you via automated instance selection. The broad range of optimization features combined with automated cost forecasting and unique multi-cloud functionality brings CAST AI to the top of cloud cost optimization platforms. To accurately estimate the savings that you would be able to get – start with the free AI Cluster Analyzer.

CAST AI vs. Spot.io: Two Approaches to Automated Cloud Cost Optimization

Using Sudoku to explore backtracking Sudoku is a number-placement where the objective is to fill a square grid of size ‘n’ with numbers between 1 to ‘n’. The numbers must be placed so that each column, each row, and each of the sub-grids (if any) contains all of the numbers from 1 to ‘n’. Sudoku puzzle The most common Sudoku puzzles use a 9x9 grid. The grids are partially filled (with hints) to ensure a solution can be reached. And here’s the solution. Notice how each row, each column and each sub-grid have all numbers from 1 to 9. Some puzzles may even have multiple solutions. The solution to above Sudoku puzzle. One row, column and sub-grid have been highlighted. Aside: solving a Sudoku puzzle Sudoku is a logic-based puzzle. Needless to say, solving one requires a series of logical moves and might require a bit of guesswork. Since this isn’t an article to explore how to solve a Sudoku puzzle, I’ll just a leave a link to one that helped me getting started: . kristanix.com/sudokuepic/sudoku-solving-techniques Backtracking Backtracking is an algorithm for finding all (or some) of the solutions to a problem that incrementally builds candidates to the solution(s). As soon as it determines that a candidate cannot possibly lead to a valid solution, it abandons the candidate. Backtracking is all about choices and consequences. Abandoning a candidate typically results in visiting a previous stage of the problem-solving-process. This is what it means to “backtrack” — visit a previous stage and explore new possibilities from thereon. Usually, apart from the original problem and the end goal, we also have a set of constraints that the solution must satisfy. The simplest (read ‘dumbest’) implementations often use little to no “logic” or “insight” to the problem. Instead, they frantically try to find a solution by guesswork. A backtracking algorithm can be thought of as a . In this tree, the root node is the original problem, each node is a candidate and the leaf nodes are possible solution candidates. We traverse the tree depth-first from root to a leaf node to solve the problem. tree of possibilities Tree of Possibilities for a typical backtracking algorithm The tree diagram also shows 2 groups — and . Unexplored Possible Candidates Impossible Candidates UPC marks nodes that were never explored. Some of them could have been viable candidates, leading to another solution. Since we never explored them, we can never know. Problems where multiple solutions are acceptable won’t have this group. IC groups are the obvious ones. It contains nodes which have a failed candidate node as one of their ancestor nodes. None of the nodes in this group are candidate nodes and none of the leaf nodes are solution nodes. Sudoku & Backtracking We will now create a Sudoku solver using backtracking by our problem, goal and constraints in a step-by-step algorithm. encoding Problem Given a, possibly, partially filled grid of size ‘n’, completely fill the grid with number between 1 and ‘n’. Goal Goal is defined for verifying the solution. Once the goal is reached, searching terminates. A fully filled grid is a solution if: Each row has all numbers form 1 to ‘n’. Each column has all numbers form 1 to ‘n’. Each sub-grid (if any) has all numbers form 1 to ‘n’. Constraints Constraints are defined for verifying each candidate. A candidate is valid if: Each row has unique numbers form 1 to ’n’ or empty spaces. Each column has unique numbers form 1 to ‘n’ or empty spaces. Each sub-grid (if any) has unique numbers form 1 to ‘n’ or empty spaces. Termination conditions Typically, backtracking algorithms have termination conditions other than reaching goal. These help with failures in solving the problem and special cases of the problem itself. There are no empty spots left to fill and the candidate still doesn’t qualify as a the solution. There are no empty spots to begin with, i.e., the grid is already fully filled. Step-by-step algorithm Here’s how our code will “guess” at each step, all the way to the final solution: Make a list of all the empty spots. Select a spot and place a number, between 1 and ‘n’, in it and validate the candidate grid. If any of the constraints fails, . Otherwise, check if the goal is reached. abandon candidate and repeat step 2 with the next number If a solution is found, stop searching. Otherwise, repeat steps 2 to 4. Pen-paper demo . Now let’s try all this in practice with a simple 3x3 grid. Groovy A 3x3 Sudoku puzzle We start off by listing all the empty spots. If we label each cell in the grid with a pair of numbers and mark the first cell , then our empty spots will be at locations: (x,y) (1,1) (1,2) (2,2) (2,3) (3,1) (3,2) We now select the first spot to work with. Since this is a 3x3 grid, we have numbers 1 to 3 at our disposal and no sub-grids to worry about (sub-grids are only a bother for grids with squared sides, like 4, 9, 16 etc.). (1,2) Let’s place number in this spot and see if it fits. 1 Filling ‘1’ in spot (1, 2) It does. Great. We can now select the next spot on the list and do the same thing again. This time however, it fails. We already have a in this row. This means that we must — which is . (2,2) 1 abandon candidate and repeat step 2 with the next number 2 Filling 2 in spot (2, 2) One more spot is filled. Also, it might not look like it, but we did just perform backtracking on a single spot. We abandoned a candidate solution ( at spot ), visited a previous stage (empty spot ) and explored a new candidate solution (number at spot ). Huzzah! 1 (2,2) (2,2) 2 (2,2) When we move on to spot , we have another problem. As you can see, we are all out of options. None of the possible numbers fit in. This means that we must now . Only this time, we must visit spot first to fix spot . (2,3) abandon candidate and repeat step 2 with the next number (2,2) (2,3) Failure to fill spot (2, 3) We need to fill number in spot and that will resolve the issue. 3 (2,2) Backtracking to spot (2, 2) and then re-visiting spot (2, 3) We now repeat this process until with either reach the goal or we hit one of the termination conditions. Since this was a demo problem, it should be obvious that we’d arrive at the solution without any further complications. Solved 3x3 Sudoku puzzle However, consider the same grid with one small change. Replacing the in cell with a renders the grid unsolvable. Similarly, removing hints from cells and allows for multiple solutions. But since this algorithm has a single goal, it stops after the first solution is reached. 1 (3,3) 2 (2,1) (3,3) Unsolvable 3x3 puzzle (left) and Multi-solution 3x3 puzzle (right) Here’s what the looks like: tree of possibilities Tree of Possibilities for 3x3 Sudoku Implementation Enough talk. Let’s code … Disclaimer (for python-istas): The code you’re about to see is not pythonic.IMHO, it is borderline ugly. The purpose of this snippet is to explain convert the steps shown above into simple, meaningful code and not to boast the elegance of python. What next? This article aims to strengthen the concept of backtracking by drawing connections with a popular game of logic. I should tell you that Sudoku is an ‘ . As complex as it may sound, it really isn’t (not for the scope of this article): NP-complete combinatorial problem’ means that while we can verify a solution, it is rather to arrive at one. NP-complete easily difficult means that to arrive at a solution, we must perform selection and arrangement of some data — combination and permutation. Combinatorial Sample problems We can try to solve some other problems by basing our approach on our current understanding. The problem is a close enough relative to the Sudoku solver. Two more problems that rank similar are and . Binary Watch Combination Sum III Permutation Sequence There are that you can try on. However, trying to mold them into the Sudoku solver pattern might not always be trivial. It’s best to try to formulate your approach in the following pattern: a lot more problems Problem Goal Constraints Termination conditions Step-by-step algorithm

Sudoku and Backtracking

In the context of global digitalization, governments have implemented various legislations on data privacy. However, some companies make minimal changes to their operations to formally comply with requirements or even ignore them if there are no precedents of sanctions. Moreover, violations can happen involuntarily. Using link shorteners is a common practice. You can create whatever link you want using services like Bitly, Rebrand, TinyURL, IPLogger, Cuttly, or many others, and instead of showing a user a long, clumsy link, give them one that looks good. Privacy policies of link shorteners state compliance with all legislative requirements concerning the processing and storage of personal data. If you are the one creating a link on the website, you will be asked to express consent to your data being collected. But what happens if you just click a link created by someone else? Your data is gathered and processed, and in most cases, without your consent, as you do not have the opportunity to give it; you just follow a link. While in some instances, the processing of personal data can be justified, for example, for purposes connected with the functioning of the service, sometimes such collection goes above and beyond the norm. One way link-shortening services monetize is by selling analytical data about clicks to different companies. The data may include details about the geography of clicks, sources of traffic, types of devices and browsers used, as well as language preferences - all of which are of significant interest for optimizing marketing campaigns, analyzing sales effectiveness, and so on. To provide such analytics, link-shortening services may need to collect, process, and store personal data on their servers. Some of this information, for example, the country and city, is usually based on the user's IP address. This pertains to the processing of personal information according to data privacy regulations such as GDPR classification. Often, users are not aware of such processing - even if mentioned somewhere, it may be buried in tons of legal documents located on an external website, which is rarely, if at all, being visited.


Many link-shortening services use cookies, recording them in the browser of the user who clicked on the link. In the EU and many other countries, placing non-functional cookies in users' browsers requires active opt-in.


Some of the services offer integration into the short links tracking pixels from third-party services, such as Facebook, which also uses cookie technology. Scripts executed to make it work collect data and send it back to the platform. Data policies of these platforms usually require explicit consent from end-users before loading such pixels into their browsers, but if a tracking pixel is activated during a click-through on a short link, there’s an issue with obtaining it.


And the last one - this user data can be transferred beyond the territories of the EU or the US unless there are adequate safeguards in place. Thus, if the creators of a short link are located in one country, they automatically gain access to information about all the users who click it, regardless of their geographic location. While some platforms provide such adequate safeguards, some of them do not. For example, GA4 is valid for transfers from the EU to the US, while TikTok pixels do not have adequate certification under the Data Privacy Framework. Therefore, user consent for transfers might be required. According to European legislation, the user's consent to the processing, and transferring, of personal data must be explicit, informed, and given freely. In the US context, similar initiatives for the protection of personal data also exist (the California Consumer Privacy Act (CCPA), the Virginia Consumer Data Protection Act (VCDPA), and the Children’s Online Privacy Protection Act (COPPA)). These laws, although not as unified as the GDPR in Europe, reflect a growing trend in the United States toward more stringent data protection. Still, there are hundreds of millions of users, who use short links and leave their data without realizing that it can be used for commercial purposes. According to Bit.ly, it processes 10 billion redirects through its short links per month. Rebrand.ly reports that their links are clicked 2 billion times a month. It's crucial to note that some services may not fully grasp the extent to which they violate legislative requirements, so the initial step is to fully acknowledge the problem. Once done, efforts can be directed towards solutions, such as creating intermediary pages akin to those utilized by websites to obtain user consent. While this may lengthen the user's journey, it presents a method to adhere to regulations for both link-shortening services and the companies utilizing them. There could also be additional strategies to explore. Upon recognizing the issue, optimism can be fostered for the development of technologies that contribute to creating a safer and more ethical digital space. In the context of global digitalization, governments have implemented various legislations on data privacy. However, some companies make minimal changes to their operations to formally comply with requirements or even ignore them if there are no precedents of sanctions. Moreover, violations can happen involuntarily. In the context of global digitalization, governments have implemented various legislations on data privacy . However, some companies make minimal changes to their operations to formally comply with requirements or even ignore them if there are no precedents of sanctions. Moreover, violations can happen involuntarily. data privacy Using link shorteners is a common practice. You can create whatever link you want using services like Bitly, Rebrand, TinyURL, IPLogger, Cuttly, or many others, and instead of showing a user a long, clumsy link, give them one that looks good. Privacy policies of link shorteners state compliance with all legislative requirements concerning the processing and storage of personal data. If you are the one creating a link on the website, you will be asked to express consent to your data being collected. But what happens if you just click a link created by someone else? Your data is gathered and processed, and in most cases, without your consent, as you do not have the opportunity to give it; you just follow a link. While in some instances, the processing of personal data can be justified, for example, for purposes connected with the functioning of the service, sometimes such collection goes above and beyond the norm. One way link-shortening services monetize is by selling analytical data about clicks to different companies. The data may include details about the geography of clicks, sources of traffic, types of devices and browsers used, as well as language preferences - all of which are of significant interest for optimizing marketing campaigns, analyzing sales effectiveness, and so on. To provide such analytics, link-shortening services may need to collect, process, and store personal data on their servers. Some of this information, for example, the country and city, is usually based on the user's IP address. This pertains to the processing of personal information according to data privacy regulations such as GDPR classification. Often, users are not aware of such processing - even if mentioned somewhere, it may be buried in tons of legal documents located on an external website, which is rarely, if at all, being visited. Many link-shortening services use cookies, recording them in the browser of the user who clicked on the link. In the EU and many other countries, placing non-functional cookies in users' browsers requires active opt-in. Some of the services offer integration into the short links tracking pixels from third-party services, such as Facebook, which also uses cookie technology. Scripts executed to make it work collect data and send it back to the platform. Data policies of these platforms usually require explicit consent from end-users before loading such pixels into their browsers, but if a tracking pixel is activated during a click-through on a short link, there’s an issue with obtaining it. And the last one - this user data can be transferred beyond the territories of the EU or the US unless there are adequate safeguards in place. Thus, if the creators of a short link are located in one country, they automatically gain access to information about all the users who click it, regardless of their geographic location. While some platforms provide such adequate safeguards, some of them do not. For example, GA4 is valid for transfers from the EU to the US, while TikTok pixels do not have adequate certification under the Data Privacy Framework. Therefore, user consent for transfers might be required. To provide such analytics, link-shortening services may need to collect, process, and store personal data on their servers. Some of this information, for example, the country and city, is usually based on the user's IP address. This pertains to the processing of personal information according to data privacy regulations such as GDPR classification. Often, users are not aware of such processing - even if mentioned somewhere, it may be buried in tons of legal documents located on an external website, which is rarely, if at all, being visited. To provide such analytics, link-shortening services may need to collect, process, and store personal data on their servers. Some of this information, for example, the country and city, is usually based on the user's IP address. This pertains to the processing of personal information according to data privacy regulations such as GDPR classification . Often, users are not aware of such processing - even if mentioned somewhere, it may be buried in tons of legal documents located on an external website, which is rarely, if at all, being visited. GDPR classification GDPR classification Many link-shortening services use cookies, recording them in the browser of the user who clicked on the link. In the EU and many other countries, placing non-functional cookies in users' browsers requires active opt-in. Many link-shortening services use cookies, recording them in the browser of the user who clicked on the link. In the EU and many other countries, placing non-functional cookies in users' browsers requires active opt-in. Some of the services offer integration into the short links tracking pixels from third-party services, such as Facebook, which also uses cookie technology. Scripts executed to make it work collect data and send it back to the platform. Data policies of these platforms usually require explicit consent from end-users before loading such pixels into their browsers, but if a tracking pixel is activated during a click-through on a short link, there’s an issue with obtaining it. Some of the services offer integration into the short links tracking pixels from third-party services, such as Facebook, which also uses cookie technology. Scripts executed to make it work collect data and send it back to the platform. Data policies of these platforms usually require explicit consent from end-users before loading such pixels into their browsers, but if a tracking pixel is activated during a click-through on a short link, there’s an issue with obtaining it. And the last one - this user data can be transferred beyond the territories of the EU or the US unless there are adequate safeguards in place. Thus, if the creators of a short link are located in one country, they automatically gain access to information about all the users who click it, regardless of their geographic location. While some platforms provide such adequate safeguards, some of them do not. For example, GA4 is valid for transfers from the EU to the US, while TikTok pixels do not have adequate certification under the Data Privacy Framework. Therefore, user consent for transfers might be required. And the last one - this user data can be transferred beyond the territories of the EU or the US unless there are adequate safeguards in place. Thus, if the creators of a short link are located in one country, they automatically gain access to information about all the users who click it, regardless of their geographic location. While some platforms provide such adequate safeguards, some of them do not. For example, GA4 is valid for transfers from the EU to the US, while TikTok pixels do not have adequate certification under the Data Privacy Framework. Therefore, user consent for transfers might be required. According to European legislation , the user's consent to the processing, and transferring, of personal data must be explicit, informed, and given freely. In the US context, similar initiatives for the protection of personal data also exist (the California Consumer Privacy Act (CCPA) , the Virginia Consumer Data Protection Act (VCDPA) , and the Children’s Online Privacy Protection Act (COPPA) ). These laws, although not as unified as the GDPR in Europe, reflect a growing trend in the United States toward more stringent data protection. According to European legislation According to European legislation (the California Consumer Privacy Act (CCPA) (the California Consumer Privacy Act (CCPA) the Virginia Consumer Data Protection Act (VCDPA) the Virginia Consumer Data Protection Act (VCDPA) the Children’s Online Privacy Protection Act (COPPA) the Children’s Online Privacy Protection Act (COPPA) Still, there are hundreds of millions of users, who use short links and leave their data without realizing that it can be used for commercial purposes. According to Bit.ly, it processes 10 billion redirects through its short links per month. Rebrand.ly reports that their links are clicked 2 billion times a month. reports reports It's crucial to note that some services may not fully grasp the extent to which they violate legislative requirements, so the initial step is to fully acknowledge the problem. Once done, efforts can be directed towards solutions, such as creating intermediary pages akin to those utilized by websites to obtain user consent. While this may lengthen the user's journey, it presents a method to adhere to regulations for both link-shortening services and the companies utilizing them. There could also be additional strategies to explore. Upon recognizing the issue, optimism can be fostered for the development of technologies that contribute to creating a safer and more ethical digital space.

Link Shorteners: Yet Another White Spot in Data Collection

AI has been all the rage since late 2022, and it has many more practical applications than we saw from the blockchain craze. We’re seeing AI crop up in many products and, in many ways, some more useful than others. One of the segments that I’ve been watching is how it can work in a data exploration context. To that end, I ran across a new product called “ ,” created by the originators of the BI tool , which I in 2019. They say it is the world’s first NLP & AI-based Data Engineering tool, so let’s take a look. Ask On Data Helical Insight wrote about Getting Started I got an early look at the product a couple of months ago, and they are iterating quickly with updates. The UI was updated even when I started to write this piece a few weeks ago. The are being kept up to date, though, which is what I used to try out the product. The docs are clean and succinct, making them easy to reference. docs The UI presents a clean interface, and the first thing you need to do is add some data, which is done with that center icon in the upper right: A robust choice of connectors for a product just coming out of the gate exists. I tried some voter registration Excel files I was just looking at, so we go with the Flat Files option here. Now, we go back and create a new job. The icon on the home page, upper left, that looks like a speech bubble. You connect a job to data files that have been registered, which is convenient because you don’t have to keep loading them for each job. Working with your data With my votre role file loaded, I first wanted to sort it by the last name, and I can do that by literally saying “sort by sznamelast ascending”: Next, I wanted to count each occurrence of the street name so I’d know how many voters live on each street. AskOnData has autocomplete of commands and columns, which is convenient: This command gave me the following: Export options are also included, so any of these resulting datasets can be exported to use in another tool. Take a look at the for a complete list of currently available transformations. docs Those are some quick examples, but it was fascinating to say what I wanted from the data and get it back rapidly. I had an older friend whose data I was working with give it a little try; he hates computers, so he asks me to help him. This was a much more intuitive experience for him than understanding the user interface of something like Excel. That was an eye-opener to me, as computers are like swimming for me, I have done it for so long that I have trouble understanding when people can’t. Other features In the non-free version of the application, you can also schedule these as jobs. For example, you can connect to a database, pull weekly sales data, and run it through some aggregation functions. That could be set up to run every Sunday night, and then you come in on Monday morning and have your sales report ready. The command window also has slash (/) commands that allow you to execute an Excel-like expression, SQL, or BI style command. I tested out some expressions, which were straightforward enough; the SQL commands are also what you’d expect, except you refer to the current working data as for . It looked like this: df dataframe If you’re an SQL person, then this will feel pretty natural for you. I think these slash commands are very much a work in progress at the moment, but those two worked well for my use case. Summary This is a new product, and as such, it is iterating rapidly. Some of the UX flow needs some polish, but I’m told that some of that is related to the training. For example, I had specified the entire command in the earlier command, but after I issued it, the product asked me to specify what aggregation I wanted to perform, so I had to say again. My initial hurdle was just the mindset of saying what I wanted. I’ve been using computer software for so long that I’m accustomed to working with it in a particular way. Understanding prompt engineering is definitely the wave of the future, and it behooves all of us to add it to our arsenal. count count This is a fun product to work with. I appreciate the unconventional thinking that went into it. There is definitely a segment of the public that can use an easier way to interact with data that doesn’t require that they learn a lot of new skills. Is it a good tool for your use case? Try it and see. I liked it.

Spotlight on Ask On Data

NFTs have taken the crypto world by storm over the past year. From Bored Apes to CryptoPunks, valuable digital collectibles are selling for millions. But what about the rest of us who can't afford a whole NFT but still want in on the action? That's where fractionalization comes in. Platforms like Pandora have pioneered the concept of dividing up ownership of an NFT into multiple tokens. This allows anyone to invest a small amount and own a piece of the pie. However, existing fractionalization methods have their limitations. You have to trust a middleman to securely store your NFT. Liquidity can be an issue if you want to sell your fraction. And recombining pieces back into a whole NFT is a pain. A solution to this is ERC-404 - a proposed standard that aims to revolutionize fractional NFT ownership. By the way: if you are keen on expanding your knowledge on AI, we have a good news for you: our newsletter, was launched to present our audience the crème-de-la-crème of the AI world. The best thing - it comes completely free of charge! , AI Huntees And now, here’s a deep dive into what ERC-404 is all about: A World of Native Fractionalization Most tokens issued on Ethereum and traded on exchanges follow the ERC20 standard. NFTs, on the other hand, adhere to the ERC721 standard. However, the popularity of NFT projects like CryptoPunks and Bored Ape Yacht Club has left many crypto enthusiasts frustrated that they only have a limited amount of funds in their wallets but want to profit from the hype surrounding expensive NFTs. With ERC-404, fractionalization is baked directly into the token standard rather than handled off-chain. When an NFT is initially minted on ERC-404, it simultaneously mints a set of ERC-20 tokens that represent ownership shares. What's the Point of ERC-404? Each fractional token is cryptographically linked to its corresponding piece of the NFT. Buy 0.5 tokens? You own half the asset. Collect enough to make a whole token? The full NFT is migrated to your wallet. No more relying on third parties. Let us consider a practical example. Say, I issue 5000 PIXEL tokens in the ERC-404 format. PIXEL tokens include 5000 ERC-20 tokens and 5000 NFTs. Each ERC-20 token in this system is linked to a specific NFT, allowing for fractional ownership. • When buying 1 whole ERC-20 token, the corresponding NFT automatically appears in the buyer's wallet, confirming full ownership of the asset.
• If only a fraction of the ERC-20 token is purchased (for example, 0.5 PIXEL), the associated NFT is destroyed. As a result, the buyer only has a share of the token without linking to the NFT.
• When the owner of the fractions collects enough to form a full ERC-20 token (for example, bought 0.2 PIXEL, then 0.5 PIXEL, and another 0.3 PIXEL), a new NFT is created in their wallet, restoring full ownership of the unique asset. Built-In Liquidity From Day One Because ERC-404 tokens behave just like normal ERC-20s, liquidity pools can be set up from the beginning. Want to sell your fractions? Just swap on an AMM dex like usual. No manually finding a buyer or dealing with order books. Additionally, unlike ordinary fractionalized NFTs, ERC-404 can be automatically fractionated into one NFT or an entire collection. Massive Potential But Major Caveats The promise of smooth, trustless fractionalization is undeniably appealing. However, ERC-404 is still very early and carries risks like bugs, scams, and lack of adoption. Let’s not disregard the fact that the Ethereum developer community has not officially approved the standard, so rug pulls, vulnerabilities, and other issues are quite possible. Moreover, combining two tokens will not return the same NFT, so its value may be variable—this will depend on the specific project. Last but not least, eternal mints, remints, and burns are driving up the price of gas. Today, it reached its maximum in 8 months - $60 for an ordinary transaction in the Ethereum network. We strongly believe that with refinement, ERC-404 could be huge. We already started to work with . However, in its current state, it’s better to keep a close eye on ERC-404 as it develops — only time will tell if it lives up to the lofty vision. ERC-404 projects P.S. Check out my previous articles at HackerNoon: DeFi Community Building: A Step-by-Step Guide for Crypto Startups The Best Of The AI World: Spotlighting 5 Projects and Researches Pushing The Paradigm This Week Crypto's Next Chapter: 2024's Game-Changing Predictions Top 10 AI Trends of 2024: How AI Transforms Everything How to Build Your Personal GPTs: From Zero to AI Hero GPT-4 Turbo: The Most Monumental Update Since ChatGPT's Debut! Essential Insights from 'State of AI 2023' GPT-4V Unveiled: From Detecting Emotions to Ordering Food - You Won't Believe What Else It Can Do! ChatGPT Now Speaks, Listens, and Understands: All You Need to Know

Breaking Down the Next Big Thing in NFTs: ERC-404 Spotlight

The world of AI moves fast, and staying on top of the latest breakthroughs can oftentimes feel near-impossible. That's why we decided to bring you a weekly roundup of the most impactful and innovative AI projects to help you keep up with this fast-paced field. In this edition, we present you with an exclusive compilation of the most exciting projects and noteworthy developments from the past week. Join us as we dive into the forefront of the AI revolution with , your one-stop destination for all things AI — absolutely for free! AI AI Hunters And now, let’s get into it: OpenVoice Opens New Phase in Voice Cloning , a collaborative effort by MIT, Tsinghua University, and MyShell, introduces a game-changing AI-based voice cloning tool. Unparalleled in its precision, OpenVoice empowers users with granular control over tone, emotion, accent, rhythm, pauses, and intonation. Addressing the lack of robust open-source voice cloning research, this cost-effective tool promises to revolutionize the field. OpenVoice OnlyBots Launches First Social Network for AI Imagine bot AIs cooperating on problems or keeping each other updated on the latest developments. , the pioneering AI social network, designed its platform as a bot-to-bot interaction, this way fostering innovations and ideas exchange within the AI community. That level of integration between non-human intelligence allows for pushing frontiers of collaboration and problem-solving. OnlyBots Trellus Offers a Real-Time AI Coach to Join Sales Calls leverages AI and machine learning to deliver real-time feedback and training to sales reps. Packed with features such as an embedded Auto Dialer, localized data, call summarization, and an AI-powered assistant, it empowers sales professionals to boost productivity without compromising quality. By analyzing call patterns and outcomes, Trellus can identify strengths and weaknesses and even recommend rebuttals. With an embedded dialer, too, it looks to streamline the sales process from start to close. Trellus Rosebud AI Automates Game Development The makers of are using generative models to create game assets, worlds, and even animated characters - all without human designers. Tools like their conversation AI "Tokkingheads" bring new interactive life to games through avatar animation, breathing life into portraits by seamlessly syncing lip movements with text or audio. As AI-powered content creation scales, indie devs may find new creative space for self-realization. Rosebud AI Coursebox Supercharges Online Learning with AI harnesses the power of AI to streamline the course creation process. With Coursebox, educators and individuals can design course structures and content in minutes, unlocking unprecedented efficiency in online course development. As online learning grows, AI stands to upturn the access to education globally. Coursebox Research and Reports That Are Worth Your Attention Dissecting Chatbots with The Guardian Discover the inner workings of AI chatbots, including ChatGPT and Bard, in this piece by . Delving into the crucial aspects of large language models (LLMs), such as the "transformer" reweighting step and the "attention" principle, the article sheds light on the extensive training required for refined question-and-response skills while filtering out undesirable replies. The Guardian Neural Network Explainer Series Join renowned researcher Andrej Karpathy in his captivating on neural networks. Karpathy introduces insights into the architecture and training process of large language models (LLMs), unraveling the fundamentals behind these powerful AI systems. For those looking to better understand the technical foundations of conversational AI systems, this is a must-watch. video series AI Detects Unknown Artist's Touch on Raphael Painting Witness a as AI researchers analyze Raphael's "Madonna della Rosa”. By training an AI algorithm on Raphael's style, experts meticulously scrutinize every detail, shedding new light on the artist's work and authorship. This breakthrough opens up exciting possibilities for understanding and appreciating art in unprecedented ways. groundbreaking discovery

The Best Of The AI World: Spotlighting 5 Projects and Researches Pushing The Paradigm This Week

The Noonification: Microsoft, Apple Trade Blows For Top Spot (1/31/2024)

What company is more valuable, or ? That's the question Wall Street wants to answer entering into 2024 as both firms compete head to head in a race to be crowned victor. Microsoft Apple With a market capitalization of over $3 trillion, Apple has been the in the world for quite some time now, but after the ultra sensationalized success of Microsoft-backed OpenAI's ChatGPT, the Windows maker has slowly and broke the $3 trillion threshold to appear as a formidable challenger to the creator of iPhone. most valuable company gained ground finally In fact, at the time of writing, Microsoft already the most valuable company in the world, but in the of Dr. Dre, "Anybody can get it; The hard part is keepin' it, motherf*cker." was infamous words So now the question is, will Microsoft remain the most valuable company in the world? Well.. Say what you will of Microsoft's business, products, and business products, the company holds a commendable sway over the industries it operates in. We're talking OSs; Productivity tools; Cloud; the list goes on. As we understand it, there's no part of the technology world that doesn't rely on or use a Microsoft product in some shape, way, or form to function, and that's why the company has been able to invent and reinvent itself while staying relevant since the time it was founded by Bill Gates. precisely Instead of wanting to sell products directly to customers, a majority of Microsoft's business has to do with offering tools to the people that make the products that then customers want to buy. And that's a very important distinction to make because that's what makes Microsoft a little different from Apple, which is very, very reliant on customer trends. Apple's entire business model has to do with making products people want, and it is very, very good at what it does. Apple products are cleverly designed, often innovative, and come with the oomph consumers are looking for, but there's really not a lot the company can do if people just can't (or won't!) buy its iPhones, as was the case recently when the company reportedly saw a 30% decline in the smartphone's sales in China due to growing competition from the likes of Huawei. And THAT perhaps is the biggest reason why the company's stock price has been taking a dip, leaving Microsoft with the opportunity to zoom on past ahead. Microsoft's stock also did phenomenally well last year, 57% in 2023 as compared to the 48% rise Apple shares experienced last year. So it's safe to say, the future, as it stands, belongs to Apple and Microsoft, at least, in terms of who is the most valuable — regardless of who is #1. rising So with Microsoft and Apple so far ahead, where does that leave the likes of and ? Unfortunately for Google parent Alphabet, CEO Sundar Pichai's prediction that the success of ChatGPT was a for the company may be coming true since the company hasn't even reached the $2 trillion mark! Meanwhile, Amazon is stuck in a involving its business practices and finds itself at an even lower valuation than Google. Google Amazon code red range of legal issues The one rising star amongst all of these companies continues to be , which not only became worth last year, has already experienced such a in its share price that it's already halfway through to adding trillion to its market share. For those that don't know, Nvidia sells the hardware that makes generative AI possible. Nvidia $1 trillion surge another Anyway, it's going to be a ride this year and we'd be excited to see who comes up on top. wiiiiiiiiiiild Microsoft was ranked #1 on HackerNoon's this week, followed by Apple at #3, Google at #5 and Amazon at #6. Tech Company Rankings 👋 You’re reading HackerNoon's , a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Subscribe to receive the newsletter in your inbox every Tuesday. Tech Company News Brief here complete Reddit, Now Coming to a Stock Exchange Near You! 👽 Love it or hate it, Reddit is as much a part of the internet lexicon as Google or Facebook. Depending on what you fancy, there's almost always a community to be found, and some reddit threads are.. Well, . classic Reddit might not necessarily have the same corporate clout as traditional social media companies, or, atleast, the deep coffers that run in billions, but it does command sizable respect around the web, particularly as an outlet for some of the more niche communities. I mean, who hasn't turned to Reddit to find answers to burning questions about.. Ahem, . bowel movements Now, Reddit wants a seat at the big boys' table. Having been the platform where "meme stocks" originated, the social media company now wants to float its own stocks to the public market with a soon-to-be-coming initial public offering this year. According to media reports, the mecca of memes (4chan not counted because of 😉) could file for an IPO as early as February, with plans to wrap up the entire process by the end of March. The IPO has been a long time coming, with the platform said to have sketched plans to go public as far back as 2021; for one reason or the other, the company held up on actually pulling the trigger, but the plan seems to be picking up steam. Rule #1 So how much Reddit going to be worth? During its last funding round in 2021, the platform was said to be worth about $10 billion despite the fact that it has never come close to profitability. The valuation might sound like a lot until you realize that it's next to nothing when compared to the likes of Meta (close to a trillion dollars in valuation) and TikTok-owner Bytedance (hundreds of billions of dollars). is Nonetheless, the public at large will have a chance to own a piece of the pie with the IPO which would see Reddit float 10% of its ownership in public markets. So keep your eyes peeled for when that happens! What's Up With Bitcoin? 🪙 To any crypto pundit who thought the world's largest currency was headed To the Moon™, is going on with Bitcoin?? what the heck Ever since the US Securities & Exchange Commission approved a bunch of spot bitcoin exchange traded funds (ETF), the price of the cryptocurrency keeps falling. In fact, as of the time of this writing, bitcoin has gone down to $40,000 at least once! below But don't worry, if you're just as confused as we are as to what's going on, we just might have the answer for you. The ETF approval was already pegged as a "sell-the-news" event by on-chain analysis firm CryptoQuant, one of the very few firms that bitcoin prices would go down following the SEC action. The firm continues to maintain that bitcoin will fall to around $32,000 as the market corrects itself, possibly spelling doom for Hodlers who got in the action when bitcoin was in the $40,000 range (unless said Hodlers have diamond hands). And if things continue the way they are, it's likely the firm's analysis will come true. warned But keeping aside what analysts say, part of the reason why bitcoin prices have gone down has to do with now defunct crypto exchange FTX, which apparently sold $1 billion worth of  Grayscale's Bitcoin ETF as part of its . bankruptcy proceedings Whether bitcoin is going to go up or down is anyone's guess, but it should be interesting to see how the crypto landscape evolves with the SEC's oversight (the cryptocurrency is already up back to $42k levels!). Fun fact: HackerNoon is running a poll asking the community what THEY think about the whole bitcoin pricing scenario, so feel free to add your . voice to the discussion In Other News.. 📰 NFTs Outpaced Ether's Gains in January — via CoinDesk Elon Musk’s $56B Tesla pay deal is unfair, judge rules — via TechCrunch MrBeast tested Elon Musk’s theory and took home $250,000 — via CNN Investors punish Microsoft, Alphabet as AI returns fall short of lofty expectations — via Reuters Tech rivals hound Apple over EU App Store plans — via Axios Lawmakers to grill CEOs of Meta, TikTok, X and other social media firms at hearing on child safety — via CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's page. Tech Company Rankings

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