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Learners at Mvalo Secondary School will have an opportunity to get computer literacy skills ... Rowe noted that the initiative forms part of the company’s commitment to support skills development among ZAC’s host communities. He also thanked the ...

ZAC delivers Laptops to help learners gain digital skills

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ABST), said the software security company's planned $11.50 as share sale to Crosspoint Capital Partners undervalues the company. Edenbrook, which has a 10.4% stake in Absolute Software ...

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What the company is: Adobe, one of the most established computer software companies in the U.S., is known for its innovative programs like Adobe Photoshop, Adobe Illustrator and Adobe Acrobat Reader.

20 Big Companies That Hire Remote Workers

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Integrating Launchable's Predictive Test Selection with Pytest In the ever-evolving landscape of software development, the need for scalable and effective testing processes has never been more crucial. As the complexity of applications grows, it becomes increasingly challenging to maintain a fast, reliable testing workflow. Enter pytest, a popular testing framework for Python that makes writing and organizing tests a breeze for developers. But what if we could make pytest even better? leverages machine learning to predict which tests are , drastically reducing the time spent on running irrelevant tests. By combining the simplicity and flexibility of pytest with the powerful predictive capabilities of Launchable, you'll be able to achieve a new level of testing efficiency and accuracy. Launchable most likely to catch potential defects Dive into the benefits of using pytest with Launchable's Predictive Test Selection, walk through the setup process, and see how these tools can work in harmony to revolutionize your testing workflow. Get ready to transform the way you test your Python applications! Understanding the Basics of Pytest (With Hands-On Code Examples): Writing Tests, Assertions, Fixtures, and Plugins in Pytest Pytest's elegance and simplicity make writing tests, assertions, fixtures, and plugins a seamless experience for developers. With its intuitive syntax and powerful features, you can craft tests for that are both easy to understand and maintain. Let's explore these concepts in more detail and see how they can be utilized in your testing workflow. all types of software testing Pytest Tests and Assertions Pytest allows you to write test functions using standard Python assert statements, making your tests clean and readable. To create a test, simply define a function with a name starting with , and use assertions to check if the expected behavior is met. Here's a simple example: test_ def add(a, b):
    return a + b

def test_add():
    assert add(2, 3) == 5
    assert add(-1, 5) == 4
    assert add(0, 0) == 0 Pytest Fixtures Fixtures in pytest provide a convenient way to set up and tear down reusable resources, such as database connections, temporary files, or test data. They help you to maintain a clean, modular test suite. To create a fixture, use the @pytest.fixture decorator shown in the example below. import pytest

@pytest.fixture
def sample_data():
    return {"name": "John Doe", "age": 30}

def test_sample_data(sample_data):
    assert sample_data["name"] == "John Doe"
    assert sample_data["age"] == 30 In the example above, the fixture is automatically passed to any test function that requests it as a parameter, ensuring consistent test data across your test suite. sample_data Pytest Plugins Pytest's plugin system allows you to extend its functionality or integrate it with other tools, making it even more versatile. You can either use existing plugins or create your own. To install an existing plugin, use the pip package manager. For example, run the following in your command line to install the pytest-cov plugin. pip install pytest-cov To create a custom plugin, define a new python module (named in the example). From there, you will register the module as an entry point in your setup.py file. my_plugin_module # setup.py
from setuptools import setup

setup(
    ...
    entry_points={"pytest11": ["my_plugin = my_plugin_module"]},
    ...
) Pytest Benefits and Limitations Testing is an essential aspect of software development, ensuring that your code is robust, reliable, and bug-free. Pytest has emerged as a popular choice among Python developers for its simplicity, flexibility, and powerful features. However, like any tool, it has its limitations. Pytest Benefits Pytest offers a simple and intuitive syntax, making it easy to write tests even for beginners. With its built-in test discovery, pytest automatically detects and runs tests, saving developers time and effort. Easy to use - Simple syntax, Easy to write tests, Automation of tests: Pytest provides a suite of powerful features like parameterized testing, fixtures, and advanced assertion capabilities that make it easier to write comprehensive and maintainable tests. Comprehensive features: Parameterized testing, Fixtures, Assertions: Pytest's plugin system enables developers to extend its functionality or integrate it with other tools, increasing its versatility. Extensibility: Plugins, Ability to extend functionality: Pytest's well-organized provides clear instructions and examples, making it easy for developers to learn and master the framework.  The Launchable integration for pytest is - this can be helpful as you’re getting started with pytest and Launchable. Comprehensive documentation: Easy-to-understand instructions and examples: documentation documented with code samples Pytest is cross-platform compatible, which means it can run on various operating systems like Windows, Linux, and MacOS, ensuring a smooth testing experience. Cross-platform compatibility: Runs on Windows, Linux, and MacOS: Pytest boasts a large and supportive community, which is invaluable when it comes to troubleshooting issues, sharing knowledge, and staying up-to-date with the latest developments. Community support: Access to a large, helpful community of users: Pytest Limitations Despite its numerous benefits, pytest also has some limitations that developers should consider: Pytest is designed with Python in mind, so it does not have extensive support for other languages. This can be a problem if you need to test code written in a language other than Python. Limited support for non-Python languages: Pytest can be difficult to debug when dealing with complex tests. This can be especially challenging if the test involves multiple components or requires a deep understanding of the code being tested. Difficult to debug complex tests: While pytest is great for unit testing, it may not be suitable for all projects. For example, if your project requires integration testing or end-to-end testing, then pytest may not be the best option. Not always suitable for all projects: The good news is that you don’t need to run hours of complex integration test suites if you use Launchable’s Predictive Test Selection. How Launchable and Pytest Work Together In today's fast-paced development environment, every minute counts. Lengthy test runs can hamper productivity, delay deployments, decay the developer experience, and increase costs. Fortunately, with the Launchable pytest integration, you can harness the power of predictive test selection to optimize your testing workflow, speed up your tests, and improve your developer experience. Launchable, the test intelligence platform, which tests are most likely to detect potential defects. uses machine learning to predict With Launchable’s pytest integration, you can prioritize running the most relevant tests, saving precious machine hours and providing faster feedback to developers. Adding Launchable to pytest allows developers and DevOps teams to: : By only running the most relevant tests, you can significantly cut down the time spent on test execution, enabling quicker iterations and faster deployments. Reduced test execution time : Launchable's intelligent test selection ensures that your computing resources are used efficiently, reducing the overall cost of testing and freeing up resources for other tasks. Optimized resource utilization By prioritizing the tests most likely to catch defects, you can detect and fix issues early in the development cycle, improving the overall quality and reliability of your codebase. Increased test suite reliability: Hands-On Tutorial for Pytest and Launchable To get started with the Launchable pytest plugin, it takes four simple steps. ✅ Install the Launchable Pytest Plugin Install the Launchable pytest plugin: pip3 install pytest-launchable ✅ Set your Launchable API Key Sign up for a Launchable account (if you haven't already) at and create your API key. Export your key as an environment variable in your CI script: https://app.launchableinc.com/signup/ export LAUNCHABLE_TOKEN=<your_launchable_api_key> Save this key somewhere safe - avoid leaving it in your source code for all to see. ✅ Record and submit test data to Launchable: Before Launchable can predict which tests to run, it needs historical test data. To record and submit test data, set up your launchable config. You can generate a Launchable config by running via pip: , or you can copy this example to a new file called : launchable-config --create .launchable.d/config.yml # Launchable test session configuration file
# See https://docs.launchableinc.com/resources/cli-reference for detailed usage of these options
#  
schema-version: 1.0
build-name: commit_hash
record-build:
  # Put your git repository location here
  source: .
  max_days: 30
record-session:
subset:
  # mode can be subset, subset-and-rest, or record-only
  mode: record-only
  # if mode is subset or subset-and-rest, you must specify one of target/confidence/time
  # examples:
  #   target: 30%  # Create a variable time-based subset of the given percentage. (0%-100%)
  #   confidence: 30%  # Create a confidence-based subset of the given percentage. (0%-100%)
  #   time: 30m  # Create a fixed time-based subset. Select the best set of tests that run within the given time bound. (e.g. 10m for 10 minutes, 2h30m for 2.5 hours, 1w3d for 7+3=10 days. )
  confidence: 99
record-tests:
  # The test results are placed here in JUnit XML format
  result_dir: launchable-test-result ✅ Enable Predictive Test Selection: Once you've submitted enough test data, you can start using Launchable's predictive test selection. All you need to do is update your file. Change the to , set an optimization target (one of , , or ), and save the file. This enables subsetting when you run . config.yml subset mode subset target time confidence pytest --launchable Easy peasy, lemon squeezy! Launchable will then select the most critical and relevant tests, optimizing your testing workflow and providing quicker feedback to your development team. For comprehensive documentation, see . pytest (Integration) | Launchable Docs Final Remarks on Pytest and Predictive Test Selection Integrating Launchable into your pytest testing workflow can lead to substantial time and resource savings, allowing you to accelerate the development cycle and deliver high-quality code more efficiently. By prioritizing the most relevant tests, you'll not only save machine hours but also enable your development team to receive faster feedback leading to quicker issue resolution and improved overall code quality. , Also published here.

Accelerate Your Pytest Performance for Enhanced Code Quality and Faster Feedback

Acelere el rendimiento de Pytest para obtener una calidad de código mejorada y comentarios más rápidos

Accélérez vos performances Pytest pour une qualité de code améliorée et des commentaires plus rapides

बढ़ी हुई कोड गुणवत्ता और तेज़ प्रतिक्रिया के लिए अपने पाइटेस्ट प्रदर्शन को गति दें

コード品質の向上とフィードバックの高速化のために Pytest のパフォーマンスを加速する

Acelere o desempenho do seu Pytest para qualidade de código aprimorada e feedback mais rápido

Tăng tốc hiệu suất Pytest của bạn để có chất lượng mã nâng cao và phản hồi nhanh hơn

加速您的 Pytest 性能以提高代码质量和更快的反馈

TL, DR 🤖 AGI, or artificial general intelligence, is the holy grail of AI research, but it faces many challenges such as fragmentation, lack of collaboration, and ethical issues. 💿 Blockchain can help overcome these challenges by providing a decentralised, transparent, and secure platform for AGI researchers to share data, code, and resources. 🪙Blockchain can also enable new models of innovation such as tokenization, incentivization, and governance for AGI projects, fostering a more diverse and collaborative ecosystem. 🤝Blockchain can also help address the ethical and social implications of AGI by ensuring accountability, traceability, and fairness in the development and deployment of AGI systems. ⚠️However, blockchain faces some challenges such as scalability, privacy, and interoperability 💡But startups such as Polygon, Solana, Filecoin, and more offer potential solutions : This article is for informational and educational purposes only and does not constitute financial advice. The author and the publisher are not responsible for any financial decisions or actions taken by the readers based on this article. Readers should do their own research and consult a professional financial advisor before making any investments or transactions involving cryptocurrencies or blockchain technology. ⚠️ Disclaimer 👋 gm fellas 🥳! today, we're going to talk about something that's been on everyone's mind - the next big breakthrough in artificial intelligence - and - the future of AI. But before we dive in, let's quickly review what AGI is all about. how blockchain technology can pave the way for Artificial General Intelligence or AGI 🏆 The Holy Grail of AI: What is AGI and Why Does it Matter? As we know, AI has come a long way, and we are witnessing some impressive advancements in the field in real-time. However, most AI systems are designed for specific tasks, such as image recognition or language translation. , on the other hand, is the anticipated holy grail of AI - . It would be a game-changer, revolutionizing the way we live, work, and interact with machines. AGI an AI system that can perform any intellectual task that a human can do, and potentially do it better AGI requires massive amounts of data to be trained effectively. However, , making it challenging for researchers to access the data they need. the current data-sharing landscape is often siloed, centralized, and fragmented Blockchain technology can solve this problem by . enabling secure, transparent, and decentralized data sharing and management With blockchain, researchers can access data from various sources and collaborate with others in a secure and transparent way. This would accelerate the pace of AGI development and allow researchers to train AI systems on more diverse and representative datasets, leading to more accurate and robust AGI models. Blockchain can also foster new methods of incentivizing and rewarding data providers and users, as well as powering decentralized autonomous organizations (DAOs) that can govern and coordinate data-related activities. In this article, we will explore some of the benefits and challenges of using blockchain for data sharing and management for AGI development, let’s start 😎👇 💿 Data Sharing: How Blockchain Can Break Down the Walls of Data Silos and Push AGI Development One of the main benefits of using blockchain for data sharing is that it can eliminate the need for intermediaries or trusted third parties that often control or limit access to data . Blockchain can provide a peer-to-peer network where data owners can share their data directly with researchers or other parties who need it, without compromising their privacy or ownership rights. Blockchain can also , which can enhance its quality and reliability. ensure that the data is immutable, verifiable, and traceable 🟢For example, is a decentralized data exchange protocol that aims to unlock the value of data for AI by connecting data providers and consumers through blockchain-based smart contracts. Ocean Protocol Data providers can publish their data assets on the protocol and set their own terms and conditions for access and usage. Data consumers can discover and purchase the data they need and use it for their AI models. Ocean Protocol also provides a token system that rewards data providers for sharing their data and data consumers for curating and rating the data. 🟢Another example is , a decentralized platform that aims to create a global network of AI agents that can collaborate and exchange services using AGI tokens. SingularityNET allows anyone to create, share, or monetize AI services at scale. Data providers can contribute their data to the platform and receive AGI tokens in return, which they can use to access other AI services or sell them for other cryptocurrencies or fiat money. SingularityNET also leverages blockchain to ensure that the AI agents are interoperable, transparent, and trustworthy. SingularityNET 🪙Token Rewards: Incentivizing Collaboration in AGI Development with Blockchain . Data providers can monetize their data by selling it to researchers or other parties who need it, or by receiving tokens or rewards for sharing it. Data users can also earn tokens or rewards for providing feedback, ratings, or reviews on the data they use, or for contributing to its improvement or enrichment. Blockchain can create a where data is treated as a valuable asset that can be exchanged for other goods or services token economy 🟢For example, is a decentralized marketplace that allows users to securely store, share, and sell their personal data on a blockchain-based platform. Users can control who can access their data and how much they want to charge for it. Users can also earn DAT tokens for sharing their data with trusted parties or for participating in surveys or other activities. Datum also provides a reputation system that rewards users for providing high-quality data and penalizes them for providing low-quality or fraudulent data. Datum 🟢Another example is , a decentralized network that uses blockchain and AI to connect autonomous agents that can perform various tasks such as data collection, analysis, processing, or delivery. Fetch.ai enables agents to cooperate with each other and with humans through smart contracts that define the terms and conditions of their interactions. Fetch.ai also uses a native token called FET that agents can use to pay for services or resources on the network or to receive rewards for providing them. Fetch.ai 🦾 From Skynet to Decentralized Autonomous Organizations: The Future of AGI Development with DAOs A third benefit of using blockchain for data sharing and management is that it can enable the creation of decentralised autonomous organisations (DAOs) that DAOs are self-organizing entities that operate according to predefined rules encoded in smart contracts on a blockchain. DAOs can have various goals and functions, such as managing a common pool of resources, facilitating collaboration among members, enforcing policies or standards, or distributing rewards or penalties. . can govern and coordinate data-related activities 🟢For example, is a project that aims to create a DAO that can manage and monetize data for AI applications. DataDAO allows data owners to pool their data together and share the benefits of its usage. DataDAO also allows data users to access the data they need and pay for it with tokens or other forms of value. DataDAO uses a governance system that allows its members to vote on important decisions, such as setting the price of data, allocating funds, or resolving disputes. DataDAO 🟢Another example is , a project that aims to create a DAO that can fund and support AI research and development. AI DAO allows anyone to propose, review, or fund AI projects that can benefit humanity. AI DAO also allows anyone to contribute their skills, resources, or data to the projects and receive rewards or recognition. AI DAO uses a governance system that allows its members to vote on the allocation of funds, the evaluation of projects, or the distribution of rewards. AI DAO 🏋️ Challenges: How Blockchain Can Overcome the Hurdles of Data Sharing and Management While blockchain can offer many benefits for data sharing and management for AGI development, it also faces some challenges that need to be addressed. Some of these challenges are: : Blockchain networks often have , which can affect the performance and efficiency of data sharing and processing. Moreover, storing large amounts of data on a blockchain can be costly and impractical. Therefore, blockchain solutions need to find ways to optimize their scalability and storage, such as using off-chain or side-chain techniques, sharding, or compression. 📈 Scalability limited throughput and high latency Some startups or companies that are working on blockchain scalability solutions include , which provides a framework for building and connecting scalable Ethereum-compatible networks; , which claims to be the fastest blockchain in the world with over 50,000 transactions per second; and , which leverages blockchain to create a decentralized marketplace for data storage and retrieval. Polygon Solana Filecoin : Blockchain networks often operate on a public or permissionless basis, which means that . This can pose privacy risks for data owners and users, especially when dealing with sensitive or personal data. Therefore, blockchain solutions need to find ways to protect the privacy and confidentiality of data, such as using encryption, anonymization, zero-knowledge proofs, or differential privacy. ⛔️ Privacy anyone can join and access the data on the network Some startups or companies that are working on blockchain privacy solutions include , which uses secure multi-party computation to enable private and scalable computation over encrypted data; , which uses zero-knowledge proofs to enable anonymous transactions on a public blockchain; and , which combines blockchain and confidential computing to enable privacy-preserving smart contracts and data markets. Enigma Zcash Oasis Labs : Blockchain networks often use different protocols, standards, or formats, which . This can limit the diversity and availability of data sources and services for AGI development. Therefore, blockchain solutions need to find ways to enhance their interoperability and compatibility, such as using common APIs, bridges, or wrappers. 🔁 Interoperability can make it difficult for them to communicate or exchange data with each other or with other systems Some startups or companies that are working on blockchain interoperability solutions include , which provides an ecosystem of interconnected blockchains that can exchange data and value; , which enables cross-chain communication and coordination among different blockchains; and , which provides decentralized oracle networks that connect blockchains with external data sources and systems. Cosmos Polkadot Chainlink ⏮️ To Recap Blockchain technology can revolutionize data sharing and management for AGI development by enabling secure, transparent, and decentralized data exchange and collaboration. Blockchain can also enable new ways of incentivizing and rewarding data providers and users, as well as creating decentralized autonomous organizations that can govern and coordinate data-related activities. However, blockchain also faces some challenges that need to be addressed, such as scalability, privacy, and interoperability. By overcoming these challenges and leveraging the synergies between blockchain and AI, we can unlock the full potential of data for AGI development and create a more intelligent and trustworthy data economy. 🔥If you've been reading this far, you are an absolute legend 😎 and I sincerely appreciate it 🫰. Consider leaving a like or a comment for more content like this. Follow me on twitter 🐣: @stephabauva See ya 👋

How Blockchain Can Unite and Accelerate the Quest for Artificial General Intelligence

Why Accelerators Are Vital for Web3 Startups Working on Complex Challenges in 2023 In 2023, Web3 startups face complex and evolving regulatory challenges that require specialized support, due to which accelerators have emerged as a vital component of this support system, providing startups with the necessary resources and support to bring their ideas to fruition. Further, according to a by Outlier Ventures, there has been a significant increase in the number of blockchain startups, with over 3,000 active startups in the ecosystem. The same report notes that the blockchain industry raised over $20 billion in funding in 2021, with significant growth in sectors such as decentralized finance (DeFi) and non-fungible tokens (NFTs). T report These programs offer funding, mentorship, networking, and marketing opportunities to startups committed to pursuing web3 implementations over a multi-year timeframe. Further, in a by the Global Accelerator Learning Initiative (GALI), startups that participated in accelerator programs reported a 63% increase in revenue compared to non-participating startups. survey Lisk Launches Accelerator Program for Startups Building Web3 Apps: A Game Changer for Web3 Innovation Recently, the open-source web3 platform Lisk launched an accelerator program to support startups building web3 solutions. This program addresses the lack of support for web3 implementation and provides funding, mentorship, networking, and marketing opportunities for startups committed to pursuing web3 implementations over a multi-year timeframe. With the Lisk Accelerator Program, startups can access the support they need to turn their ideas into reality, driving innovation within the web3 ecosystem. Lisk CEO Max Kordek said, "Web3 applications can disrupt many industries, from finance to healthcare to supply chain management. They can eliminate intermediaries and enable trustless interactions, reducing costs and increasing efficiency. We believe that entirely new business models can be created. The Lisk Accelerator is our way to find and support those." The major problem that startups face is the lack of support for web3 implementation. This is where Lisk’s accelerator program comes in, providing funding, mentorship, networking, and marketing opportunities for startups committed to pursuing web3 implementations over a multi-year timeframe. In my opinion, the Lisk Accelerator Program is a game-changer for web3 innovation, offering four funding stages: Bootstrap Grant, Builder Grant, Booster Grant, and Breakout Grant. These grants provide startups with the necessary funding to develop and turn their ideas into reality. The program will operate in two phases, with Phase 1 running from March 20 - June 30, 2023, and Phase 2 set to operate from September 1 - November 30, 2023. The initiative will disburse grant funding of up to 250,000 CHF ($270K) per project. Lisk’s Javascript SDK makes it easy for developers to create their own Lisk-compatible sidechains and web3 applications. Its accelerator program will incentivize the development of Lisk’s tech stack and support web3 innovation. About Lisk Lisk is an open-source web3 application platform designed for interoperability with sidechains. Its JavaScript SDK gives developers a straightforward path into launching their own Lisk-compatible blockchains, enabling them to build scalable web3 applications. Each application has its own blockchain, allowing for virtually infinite customization. Lisk is committed to promoting the growth of web3 innovation, and its accelerator program is a step towards realizing this goal. Don’t forget to like and share the story! Image credits: . DeepMind : Vested Interest Disclosure The author is an independent contributor publishing via our . Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR brand-as-author program

Lisk’s Accelerator Program a Game Changer for Web3 Innovation

El programa acelerador de Lisk cambia las reglas del juego para la innovación Web3

Le programme Accelerator de Lisk change la donne pour l'innovation Web3

लिस्क का एक्सीलरेटर प्रोग्राम वेब3 इनोवेशन के लिए गेम चेंजर है

Lisk のアクセラレータ プログラムは、Web3 イノベーションのゲーム チェンジャーです

O Programa Accelerator da Lisk é um divisor de águas para a inovação Web3

Chương trình tăng tốc của Lisk một công cụ thay đổi cuộc chơi cho đổi mới Web3

Lisk 的加速器计划改变了 Web3 创新的游戏规则

There are many approaches to business in 2023, but one thing all leaders agree on is that the future of digital transformation lies in “the great dig” – unearthing the goldmine of data lying just beneath the surface. The trouble is, there is so much data flowing through businesses that it can be hard to separate the wheat from the chaff. How does a business know when it has tapped the right vein of data ore, and more importantly, how can it gather and mobilize that data into actionable business intelligence? How Can Businesses Convert Valuable Data Into Actionable Business Intelligence? Increasingly, the obvious answer is a combination of artificial intelligence (AI) and machine learning (ML).  In other words, . AI models can be deployed to help businesses make predictions, take advantage of market opportunities, measure performance and innovation, and react optimally to external events beyond their control. data science In a recent report, posited that by 2025, AI-driven workflows and seamless interfacing between humans and machines will become standard. Put simply, data-driven decision-making is going to become a fundamental part of day-to-day operations, from menial tasks to broad-sweeping business decisions. McKinsey That’s all good and well, but the sheer volume of data combined with the intricacies of devising and deploying AI models makes this a little too good to be true. The amount of data businesses have access to has reached saturation point, and not all of that data is good or useful. When a business does “strike it rich” by tapping a nice supply of data, employing AI to turn that data into business insight can take weeks if not months, by which time any opportunity to put that data to good use has passed. The current process for setting up AI models to interpret data is long and complex, requiring input from data scientists, developers, analysts, and users. According to , once a use case for an AI model has been identified, it takes two-thirds of organizations more than a month to develop a useable model, and another whole month to deploy it. The amount of time and resources invested is wasted if the opportunities to apply learnings from that model have passed. What results is a revolving door of high-investment development and deployment with minimal gain. Algorithmia’s 2021 report Resource is key here. In order to implement AI modeling effectively, an organization will need advanced in-house knowledge of coding and machine learning, or at least a hefty budget to employ a third party.  Even then, the data efficiency bottleneck remains. Once an expensive team of experts has been assembled, they’ll need time to work on developing a usable model, and once that model is outdated, more time again. So how do businesses get ahead of the curve and speed up the excavation and refinement of their data? The Answer Lies in Generative AI and Natural Language Processing (NLP) can be used to create predictive models based on large datasets. For example, an NLP language model could be trained on customer reviews to predict which products are likely to receive positive or negative feedback. It can also be used to train predictive models in real-time, which is particularly useful when there is limited historical data available, or when new and unexpected events occur that are not accounted for in existing data. A business that sells products online may use generative AI to create new variations of product images that can be used to train models to recognize and classify products more accurately. Or a business that analyzes customer behavior may use generative AI to create new customer profiles that can be used to train a machine learning model to predict customer preferences and behaviors more accurately. Generative AI can also be used to simulate different scenarios and outcomes, allowing businesses to explore the potential impact of different decisions before they’re made. This can help businesses to make more informed decisions, as well as identify potential risks and opportunities. Generative AI The real trick is being able to apply generative AI and NPL model training into databases seamlessly. This is the hump many businesses fail to get over, or if they do get over it, it’s expensive, resource-intensive, and too time-consuming, not to mention the sheer level of expertise required to make it happen. This technology needs to be democratized to the point where virtually all users, with a little bit of training, can use it. There are solutions out there that do just that, allowing users to bring state-of-the-art natural language processing and generative AI models into their databases with just a few lines of basic SQL. What results is a form of real-time in-database machine learning. Instead of AI models existing on the periphery, separate from a business database, the model becomes one with the database and provides real-time insights into datasets that can be actioned in a matter of hours and days instead of weeks and months. If the hunt for high-value data is “the great dig”, then the democratization of generative AI and NPL are the shovels that will help businesses unearth it. Lead image generated with stable diffusion. Prompt: Illustrate a gold mine.

Accelerating Excavation and Refinement of Data Gold Mines

Launching a B2B department is a turning point for many B2C tech companies. However, such an expansion brings many strategic misperceptions and challenges. The first and foremost rule to succeed is to , even if you aren’t introducing a new product. treat the creation of a B2B department like a startup The difference between B2B and B2C approaches is quite evident regarding sales. In terms of strategy, many companies that launch a B2B department after years of successful B2C performance still fall into the trap of extrapolating the previous experience. And this may become the biggest obstacle to a good start. I will share the five tips for a successful B2B launch and fallacies to avoid at each stage. I defined these principles during the B2B department launch at Headway, a Ukrainian EdTech startup, in March 2022. Owing to this startup-inspired strategy, we managed to boost revenue growth x7 despite the low summer season and the war. The B2B launch needs unique answers to , and . These may dramatically influence the existing product, its positioning, and the overall roadmap of the market entry. You may assume that you’ve refined your product and dive deep into all the past findings to lay the foundation for future B2B growth. 1. Ideating: inspect your product first, don’t skip the problem/solution stage what, why, to whom how What you should do, however, is ignore almost all the B2C learnings. This first stage is an essential prerequisite to market research. To find the right product-market fit, the primary subject of your investigation should not be the market but your product through the eyes of the audience. We talked with 100+ companies from different markets and niches. During personal interviews, we had two primary focuses: what problems potential customers were having and what modification of the product would make the biggest positive impact in that field. In two months, we developed a dashboard with the ICPs and product features clients needed, which helped us identify crucial pre-launch changes, prioritize the next steps of product development, and create a proper basis for further market research. What we did: 2. Concepting: prioritize areas for market research by snooping on your competitors Market research is an obvious prerequisite to entering a new niche and tailoring value propositions. However, how to approach the research and deal with the findings are the critical steps where many fail. Challenges arise when you create the framework for the research. Consider that you compete with businesses from many other niches except your own, your core geographies vary from the B2C scene, and the B2B performance is not limited to product sales, as you may also rely on partnerships for revenue. The research approach is critical because your final users and stakeholders have different pain points. Also, product positioning may differ but not contrast with the one you have for B2C. We keep abreast of Crunchbase and Dealroom to check updates from our business environment, reconsider value propositions and formulate hypotheses for subsequent outbound campaign testing. Some of their cases may help you skip your own long-running tests. Having a broad picture is critical: we keep abreast not only of education apps but all products that boost employee wellbeing and growth, from sports to time management and awareness. What we do: The landscape for investigations may seem limitless. But don’t let your strive to stand out from competitors keep you away from the valuable insights they already have. 3. Commitment: don’t mess with people and processes In many cases, B2B brings the need to switch to a sales-led or hybrid approach to growth in contrast to product-based, which is typical for B2C software. Thus, the B2B performance largely depends on the right team and accurately chosen key roles. For two reasons, many businesses need to pay more attention to processes at this stage: roles can get blurred due to a lack of human resources, and the final agenda may dramatically differ from what it is expected to be afterward. Workflow clarity is crucial during the B2B launch, as the share of outbound leads is predominant, and the closing deal period usually spans three to four months. From the onset, we clarified responsibilities, synchronizing roles with core sales funnel stages. Our key processes include: market and ICP updates, database management and contact validation, outbound sequences and funnel distribution development, marketing activities to increase the inbound leads to share, hot leads processing, and customer success management. Proper task decomposition, alignment, and automation helped our small team of six members close deals for five clients each month, send up to 800 e-mails per sequence, and maintain consistent communication. What we did: A solution that worked for Headway's sales team was adding a Sales Development Representative to search and qualify leads, make the first touch, and then pass the baton to a Sales Manager. 4. Validation: identify common denominators for your core goals Validation is the MVP-testing stage for most startups, and To maximize benefits from dozens of simultaneous tests running during launch, create separate dashboards for each business stage and link to a common denominator of the strategic goal. Those early tests may provide you with growth options for years ahead. even if your product has been up and running for years, you shouldn’t frame yourself. It's all about balancing product modification with its marketing strategy and coordinating those efforts. For Headway, we gathered insights on how to market the current version of the app and what updates to implement into the software, eventually expanding the product's marketing potential on the B2B scene. For example, after one month of consistent work, we realized that depending on the size of the company we are targeting, our buying persona is not only a learning and development specialist but also a CEO/COO in smaller businesses. Then we expanded our focus to heads of departments. Our idea is that even a small team using the product may eventually result in further expansion at the company level. What we did: This modified approach increased our open rate from 65% to 87% and the reply rate from 12% to 35%, which eventually resulted in +600% revenue growth. 5. Scaling: know your focus, but be omni There are countless scaling options to test, and all vary in one way or another. But focus is crucial to avoid wrong conclusions when your sample is relatively small.  We concentrated our initial efforts on content marketing and expanding the variety of communication channels. Due to the longer sales cycle and specifics of fact-based decision-making, longer-form content and business use cases take center stage. This issue may be an obstacle when resources are limited, so an omnichannel approach is useful. In B2B sales, the performance of various channels is less predictable, so you need to test all the platforms and processes consistently. What we did: As an EdTech startup, we identified the gap in understanding the benefits of corporate learning and started creating content to educate potential customers on the topic. We filled our blog with practical advice on team management: building a solid corporate culture, boosting employee productivity, and negotiating skills. Those articles were also an important component of our performance marketing campaigns, affiliate publications, and SMM strategy because they all add to the core goal of cultivating interest in the product by providing customers with practical value. Additionally, we expanded our use scope by integrating into major learning and management systems. Omnichannel content strategy creates a seamless experience for clients, strengthening each channel and breaking the content-creation limits. Approach your B2B department launch like a new startup to accelerate your progress. Using most of your B2C experience as a base may only lead you to the wrong hypotheses that will ultimately fail. Research and testing will consume most of your resources at the initial stages. You will need to find product-market fit, develop ICP, investigate the new niche, define core processes, sales funnel stages, and roles, and start from scratch with marketing and brand development. For a quick start, both flexibility and focus are crucial. Make a lot of tests, align short-term goals with long-term, and be bold and quick when switching from non-working tools to those that maximize your revenue.

Approach Your B2B Sales Launch Like Another Startup: 5 Tips to Accelerate Growth

Blockchain technology has disrupted several significant industries like Banking, Cybersecurity, Healthcare, Supply Chain Management, etc. As many as 65 big industries have either adopted blockchain or plan to adopt it in the near future. However, widespread adoption of the technology remains a challenge. The biggest challenge facing emerging blockchain solutions is scalability, which hinders the widespread adoption of enterprise blockchain. The reason behind limited scalability is the Blockchain Trilemma. What Is The Blockchain Trilemma? Enterprise blockchain solutions have three goals: scalability, security, and decentralization. However, to increase scalability, enterprise blockchain solutions must compromise on decentralization and security. The confusion over which of the three goals to prioritize during the deployment of a protocol is known as the Blockchain Trilemma. While Layer 2 solutions help protocols tackle the challenge to some extent, the need for more effective and innovative solutions is always there. This is where Masternodes emerge as a viable solution. What Are Masternodes in Blockchain? One must understand the role of nodes in a blockchain network to understand the concept of Masternodes. A node is the smallest fundamental unit in a blockchain network. Also known as the custodian of the blockchain network, a node refers to a computer in the network that adds a new block to the network, validates transactions, and keeps a copy of the ledger to keep the network secure. Unlike regular nodes, Masternodes do not add new blocks to the network. They validate new blocks and perform special governance roles. It means that Masternode operators must hold a certain amount of cryptocurrencies to set up a Masternode. But why would someone purchase cryptocurrencies and set up a Masternode to power a network? Because Masternode operators are rewarded with guaranteed crypto earnings (usually a fixed percentage of their stake at regular intervals). It is a win-win situation for both parties. The network gets added security, whereas the node operators get a steady passive income. Accelerating Enterprise Blockchain Adoption Through Masternodes As mentioned earlier, crypto protocols face substantial challenges in increasing scalability as it affects the security as well as decentralization of the network. Masternodes create a digital twin of the data that passes through the ledger, enhancing the network's security. With a digital backup of critical data, enterprise blockchain solutions can guarantee complete data security for their clients. Also, Masternodes help crypto protocols enhance decentralization by adding more voices to the decision-making or governance process. Expanding a network is costly. Adding Masternodes to the network reduces the cost burden as it is the validators who set up the node using their computer and energy resources. With a guaranteed passive income, there are enough takers of this give-and-take arrangement. Clearly, Masternodes appear as a viable solution to the Blockchain Trilemma, one of the biggest challenges in the widespread adoption of enterprise blockchain. With that hurdle out of the way, the adoption of enterprise blockchain solutions is bound to skyrocket. Benefits of Masternodes in Blockchain: Masternodes help blockchain solutions establish a network of servers to make the implementation of the decentralized distributed ledger easier. One of the biggest selling points of the blockchain ledger is its immutability. Masternodes provide better outputs, making the platform immutable, per se. Masternodes also enable instantaneous transactions, enhancing the performance of a blockchain network substantially. Enhanced security, Secure Transactions, and Instantaneous Transactions are the three key benefits of Masternodes from the output perspective. While the functions of Masternodes may vary from crypto to crypto, here are some of the most common functions: : Masternodes serve one of the primary purposes of blockchain - decentralization. The validator nodes in a Masternode get voting rights. This enhances the decentralization in the blockchain network. Having a say in critical decisions ensures that node operators remain committed to the security and performance of the network. Decentralized Governance : When you add Masternode validators to an existing network, the capacity of a blockchain network increases manifold. Consequently, the network can verify transactions at a lightning-fast speed. Remember the scalability challenge? This is how Masternodes help blockchain solutions tackle that challenge. Lightning Fast Transactions : A blockchain network needs to be up and running 24/7. In order to have such a performance, quick detection and resolution of issues are critical. Masternode operators are the first ones to know if something goes wrong with the blockchain network. As a result, they can respond quickly to ensure that the network remains functional. Increased Preparedness : We have another of the Blockchain Trilemma issue addressed through Masternodes. The instances of attacks and breaches on blockchain networks have been rising exponentially over the past few years. Masternodes add to the security of the network by acting as a force multiplier against hacks and breaches. Increased Security : Another primary principle of a blockchain network is to ensure secure storage and transfer of data. In the form of Masternodes, a blockchain network gets dedicated high-speed servers. Masternodes remain synchronized to serve as a reliable source of information for every participant on the network. Data Security Blockchain solutions have a lot to gain from setting up Masternodes. However, encouraging more users to set up validator nodes is a task. Masternode validators need to fulfil specific requirements. These requirements generally include the following: Having a certain amount of tokens as collateral Having a computer or a VPS that remains online 24/7 to run the node Having a full copy of the blockchain Conclusion Many Layer 1 blockchain solutions are setting up Masternodes as they are unable to scale. Major cryptocurrencies like Bitcoin and Ethereum have struggled to increase the TPS (number of transactions per second) since they are Layer 1 blockchains. Developers have been working tirelessly to find scalable solutions. When something as simple as users putting their cryptocurrencies as collateral can solve the problem, the importance of Masternodes increases substantially. Some of the most popular cryptocurrencies, like Dash, ChainLink, and Stratis, have embraced the concept of Masternodes. Going forward, many more Layer 1 networks can follow suit to boost the TPS. Scalability is critical to the mass adoption of enterprise blockchain solutions, and Masternodes can play the catalyst in that adoption.

Masternodes Can Help Accelerate Enterprise Blockchain Adoption — Here's Why

THE NEW ACCELERATOR

This is by (source: ). Kahn is a self-proclaimed “marketing and psychology nerd” Twitter Thread Zain Kahn @heykahn 08-09-2022 Hard skills help you get a job. But meta-skills help you build a career. 11 meta-skills to accelerate your career: 1. Decision-making: • Take a step back when faced with a big decision. • Identify the key emotions and biases affecting the decision. • Create a list of all the available options. • Understand the short and long term consequences of each option. • Decide accordingly. 2. Communication: • Listen without interrupting. • Speak with a positive tone. • Pay attention to your body language. 3. Prioritizing: • Create a list of everything you have to do. • Rank things by urgency and importance. • Do things that are urgent and important. • Delegate, schedule, or delete everything that isn't urgent and important. Self awareness: • Be curious about how your mind works. • Pay attention to your thoughts and feelings. • Identify which situations or events trigger certain reactions. 5. Time management: • Learn to prioritize. • Learn to delegate. • Learn to say no. 6. Creativity: • Experiment with new routines. • Try different solutions to existing problems. • Try the opposite of what people are currently doing. • Try as many new ideas as quickly as possible to increase your odds of finding a new insight. 7. Storytelling: • Identify what problem people are trying to solve. • Show them how you will help them solve the problem. • Identify the right emotions that will help your audience go from understanding their problem to accepting you as the solution. 8. Resilience: • Do more things your are not qualified to do. • Reframe every failure as a learning opportunity. • Keep repeating this till you convert failure into success. 9. Emotional intelligence: • Never act impulsively. • Take a step back when you're upset. • Understand what you're feeling. • Act accordingly. 10. Connecting the dots: • Go deep into a subject or fields of interest. • Then explore other fields similar to yours. • Read widely and talk to people in these new fields. • Zoom out and identify recurring patterns of success across these fields to connect the dots. 11. Grit: • Pick a long term goal. • Practice it everyday. • Identify ways you can maintain your motivation when the going gets tough and you hit a block. Thanks for reading! If you found this helpful, follow me at to get more threads like this. @heykahn Feature image generated via Prompt of ‘Use These 11 Meta-Skills to Accelerate Your Career’ HackerNoon Stable Diffusion

Use These 11 Meta-Skills to Accelerate Your Career

Many software businesses focus on maximizing velocity and quickly getting new features to the market. But, the "move fast and break things" mentality can quickly lead to costly quality control issues. A better approach involves monitoring applications for error in real-time to strike the right balance between quality and velocity. Let's examine why error tracking matters and how Bugsnag can help you save time and accelerate development. Real-time error monitoring solutions can help you strike the right balance between quality and development velocity. What is Error Tracking? Error tracking involves proactively identifying and fixing an application's issues as quickly as possible. While these processes may have been straightforward a decade ago, increasingly complex applications and infrastructures have complicated the process. As a result, many teams use dedicated error-tracking software to ensure complete coverage. At the same time, the user experience has become essential for success as the software landscape becomes more competitive. Errors that negatively impact the user experience or cause unplanned downtime can lead to lost revenue and brand equity among customers. In fact, website conversion rates drop an with each second of load time. average of 4.42% Error-tracking software can help mitigate these problems and ensure an optimal user experience. By monitoring server requests and responses, these applications can flag, document, and categorize errors, making it easy for development teams to assign and fix bugs quickly. That way, companies can confidently deploy changes and save time. Error Tracking Strategies & Metrics Most organizations appreciate the need for error tracking, but without a plan, these efforts aren't as effective as they could be. For example, development teams may install error-tracking software and see a lot of errors. Without a way to prioritize them, teams may spend time fixing low-impact errors or experience notification fatigue and tune them out. Successful error-tracking processes typically include: – Error tracking software should record errors and make them accessible for development teams to fix. By grouping errors, you can also understand what underlying code may be most problematic. Ideally, these capabilities interface with development tools, making it easy to create and address new issues during a sprint. Detection – Development teams must prioritize errors based on their severity – not just the number of users impacted. For instance, an error processing payment may only affect a handful of users but could significantly impact revenue. Other errors, such as bots spamming applications with nonsense form data, may not matter. Prioritization – Alerts should route errors to the correct teams rather than broadcasting them to everyone. Every developer should have an “error inbox” with bugs worth fixing and actionable background information. That way, developers understand what they need to do without succumbing to the effects of notification fatigue. Intelligent Alerts In addition to creating these processes, organizations should develop key performance indicators (KPIs) to measure success and ensure quality. For example, they might track the error rate (e.g.,the rate of errors to requests) to assess the quality or the mean time to close errors (e.g., the time from error notification to fix) to evaluate efficiency. But, at the same time, it’s a good idea to have a single north star metric. For example, you might use a stability score that reflects the number of unhandled errors versus total requests. You can use these metrics to determine when to focus on bugs versus new features and when a new or canary release is ready for deployment. Best Practices with Bugsnag is a robust platform that can help your organization track and fix errors quickly and efficiently. In particular, the platform can help you quickly set up error tracking and stability monitoring, automatically prioritize errors, efficiently route alerts to individual developers or teams, and trace errors through the application technology stack. Bugsnag Identify & Prioritize Errors Bugsnag makes it easy to pinpoint errors with the most significant impact using powerful search and segmentation. For example, you can bookmark different error segments, such as errors in a shopping cart or errors in the latest release. You can also segment errors by user spending, service level agreements, or subscription tiers to focus on what matters most. Creating Intelligent Alerts Bugsnag makes it easy to customize alerts based on specific segments and route them to specific teams or developers. You can easily drive code ownership and accelerate DevOps workflows around incident investigation and resolution through integrations with team chat, issue trackers, and incident management tools. Effectively Group & Trace Errors Bugsnag makes it easy to debut web, mobile, and server-side applications with a complete stack trace for every crash and breadcrumbs to help developers understand what happened. In addition, the platform automatically groups errors based on their root cause, making it easier to focus on the most problematic code. Balance Bugs with Features Bugsnag's Stability Scores enable organizations to understand their application health at a glance. When a release experiences more unhandled errors than the target, the Stability Score falls into yellow or red territory, telling developers it's time to take action. When the StabilityScore is green, the team can confidently focus on building new features. In addition to these capabilities, Bugsnag integrates with all of the most common development tools, ranging from GitHub to GitLab to Jira. Enterprises can also opt to install an on-premise version of the software to maintain tight control over sensitive data while still reaping the benefits of real-time error tracking and remediation tools. The Bottom Line Error tracking is essential to ensure a robust user experience. Fortunately, Bugsnag makes it easy to monitor applications across the technology stack easy and intelligently route errors to developers. Just as important is the platform's Stability Scores help organizations balance the need to build new features with the need to maintain quality. As a result, organizations can maximize their development velocity while ensuring an optimal user experience. Also published here. or ! Start your free trial request a demo today

How Error Tracking Saves Time and Accelerates Development 

Twitter v. Elon Musk Court Filing by Potter Anderson & Corroon LLP, July 12, 2022 is part of . You can jump to any part in this filing . This is part 2 of 31. HackerNoon’s Legal PDF Series here THE PARTIES 12. Plaintiff Twitter, Inc. is a Delaware corporation headquartered in San Francisco, California that owns and operates a global platform for real-time self-expression and conversation. 13. Defendant Elon R. Musk is a sophisticated entrepreneur who owns approximately 9.6% of Twitter’s stock. He is the CEO of Tesla and leads SpaceX, among other entities he founded or co-founded. Musk is referred to in the merger agreement as Equity Investor, and is the President, Secretary, Treasurer, and sole shareholder of both Parent and Acquisition Sub. Musk signed the merger agreement on behalf of both Parent and Acquisition Sub, and agreed to be a party to the agreement in his individual capacity as Equity Investor with respect to several “Specified Provisions.” Ex. 1, Preamble. 14. Defendant X Holdings I, Inc., or Parent, is a Delaware corporation formed on April 19, 2022 solely for the purpose of engaging in, and arranging financing for, the transactions contemplated by the merger agreement. 15. Defendant X Holdings II, Inc., or Acquisition Sub, is a Delaware corporation and a wholly owned subsidiary of Parent. Acquisition Sub was formed on April 19, 2022 solely for the purpose of engaging in, and arranging financing for, the transactions contemplated by the merger agreement. Continue reading here

'Buying Twitter is an accelerant to creating X, the everything app', says Elon Musk

"Comprar Twitter es un acelerador para crear X, la aplicación de todo", dice Elon Musk

"L'achat de Twitter est un accélérateur pour créer X, l'application de tout", déclare Elon Musk

एलोन मस्क कहते हैं, 'ट्विटर खरीदना एक्स, द एवरीथिंग ऐप बनाने का एक त्वरक है'

「Twitterを購入することは、すべてのアプリであるXを作成するための促進剤です」とイーロン・マスクは言います

'Comprar o Twitter é um acelerador para criar o X, o aplicativo de tudo', diz Elon Musk

'Mua Twitter là một công cụ tăng tốc để tạo ra X, ứng dụng mọi thứ', Elon Musk nói

埃隆·马斯克说：“购买 Twitter 是创造 X 的催化剂，它是万能的应用程序”

Worlds Within Worlds: The Story of Nuclear Energy, Volume 2 (of 3), by Isaac Asimov is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here . Volume II, THE STRUCTURE OF THE NUCLEUS: Particle Accelerators Particle Accelerators Was there nothing that could be done to make nuclear bombardment more efficient and increase the chance of obtaining useful energy out of nuclear reactions? In 1928 the Russian-American physicist George Gamow (1904-1968) suggested that protons might be used as bombarding agents in place of alpha particles. Protons were only one-fourth as massive as alpha particles and the collision might be correspondingly less effective; on the other hand, protons had only half the positive charge of alpha particles and would not be as strongly repelled by the nuclei. Then, too, protons were much more easily available than alpha particles. To get a supply of protons one only had to ionize the very common hydrogen atoms, i.e., get rid of the single electron of the hydrogen atom, and a single proton is left. Artificial radioactivity. 88 Of course, protons obtained by the ionization of hydrogen atoms have very little energy, but could energy be imparted to them? Protons carry a positive charge and a force can therefore be exerted upon them by an electric or magnetic field. In a device that makes use of such fields, protons can be accelerated (made to go faster and faster), and thus gain more and more energy. In the end, if enough energy is gained, the proton could do more damage than the alpha particle, despite the former’s smaller mass. Combine that with the smaller repulsion involved and the greater ease of obtaining protons—and the weight of convenience and usefulness would swing far in the direction of the proton. Physicists began to try to design “particle accelerators” and the first practical device of this sort was produced in 1929 by the two British physicists John Douglas Cockcroft (1897-1967) and Ernest Thomas Sinton Walton (1903- ). Their device, called an “electrostatic accelerator”, produced protons that were sufficiently energetic to initiate nuclear reactions. In 1931 they used their accelerated protons to disrupt the nucleus of lithium-7. It was the first nuclear reaction to be brought about by man-made bombarding particles. Other types of particle accelerators were also being developed at this time. The most famous was the one built in 1930 by the American physicist Ernest Orlando Lawrence (1901-1958). In this device a magnet was used to make the protons move in gradually expanding circles, gaining energy with each lap until they finally moved out beyond the influence of the magnet and then hurtled out of the instrument in a straight line at maximum energy. This instrument was called a “cyclotron”. Inventors of one of the first accelerators, Ernest T. S. Walton, left, and John D. Cockcroft, right, with Lord Ernest Rutherford at Cambridge University in the early 1930s The bombardment of lithium-7 with protons was the first nuclear reaction caused by man-made particles. 90 The cyclotron was rapidly improved, using larger magnets and increasingly sophisticated design. There are now, at this time of writing, “proton synchrotrons” (descendants of that first cyclotron) that produce particles with over a million times the energy of those produced by Lawrence’s first cyclotron. Of course, the first cyclotron was only a quarter of a meter wide, while the largest today has a diameter of some 2000 meters. As particle accelerators grew larger, more efficient, and more powerful, they became ever more useful in studying the structure of the nucleus and the nature of the subatomic particles themselves. They did not serve, however, to bring the dream of useful nuclear energy any closer. Though they brought about the liberation of vastly more nuclear energy than Rutherford’s initial bombardments could, they also consumed a great deal more energy in the process. It is not surprising that Rutherford, the pioneer in nuclear bombardment, was pessimistic. To the end of his days (he died in 1937) he maintained that it would be forever impossible to tap the energy of the nucleus for use by man. Hopes that “nuclear power” might some day run the world’s industries were, in his view, an idle dream. Ernest O. Lawrence holds a model of the first cyclotron in 1930, a year after its conception. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Isaac Asimov. 2015. Worlds Within Worlds: The Story of Nuclear Energy, Volume 2 (of 3). Urbana, Illinois: Project Gutenberg. Retrieved May 2022 from https://www.gutenberg.org/files/49820/49820-h/49820-h.htm#c22 This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

The Story of Nuclear Energy, Volume 2 of 3: Particle Accelerators

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🪐 has got you covered with fresh content from our top 5 stories of the day, every day at noon your local time! Set email preference . What's happening in tech this week: The Noonification by HackerNoon here It is Some Horrible Inhabitant of Space, Something Unknown to us on Earth By [ 32 Min read ]
They were moving sluggishly along the red light, seeming to flow rather than crawl. @astoundingstories Read More. Accelerating Android Application Development With the ADB Idea Plugin By [ 2 Min read ]
In this article, I want to tell you about a useful plugin ADB Idea. I use it every day, but I noticed that others use it in their work quite rarely. 🧑‍💻 What happened in your world this week?It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.See you on Planet Internet! With love,
The Hacker Noon Team ✌️ @leonidivankin Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The Noonification: Accelerating Android Application Development With the ADB Idea Plugin (10/12/2022)

In this article, I want to tell you about a useful plugin ADB Idea. I use it every day, but I noticed that others use it in their work quite rarely. Working With ADB Idea The plugin is off by default. After adding it, the toolbars will appear: All this plugin does is replace the standard ADB commands. For example, the is analogous to the terminal command. The advantage of ADB Idea is that the most frequently used commands are placed in the toolbar and you don't have to remember them all the time. ADB Kill App ADB shell am kill Start the app. Click on the command, and verify that the application has closed and disappeared from the recently used stack. ADB Kill App You can optimize even more. Since the commands are present in the panel, you can assign keyboard shortcuts to them, just like any other, which will also speed up development. Let's go into the Keymap settings: In the search box, type ADB and you will see the necessary commands. Find the previously described and assign a key combination to it, such as . Click OK. Close the menu, launch the app, and press . We will make sure that the application is closed. ADB Kill App Option+K Option+K Creating an ADB quick list There are quite a lot of useful adb commands. So, we run the risk of cramming all the key combinations. The way out of this is to create a quick list. Let's go to Preferences > Appearance & Behavior > Quick Lists: Create a new Quick List (point 1). Give it a name (point 2). Fill it with the commands we need (point 3). Go to Keymap, find Quick Lists, and then the adb we created and assign a key combination to it. In my case, it's . Let's press OK: Launch the application again and press and fast 4. Make sure that the application is closed. Option+F2 Option+F2 You can read more about the plugin here: https://plugins.jetbrains.com/plugin/7380-adb-idea https://github.com/pbreault/adb-idea Conclusion As you can see, a small ADB Idea plugin can speed up development considerably. You don't need to type long commands in the terminal and memorize them. You can set keyboard shortcuts on the commands and enter them into the . In my experience, there are a few disadvantages to ADB Idea: Quick list When updating the Android Studio, the plugin does not always have time to quickly update and is sometimes no longer compatible. Sometimes the plugin stops attaching to the application process. There is no possibility of creating custom more complex commands.
However, despite all these disadvantages, ADB Idea still greatly speeds up application development.

Accelerating Android Application Development With the ADB Idea Plugin

Acelerar el desarrollo de aplicaciones de Android con el complemento ADB Idea

Accélérer le développement d'applications Android avec le plugin ADB Idea

एडीबी आइडिया प्लगइन के साथ एंड्रॉइड एप्लिकेशन डेवलपमेंट को तेज करना

ADB Idea プラグインで Android アプリケーション開発を加速

Acelerando o desenvolvimento de aplicativos Android com o plug-in ADB Idea

Tăng tốc phát triển ứng dụng Android với plugin ADB Idea

使用 ADB Idea 插件加速 Android 应用程序开发

TL;DR: Ingonyama has  open-sourced new way to accelerate Zero Knowledge Using FPGA. In AWS cloud. Easy. Accessible. Cheap. Link to Github Zero Knowledge (ZK) technology is a fundamental building block for decentralized computing. Its two main applications are privacy-preserving computation and verifiable computation. For specific types of ZK such as SNARK and STARK-based systems, additional properties include public verifiability, smaller proof sizes, and fast verification, making these kinds of ZK perfect for use in blockchains for and purposes. scalability privacy At present, ZK tech is being developed and used by leading blockchains (e.g. Filecoin, Aleo), L2s (e.g. Starknet, zkSync) and decentralized applications (e.g. Dark Forest, ZKAttestor). Unfortunately, nothing great ever comes easily. The Prover, responsible for generating the proof, must run a computationally intensive algorithm with significant data blowup during the computation. suggest a factor of up to 10 million in prover overhead while producing the proof, compared to directly running the computation. Recent estimates Today, prover overhead is considered the main computational bottleneck for applied ZK. Without exception, every project built on ZK technology is facing or will face this bottleneck, which manifests adversely in either latency, throughput, memory, power consumption, or cost. A unique property of Zero Knowledge computation is that it runs modular arithmetic under the hood, on enormous field sizes. This requirement and its trials on CPUs lead to the conclusion that modern CPU architecture is simply not built to handle this form of computation efficiently. As a result, the need for specialized hardware ZK prover acceleration is clear. ZK Acceleration on FPGAs Until now, the majority of hardware experimentation for accelerating ZK has been done with GPUs. In Ingonyama's recent paper, , we explored bringing functioning and operational ZK for the first time to FPGAs. We believe this to be a superior approach for accelerating ZK computation on the path to developing Zero Knowledge for Application Specific Integrated Circuits (ASICs). PipeMSM It is our belief that the energy efficiency in FPGAs is more suitable for ZK due to their function-specific design compared with GPU’s narrower flexibility. With FPGAs at the base, we take a holistic approach to ZK optimization with designs based on a novel algorithmic approach and hardware-specific optimizations. In the paper, we use the Parallel Bucket Method and low latency Complete Elliptic Curve addition formulae along with to produce MSMs, a major bottleneck for many ZK provers, with improved energy efficiency and speeds comparative to GPUs. Domb-Barret Reduction We implemented and tested our design on FPGA, and highlight the promise of optimized hardware over state-of-the-art GPU-based MSM solvers, in terms of both speed and energy expenditure. Using MSM accelerator in the cloud we can achieve significant ZK acceleration. A disadvantage of FPGAs compared to GPUs is their lack of accessibility, while GPUs have effectively become commodity hardware. This means there is a high barrier for ZK users simply getting an FPGA into their hands. One promising approach to overcoming this barrier is by utilizing cloud computing. Similar to the way cloud providers have enabled easy and immediate access to massive data center resources which has lowered the high barrier to entry for small companies, clouds offering FPGA resources such as AWS, Alibaba Cloud and others have made FPGAs more accessible with the same kind of “on-tap” accessibility. This is a GAME-CHANGER in the world of hardware acceleration. Introducing Cloud-ZK With the Ingonyama has made open source, the benefits of ZK hardware acceleration on FPGAs are accessible to anyone, anywhere, anytime and with costs comparable to any other standard CPU instance on an hourly basis. Cloud-ZK toolkit As part of the initial release we have included: 1. An example AFI for BLS12–377 Multiscalar Multiplication (MSM) on instance. AWS EC2 F1 2. A Rust library for developers to run variable-size MSM in their code, accelerated in the cloud. Use Ingonyama FPGA-accelerated MSM of any size 3. A Rust implementation for AWS XDMA Driver, to transfer data between AWS FPGA and host CPU 4. Benchmarks and tests using arkworks for reference 5. A developer guide for creating your own Amazon FPGA Images (AFIs) Our FPGA code achieves 4x the baseline of FPGA MSM competition, where max prize criteria is 2x :) Zprize As an example application, Ingonyama's AWS F1 instance can be used to accelerate Aleo prover. In terms of proofs per second, the accelerator can generate up to ~5x proofs per second compared to running on CPU alone. In the future, we plan to improve the toolkit in the following ways: 1. Improving the MSM accelerator core: power consumption, speed, functionality (more curves) 2. Adding NTT accelerator AFI 3. Supporting Ali Cloud and other FPGA based instances Follow the Journey on Twitter: https://twitter.com/Ingo_zk Github: https://github.com/ingonyama-zk https://medium.com/@ingonyama/ Blog: Join the team: https://www.ingonyama.com/careers

Using Cloud-ZK for Developing ZKP Acceleration in the Cloud

Participating in startup accelerators is one of the best ways to grow and scale up your startup. Accelerator programs are specially designed for founders and teams looking to refine their strategy, receive qualified mentorship, raise funding – and much more. Top reasons to join startup accelerators include: ➕  Access to exclusive coaching from experienced mentors, successful startup founders, and industry leaders ➕  Joining a network of other fellow startup founders, senior executives, investors, and even government authority representatives ➕  Opportunities to find clients and institutions for pilot projects and sales ➕  Polish and get feedback on presentations, pitches, press releases, and other materials that are important for your fundraising and sales activities ➕  Get funding – from small early-stage angel investments to closing seed rounds worth a few million. The more benefits the accelerator program offers, the fiercer the competition for participating in it. Contrary to a popular belief that it’s passion and dedication that matters most, it’s important to understand that neither of these two will actually make your startup stand out. In the 2020s, the whole startup scene is passionate and dedicated by default – you need more than that to differentiate yourself from the rest. Here are a few tips that will help you secure your seat on some of the most desired startup accelerator journeys. Tip 1: Narrow Down Your Choice The first thing to understand about startup accelerators is that there are hundreds of them out there. Some of them are indeed extremely competitive – the rumored acceptance rate for the world-famous Y-Combinator program is said to range around 1.5-2%. However, you don’t necessarily need to target the most famous accelerators to get the opportunities you’re seeking. In fact, some smaller niche programs may give you a much better understanding of a particular sector or a regional market. The best way to approach your accelerator-enhanced growth strategy is to do your research and make a list of programs that you are specifically interested in. Put them together into a spreadsheet and fill it in with details such as hosting institutions, deadlines, timeframes, and other notes. Check your eligibility for each accelerator: you don’t want to waste time applying for a program you can’t qualify for. Some things to consider: 📌 If you are applying for a program in a different country, do they accept international entries, or do you need to register a local entity? 📌 Does your funding stage match the requirements? 📌 Are there any particular market sectors or challenges that the program is focused on? If yes, is your startup the right fit? 📌 What do they require in return? If it’s an equity share, are you willing to give up the share they are asking for? Once you’ve put together your shortlist, you can start applying. Make sure you decide which programs are most important to you, and which you can skip. Even if you pass the selection, you can cancel your participation before the program begins – but doing that when the program has already kicked off will cause the organizers a lot of inconveniences. It’s not the end of the world, but the startup world is smaller than you think – so it’s best to mind your reputation and keep your records clean. Tip 2: Prepare and Preserve Your Responses (To Recycle Them!) Filling in all these application forms requires quite some time. The good news is, that you don’t have to write all your answers from scratch – many questions in these questionnaires tend to be similar. To save your efforts, create a file where you will store this information for future applications. The file should contain anything from the basic questions (e.g., founders’ backgrounds, current funding, elevator pitches, brief product overviews) to more program-specific points covering how exactly you will tackle certain challenges or what your desired program outcomes are. Whenever the question in the application form is slightly different from the ones you have answered before, make a new edit of your previous answers and save it, too. You can keep it in a simple Google Doc file on your drive (so you can find the right information by searching with relevant keywords) or even create a separate database with FAQ for startup accelerators. Whatever works for you and is simple enough to use for your team. Having these answers at hand will save you a good deal of time, as you’ll only have to copy and paste your answers with minor edits. You’ll thank me for this tip next time you’ll find yourself applying for a program last-minute! Tip 3: Craft Your Visuals Almost every accelerator will require you to submit your pitch deck presentation. On top of that, some may also request a company one-pager or even video materials – such as a short product demo or a founder’s pitch. As visuals generally take longer to produce, it’s best to have them at hand – although they are more difficult to make than write-ups, it is also a great opportunity for you to make a great impression and stand out. With pitch decks and one-pagers, it can be a one-time commitment – as long as you put a reasonable amount of effort into making them, you should be able to reuse them as much as needed. Just make sure you update important information such as product use figures, funding, and other details that may change over time. Video materials may seem more difficult to produce, but in fact, you really don’t need to hire professional videographers or animators to do it. Here are a few multimedia pieces you can stock up on for your accelerator applications: ✅ Record a quick product demo and edit it into a one-minute movie with clear, basic subtitles explaining what is going on in the shot. You can use free intuitive video software like iMovie or OpenShot, or opt for more sophisticated solutions like Adobe Premiere Pro. ✅ Make a minute-long team video presentation. It can be an actual video with each of your team members saying something about what you do on camera or a slideshow. If you don’t have any good-quality images of your team, consider creating a fun animated video with characters looking like your colleagues! Use online animation tools such as Vyond or Toonly to put together your cartoon team and animate them with subtitles. ✅ Record a brief elevator pitch of your company. Make sure you articulate the problem you are trying to solve, how your product tackles it, who your customers are, and who is going to pay for your solution. Although few startup accelerators ask you for this piece of media (for example, the Pitch competition at the annual WebSummit in Lisbon does), it’s always handy to have it – after all, you can always enclose a link to this video in an answer to one of the questions about your product. Tip 4: Concentrate on the Problems and Solutions (Not the Tech!) There is no point in bragging about your smart AI, NLP, OCR, and fancy cloud solutions if you cannot clearly articulate how exactly they are solving an existing problem. What is the need that you are addressing? What will happen when your innovation is adopted? Concentrate on answering these two questions as clearly and concisely as you can – the technology itself comes next. Don’t say something like “We have developed an AI-powered gamified behavioral health app for curing endorphin-mediated disorders” – it is highly unlikely that anyone at all will understand what your product is, and why the world needs it. Nor do accelerator organizers have time to google the background behind your innovation. If you’re not too limited in symbols, you can write something like: “We have developed a smart app for people suffering from addictions that will educate them about their condition and maximize the impact of treatment.  We use a gamified approach to transform their routine into daily quests that keep them engaged.” Or shorten it down by cutting the second sentence – it will still give a better idea of what your product is about. You can always go into further technical specs of your product at the interview if you pass the first round of selection. Tip 5: Be Reasonable and Specific Randomly inserting words like “biggest”, “disruptive”, “innovative” and “global” will not add extra points to your application. Rather than flooding your statements with generic adjectives that really say nothing about your project, focus on listing facts that will make the organizing committee figure out how great it is. Use numbers and clear evidence – and if you don’t have any, be sure to articulate specific expected outcomes. Compare: “We have invented a disruptive technology for capturing carbon dioxide from the air” Vs “We have developed a technology for capturing carbon dioxide from the atmosphere using the electrochemical approach. This method requires up to 70% less energy compared to other CO2 removal technologies, making our solution more cost-effective and scalable.” The same applies to answering the question about your expectations from the program – almost every accelerator application form will ask you about that. Having gone through a lengthy questionnaire, you are likely to experience an urge to write something very generic in response. “Pilot opportunities in the local ecosystem”, “contacts with potential partners”, and “investments” – well, yes, all of that might very well be true. But these answers give zero foundation for your desire to join this particular accelerator. Nor do these phrases help you stand out amongst dozens or hundreds of other candidates looking for precisely the same things. There’s nothing wrong with any of these answers as long as you stick to being specific. Look at the accelerators’ lists of partners and explain how they could help you in carrying out your pilot projects. Alternatively, do your research on previous cohorts: find other startups in your sector which have participated in the program and bring them up as an example of what you are aiming to achieve. This bit of extra effort will make the organizers appreciate your attitude and dedication to getting into this particular program. Last, but Not Least Remember that all these principles apply to further stages of startup accelerator selection, too. Have your answers ready, keep your visuals at hand, talk about problems and solutions, and be specific. As long as you stick to this formula during interviews, your chances of success will be maximized. And, of course, be passionate. Paired with the right preparation, that’ll do the trick.

Top 5 Tips to Pitch Your Way Into Startup Accelerators

Building a product with quality in mind not only improves product performance but also helps build a strong reputation and loyal customer base in the long run. Let’s take a closer look at what performance engineering is in detail. What Does Performance Engineering Stand For? Say you are building , a , or a and you want to make sure that it runs smoothly under different circumstances. This process is called performance engineering. It’s an umbrella term for different methods, technologies, and people that are all engaged throughout a software development life cycle to verify compliance with the performance criteria. loan management software social network application B2B education platform In performance engineering, a set of different tests is applied to eliminate bottlenecks and see how the software performs in particular scenarios that are most likely to occur in the post-production stage. During the project lifecycle, software performance engineering is closely intertwined with the architectural design to detect performance and stability issues. This makes performance engineering a viable method for getting things done right on the first try. Performance Engineering Best Practices That Drive App Performance The quality of your end product is much dependent on the effectiveness of the performance engineering strategy that you choose. The right engineering performance objectives establish crucial connections within the team by helping understand what tools and techniques work best. A software performance engineer understands that concentrating just on the task of moving fast is insufficient. Speed performance engineering is beside the point here since the difficult part is determining how the software benefits the organization, its personnel, and its consumers. If they succeed, the software will be a success as well. Therefore, the can be split among the teams. Some of these, however, are listed below as being the most crucial: best practices in performance engineering The selection of the appropriate caching mechanism is critical to the product’s proper operation. Make the most of caching: This practice is a time-saver and efficiency booster when it comes to performing operations. Keep the requests to the server to a minimum: , which is also applicable to network connections and database calls. Take care of the memory , a viable strategy to reduce the workload. Try mastering asynchronous processing , which is an important technique to avoid unexpected disruptions and accelerate the workflow. Don’t disregard performance auditing Read also: What are the essentials of the best project management software? All in all, performance engineering is a tried-and-true method of enhancing the end product’s performance. Practices for Architecture & Design Create performance-centered culture; Specify your performance budget; Determine the components; Set your acceptance criteria; Prepare for deviations from the norm; Prototype and test. Practices for Development Testing Integrate performance into your build validation tests (BVT) and collect data after each build; Make your UNIT tests more performance-oriented; Automate quality gates during the build process to prevent reusing subpar components; Deploy a branching technique to not let the parts break the code or cause its poor performance; Follow the outcomes of systems and components to see how they change over time. Practices for Operations Ensure that disaster recovery, capacity planning, and resiliency are of the highest priority; From pre-production through production settings, deliver continuous deployment and operations; Create a production environment using the following deployment methods: canary, live/live, or blue/green; Establish a system for predictive and scaled growth, as well as tracking features and configurations, and providing ongoing feedback; Maintain an all-encompassing monitoring approach that includes comprehensive and ongoing feedback in all contexts; Know your most used features and functionalities across the stack and lifecycle; Define your hot spots (e.g., software, hardware, configurations, etc.); Create a procedure for reviewing production incidents that focuses on learning and long-term stability. Final Thoughts Poor application performance undermines the reputation and potential success of the product. This is why software performance engineering matters. It encourages tech engineers to shift their mindset toward performance culture within the organization. Performance issues must be identified early in the design stage when it’s easier to fix them. Also Published At: https://www.visartech.com/blog/performance-engineering-quality-at-scale/

How to Accelerate App Performance by Performance Engineering? [Best Practices Inside]

After switching my career from the creator economy to Web 3 late last year, I struggled initially as I found the learning curve to be quite steep. Here are a few things I did to accelerate my growth. 1. Start an Alpha Chat With Friends. This was initially a proposal from a buddy who was also getting into Web 3 at the time. His premise was that three heads were better than one. We would meet for an hour each week and share what we all learned about the crypto space. We each picked a topic and created a slide deck with the goal of educating the others about a specific chain, project, or NFT collection. Our Alpha chat is still going strong over telegram where we have over 30 members with quality discussions on all things Web 3. 2. Curate a High-Quality News Feed. There is a lot of noise in the Web 3 space. It’s often difficult to find quality content with an unbiased analysis of news and events. My two go-to sources for news are Decrypt and CoinDesk. https://decrypt.co/ https://www.coindesk.com/ 3. Follow the Right Content Creators. I vastly accelerated my learning curve through a steady diet of YouTube videos and Podcasts. I spent the first few months of my educational journey watching and listening to 3+ hours of Web 3 content. My go-to shows are: . Bankless hosts some very knowledgeable guests, and the conversations are always informative and educational. Bankless with Ryan Sean Adams and David Hoffman is one of the best Web 3 shows on YouTube. The host goes by the pseudonym Guy, and his ability to present complex ideas in a simple and easy-to-digest manner is unparalleled. Beyond Web 3, Guy has also covered wider macro-economic news providing much-needed context for the bigger picture beyond just the crypto market. The Coin Bureau For NFT news, I like to have a good mix of educational and fun content. is one of the best shows in the NFT space and covers a wide range, from degen projects to blue chips and fine art plays in Web 3. The show is very professional and has great guests from diverse backgrounds in the NFT scene. Proof with Kevin Rose is my daily dose of NFT degen fun. I wake up with their morning show and always look forward to the banter between hosts Pio, NFT Nick, and Captain Kix. The intro music is on point, the NFT weather report is informative, and the guys always manage to make me laugh even during the brutal bear market. The Nifty Alpha 4. Start Writing. I cannot emphasize how powerful writing can be in accelerating your learning curve. I began writing consistently back in May as a way to hone my ideas around Web 3 and become more articulate in my thoughts on the space. Writing forces me to really engage with what I am learning about and deeply embeds concepts and ideas that serve as the foundation for my Web 3 knowledge. As always, thank you for reading. Check out my unfiltered thoughts on Twitter: https://twitter.com/wasifmrahman Follow my career on LinkedIn: https://www.linkedin.com/in/wasifmrahman/ My other Shower Thoughts on Medium: https://medium.com/@wasifmrahman Also published here

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Are you looking for ways to accelerate growth for your company? If yes, then these 7 tools should be at the top of your wishlist. The cloud has become indispensable to modern businesses. More companies are now turning to cloud computing solutions to reduce costs, improve productivity, and boost customer service. Here's a list of 7 SaaS Tools that can accelerate your business growth. Before we look into the list, why must your business invest in SaaS Tools? Let's take a quick look. Why Must Your Business Invest in SaaS Tools The cost of running an on-premise server is very high. It requires constant maintenance and upgrades. In addition, it needs a lot of space. On the other hand, with SaaS, you only pay for what you use. You don't need to buy new servers or upgrade them every time there is a change in technology. Cost-effective: With SaaS, you get access to all the resources as they grow. This means that your application will scale automatically as your business grows. Scalable: When you have a reliable solution like SaaS, you don't have to worry about downtime. All your data is stored online and accessible from anywhere. Reliable: With SaaS Tools, you can easily add more users without having to purchase additional hardware. You also don't need to hire IT experts to manage your infrastructure. Flexible: Most SaaS applications are easy to use. They provide intuitive user interfaces so that even non-technical people can operate them effectively. Easy to Use: These are some of the top reasons to induct SaaS Tools into your business process. However, the benefits of SaaS Tools are invaluable to any business that intends to grow. 7 SaaS Tools to Guarantee Your Business Growth Project Management SaaS Platform Project Management SaaS Platforms help you plan, organize, track, and control projects with ease. They allow you to create project plans, assign tasks, monitor progress and communicate with your team members. These platforms also offer features such as task management, resource planning, reporting, and analytics. With these features, you will have better team collaboration that results in a shorter turnaround time. Also, Project Management SaaS Platforms like NativeTasks enable teams to work remotely and get more things done with more flexibility. CRM SaaS Platform CRM SaaS Platforms are designed to help organizations collect, store, analyze, and share information about their customers. It helps you build relationships with your clients by providing detailed insights into their buying behavior. It also allows you to automate repetitive processes and streamline sales activities. This tool provides real-time updates on client activity, which makes it easier to respond quickly to changes in demand. Customer Support SaaS Platform Customer Support SaaS Platforms give you a centralized location where you can view and manage all your support tickets. This way, you can keep track of issues and resolve them faster. You can also set up automated responses to common questions and requests. Marketing SaaS Platform Marketing SaaS Platforms let you send personalized emails to your customers. They also allow you to schedule campaigns, track reach, and measure performance. In addition, the marketing SaaS platforms enable you to generate reports and track customer interactions. You can use these SaaS tools to automate content marketing and email marketing campaigns. It will result in easy high-quality lead generation from your marketing campaigns. Accounting SaaS Platform Accounting SaaS Platforms simplify accounting functions and ensure accurate financial statements. They also help companies prepare for tax season. This is because they provide pre-built templates to make filing taxes simple. Moreover, accounting SaaS Platforms improve the information security of your financial information. And it helps avoid financial frauds and errors by a huge margin. HR SaaS Platform HR SaaS Platforms integrate employee data across various departments. This way, employees can access relevant information easily. You can also use this tool to manage payroll, onboard new hires, and conduct background checks. The HR SaaS platform also enables you to perform compliance audits and maintain records of employment agreements. Analytics SaaS Platform Analytics SaaS Platforms provide business intelligence (BI) solutions. They help you gain valuable insights into your operations. For example, you can use this tool to identify trends and patterns in your business. And you can use it to predict future outcomes based on past events. Conclusion Nowadays, there are many different types of SaaS platforms available. These include project management, CRM, customer support, marketing, accounting, HR, analytics, etc. These platforms are used to solve specific problems in an organization. But, if you want to grow your business, then you need to choose the right one. So, before selecting any SaaS solution, explore a or a SaaS Community. It will help you find the right SaaS tool that will fit your need. SaaS Marketplace

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