OWL Intelligence Platformis in the Business Intelligence Industry

OWL Intelligence Platform

The long awaited of this series has arrived. It has taken me a significant amount of time longer to put together than I had anticipated. Now the wait is over, here it is… Part 2 of 3 This list contains companies working on artificial intelligence and machine learning products primarily for business use, non-specific to any industry. Industry specific AI will be the final part of this series. Rise of artificial intelligence is rapidly taking over the world, especially countries like Anguilla; a small island in the Eastern Caribbean with the use of their .ai top level domain for companies within the AI and robotics industry. But in all seriousness, AI is without a doubt accelerating much faster than is probably known and much more established within our daily lives than most would realise. Conducting this research has demonstrated sheer scale of the landscape and progress of the artificial intelligence industry. “Already humans and AI are co-evolving and no one has paid attention to this yet…” “When we search on Google, it’s an AI deciding what we should see. When a dating site matches two people together there’s a machine learning algorithm… that is getting people together, that then have babies. And so in effect you have this machine learning algorithm that is breeding humans.”— Sam Altman, discussing AI . here In the case of the companies listed below, business and AI are co-evolving. With so many websites to go through and dissect there may be some descriptions or names that need changing. Please let me know if that’s the case or if you think there are companies I should add to the list. Shoutout to me , and I’ll get on to it! here Artificial Intelligence for businesses (enterprise intelligence): 🔉 Audio — language transcription and recognition — ? — transcribes insights from phone calls, video footage, and online — discover more customer and employee conversations** **— makes sound searchable — critical insights about your customers conversations — building blocks to add messaging, voice, and video to web+apps Capio Clover Intelligence Deepgram Gridspace MindMeld — advanced AI to power conversational interface Nexidia — turns customer interactions into valuable insights Pop Up Archive TalkIQ Twilio 📊 Business Intelligence & Analytics — optimise and autonomously IT and business operations** ** —behavioural AI for IoT — a suite of intelligent applications for enterprise — a range of products to improve enterprise products** ** — automates repetitive tasks within your business — making complex data science easy for enterprise Arago/HIRO Arimo Ayasdi DataRobot Dataminr — discovers events and breaking information before the news — helps you to answer questions about your business — a smarter Salesforce — adds intelligent decision making to web and mobile apps — helps you index, search, visualise and analyse your data — is a framework for temporal pattern recognition and prediction — to transform raw data into useful information automatically — helps you monitor server bugs Electra by Lore Einstein Fuzzy AI Logz.io NXT AI Paxata Poweredby.ai Sundown UBIX Ruths.ai — helps you do more with your data — a marketplace for analytics — captures, categorises, and extracts key information from all your data — fast data insights using search — solves big data better, faster and at less cost — find hidden value in complex human and business ecosystems — helps to optimise pricing Exchange.ai Owl.ai AnswerRocket iSeek.ai Ecosystem.AI Prix 🍎 Core AI — a common API for many algorithms, functions and models — workbench for neural networks — advanced industry specific ML for the enterprise — advanced machine learning for enterprise — advanced machine learning for enterprise — open source machine learning and deep learning platform — advanced machine learning for enterprise — deep learning as computational system — advanced machine learning for enterprise — advanced machine learning for enterprise — range of financial, ecommerce and digital marketing AI products — open-source deep learning and ETL for enterprise on the JVM — advanced machine learning for enterprise — log Analysis for enterprises Algorithmia Arya CognitiveScale Digital Reasoning Fluid AI H2O.ai Loop AI Labs Nervana Petuum Scaled Inference Sentient Skymind Vicarious Loom Systems PipelineAI — solves the problem of production ML and AI at scale — building AI using neuroscience Ogma 📋 Data Capture — marketplace to automate simple processes — automate the discovery of objects at scale — automatically prepare any data for immediate & compliant use — helps structure data from social media and blog — automatically extract web pages as structured data — extract data from almost any website — training data, image annotation and more for enterprise** ** — tools for operations team to automate business processes Amazon Mechanical Turk CrowdAI Datalogue DataSift Diffbot Import.io Playment WorkFusion 🔬 Data Science — single platform for all predictive use cases — training data, image annotation for machine learning teams — data science platform for prototype, deploy, and run at scale — enterprise data science platform for R&D and production** ** — helps you learn, work, and play with machine learning models — makes data science teams more productive — helps DS teams put machine learning models into production — a platform to build, test, and deploy AI algorithms** **— research engine, capable of discovering complex patterns in data — makes data unification of data silos possible — helps put data into useful structures for analysis — allows data scientists to deploy and update predictive models rapidly — automate the writing of reports, websites, emails, articles and more BigML CrowdFlower Dataiku DataScience Domino Data Lab — platform for collaborating, building and deploying — makes DS accessible to analysts with OpenSource algorithms Exploratory Kaggle RapidMiner Seldon SherlockML Spark Tamr Trifacta Yhat Yseop 💻 Development — detects business incidents — develop more adaptive, trusted and programmable AI models — helps predict project timelines — adds intelligent decision making to web and mobile apps — connecting projects with the right team — augments your coding environment with web available knowledge — deep learning platform for prediction and personalisation — makes developing chatbots for your business easy — make your bot smarter, by helping it self learn — rapidly web and mobile app testing — increase server uptime and predict downtime — project management and chat software that’s easy for teams AnOdot Bonsai Deckard.ai Fuzzy.ai Gigster Kite Layer 6 AI Morph Ozz RainforestQA SignifAI Turtle Improve.ai — automatically optimises app content, design, pricing etc. — gesture recognition for developers — trains deep learning algorithms to learn like human brain — abstracts away the complexity of ML libraries like TensorFlow for more effective management of AI models — helps with decision making for designers, engineers and leaders — helps analyse algorithm Gesture.ai Cognitive Toolkit Bonsai Tangle Imandra 📂 Internal Data — helps you work together, improve productivity, and data indexing** ** — helps employees with tasks and access data using micro apps — better website analytics Alation Cycorp — a range of different AI enterprise products — takes the pain of cluster management away to focus on DS — helps predict project timelines — insight into online trends and other text analytics tools — AI platform for business Databricks Deckard.ai Gavagi IBM Watson Kyndi — helps knowledge workers process vast amounts of information — SaaS AI for risk management and operations — makes your business software smarter oneFactor Probot Sapho Sofia eContext — structure for unstructured data — create intelligent interactions between people, devices, and data — deep insights into customers and internal data —automate decision-making at scale Hayley RelativeInsight Rainbird 🤖 Machine Learning —No-code end-to-end AutoML tool that takes you from data to predictions in minutes* *__ — a range of different AI enterprise products — helps you focus your digital ad on people you want to target — analyse data in the form of images, speech, text and video — now apart of the Uber AI Labs — can do menial task work, saving time for employees — platform to unite siloed data for better recommendations — improves machine learning models 100x faster PI.Exchange — develop more adaptive, trusted and programmable AI models__ Bonsai Cycorp Datacratic deepsense.io Geometric Intelligence HyperScience Nara Logics SigOpt Amazon Machine Learn — ML-as-a-service, amongst other things — import predictive models and scale infinitely to answer existential questions Providence 📡 Sensor (IoT/IIoT) — platform delivers real-time operational insights for industry — learns about shoppers behaviour in your store — helps to unify application development and data science — sensor analytics solution for businesses — machine learning for manufacturing process optimisation — a range of workflow optimisation products for fuel and industry — helps you develop, deploy, and operate industrial apps — helps renewable energy companies utilise their data better — manufacturing analytics — automates data engineering for data science — add a voice assistant to your connected product — platform to manage the development for your IoT applications — a predictive platform for major industries — smart building management for commercial buildings Alluvium Black C3 IoT KONUX Imubit Maana Predix Planet OS Sight Machine Sentenai Snips ThingWorx Uptake Verdigris 📚 Text Analysis/Generation — creates summaries from your text and information in real-time — extract meaning from your text and visuals — text analytics and mining which works without any training** **—automatic knowledge acquisition from text — build profile and understand your users better — scaleable text analytics software — capture, measure, and act on customer feedback — scalable API to automate text classification — interprets your data more useful information — helps you find errors and inaccuracies in documents — free open-source library natural of language processing in Python — automates information extraction, management and analysis — turn text into insights — helps improve how your job ads are written — automate the writing of reports, websites, emails, articles and more Agolo AYLIEN Compreno Cortical.io — advanced language processing fido.ai IntroSpect by Lore Lexalytics Luminoso MonkeyLearn Narrative Science Qeep spaCy Salient Stride Textio Yseop 😎 Vision — add instant text capture functionality to mobile apps and more! — automated drones with vision and diagnosis capabilities — analyses subtle facial expressions to identify human emotions — makes every camera in the world smart — helps cameras to detect analyse the video feed — finds defects in wind turbines — extracts and transforms data from handwritten and typed forms — helps you to organise media libraries — visual analysis for medical and transport industry — image detection for a range of uses and industries — brand and face recognition — makes satellite imagery useful — the first intelligent cloud video platform** ** — computer vision for automative and human detection — matches similar products and helps to suggests combinations — facial recognition — uses facial recognition to help you decided on job candidates — medical data analysis and interpretation — recognises different objects and things — dedicated brand recognition for social networks — satellite image analysis — deep-learning based computer vision platform — planet monitoring and analysis using satellite imagery — satellite image analysis — is an eye and emotion tracking platform — understands and describes video content — image analysis primarily for industrial purposes ABBYY Achron Affectiva Algocian __ __i Angus.a Birds.ai Captricity Clarifai Cortica Deepomatic DeepVision Descartes Labs Flixsense FotoNation GrokStyle Haystack HireVue Lunit Inc. Matroid Netra Orbital Insight Pilot AI Labs Planet Spaceknow Sticky.ai Valossa Vidi CloudSight — high quality understanding of images within seconds — detects foreign and intentionally placed objects for security — a range of intelligent computer vision techniques Irvine Sensors Pilot.ai Originally posted → liamiscool.com

A list of artificial intelligence tools you can use today — for businesses (2/3)

Intelligent DevOps: 8 Lessons Learned from Nature

ইন্টেলিজেন্ট ডিওঅপস: প্রকৃতি থেকে শেখা ৮টি পাঠ

Intelligentes DevOps: 8 Lektionen aus der Natur

DevOps inteligente: 8 lecciones aprendidas de la naturaleza

DevOps intelligent : 8 leçons tirées de la nature

इंटेलिजेंट DevOps: प्रकृति से सीखे गए 8 सबक

インテリジェントな DevOps: 自然から学んだ 8 つの教訓

지능형 DevOps: 자연에서 배운 8가지 교훈

DevOps Inteligente: 8 Lições Aprendidas com a Natureza

Интеллектуальный DevOps: 8 уроков, извлеченных из природы

Akıllı DevOps: Doğadan Öğrenilen 8 Ders

DevOps thông minh: 8 bài học rút ra từ thiên nhiên

智能 DevOps：从大自然中汲取的 8 个教训

196 Stories To Learn About Covid19

Hey, you beautiful, big-brained motherf*cker! Are you tired of being that person who can solve quantum physics problems in their sleep but can’t stick to a single project for more than a week? Yeah, I’m talking to you, the smart*sses who have a Ph.D. in overthinking and a knack for getting absolutely nothing done. Welcome to the club. We’re diving headfirst into the intoxicating world of “cerebral seduction,” where the intellectual allure of new ideas keeps us trapped in a never-ending cycle of flirting but never committing. We can debate the merits of existentialism versus nihilism until we’re blue in the face, but when it comes to actually doing something, we’re stuck in the starting blocks. But fear not, my fellow procrasti-geniuses! This blog post is here to help you break free from the chains of cerebral seduction and finally commit to doing something for a f*cking change. We’ll explore why we’re so addicted to shiny new ideas, how to recognize the distractions that keep us from committing, and the strategies that can help us make tangible progress in our lives. It’s time to put your big ‘ol brain and start getting sh*t done. Are you with me? Let’s do this! to work The Appeal of New Ideas So, what’s the f*cking deal with our obsession with shiny, new ideas? Let’s face it; we’re all a bunch of intellectual magpies, chasing after the next fascinating concept that tickles our curiosity and curbs our ooh-shiny craving. The more complex and abstract the idea, the more we’re drawn to it like moths to a flame. But why is this? For starters, very smart people often thrive on intellectual stimulation. The dopamine rush we get from engaging with a new idea is like a drug we can’t resist. We find comfort and validation in our ability to grasp and dissect complex concepts, and motherf*cker, it feels good. But there’s a darker side to this cerebral seduction, and it’s called “intellectual procrastination.” It’s the trap of constantly seeking out new ideas, theories, and perspectives while neglecting to make any real progress in our own lives. We become masters of the theoretical, but novices at actually getting sh*t done. This tendency has some ugly consequences. Our lack of focus means we struggle to achieve our goals, whether it’s writing that novel, launching that startup, or finally f*cking learning to play the guitar. We become paralyzed by the endless options available to us, and instead of focusing on one project, we end up spinning our wheels in a whirlwind of half-baked ideas and unrealized dreams. It’s time to put an end to this frustrating cycle of cerebral seduction and start committing to something for a change. Because, let’s be honest, as great as it is to be a smartass, it’s even better to be a smartass who gets sh*t done. Identifying Your Distractions Alright, smarty-pants, it’s time for some tough love. To overcome this cerebral seduction bullsh*t, we need to face the demons that keep us distracted from making progress. It’s time to dig deep and identify those pesky triggers that send us down the rabbit hole of endless intellectual exploration. You know the culprits I’m talking about: social media, news articles, online debates, podcasts, YouTube videos — the list goes on. These distractions are like kryptonite to our already scattered brains, making it nearly impossible to focus on one task for an extended period. And let’s not forget about FOMO, the Fear of Missing Out. As intellectual junkies, we’re constantly afraid that we’ll miss out on the next groundbreaking idea or that we’ll fall behind in our fields if we don’t consume every f*cking piece of information available (even if we know rationally that that’s not possible). This FOMO fuels our insatiable hunger for new ideas, making it even harder to commit to a single project. FOMO can be a real b*tch. Ironically, if you’re always too afraid of missing out to commit, you guarantee that you’re missing out. While you were over-optimizing, the train has already sailed. But here’s the good news: self-awareness is the first step to overcoming these distractions. By recognizing our personal triggers and acknowledging our FOMO, we can begin to take control of our wandering minds and start focusing on what truly matters. (More on that another day.) So, take a moment to reflect on your own habits and distractions. Be brutally honest with yourself. What’s keeping you from committing to a single idea? Once you’ve identified these roadblocks, you’ll be better equipped to tackle them head-on and break free from the vicious cycle of cerebral seduction. It’s time to start getting shit done, and it starts with recognizing what’s holding you back. The Art of Commitment Alright, brainiacs, let’s throw conventional wisdom out the f*cking window. We’re not here for the same old productivity advice that never seems to work for us. We need something tailored to our big, beautiful, overthinking minds. So let’s dive into the unorthodox art of commitment. Procrastinate as long as possible — until the pressure to deliver becomes irresistible. Instead of fighting your natural tendency to procrastinate, use it to your advantage. You might find that you work best under pressure, and that focused, last-minute effort can lead to great results. Embrace your inner procrastinator: Commit to one task at a time, but only for a short period. Pick a task, set a timer for 25 minutes, and work like a mad genius until the timer goes off. Then, take a break before moving on to another task or idea. This way, you’re still focusing on one thing at a time without feeling overwhelmed by long-term commitments. Become a serial mono-tasker: Design a personalized productivity system that caters to your quirks and habits. Throw conventional productivity advice to the wind and do what works best for you. If you’re a night owl, schedule your work when you’re most awake and creative. If you find inspiration in chaos, embrace it. Create your own rules: Identify your biggest distractions and find a way to incorporate them into your work. If you can’t resist scrolling through Twitter, use it as a source of inspiration or a platform to share your progress. The key is to accept your quirks, and use them to fuel your creativity. Turn your weaknesses into strengths: Be prepared to pivot or abandon ideas that aren’t working. It’s okay to change your mind or take a different direction if you’re not making progress. The goal is to be adaptable and open to new possibilities. Adopt a “f*ck it” mindset: When to Say “F*ck It” and Move On Now, let’s talk about the elephant in the room: not every idea or project is worth pursuing indefinitely. Sometimes, we need to recognize when it’s time to say “f*ck it” and move on. The point of the exercise is to remain intellectually committed to something and to invest the time and energy into those things you’ve chosen to prioritize. The point is to pursue a deadend indefinitely for the sake of “commitment.” not If the idea is a dead-end of any new shiny concepts that are vying for your attention, it may be time to move on. regardless Knowing when to abandon a project or idea can be crucial to our success. Clinging to a sinking ship can drain our time, energy, and resources, keeping us from pursuing more fruitful endeavors. So how do we know when it’s time to throw in the towel? Here are some guidelines: If you’re failing to make headway, it might be a sign that the idea isn’t worth pursuing. Lack of progress: consistently When the effort you’re putting into a project is no longer yielding meaningful results, it’s time to reevaluate. Diminishing returns: If you no longer feel excited or motivated by the idea (even when you’re actively engaged in it), it be time to let it go. Pay attention to the feelings you have surrounding the idea. Do you feel like you don’t have enough time to pursue the idea? Are you nervous or struggling with impostor syndrome? Key in on which feelings you’re experiencing and evaluate whether or not it’s best to let it go or hang on a while longer if the issue doesn’t actually stem from the idea itself. Loss of passion: might Take, for example, the story of Instagram’s founders. They initially created a location-based app called Burbn, but quickly realized that users were more interested in the photo-sharing feature. So they pivoted, dropped the original concept, and created Instagram — a decision that ultimately led to a billion-dollar acquisition. The lesson here is clear: Be willing to let go of ideas or projects that aren’t working and embrace new opportunities. The key to success lies in our ability to adapt, pivot, and move on when necessary. Building Momentum and Celebrating Success Alright, brainiacs — it’s time to talk about the sweet, sweet taste of victory. As we start committing to ideas and projects, we’ll begin to experience a sense of accomplishment that’s far more satisfying than the fleeting thrill of flirting with new concepts**. Let’s explore how to build momentum and celebrate our success in our own unique, genius way:** Learn to appreciate the victories, no matter how tiny they might seem. Finished a chapter of your book? Fucking fantastic! Solved a small coding problem? Hell yeah! These seemingly insignificant achievements add up and contribute to our overall progress. Savor the small wins: : Forget about traditional benchmarks — establish your own personalized milestones that align with your quirks and goals. Celebrate them with your own unique rituals, whether it’s dancing around your living room, ringing a f*ck yeah bell, or treating yourself to a fancy espresso. Just be careful not to put too much weight on extrinsic rewards, and savor the intrinsic value of your progress throughout your ritual. Create your own milestone markers Use your victories as fuel to propel you forward. Revel in the satisfaction of overcoming challenges and remind yourself that you’re capable of achieving even more. Don’t lose sight of your end goal, but stay focused on the journey and the progress you’re making. Read my take on why work-life balance can be total bullsh*t here. Keep the momentum going: Connect with others who share your passions and understand your struggles. Building a network of like-minded smartasses can help keep you motivated and accountable. Share your successes and setbacks, and celebrate each other’s achievements. Surround yourself with support : : Remember, you’re not just any smart person — you’re a f*cking genius. Use your incredible brainpower to create tangible achievements that you can be proud of. Show the world what you’re capable of when you commit to your ideas and projects. Embrace your unique intelligence By building momentum and celebrating our successes, we not only break free from the trap of cerebral seduction (by training ourselves like one of Pavlov’s favorite puppers) but also become more fulfilled and productive individuals. Let’s lean into our weird, wonderful, and wickedly smart selves, and start making sh*t happen! (Woof, woof, motherf*cker.) Conclusion: Well, brainiac, we’ve reached the end of our journey. Let’s recap the key takeaways before we set forth to conquer the world: , and use them to fuel your creativity. Identify and embrace your personal distractions and design your own unorthodox approach. Throw conventional productivity advice out the window, and find the right balance between flexibility and focus. Learn the art of commitment, and move on from projects that aren’t working. Recognize when it’s time to say “f*ck it”, , celebrate your successes, and use your unique intelligence to achieve greatness. Build momentum Now it’s time to put these strategies and tips into action. Let’s find an idea, put a ring on it, and embrace commitment like never before. (Cue bad b*tch energy Beyonce playlist) So go forth, my dear, brainy comrades, and show the world that we’re not just a bunch of burnt-out intellectual-f*ckboi smartasses. We’re a force to be reckoned with, and we’re ready to make our mark on the world — one committed, unorthodox, and f*cking brilliant idea at a time! Are you ready to finally see what you’re capable of with people who get it (and who aren’t going to just give you a list of the same old productivity hacks)? Find success on your own f*cking terms. actually ➡️➡️🤓Join us at Liferise. At the time of this writing, you can join on a donations-only basis (e.g., free) in exchange for feedback during the alpha phase. or . 💯 Sign up using Gumroad here learn more here Also published here

Cerebral Seduction: How To Stop Flirting With New Ideas

Graph Therapy. The Year of the Graph Newsletter, June / May 2020 Parts of the world are still in lockdown, while others are returning to some semblance of normalcy. Either way, while the last few months have given some things pause, they have boosted others. It seems like developments in the world of Graph are among those that have been boosted. An abundance of educational material on all things graph has been prepared and delivered online, and is now freely accessible, with more on the way. Graph databases have been making progress and announcements, repositioning themselves by a combination of releasing new features, securing additional funds, and entering strategic partnerships. A key graph database technology, RDF*, which enables compatibility between RDF and property graph databases, is gaining momentum and tool support. And more cutting edge research combining graph AI and knowledge graphs is seeing the light, too. Buckle up and enjoy some graph therapy. Stanford’s series of online seminars featured some of the world’s leading experts on all things graph. If you missed it, or if you’d like to have an overview of what was said, you can find summaries for each lecture in this series of posts by Bob Kasenchak and Ahren Lehnert. Videos from the lectures are available here. Stanford Knowledge Graph Course Not-Quite-Live-Blog Stanford University’s computer science department is offering a free class on Knowledge Graphs available to the public. Stanford is also making recordings of the class available via the class website. Another opportunity to get up to speed with educational material: The entire program of the course “Information Service Engineering” at KIT – Karlsruhe Institute of Technology, is delivered online and made freely available on YouTube. It includes topics such as ontology design, knowledge graph programming, basic graph theory, and more. Information Service Engineering at KIT Knowledge representation as a prerequisite for knowledge graphs. Learn about knowledge representation, ontologies, RDF(S), OWL, SPARQL, etc. Ontology may sound like a formal term, while knowledge graph is a more approachable one. But the 2 are related, and so is ontology and AI. Without a consistent, thoughtful approach to developing, applying, evolving an ontology, AI systems lack underpinning that would allow them to be smart enough to make an impact. The ontology is an investment that will continue to pay off, argue Seth Earley and Josh Bernoff in Harvard Business Review, making the case for how businesses may benefit from a knowldge-centric approach Is Your Data Infrastructure Ready for AI? Even after multiple generations of investments and billions of dollars of digital transformations, organizations struggle to use data to improve customer service, reduce costs, and speed the core processes that provide competitive advantage. AI was supposed to help with that. Besides AI, knowledge graphs have a part to play in the Cloud, too. State is good, and lack of support for Stateful Cloud-native applications is a roadblock for many enterprise use-cases, writes Dave Duggal. Graph knowledge bases are an old idea now being revisited to model complex, distributed domains. Combining high-level abstraction with Cloud-native design principles offers efficient “Context-as-a-Service” for hydrating stateless services. Graph knowledge-based systems can enable composition of Cloud-native services into event-driven dataflow processes. Kubernetes also touches upon Organizational Knowledge, and that may be modeled as a Knowledge Graph. Graph Knowledge Base for Stateful Cloud-Native Applications Extending graph knowledge bases to model distributed systems creates a new kind of information system, one intentionally designed for today’s IT challenges. The Enterprise Knowledge Graph Foundation was recently established to define best practices and mature the marketplace for EKG adoption, with a launch webinar on June the 23rd.. The Foundation defines its mission as including adopting semantic standards, developing best practices for accelerated EKG deployment, curating a repository of reusable models and resources, building a mechanism for engagement and shared knowledge, and advancing the business cases for EKG adoption. Enterprise Knowledge Graph Maturity Model The Enterprise Knowledge Graph Maturity Model (EKG/MM) is the industry-standard definition of the capabilities required for an enterprise knowledge graph. It establishes standard criteria for measuring progress and sets out the practical questions that all involved stakeholders ask to ensure trust, confidence and usage flexibility of data. Each capability area provides a business summary denoting its importance, a definition of the added value from semantic standards and scoring criteria based on five levels of defined maturity. Enterprise Knowledge Graphs is what the Semantic Web Company (SWC) and Ontotext have been about for a long time, too. Two of the vendors in this space that have been around for the longer time just announced a strategic partnership: Ontotext, a graph database and platform provider, meets SWC, a management and added value layer that sits on top. SWC and Ontotext CEOs emphasize how their portfolios are complementary, while the press release states that the companies have implemented a seamless integration of the PoolParty Semantic Suite™ v.8 with the GraphDB™ and Ontotext Platform, which offers benefits for many use cases. Semantic Web Company and Ontotext Partner to Advance Enterprise Knowledge Graphs Ontotext and Semantic Web Company (SWC) — two of the strongest voices advocating the value of knowledge graphs for organizations dealing with large amounts of diverse data — have announced a strategic partnership. Stardog is another graph database and platform provider. Stardog announced it has expanded it completed a Series B round of $11.4 million venture capital funding to mature its go-to-market initiatives. Its CEO set the goals of expanding EU operations, strengthening work in public sector, and developing tools and partnerships. Stardog, the leading Enterprise Knowledge Graph platform, expands Series B to $11.4 million to mature go-to-market initiatives Stardog, the leading Enterprise Knowledge Graph platform, today announced it has expanded its Series B round to $11.4m, securing an additional $3 million from new investors. NebulaGraph is an open source graph database developed by VESoft, a Chinese enterprise. VESoft is ready for further growth after closing an $8 million funding round led by Redpoint China Ventures, an investment firm launched by Silicon Valley-based Redpoint Ventures in 2005 NebulaGraph lists some 20 enterprise clients as users from domains such as social media, ecommerce, and finance. These include the likes of Meituan, Xiaohongshu, and JD.com. NebulaGraph has also been releasing new features, such as the Nebula Studio graph data visualization tool. VESoft raises $8M to meet China’s growing need for graph databases Sherman Ye founded VESoft in 2018 when he saw a growing demand for graph databases in China. VESoft is ready for further growth after closing an $8 million funding round. Microsoft Azure CosmosDB is a globaly distributed, cloud based, multi-model database which also supports graph. New autoscale and serverless features have been announced, to allow better alignment of billing to active usage. Furthermore, a new change feed, and a new Java API. Microsoft is grooming Cosmos DB as its developer-friendly NoSQL database that accommodates massive global web-scale applications but can also be cost-effective for much smaller ones. Microsoft Build brings announcements for cloud data, analytics services, and intersection of the two A series of announcements around Synapse Analytics, Cosmos DB, Azure Database and SQL Edge make this year’s Microsoft Build conference a virtual event revealing actual advances and concrete integrations. As we have often highlighted, a key differentiation among graph databases is their data model. Some are based on RDF, while others on property graphs (even though hybrids exist, too). RDF graph databases are also known as triple stores. Here Alan Morrison answers the question “What are the main pros of property graph databases compared to triplestores?”, quoting Marko Rodriguez, one of the most knowledgeable people in this space. What are the main pros of property graph databases compared to triplestores? How do property graph databases compare to RDF triplestores? RDF is best as a means of strategic integration, property graphs are best for tactical analytics. Neo4j is among the most popular graph databases. Even though it leverages property graphs, it also has an open source plugin called Neosemantics which enables it to work with RDF. A new version of Neosemantics has been released, supporting Persisted Graph Configurations, Model Validations with SHACL, and SKOS import. Some key features of Neosemantics are storing RDF data in Neo4j in a lossless manner (imported RDF can subsequently be exported without losing a single triple in the process), and on-demand exporting property graph data from Neo4j as RDF. Neosemantics 4.0 is out! Neosemantics is a Neo4j plugin that enables the use of the Resource Description Framework (RDF) W3C standard model for data interchange in Neo4j. RDF* is an extenstion to RDF that enables way of mapping RDF and property graphs. RDF* and SPARQL*, the extension to the RDF SPARQL query language, are undergoing standardization via the W3C. Olaf Hartig, RDF* creator, has put together a collection of command line tools and Java libraries to process RDF* data and SPARQL* queries. and , both popular open source tools for working with RDF, have added support for RDF*. RDF graph databases Cambridge Semantics AnzoGraph, Ontotext GraphDB and Stardog now support RDF* and SPARQL*. And Yago, a well-known open knowledge graph uses RDF* to represent statement-level annotations. RDF4J Jena YAGO 4 YAGO 4 is the latest version of the YAGO knowledge base. It is based on Wikidata — the largest public general-purpose knowledge base. The good news for RDF and SPARQL do not end here. Now data science notebook users can query public knowledge graph SPARQL endpoints directly, via integration with Jupyter and Zeppelin Notebooks, as Bob DuCharme shows. In addition, , which lets users visually browse the endpoints. Zazuko has released an open source SPARQL endpoint explorer SPARQL in a Jupyter Notebook Paulo Villegas has released a SPARQL kernel for Jupyter notebooks that lets us run queries natively, and I have been having some fun with it. More AI and data science overlap with the graph world: StellarGraph, an open source library for machine learning on graphs & networks, has released version 1.0. It includes algorithms and examples for Node classification, Link prediction, Unsupervised training / representation learning, and Graph classification. StellarGraph 1.0 — taking graph machine learning to a new level Today we delivered version 1.0 of the open-source, user-friendly StellarGraph library for machine learning (ML) on graphs and networks. It’s the culmination of three years of active research and engineering. Jure Leskovac, one of the key researchers in Graph AI, has recently presented advancements in Deep Learning for Graphs at the Deep Learning for Graphs workshop at The Web Conference. This includes a new version of the , a collection of realistic, large-scale, diverse benchmark datasets for machine learning with graphs. Open Graph Benchmark Advancements in Deep Learning for Graphs Position-aware Graph Neural Networks, Strategies for Pretraining GNNs and the Open Graph Benchmark. More cutting edge graph + AI research: SeMi, the SEmantic Modeling machIne, is a tool to semi-automatically build large-scale Knowledge Graphs from structured sources: CSV, JSON, or XML. It builds semantic models of data sources with concepts and relations in a domain ontology, and uses a graph neural network SeMi: A SEmantic Modeling machIne to build Knowledge Graphs with graph neural networks SeMi (SEmantic Modeling machIne) is a tool to semi-automatically build large-scale Knowledge Graphs from structured sources such as CSV, JSON, and XML files. Wrapping up with some COVID-19 related initiatives. The NSF has awarded funding for a Semantic Integration Platform to Combat COVID-19. COVID-19 Net will refine a knowledge graph and integrate it with complementary knowledge graphs. The Italian government publishes daily official COVID-19 open data. Now the , using the RDF Data Cube Vocabulary. data is available as linked data A that enables users to compare news from the BBC, CNN, Fox and DW News has been created by Loomi Assistant COVID-19 Knowledge Graph Web Tool NSF Awards Funding for Semantic Integration Platform to Combat COVID-19 The NSF has awarded two researchers at the San Diego Supercomputer Center (SDSC) funding to organize COVID-19 information into a transdisciplinary knowledge network that integrates health, pathogen, and environmental data to better track cases to improve analysis and forecasting across the greater San Diego region. To subscribe the to the Year of the Graph Newsletter, click here Previously published at https://yearofthegraph.xyz/newsletter/2020/06/graph-therapy-the-year-of-the-graph-newsletter-june-may-2020/

Buckle Up and Enjoy Some Graph Therapy

Towards a Knowledge Graph economy. The Year of the Graph Newsletter, Summer 2020 These past few months have not been kind to any of us. The ripples caused by the COVID-19 pandemic are felt far and wide, and the world’s economies have taken a staggering blow. Is there hope? And what’s that got to do with graphs, you might ask. Knowledge graphs have become an iconic technology trend for a reason. Knowledge graphs exemplify the emphasis on knowledge, and connections. In the current state of the economy, knowledge-based and remotely delivered activities have an advantage over service-based ones requiring real-world interaction. Whether this is necessarily a good thing is another issue entirely. In any case, we have to note the fact that knowledge graphs seem a natural fit for the unofficial title of the foundation on which a next-day economy can be built. That’s the thinking behind Meetup on September the 23rd. Steering towards a knowledge-based economy – how knowledge graphs can catalyze digital transformation and AI in the enterprise and beyond. Connected Data London’s A UBS Information Architect will talk about a data revolution – the emergence of the decentralized Enterprise Knowledge Graph to vastly increase data connectivity. The CEO of Franz Inc will outline the future of AI in the Enterprise is tied to Entity-Event Knowledge Graphs for Data-Centric organizations. A Knowledge Engineer from Engine B will show how Knowledge Graphs can be used for Data integrity, innovation and digitalization in professional services. Towards a knowledge-based economy: how Knowledge Graphs can catalyze digital transformation and AI in the enterprise and beyond Digital transformation and AI may have become overworn buzzwords that mean very little. In essence, however, they’re more needed than ever for businesses that want to survive and thrive in a new economy. In this Connected Data London Meetup, we take a look at how Knowledge Graphs are redefining digital transformation and powering AI in the enterprise and beyond. Case in point: Intuit is on a multi-year digital transformation journey to become an Expert Platform company, combining symbolic AI and machine learning. Its Tax Knowledge Engine allows domain experts to specify logic using Knowledge Graphs in a declarative and modular way. Intuit Tax Knowledge Engine: Practical AI for a Smarter and More Personalized TurboTax We share a technical overview of Tax Knowledge Engine, the key innovation we’ve pioneered to make TurboTax smarter and more personalized for 37M+ consumers. Beyond business, Knowledge Graphs have a role to play in organizations of all sizes and shapes. This includes the UN, championing Knowledge Graphs for Social Good. Furthermore, the Emerging Tech Lab (ETL) of the Office of Information and Communications Technology (OICT) has . embarked on several projects that explore how to store knowledge in graphs Applying knowledge graphs for social good You might wonder how a KG can reduce poverty or improve health. The answer is in the insights that Knowledge Graphs let us draw. Knowledge Graphs provide a means to understanding context, and that is the key to comprehending SDG data The GOV.UK team explored graph databases and knowledge graphs for their applications. The goals were to collaborate with other teams and communities to help them find content more easily, to build products and apps that allow further insights about the content, to upskill colleagues and drive culture change to make better use of data, and to provide early adopters with access and training to help scale use of data apps and product. One graph to rule them all Initially, we experimented with representing user journey data in our graph and then added other, previously siloed, data sources. In the context of a graph, all metadata was added as node properties. At that point, we had the early makings of a knowledge graph; a rich, canonical source of data that brings together datasets from across GOV.UK and the wider world. Another testament to the importance and timeliness of Knowledge Graphs, Graph Databases, Graph Analytics and Graph AI: the Noonies nomination. are Hacker Noon’s way of recognizing the tech industry’s top writers, thinkers, hodlers, leaders, and makers. George Anadiotis, the Year of the Graph Newsletter curator, has been nominated for Hacker Noon Contributor of the Year in Analytics. The Noonies is built for technologists to read, write, and publish. It’s an open and international community of 12,000+ contributing writers publishing stories and expertise for 4,000,000+ curious and insightful monthly readers. This nomination comes as a recognition of the importance of the topics the Year of the Graph spreads knowledge on. If you want to show your support, cast your vote! Hacker Noon Hacker Noon Contributor of the Year – ANALYTICS The Tech Industry’s Greenest Awards. The Noonies are Hacker Noon’s way of recognizing the tech industry’s top writers, thinkers, hodlers, leaders, and makers and you’ve been publicly nominated for: Hacker Noon Contributor of the Year – ANALYTICS If you want to learn more about Knowledge Graph modeling, then these books may be what you need. The Semantic Web for the Working Ontologist, one of the most highly regarded books in this domain, just got a new release. Datasets and queries mentioned in the book are available online, too. Ilaria Maresi encountered a range of challenges on her Knowledge Graph data modelling journey. If you are wondering what is a asemantic model and why you should consider building one, you can / check her book, in which she shares lessons-learned Semantic Web for the Working Ontologist, Third Edition Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. The most widely used Knowledge Graph schema is . If you want . schema.org, which just had a new release – v.9 to get started with schema.org, a little bit of history may help If you have already mastered that, then you may be interested in a way to get your brand in Google’s Knowledge Graph without a Wikipedia page, or in . learning practical NLP while building a simple Knowledge Graph from scratch with Python How to Get Your Brand in Google’s Knowledge Graph Without a Wikipedia Page Make sure you set out who you are and what you do clearly in the copywriting on your About Us page. Add Schema.org markup – make it as detailed as possible and cite sources that confirm. Get significant coverage in multiple independent, reliable, secondary sources. Knowledge Graphs power the medical domain too. PubMed is an essential resource for the medical domain, but useful concepts are either difficult to extract or ambiguous. This hinders knowledge discovery. To address this, . a PubMed Knowledge Graph was built Traditionally, Knowledge Graphs have been curated manually by experts, but machine learning can speed up the process. Here is a a review of advances in machine learning for constructing biomedical knowledge graphs. Advances in machine learning for constructing biomedical knowledge graphs By representing biomedical information as nodes, and the relationships between nodes as edges, KGs can be used to map out relationships between biomedical concepts to understand drug-target interactions or identify genes that play a role in disease progression. Advancements in Natural Language Processing and Graph machine learning powered by Knowledge Graphs is something Michael Galkin has been keeping track of. Here he summarizes the latest research from ACL 2020. In a similar vein, Sergei Ivanov summarizes the . highlights from KDD 2020, from a graph and recommender systems perspective Knowledge Graphs in Natural Language Processing @ ACL 2020 Did something change in the KG & NLP field comparing to ACL 2019? Yes! I would summarize this year’s contribution as: Knowledge graphs demonstrate better capabilities to reveal higher-order interdependencies in otherwise unstructured data Michael Bronstein is a Professor at the Imperial College London and the Head of Graph Machine Learning at Twitter. He recently started a series on blog posts on Graph Machine Learning, on topics such as , the issue of , and temporal graph networks. graph neural network architectures that can work on very large graphs depth on graph neural networks Temporal Graph Networks Many real-world problems involving networks of transactions of various nature and social interactions and engagements are dynamic and can be modelled as graphs where nodes and edges appear over time. In this post, we describe Temporal Graph Network, a generic framework for deep learning on dynamic graphs. Some notes on Graph theory. Centrality measures are an important tool to analyze networks. Analysis can be done with simple topological measures that score nodes by their importance as a part of the big network. Here is the . And to top it off: more graph theory, this time 10 graph algorithms, visually explained. definition and the tradeoffs involved 10 Graph Algorithms Visually Explained Graphs have become a powerful means of modelling and capturing data in real-world scenarios such as social media networks, web pages, and locations. If you have a set of objects that are related to each other, then you can represent them using a graph. Graph databases have been making progress. We have new releases from and ArangoDB, the , and . Dgraph general availability of Neo4j on Google Cloud new visual capabilities for AWS Neptune by integrating Jupyter Notebooks Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7 A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its offering. Analysis on data from different databases requires some kind of cross-walk or mapping. Mappings are a big deal for ontology too. Unfortunately mapping is fraught with problems. Here Chris Mungall introduces SSSOM: A Simple Shared Standard for Ontology Mapping A simple standard for sharing mappings Within the Open Bio Ontologies project we attempted to avoid the mapping issue by promoting reuse of ontologies and concepts from ontologies. However, not all ontologies are in OBO, and not all ontologies in OBO are perfectly modular and non-overlapping, so mapping remains a necessary evil. Data ingestion typically comes before mapping. Here are a couple of simple but useful tools for data ingestion, enabling users to convert CSV to RDF, , and . query RDF datasets & documents in arbitrary formats make diagrams from SPARQL queries Converting CSV to RDF with Tarql Quick and easy and, if you like, streaming. A year or two ago I learned about Tarql, which lets you query delimited files as if they were RDF triples. Inrupt exists to drive a course-correction of the web, using the tools and principles embodied in Solid. Those tools and principles are very much based on W3C and Semantic Web standards, applying them to shape a new era, built on the web but encompassing much more. Inrupt just released new beta versions of its software. Inrupt Beta Goes Live Inrupt is pleased to announce that the following products are now available for Beta evaluation. Feedback received during this Beta period will influence the roadmap for General Availability. Enterprise Solid Server: designed for mission critical workloads, demanding use cases. PodBrowser: app enabling users to navigate/manage data in Pods. Javascript Developer Libraries Lest we forget, we are still living in COVID-19 times. People are using Knowledge Graphs to consolidate medical knowledge: in addition to , is another effort that leverages a Knowledge Graph. COVID Graph Corona Why Other researchers have created an , integrate them as RDF under a simple ontology built on top of OWL-Time, GeoSPARQL, SIOC, and link the resulting dataset to linked to data providers such as Wikidata. Another contribution: a knowledge base of 8M+ Covid-related tweets. automated process to retrieve COVID19 data from public sources TweetsCOV19 — A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic A publicly available knowledge base of 8M+ tweets between Oct’19 – Apr’20. Metadata and entities, hashtags, user mentions, sentiments, URLs shared using RDF/S vocabularies, facilitating knowledge discovery tasks What would reinventing email as a graph look like? The interface for email conversation traversal is usually a linear column of timestamped message excerpts with nested replies inlined within message body. Ryan Bell created InboxGraph, a property graph representation for email Constructing directed graphs of email conversations The interface for email conversation traversal most often takes the form of a linear column of timestamped message excerpts with nested replies inlined within the message body. This is an excellent way to visualize the newest messages awaiting a response or action, but fails to illustrate the community structure and information flow within an inbox. To get the Year of the Graph Newsletter in your inbox, subscribe . here

Knowledge Graphs Exemplify the Emphasis on Knowledge and Connections

What pulls customers to an E-commerce store? Yeah, sure there are many aspects including content, graphics, images, information, security, user experience and much more. However, if we look at the users’ trend nowadays, we get to know that users’ take no more than a few seconds to decide if they want to purchase from an eCommerce platform or not. But, how did they assess the credibility of a website in a few seconds? Surely they can’t go through the content, information or products on offer at your eCommerce store in few seconds. Rather, the first and the most important aspect from the users’ perspective is the website layout and graphics. As soon as a user lands on your website, he will have a brief overlook at the appearance of the website and immediately asses if he wants to go on or switch to another side. And unfortunately, most eCommerce development lacks this one important aspect that directly influences the overall sales and revenue for the store. Ever heard of “User Experience”, that’s exactly what the users are looking for in any eCommerce design they visit. So, next time around when you are designing an eCommerce store, consider integrated latest website trends and maximize user experience to get more conversions. Below, we have a line-up of some of the best eCommerce website designs in 2020 to help you get some inspiration for your store. 1. New York Times Store The New York Times Store is definitely the top contender as the best example of eCommerce development. The entire design of the store revolves around the legacy of the New York Times, as one of the premium American newspapers. The store comes with plenty of breathing spaces, minimal cluttering and a simple yet elegant appeal that engages the users and delivers all the relevant information, offering a seamless journey for users. So, here’s the success recipe for the New York Times Store; minimal cluttering, elegant design, seamless navigation, and attractive graphics. 2. Rebecca Atwood Store Next in line, we have a contemporary and highly innovative eCommerce website design from Rebecca Atwood. The moment you lands on the website, you will be hooked with a brilliant strategy of content delivery, which we believe remains the secret to success for Rebecca Atwood. The complete feel of the website is utterly different from the traditional eCommerce store. You won’t find endless categories of products with flashy discount banners. The website rather gives a transparent, persuasive and clean vibe, which makes the entire browsing experience pleasurable and laid back, so you won’t feel like someone is desperate to get your credit card number. 3. Owl Ok, let us admit that Owl was no less than a surprising website for us as the top eCommerce website design contender. Just imagine, when was the last time you actually enjoyed buying a pair of spectacles. Yeah, it has always been a boring and dull experience for most of us. Nonetheless, Owl has been able to completely evolve the spectacle purchasing experience, making it an adventurous and engaging experience that will pull you back every time you need to buy the next spectacles. The secret to the great design for Owl lies in its graphics. The designers have intelligently used high-definition images of real people wearing the glasses, so you have a better understanding of what will look good on you. Overall, it carried all the right vibes of a great eCommerce website design including minimal cluttering, minimalist approach, simple design and plenty of breathing space (white spaces). 4. Bon Bon Bon . Bon Bon Bon is yet another spectacular example of how an intelligent eCommerce website design can help businesses expand into newer markets and create an utterly new brand. The company is a Detroit, USA based artisan chocolate company, and in its bet to expand from brick-and-mortar stores to the online industry, it has successfully created a completely customized and aesthetically pleasing website to engage online customers. The company has come up with a rather funky and user-friendly responsive website, which actually relates to the spirit of Bon Bon Bon, thus essentially sealing the deal for them. Another great feature that we find over the website is “Build a Box Box Box”. This feature essentially enables users to choose their preferred confections, choose the corrugated cardboard box and order delivery to anywhere they want, pretty intelligent! 4. Baron Fig The next in our list of best eCommerce development efforts is a website that has done complete justice to its branding efforts and made a clear point that intelligent use of graphics can bring in plenty of recognition and traffic for the brand. The Baron Fig website is made up of lots of innovative elements along with some impressive use of quotations that do complete justice with the brands’ values and philosophy. The designers have not shied away to use vivid colors and vibrant elements to make it stand out amongst the competition. If you are looking for a lively and engaging eCommerce website design, do check out this amazing platform to get some incredible inspiration. 6. Beacon The website design adapted by Beacon is simply intelligent. Imagine how would a website for colorful poster designing appear and now imagine how it would appear if it is converted into an eCommerce store. What’s even more impressive that Beacon is a project aimed for “Posters for good”, which means that all purchases from the print or donations are processed to Direct Relief to fight against natural disaster relief efforts. The website is a great arrangement of intuitive design, vibrant colors and generous appeal that simply gives a welcoming and warm gesture to users. 7. Storm Watch One look at the Storm Watch e-commerce portal and we are convinced of the ingenuity and intelligence that goes behind the website’s design. They have simply excelled to present their products with stunning graphic designs and enchanting appeal. While the company is known for its high-quality products, the website takes it a step further making it a whole different experience for online shipping. Check out this innovative e-commerce development effort to be impressed and inspired by the creativity of the design. 8. The Mountain . The Mountain is yet another impressive eCommerce development effort that brings an interactive and easy to navigate interface for users. What gives the website an explicit appeal is how the designers are able to insert a sense of urgency for users intelligently using key coupon codes. It undoubtedly a great contender if you are looking to develop a website with plenty of coupons and discounts for users to avail of. 9. Skullcandy . What brings this site to life is the efficient use of vivid colors and exceptional product photography. The designers were able to bring in the users’ consideration into effect by delivering exclusive high-quality product images and blending them perfectly with vibrant colors, making it an exquisite experience to shop from the platform. 10. Roc Making it to our list of top 10 eCommerce website designs for 2020, Roc is no less an inspiration for young eCommerce developers looking to get creative with their design. The overall design gives rather a busy vibe, which may seem a little overwhelming at first sight. However, it’s an intelligent design that is purposely made to depict the ethos of the brand. The high-quality imagery and an upbeat feel give the website the attraction to hook users and motivate them to use wireless headphones (that’s their product). Conclusion Have you got your inspiration? See, one element that is common across all these inspirational eCommerce development projects is the fact that they relate completely to their brand ethos and offer a seamless browsing experience to engage and convert users. So, check out these amazing eCommerce website designs and we are sure that you will get the right inspiration for your platform. References https://www.digitalgravity.ae/services/web-development/ecommerce-development/ https://www.digitalexpress.agency/ecommerce-development-solution/

Top 10 E-commerce Website Designs for 2020

Facebook’s data breach exposes the accounts of 50,000,000 individuals [ ] 2018: source Equifax, one of the three largest credit agencies in the U.S., suffered a breach that may affect 143 million consumers [ ] 2017: source AdultFriendFinder network hack exposes 412 million accounts [ ] 2016: source Insurance giant Anthem hit by massive data breach compromised the data of 112,000,000 individuals. [ ] 2015: source eBay faces massive data breach of 145,000,000 individuals. [ ] 2014: Source Yahoo!’s data breach compromised the data of 3 billion individuals [ ] 2013: Source These incidents leave us with the questions like: In spite of high-end security, aren’t giant servers capable enough to protect data? Isn’t data security should be a key factor for all the upcoming large and small enterprise? What web has stored-in for the future when it comes to security and privacy? Will the big giants suffer data breach in future as well? Let’s understand what more www has to offer in coming future to avoid these mishaps. We are living in the era of Web 2.0 where modern technology is although used to protect data but ultimately it has lack of control over security and privacy. So, we will soon be bidding adieu to Web 2.0 and welcome Web 3.0! Web 2.0 Will Be Soon Dead: Long Live Web 3.0 When something leaves the world, something new is born! Web 2.0 is soon going to be replaced with its smarter sibling i.e. Web 3.0; overcoming the issues of security and privacy. Instead of insecure databases and opaque data sharing practices, Web 3.0 will return control to the users which mean they will be able to access data from anywhere; mainly being driven by cloud applications and smart-phones. Apart from security, personalization is another add-on! What Web 3.0 brings to the table? Web 3.0 can be rightly said as an intelligent web! It is all about the evolution of third generation internet services that is a blend of Semantic web, Microformats, Artificial Intelligence, Data Mining, Natural Language Search and Machine Learning technologies. Experts say that Web 3.0 is a data-driven and semantic web. The user will type a query on the web; the web will understand the context and essentially will meet the needs of the user. So, if you perform more searches related to travel destinations, you’ll receive more ads related to the travel places. Also when you search for the cheap tickets, the search engine will keep in mind about the previous search and show you the results combining “travel destination and cheap tickets”. So, the next gen search engine will not only search for the matching keywords but also perform the context search based on user’s behavior and preference. Web 2.0 is largely about words; Web 3.0 will be the blend of words and visualization Web 3.0 will focus more on web interaction and will:- Limits and control users content Turns web into a big database Focuses on organizing data in a meaningful way Let’s get simpler Web 2.0 Lucy wants to go for a movie and gaming zone followed by shopping and dinner in her vicinity. She will go to Google and look through a bunch of information on the web comparing timings, rate etc. which would consume much of the time. Web 3.0 With the help of the search engine, Lucy will be able to generate this information faster. Search Engine will provide highly accurate and recommendations in a very intelligent way based on Lucy’s profile. Lucy will get the information needed at one go and ultimately it will save much of the time. Search Engine will learn about you and your habits from each search you perform and will gather details about your from your previous activities like likes and social postings and present the answers as per your preferences. So, how Web 3.0 will be different from previous Web versions? Quick Comparison: Web 1.0 vs. Web 2.0 vs. Web 3.0 Coming Back To Web 3.0 — Concerns of using Web 2.0 As everything on the web will be linked and the machine will save the user’s preferences, it raises the issues about security and privacy! When the user engages deeply and consistently, web will generate more verifiable and minable pieces of data. The more information is provided, the more they are rewarded with a richer and more dynamic experience. However there raises the question of security! So, what would be the technology that can help to stay secure? Blockchain Technology — Answer to the security and Privacy concerns Blockchain Technology makes it possible to store data in a secure way. With the decentralization of data, personal information will not be stored in the large data centers and databases of the companies. Rather all data will be controlled by a single company which would drastically decrease the personal data breaches. Bitcoin was the opening act. That was the beginning of Web3.0. Public Blockchain such as Etherum provides the decentralized platform to run smart contracts and removes the middlemen enabling the individual to communicate directly. In Web 3.0, Apple, Google, Facebook to the name of few would have no control over the data of the users which would result in a high security and privacy. Let’s see what kind of platforms Web 3.0 has stored-in. The Upcoming Platforms of Web 3.0 Below-mentioned are just examples that will be used in web 3.0 to avoid security and privacy issues. If we look at the current scenario, decentralized apps, wallets, platforms etc. that makes up web 3.0 are all scattered. To use this, there is always a need for identities, logins, OTPs etc. which disturbs the security. So, how about using Web 3.0 to avoid privacy clutters? is a cloud-based data storing platform that uses client-side encryption for security reasons. Data owners can trust and access their files easily. It is a decentralized network that delivers great performance, functionality and durability. Storj is a browser that provides unparallel privacy and security. It prevents tracking and keeps information safe and secured. It stays private on your device until you delete it. Brave The applications mentioned in the example are semantic and intelligent in nature which results in an improved communication. How Web 3.0 Can Make Decentralization Possible? As per , Web 3.0 is synonymous to Semantic Web! However, with the help of Artificial intelligence and Semantics, it will help to give the meaning to the data and solve the problems. Web 3.0 is a sure shot to understand the human mind closely. Wikipedia Web stack used in Developing Semantic Web 3.0 From a technical standpoint, the Semantic Web primarily consists of three standards: RDF (Resource Description Framework): It is a data modeling language where web information is stored and represented in RDF SPARQL (SPARQL Protocol and RDF Query Language): It is the query language which is specifically designed to query data across various systems. OWL (Web Ontology Language): This is the schema language or Knowledge Representation (KR) language which enables you to define concepts so that they can be re-used as much and as often as possible. Advantages of having Web 3.0 There are a number of advantages that Web 3.0 offers: -> As stated above, Etherum would provide a platform where data will be decentralized, where no entity will be able to alter the code without the permission of other entities in the network. Moreover, no one will have rights to block the websites and services. No middlemen to control data: -> Because data will be decentralized and distributed, it will be difficult for hackers to have control over the entire network. However, data cannot be erased or altered once it is in the block chain. This will create a continuous flow of accurate information and ultimately result in no data loss. Reduced data breaches: -> Today, applications are OS-specific which means it runs on a single operating system. Web 3.0 will provide easy to customize and device-agnostic applications i.e. applications will run on any device which includes television, refrigerators, microwaves, sensors, smart-phones and many more devices. Ability to work on any gadgets: -> DDoS attack will be drastically reduced! Due to the decentralized system, there will continuous data processing; no system can be blocked to stop a service; no single hardware infrastructure can hold the service. It will have multiple backups to prevent server failure. Uninterrupted service: Challenges to be considered as well Web 3.0 has a number of things to offer which can make user’s life easier. But, as said, there is always a second side of the coin. Let’s see what pain points it brings with it: -> There is no doubt of concern that www contains billions and trillions of web pages and terminologies. Existing technology is not sufficient enough to get rid of duplicated terms. The new system will have to deal with a huge input of data and may not be able to understand the context. Huge Data Set: -> Entrepreneurs will have to worry about how to manage the data in a scalable manner, that is, how to organize it, where to store it and how to find the right content. Scalability: -> With the increase in the overloaded information, visualization will play a key role for the easy recognition of the relevant content and the purposes. Visualization: 5 Main Features That Makes Web 3.0 Super Great -> Enhanced web where content is analyzed based on the meaning of words Semantic Web: -> Focuses on natural language processing where computers will understand the information more like human in order to provide faster and relevant results Artificial Intelligence: -> The Three-Dimensional design will be used in websites and services to provide a clear picture to the users. For instance: museum guides, computer games, etc. 3D Graphics: -> Information is connected to meta-data which helps to users to fetch accurate information Connectivity: -> Every device around you will be connected with the web which means content will be accessible everywhere Ubiquity: Web 3.0 — Takeaways for Business Owners -> The content of superior quality must be used all throughout the Internet to provide the value of your product in the market -> Opt for the website with 3D graphics for a more immersive and interactive experience. It will contribute to the modern look of the website -> Also, opt for an easy-to-navigate website in order to provide a simple yet engaging user experience -> As users will be able to reach any information on the Internet from everywhere; you should consider the optimization the information on all devices (mobile, tablet or desktop) -> Your customers will enjoy the flow of fresh content about your product and services -> AI-powered assistants are making the future! Entrepreneurs must focus on creating rich digital assets ensuring that search-engine can locate and serve the content easily. It may seem that, it will get harder to establish a presence online with a semantic web, but the use of best strategies will make you win the battle. Web 3.0 is all about making the life of the people easier where they don’t have to install and upgrade the applications; they just have to access the files instantly from anywhere. Beyond Web 3.0 — A look in the future It is sure that Web 3.0 will change our lives and will make it trouble-free to search anything online keeping our data secured. With the growth in the field of digital technology, Web 3.0 will be arriving soon! It’s just a matter of time before we take a leap in another era of the internet.

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