Cloudera Data Platform - Machine Learning

September 24, 2019 | 13 views

Cloudera Machine Learning is a cloud service for creating self-service machine learning workspaces and the underlying compute clusters for teams of data scientists. Enterprise data science teams need access to business data and the tools and computing resources required for end-to-end machine learning workflows, while IT and the business need to maintain data governance and control infrastructure costs. Cloudera Machine Learning brings the agility and economics of cloud to self-service machine learning workflows with governed business data and tools that data science teams need, anywhere.

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We are a group of machine learning PhDs, physicists, computer engineers, data scientists, developers, serial entrepreneurs and business leaders who are passionate to revolutionize the future of enterprises in public and private sectors across the MENA with AI and machine learning technologies.

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Is Progressive Web Apps the Way of the Future for Mobile?

Article | July 14, 2022

Progressive Web Apps (PWAs) enable cross-platform interoperability by giving users access to open web technologies. PWAs give your users an app-like experience that's tailored to their particular device. PWA development is a collection of best software development practices for making a web application behave like a mobile or desktop app. PWAs work similarly to mobile apps providing push notifications and a home screen icon. Progressive web applications, on the other hand, are more straightforward and faster than standard mobile apps, and they can be shared via a URL. According to Statista, there are around 3.5 billion smartphone users globally who utilize a variety of devices with various connection speeds and constantly changing conditions. Web App Vs. Progressive Web App The number of mobile users has expanded dramatically in recent years, necessitating the development of a better mobile web experience. Smartphones are utilized for a variety of purposes, such as reserving a cab or finding the nearest restaurant. Users expect a positive experience with their mobile devices in order to complete these tasks quickly. However, traditional websites are unable to give that experience for a variety of reasons, ranging from poor loading speeds to ambiguous user interfaces. Here's where web apps come in, which provide a better user experience regardless of the device or browser you're using. A typical web app is a website that can be accessed using a URL. Furthermore, these web apps contain several features that give them the appearance and feel of native apps, but they cannot be installed on any device. A progressive web app is the next step that can be installed on a device and appears and feels like a native app. You don't need to use a URL; just install a PWA on your device and run it like any other native app by clicking its icon on the home screen. Case Study Pinterest Pinterest built its new mobile web experience from the ground up as a PWA, with an eye toward worldwide expansion. However, due to poor mobile performance, the social network discovered that only 1% of its mobile users converted into sign-ups, logins, or app installs. Realizing that there was a big chance to boost conversion, they rebuilt the mobile web utilizing PWA technology, which resulted in a number of excellent outcomes: when compared to the prior mobile web, time spent is up 40%, user-generated ad income is up 44%, and core engagements are up 60%. Ali Baba Users of Alibaba's app were dissatisfied with their experience and refused to download or install the app. As a result, Alibaba had to make a progressive web application to make the experience much better for both first-time users and regular customers. As a result, seasoned users were re-engaged thanks to a significantly better experience for first-timers, push alerts, and home screen shortcuts. Alibaba could swiftly improve its re-engagement rate to match that of its native apps. To Sum It Up Developers may create the most excellent progressive apps using standard frameworks like React, Angular, Vue, Polymer, Ionic, and others, which have several advantages over native mobile apps and regular web pages in terms of functionality, user offline experience, and device space usage. Because of their superiority to native desktop and mobile apps in recent years, Progressive Web Programs have emerged as a wonderful alternative to those apps. PWAs take up less space on consumers' smartphones than native apps, encouraging people to install them. Because of caching capabilities, PWAs can work offline because some content is cached during the first visit to the app. Developing a great progressive web app necessitates a strong working relationship with a technical partner. Larger companies can also tap into the PWA industry by giving their users limited access to a PWA and then letting them pick how they want to continue. Overall, you should invest in PWA in 2022 since user experience is critical in this competitive market.

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SOFTWARE

What Are The Best Programming Languages To Develop AI Solution

Article | July 13, 2022

As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses. If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process. However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place! Top 12 The Best Artificial Intelligence Programming Languages 1. Python Python development is one of the most popular programming languages globally and a top choice for AI developers. It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase. Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics. Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites. 2. LISP LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958. It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications. LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network. 3. R R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.” R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering. The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code. Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches. 4. C++ It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs. Bjarne Stroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others. 5. JavaScript Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript. JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software. You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets. JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects. 6. Java Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools. Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow. Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms. 7. Haskell Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm. It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures. While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors. Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case. 8. Julia Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing. Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program. You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path. 9. Prolog One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language. Prolog uses an underlying theory called predicate logic based on facts, rules, and inference. Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world. Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification. 10. Scala Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications. Scala is easy to learn because it integrates object-oriented languages with functional programming features. It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications. It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms. Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications. 11. RUST The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010. The main goal of Rust is to provide a safe, fast, productive, and memory-safe language. Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages. Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance. 12. Wolfram Wolfram is a programming language and environment for technical computing, data science, and machine learning. Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation. Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages. It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

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SOFTWARE

Web 3.0: New Horizon of Internet

Article | July 14, 2022

Web 3.0, or as it is commonly known as Web3, is the future avatar of the world of the internet and it is based on decentralization. The present-day internet, or Web 2.0 as it should correctly be referred to, has contributed a lot more to transforming the way we live than any other tool in the universe. Web2 has been a key part of building the digital world we live in today, from Snapchat and Instagram filters to using Augmented Reality (AR) to catch Pokémon. Web3 and Metaverse are the most popular buzzwords today. With the decentralized network, Web 3.0 means that instead of having a few large companies control all the data, users will have equal access to control their data. Web3 also promises to enhance data and network privacy. What does Web 3.0 Mean for Businesses? Web 3.0 presents enormous opportunities for businesses. Let’s explore some of the ways in which Web3 will benefit from this new technology. Enhance Transparency and Trust Web 3.0 technology may help organizations and their consumers boost transparency and trust. Blockchain technology, for instance, can contribute to the creation of a tamper-proof record of transactions. This would help businesses increase customer trust by giving customers a clear picture of how they do business. Increased Security Presently, in Web 2.0, all of your data is saved in one spot in a centralized system. As a result, it is prone to exploitation. However, nothing is more crucial to a company than data security. Web 3.0 technologies decentralizes your data and assists in increasing its security. Deeper Customer Insights Web 3.0 can also help organizations acquire customer insights. How? Web 3.0 brings in data anonymization that allows businesses acquire customer data without fetching their personal data. It also helps businesses scale consumer data at large without any compromise on privacy. The data then gathered through customer insights can be utilized to enhance products and services. Finer Data Searchability Businesses can also deploy Web 3.0 technology to improve the searchability of their data. Using technologies for the semantic web can help make a data web that is easy for machines to search. This would make it easy for companies to get the information they need quickly and without wasting money or time on manual data searches. Better User Experience (UX) By offering a more customized web, Web 3.0 technologies can assist in enhancing the user experience. Artificial intelligence and machine learning algorithms can assist in giving each user a personalized experience that is suited to their specific requirements. As a result, consumer satisfaction and loyalty will rise. Web 3.0 Possible Business Applications Some of the most common possible areas where Web3 will definitely have an effect are: Social Media Web 3.0 transforms how app developers create social media apps. It returns ownership of data from platforms to end-users, making story-spinning and data exploitation impossible, as in the Facebook Cambridge Analytics Scandal. Currency Exchange Service Centralization fails in money exchange. Mt. Gox's $460 million bitcoin hack is a failure. Decentralized exchanges prevent hacker breeding grounds. Web 3.0 will see decentralized exchanges gain popularity for smooth user trades without hackers or lack of transparency. Messaging Platforms Messaging has always played an essential role in our lives. At work, Slack and Telegram replace Facebook Messenger and WhatsApp. Unsafe message transmission and centralized solutions make messaging systems exploitable. Web 3.0 messaging applications like ySign, Obsidian, e-Chat, etc., leverage Blockchain to protect users' privacy and security. Summing-up The Internet's evolution has been substantial, and this trend will undoubtedly continue. Web 3.0 will revolutionize the way we engage with the digital world, and the transition will affect more than just individuals. This will lead to more honest and transparent use of customer data, from tailored search results to cross-platform development tools and 3D graphics. A much more immersive and engaging web is on the way. The new Internet will be around very soon! Let's welcome Web 3.0 with open arms!

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SOFTWARE

Natural Language Processing: An Advanced Implementation of AI

Article | June 1, 2022

Natural Language Processing, also known as computational linguistics or NLP, is a branch of Artificial Intelligence (AI), Machine Learning (ML), and linguistics. It is a subfield of AI that enables computers or machines to understand, manipulate, and interpret human language. Simply put, natural language is the natural method by which humans communicate with one another. We have now trained computers to interpret natural language. Communicating with computers has become simpler with voice queries such as "Alexa, what's the news today?" or "Ok Google, play my favorite songs." Similarly, when you ask Siri, Apple's voice assistant, "What is the cheapest flight to New York later today?" It instantly searches airline and travel websites for flights from the user's location to New York. It also compares the prices and lists the one with the lowest fare first. So, even without specifying a date or the "lowest fare", Siri understands the inquiry and returns accurate results. This is the result of NLP in action. Natural Language Processing: Business Applications Natural language processing has a variety of applications, some of them are listed below. Summarize text blocks to extract the most relevant and core concepts while excluding unnecessary information. Develop a chatbot that makes use of Point-of-Speech tagging to enhance customer support. Chatbots are AI systems that use NLP to engage with people through text or voice. Determine the type of extracted entity, such as a person, location, or organization. Sentiment Analysis can be used to recognize the sentiment or emotions of a text string, ranging from highly negative to neutral to very positive. HR teams can utilize NLP-based solutions to scan resumes based on keyword synonyms and swiftly shortlist candidates from a pile of resumes. Extracting Text data from the data storage allows in extracting specific information from text. Text can be broken down into tokens, or words can be reduced to their root or stem. Topic categorization helps users organize unstructured text. It's a great way for businesses to obtain insights from customer feedback. How Can Businesses Prepare for the NLP-Powered Future? NLP has evolved tremendously, and has benefited both companies and consumers. NLP technologies are assisting businesses to better understand how consumers perceive them through channels such as emails, product reviews, social media postings, surveys, and more. AI technologies can be used not just to analyze online interactions and how people speak about companies but also to automate tedious and time-consuming operations, enhance productivity, and free up staff to concentrate on more meaningful duties. When it comes to NLP the sky is the limit. As NLP technology is becoming more prevalent and greater advancements in ability are explored, the future will witness enormous shifts. Here are some of the ways in which businesses can prepare for the future of NLP. Analyze your company's text data assets and evaluate how the most recent techniques can be used to add value. Understand how you can use AI-powered language technology to make wiser decisions or rearrange your skilled labor. Start implementing new language-based AI tools for a range of jobs in order to better understand their potential. Prepare now to capitalize on transformative AI and to make sure that advanced AI contributes to society fairly. Closing Note Thanks to natural language processing technology, conversational commands and everything related to conversational AI in businesses have become faster and better. Natural language processing helps large businesses make flexible choices by revealing consumer moods and market movements. Smart companies now make decisions based not only on data but also on the intelligence derived from NLP-powered system data.

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Stallion AI

We are a group of machine learning PhDs, physicists, computer engineers, data scientists, developers, serial entrepreneurs and business leaders who are passionate to revolutionize the future of enterprises in public and private sectors across the MENA with AI and machine learning technologies.

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SOFTWARE

LTI Strengthens Strategic Collaboration with Microsoft

LTI | August 03, 2022

Larsen & Toubro Infotech , a global technology consulting and digital solutions company, has announced the expansion of its collaboration with Microsoft to focus on developing high-value cloud solutions for enterprises. As a part of this multi-year collaboration, LTI has launched a dedicated Microsoft business unit that develops and offers end-to-end digital transformation solutions. Through this association, LTI will also train 12,000 professionals from its existing workforce on various Microsoft technologies by 2024. The main objective of this effort is to enable skill development of LTI employees that are a part of the Microsoft unit and enhance their competencies across technologies like cloud, data, IoT and security. “LTI has a long-standing relationship with Microsoft as a strategic partner, service provider, and customer. Our reaffirmed partnership with Microsoft will enable us to innovate and offer 170+ distinct services to our joint customers. Additionally, we will also focus on the training and upskilling of our talent pool that is a part of the dedicated Microsoft business unit, to empower them to meet changing business and market requirements.” Nachiket Deshpande, Chief Operating Officer, LTI Siddharth Bohra, Chief Business Officer & Head of Cloud Business Unit, LTI, said, “Enterprises across the globe are increasingly embracing cloud, and LTI has made impressive strides in developing a multi-dimensional capability on Azure to meet this demand. As part of this collaboration, LTI and Microsoft will jointly innovate, develop, and sell solutions to assist enterprises in acceleration of their digital transformation journeys.” Julie Sanford, Vice President, Partner GTM, Programs & Experiences, Microsoft, said, “Through their new Microsoft Business Unit, LTI will be able to help customers implement cloud strategies and drive business transformation across industries and geographies. We look forward to working with LTI as they build new capabilities and deliver innovative solutions on the Microsoft Cloud.” Through this association, LTI will attain the Solution Partner designation across all the Microsoft Solution Areas. LTI also has the following advanced specializations on Azure: - SAP on Azure: Validating the capability of implementing SAP solutions on Azure. - Analytics on Azure: Demonstrating the expertise in delivering analytics solutions in Microsoft Azure. - Windows Server and SQL Server: Expertise in migrating production workloads to Microsoft Azure. - Modernization of Web Applications: Validating expertise in migrating and deploying production web application workloads, applying DevOps, and managing app services in Microsoft Azure. - Kubernetes on Azure: validating capabilities in deploying and managing production workloads in the cloud using containers and managing hosted Kubernetes environments in Azure. - Low Code Application Development: Expertise in building solutions using Power Apps. - The Data Warehouse Migration to Microsoft Azure: Validating expertise in analyzing existing workloads and performing ETL operations to migrate data to cloud-based data warehouses. - Cloud Security: Validates a means for your company to showcase capabilities to implement comprehensive security solutions across Azure, hybrid, and multi-cloud environments. - Threat Protection: provides a means for your company to showcase proven, verifiable expertise in deploying Microsoft Threat Protection or Microsoft Cloud App Security workloads. - AI and Machine Learning in Microsoft Azure: Validates capabilities on enabling customer adoption of Al and implementing Azure solutions for Al-powered apps. LTI is an Azure Expert MSP Partner which demonstrates deep knowledge, extensive experience, and proven success in implementing specialized workloads such as Migration and Modernization, SAP on Azure, Data Analytics, Internet of things (IoT), Security, and Microsoft Dynamics 365. About LTI LTI is a global technology consulting and digital solutions Company helping more than 495 clients succeed in a converging world. With operations in 33 countries, we go the extra mile for our clients and accelerate their digital transformation journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our unique heritage gives us unrivalled real-world expertise to solve the most complex challenges of enterprises across all industries. Each day, our team of more than 46,000 LTItes enable our clients to improve the effectiveness of their business and technology operations and deliver value to their customers, employees, and shareholders.

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GENERAL AI

DataRobot AI Cloud 8.0 Helps Businesses Navigate Unpredictable Markets

DataRobot | March 21, 2022

DataRobot, one of the most widely deployed and proven AI platforms in the world, today announced AI Cloud 8.0. Designed to help every business better navigate unpredictable events and market conditions, AI Cloud 8.0 brings all organizations the ability to continuously optimize machine learning models to deliver top performance in production and connect with the broadest range of data to generate the most complete and accurate predictions. "AI is becoming increasingly mainstream with 69% of organizations either already using or planning to use AI in the next 24 months. But even more, AI has clearly moved from the experimental phase to mission critical with businesses realizing real value from improved growth and revenue to cost reduction to operational efficiency. Now more than ever, businesses need an AI platform that is adaptive, shifting and adjusting to even the most unpredictable market conditions." Jack Vernon, Senior Research Analyst, European AI Systems, IDC With AI Cloud 8.0, DataRobot enhances key innovations for every business, including: Predictive AI apps. DataRobot’s AI App Builder is extended with support for Automated Time Series, providing business consumers with the ability to help their organizations be more resilient and match the realities of today’s fluid and unpredictable market landscape. Recent Automated Time Series innovations including prediction explanation and segmented modeling can be fully brought to life in a no-code environment where AI applications can be rapidly built. Continuous optimization and trust. DataRobot’s Continuous AI capabilities are now available in on-premises environments along with leading public cloud platforms. These capabilities are especially powerful in enabling businesses to protect against real-world changes from prolonged pandemic conditions, changing economic climates, and shifting consumer behavior. Continuous AI automatically adapts and recommends the best model for predicting a desired business outcome given historical data and current conditions, to enable customers to protect performance in the future. Best in class connectivity and partner ecosystem. New integrations to Microsoft Active Directory and Scoring Code for Snowflake expand DataRobot’s extensive library of connections to data sources, data formats and business applications. This enhanced ecosystem accelerates time to value by enabling all businesses to work with an expanded library of models, a complete set of pre-built integrations, and write-back capabilities to the most popular cloud data stores. “Given today’s highly competitive and unpredictable job market, it’s critical that the tens of thousands of students enrolled at our university succeed academically,” said Dr. Hiselgis Perez, Associate Vice President, Analysis and Information Management, Florida International University. “With the help of DataRobot, we’re able to predict and identify at-risk students and proactively get them the academic support they need in order to stay on track and graduate. Our ability to quickly analyze data and make predictions for every student, has helped graduation rates triple over the past decade.” “Businesses today are navigating uncharted market challenges – from the lasting impact of the prolonged pandemic, to unreliable supply chains, to a rapidly approaching return to work,” said Nenshad Bardoliwalla, Chief Product Officer at DataRobot. “AI has the potential to help every business manage through this unprecedented time. But your AI platform must be able to anticipate and adapt faster and more intelligently to even the most unpredictable market conditions. With DataRobot AI Cloud 8.0, we’re empowering businesses to better anticipate moments of change and continuously optimize machine learning models, even those already in production, while driving new and more accurate decisions down to front line business users.” DataRobot AI Cloud 8.0 is available today to all businesses in a multi-cloud architecture. It is easily deployed to public clouds, on premises in the data center and at the edge, with unified management and operations. Learn more about DataRobot AI Cloud 8.0. About DataRobot DataRobot AI Cloud is the next generation of AI. DataRobot’s AI Cloud vision is to bring together all data types, all users, and all environments to deliver critical business insights for every organization. DataRobot is trusted by global customers across industries and verticals, including a third of the Fortune 50.

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GENERAL AI

Vectorspace AI Introduces Thematic Crypto Basket API for Exchange

Vectorspace AI | December 28, 2021

On December 22, Vectorspace AI, a Vector Space Biosciences subsidiary, released a thematic crypto basket API. It enables cryptocurrency exchanges by offering tradable crypto baskets with regard to a topic, event, or theme of any type in real-time. Through this API, retail traders and investors get an efficient ecosystem of new products. In addition, it provides enterprises handling advanced data engineering pipelines with abilities similar to asset management and hedge funds. It's like having your own dedicated NLP, AI, or Machine Learning pipeline, This opens up a new world of thematic investing where baskets of cryptos or stocks can be generated based on a theme or global event in real-time using similar 'language modeling' techniques used to predict the way proteins fold by DeepMind's AlphaFold2." Kasian Franks, Founder and CEO of Vector Space Biosciences, Inc. The thematic basket API from Vector Space AI can be used for several tasks, such as the following: Create short, long, or hedged positions among baskets Generate relationship networks and graph networks connecting stocks or cryptos Position capital across a network of thematic baskets consisting of stocks or cryptos Auto-create a no-click or one-click tradable basket of stocks or cryptos related to a topic, event, or theme in real-time The core crypto baskets API also introduced an additional filtering package called VectorScreen™. It allows advanced filtering and screening that results in additional alpha. It uses basic parameters to screen crypto baskets, such as sell pressure, liquidity, or market cap, along with advanced parameters such as fine-grained themes, concepts, or context. This API from VectorScreen™ will be available for retail and exchanges in the first quarter of 202i, enabled with a retail-driven UI/UX that will be available in the following quarter. The recently secured funding of $2 million will be used by Vector Space Biosciences to support global retail product offerings and product rollouts that will result in additional revenue.

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SOFTWARE

LTI Strengthens Strategic Collaboration with Microsoft

LTI | August 03, 2022

Larsen & Toubro Infotech , a global technology consulting and digital solutions company, has announced the expansion of its collaboration with Microsoft to focus on developing high-value cloud solutions for enterprises. As a part of this multi-year collaboration, LTI has launched a dedicated Microsoft business unit that develops and offers end-to-end digital transformation solutions. Through this association, LTI will also train 12,000 professionals from its existing workforce on various Microsoft technologies by 2024. The main objective of this effort is to enable skill development of LTI employees that are a part of the Microsoft unit and enhance their competencies across technologies like cloud, data, IoT and security. “LTI has a long-standing relationship with Microsoft as a strategic partner, service provider, and customer. Our reaffirmed partnership with Microsoft will enable us to innovate and offer 170+ distinct services to our joint customers. Additionally, we will also focus on the training and upskilling of our talent pool that is a part of the dedicated Microsoft business unit, to empower them to meet changing business and market requirements.” Nachiket Deshpande, Chief Operating Officer, LTI Siddharth Bohra, Chief Business Officer & Head of Cloud Business Unit, LTI, said, “Enterprises across the globe are increasingly embracing cloud, and LTI has made impressive strides in developing a multi-dimensional capability on Azure to meet this demand. As part of this collaboration, LTI and Microsoft will jointly innovate, develop, and sell solutions to assist enterprises in acceleration of their digital transformation journeys.” Julie Sanford, Vice President, Partner GTM, Programs & Experiences, Microsoft, said, “Through their new Microsoft Business Unit, LTI will be able to help customers implement cloud strategies and drive business transformation across industries and geographies. We look forward to working with LTI as they build new capabilities and deliver innovative solutions on the Microsoft Cloud.” Through this association, LTI will attain the Solution Partner designation across all the Microsoft Solution Areas. LTI also has the following advanced specializations on Azure: - SAP on Azure: Validating the capability of implementing SAP solutions on Azure. - Analytics on Azure: Demonstrating the expertise in delivering analytics solutions in Microsoft Azure. - Windows Server and SQL Server: Expertise in migrating production workloads to Microsoft Azure. - Modernization of Web Applications: Validating expertise in migrating and deploying production web application workloads, applying DevOps, and managing app services in Microsoft Azure. - Kubernetes on Azure: validating capabilities in deploying and managing production workloads in the cloud using containers and managing hosted Kubernetes environments in Azure. - Low Code Application Development: Expertise in building solutions using Power Apps. - The Data Warehouse Migration to Microsoft Azure: Validating expertise in analyzing existing workloads and performing ETL operations to migrate data to cloud-based data warehouses. - Cloud Security: Validates a means for your company to showcase capabilities to implement comprehensive security solutions across Azure, hybrid, and multi-cloud environments. - Threat Protection: provides a means for your company to showcase proven, verifiable expertise in deploying Microsoft Threat Protection or Microsoft Cloud App Security workloads. - AI and Machine Learning in Microsoft Azure: Validates capabilities on enabling customer adoption of Al and implementing Azure solutions for Al-powered apps. LTI is an Azure Expert MSP Partner which demonstrates deep knowledge, extensive experience, and proven success in implementing specialized workloads such as Migration and Modernization, SAP on Azure, Data Analytics, Internet of things (IoT), Security, and Microsoft Dynamics 365. About LTI LTI is a global technology consulting and digital solutions Company helping more than 495 clients succeed in a converging world. With operations in 33 countries, we go the extra mile for our clients and accelerate their digital transformation journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our unique heritage gives us unrivalled real-world expertise to solve the most complex challenges of enterprises across all industries. Each day, our team of more than 46,000 LTItes enable our clients to improve the effectiveness of their business and technology operations and deliver value to their customers, employees, and shareholders.

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GENERAL AI

DataRobot AI Cloud 8.0 Helps Businesses Navigate Unpredictable Markets

DataRobot | March 21, 2022

DataRobot, one of the most widely deployed and proven AI platforms in the world, today announced AI Cloud 8.0. Designed to help every business better navigate unpredictable events and market conditions, AI Cloud 8.0 brings all organizations the ability to continuously optimize machine learning models to deliver top performance in production and connect with the broadest range of data to generate the most complete and accurate predictions. "AI is becoming increasingly mainstream with 69% of organizations either already using or planning to use AI in the next 24 months. But even more, AI has clearly moved from the experimental phase to mission critical with businesses realizing real value from improved growth and revenue to cost reduction to operational efficiency. Now more than ever, businesses need an AI platform that is adaptive, shifting and adjusting to even the most unpredictable market conditions." Jack Vernon, Senior Research Analyst, European AI Systems, IDC With AI Cloud 8.0, DataRobot enhances key innovations for every business, including: Predictive AI apps. DataRobot’s AI App Builder is extended with support for Automated Time Series, providing business consumers with the ability to help their organizations be more resilient and match the realities of today’s fluid and unpredictable market landscape. Recent Automated Time Series innovations including prediction explanation and segmented modeling can be fully brought to life in a no-code environment where AI applications can be rapidly built. Continuous optimization and trust. DataRobot’s Continuous AI capabilities are now available in on-premises environments along with leading public cloud platforms. These capabilities are especially powerful in enabling businesses to protect against real-world changes from prolonged pandemic conditions, changing economic climates, and shifting consumer behavior. Continuous AI automatically adapts and recommends the best model for predicting a desired business outcome given historical data and current conditions, to enable customers to protect performance in the future. Best in class connectivity and partner ecosystem. New integrations to Microsoft Active Directory and Scoring Code for Snowflake expand DataRobot’s extensive library of connections to data sources, data formats and business applications. This enhanced ecosystem accelerates time to value by enabling all businesses to work with an expanded library of models, a complete set of pre-built integrations, and write-back capabilities to the most popular cloud data stores. “Given today’s highly competitive and unpredictable job market, it’s critical that the tens of thousands of students enrolled at our university succeed academically,” said Dr. Hiselgis Perez, Associate Vice President, Analysis and Information Management, Florida International University. “With the help of DataRobot, we’re able to predict and identify at-risk students and proactively get them the academic support they need in order to stay on track and graduate. Our ability to quickly analyze data and make predictions for every student, has helped graduation rates triple over the past decade.” “Businesses today are navigating uncharted market challenges – from the lasting impact of the prolonged pandemic, to unreliable supply chains, to a rapidly approaching return to work,” said Nenshad Bardoliwalla, Chief Product Officer at DataRobot. “AI has the potential to help every business manage through this unprecedented time. But your AI platform must be able to anticipate and adapt faster and more intelligently to even the most unpredictable market conditions. With DataRobot AI Cloud 8.0, we’re empowering businesses to better anticipate moments of change and continuously optimize machine learning models, even those already in production, while driving new and more accurate decisions down to front line business users.” DataRobot AI Cloud 8.0 is available today to all businesses in a multi-cloud architecture. It is easily deployed to public clouds, on premises in the data center and at the edge, with unified management and operations. Learn more about DataRobot AI Cloud 8.0. About DataRobot DataRobot AI Cloud is the next generation of AI. DataRobot’s AI Cloud vision is to bring together all data types, all users, and all environments to deliver critical business insights for every organization. DataRobot is trusted by global customers across industries and verticals, including a third of the Fortune 50.

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GENERAL AI

Vectorspace AI Introduces Thematic Crypto Basket API for Exchange

Vectorspace AI | December 28, 2021

On December 22, Vectorspace AI, a Vector Space Biosciences subsidiary, released a thematic crypto basket API. It enables cryptocurrency exchanges by offering tradable crypto baskets with regard to a topic, event, or theme of any type in real-time. Through this API, retail traders and investors get an efficient ecosystem of new products. In addition, it provides enterprises handling advanced data engineering pipelines with abilities similar to asset management and hedge funds. It's like having your own dedicated NLP, AI, or Machine Learning pipeline, This opens up a new world of thematic investing where baskets of cryptos or stocks can be generated based on a theme or global event in real-time using similar 'language modeling' techniques used to predict the way proteins fold by DeepMind's AlphaFold2." Kasian Franks, Founder and CEO of Vector Space Biosciences, Inc. The thematic basket API from Vector Space AI can be used for several tasks, such as the following: Create short, long, or hedged positions among baskets Generate relationship networks and graph networks connecting stocks or cryptos Position capital across a network of thematic baskets consisting of stocks or cryptos Auto-create a no-click or one-click tradable basket of stocks or cryptos related to a topic, event, or theme in real-time The core crypto baskets API also introduced an additional filtering package called VectorScreen™. It allows advanced filtering and screening that results in additional alpha. It uses basic parameters to screen crypto baskets, such as sell pressure, liquidity, or market cap, along with advanced parameters such as fine-grained themes, concepts, or context. This API from VectorScreen™ will be available for retail and exchanges in the first quarter of 202i, enabled with a retail-driven UI/UX that will be available in the following quarter. The recently secured funding of $2 million will be used by Vector Space Biosciences to support global retail product offerings and product rollouts that will result in additional revenue.

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