In a landmark moment, Sonar is proud to announce the acquisition of the technology and services of AI/NLP experts as they work to expedite the implementation of AI on the Sonar Platform. Meet Raghav and Josh, the newest additions to the ever growing group of developers, innovators, and dreamers who are working tirelessly to bring forth the complete vision of the Sonar Platform. Joining with us several months ago, we have now reached a developmental position to publicly announce their presence! Raghav has over 4 years of blockchain development experience, with a Master's Degree in Artificial Intelligence. Previously, he has founded an AI startup with over 7.5 million active users, and is specialized in bringing AI research to production systems. Josh has over 10 years of programming experience with expertise in Data Engineering and Web Scraping, as well as over 5 years of blockchain development in production systems.

MindsDB announces an integration with MariaDB to enable machine learning to the wildly popular open source relational database, furthering the mission to democratize machine learning. MindsDB, the open source AI layer for existing databases, today announced their official integration with the widely used open source relational database, MariaDB Community Server. This integration fills a longstanding demand of database users for the ability to bring machine learning capabilities to the database and democratize ML use. MindsDB helps apply machine learning models straight in the database by providing an AI layer that allows database users to deploy state-of-the-art machine learning models using standard SQL queries. The use of AI-Tables helps database users leverage predictive data inside the database for easier and more effective machine learning projects.

Companies of all sizes are not satisfied with their machine learning process and various challenges to widespread adoption remain. SEATTLE, Oct. 16, 2018 (GLOBE NEWSWIRE) -- Algorithmia announces the results of a survey on enterprise machine learning. The comprehensive survey, titled "State of Enterprise Machine Learning," is a first for Algorithmia and was designed to explore the ways in which companies of all sizes are utilizing machine learning. The survey was completed by over 500 data science and machine learning professionals, the majority of whom were based in North America. A report detailing the survey's findings can be foundhere.

Algorithmia today announced the commercial availability of a new tool to help companies take their machine learning models from experimentation to production. Called the Algorithmia AI Layer, the system is designed to help companies deal with the operation, integration, security, scaling, and other tasks around bringing machine learning out of the lab. It's a problem that comes up when businesses are ready to start implementing the AI models that they've built, which can often take a while. Algorithmia's own business over the past several years has positioned it to provide this AI layer. The Seattle-based startup has been operating a massive marketplace for intelligent algorithms (hence the name), which means that the team had to build a system just for running machine learning models in production with security, isolation, scalability and other key performance traits built in.

Algorithmia started out as an online marketplace for -- can you guess it? Many of these algorithms that developers offered on the service focused on machine learning (think face detection, sentiment analysis, etc.). Today, with the boom in ML/AI, that's obviously a big draw and Algorithmia is now taking its next step in this direction with the launch of a new service that helps data scientists manage and deploy their machine learning models -- and share them with others inside their companies. This basically means that the company is turning some of the infrastructure and services it built to run these models itself into a new product. "Tensorflow is open-source, but scaling it is not," said Kenny Daniel, co-founder and CTO of Algorithmia, in today's announcement.

Implementing Enterprise AI is a unique and limited edition course that is focussed on AI Engineering / AI for the Enterprise. The course is launched for the first time and has limited spaces. Created in partnership with H2O.ai, the course uses Open Source technology to work with AI use cases. Successful participants will receive a certificate of completion and also validation of their project from H2O.ai. The course targets developers and Architects who want to transition their career to Enterprise AI.

Did you know there are over 3,874 companies offering marketing technology? That's how many companies are featured on Scott Brinker's behemoth 2016 Marketing Technology Landscape Supergraphic, which drives home the challenge of navigating the marketing industry. "Marketing has the unique challenge of not having a typical stack or process. If you look into any Fortune 500 company, they will have hundreds of products that they are stitching together," says Eric Stahl, an SVP of Product Marketing at Salesforce. Leading marketing experts agree that the plethora of tools available to marketers and advertisers is both a blessing and a curse.

The Internet of Things is a powerful technological force. So many devices and activities in our personal and professional lives are connected to it--from smartphones and activity trackers to huge manufacturing centers and medical devices, more and more things are being connected to the IoT every day and transforming how we live and work. At the same time, artificial intelligence technology is also developing rapidly, with 80% of the world's largest companies having incorporated some kind of cognitive technology into their products. AI trains computers to take on some human forms and tasks and expands the world of technological possibilities to combine machine learning and human creativity. With two large technological movements making waves around the world, it makes sense to combine them and add an AI layer to the IoT.

Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit's work involves applying machine learning techniques to complex problems in the IoT and Telecoms domains. You can follow him on twitter @AjitJaokar and his blogs at Future Text. We are beyond thrilled to announce that Ajit will not only be speaking at our Big Data, Berlin meetup February 17, but he will also be at the head of the second workshop of our'Dataconomy Presents' series.

Implementing Enterprise AI is a unique and limited edition course that is focussed on AI Engineering / AI for the Enterprise. The course is launched for the first time and has limited spaces. Created in partnership with H2O.ai, the course uses Open Source technology to work with AI use cases. Successful participants will receive a certificate of completion and also validation of their project from H2O.ai. The course targets developers and Architects who want to transition their career to Enterprise AI.