More Than You Know: The Enterprise Worth of Natural Language Generation
In this contributed article, editorial consultant Jelani Harper highlights how Natural Language Generation (NLG) is arguably the nexus point of natural language technologies. It utilizes Natural Language Processing (NLP), is a prerequisite for conversational AI, and largely requires Natural Language Understanding (NLU) for meaningful responses to interrogatives or commands.
Featured Stories
“Above the Trend Line” – Your Industry Rumor Central for 6/23/2022
Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.
Streamlining Data Evolution in a Rapidly Changing World
In this contributed article, Adam Glaser from Appian believes that in a fast-changing, digital-driven world, having access to the right data at the right time is crucial. That is why, as data evolves, it must be brought together in a reliable and efficient way that creates a powerful asset, not a compliance challenge.
Making a Case for the First Open Source Platform for Synthetic Data
In this special guest feature, Yashar Behzadi, Ph.D., CEO and Founder of Synthesis AI, discusses on the importance of a community like OpenSynthetics in developing more capable AI models. OpenSynthetics, an open community for creating and using synthetic data in AI/ML and computer vision, is open to practitioners, researchers, academics, and the wider industry.
Featured Resource
Sponsored by: ImplyReal-Time Analytics from Your Data Lake Teaching the Elephant to Dance
This whitepaper from Imply Data Inc. introduces Apache Druid and explains why delivering real-time analytics on a data lake is so hard, approaches companies have taken to accelerate their data lakes, and how they leveraged the same technology to create end-to-end real-time analytics architectures.
Industry Perspectives
Artificial Intelligence & Data Analytics in the Last Mile Logistics
In this special guest feature, Anar Mammadov, Founder of Senpex, highlights how delivery logistics companies have powerful artificial intelligence, data analysis tools at their disposal, and part of the innovation in this field has been ensuring that clients can access this data. An analytic dashboard allows clients to understand what is happening with their delivery orders and ensure that their precious business is in the right hands.
Don’t Call It A “Data Product” Unless It Meets These 5 Requirements
In this special guest feature, Barr Moses, Co-founder and CEO of Monte Carlo, believes data products can transform an organization’s ability to be data-driven as long as they meet 5 key requirements. Data products can transform an organization’s ability to be data-driven, as long as they are implemented correctly and in good faith.
Featured from insideHPC
- Cerebras Claims Record for Largest AI Models Trained on a Single DeviceSUNNYVALE, Calif., June 22, 2022 — AI computing company Cerebras Systems today announced that a single Cerebras CS-2 system is able to train models with up to 20 billion parameters on – something not possible on any other single device, according to the company. By enabling a single CS-2 to train these models, Cerebras said […]
News from insideHPC
- TSMC Japan 3DIC R&D Center Completes Clean Room Construction in AIST Tsukuba Center
- Argonne to Host DeepHyper Training Session July 15
- Scalable Inferencing for Autonomous Trucking
- AMD Appoints Mathew Hein Chief Strategy Officer
- Rockport Networks Taps Phil Harris as CEO
- Cerebras Claims Record for Largest AI Models Trained on a Single Device
- @HPCpodcast: Google’s Lifelike LaMDA AI Chatbot and Questions of Being or Nothingness
Editor’s Choice
The insideBIGDATA IMPACT 50 List for Q2 2022
This special technology guide from Dell Technologies and AMD will take a closer look at some of the biggest disruptors affecting energy companies, and also examine how big data analytics can help these firms reduce risk, drive down costs, and improve efficiency. The energy industry has always faced large price swings as a result of changes in the global economy. But today, this entire sector is facing an unprecedented level of disruption. Industry analysts say it is in the throes of a dramatic upheaval that is requiring companies in this industry to reinvent themselves.
Big Data Industry Predictions for 2022
Welcome to insideBIGDATA’s annual technology predictions round-up! The big data industry has significant inertia moving into 2022. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an
The Amazing Applications of Graph Neural Networks
In this contributed article, editorial consultant Jelani Harper points out that a generous portion of enterprise data is Euclidian and readily vectorized. However, there’s a wealth of non-Euclidian, multidimensionality data serving as the catalyst for astounding machine learning use cases.
Infographic: The Rise of No-Code Development Platforms
Our friends over at Saas Platform company in Ireland called TeamKonnect have developed new infographic called “The Rise of No-Code Development Platforms” which is provided below. This infographic is a 101 guide to No-Code Development Platforms. Rising in popularity in the last decade, these platforms offer an exciting opportunity for businesses and organizations to develop apps that meet their needs without the engagement of software engineers.
What is the Difference Between Business Intelligence, Data Warehousing and Data Analytics
In this contributed article, Christopher Rafter, President and COO at Inzata,, writes that in the age of Big Data, you’ll hear a lot of terms tossed around. Three of the most commonly used are “business intelligence,” “data warehousing” and “data analytics.” You may wonder, however, what distinguishes these three concepts from each other so let’s take a look.
