IBM Watson improves AI automation and increases NLP precision, C3.ai announced winners in its COVID-19 Grand Challenge, and more.
Keeping pace with news and developments in the market can be a daunting task. We want to help by providing a summary of some of the real-time analytics items our staff came across each week. Here is a short list of some news from this week:
IBM announced new capabilities planned for IBM Watson designed to help scale the use of AI by businesses. Developed by IBM Research, the new capabilities are designed to improve the automation of AI, provide a higher degree of precision in natural language processing, and foster greater trust in outcomes derived from AI predictions. They include:
- Reading Comprehension is based on an innovative question-answering (QA) system from IBM Research. Currently in beta in IBM Watson Discovery, it is planned as a new feature that can help identify more precise answers in response to natural language queries from vast troves of complex enterprise documents. It also provides scores that indicate how confident the system is in each answer.
- FAQ Extraction uses a novel NLP technique from IBM Research to automate the extraction of Q&A pairs from FAQ documents. Currently in beta in IBM Watson Assistant’s search skill, it is planned as a new feature to help businesses keep virtual assistants up-to-date with the latest answers and reduce the time-consuming process of manual updates.
- A new intent classification model is now available in IBM Watson Assistant. It is designed to understand an end user’s goal or intent when engaging more accurately with a virtual assistant and to enable administrators to train the system faster. The model provides more accurate results from less data versus compared to commercial systems. This can help businesses go live with virtual assistants in a few days while achieving high accuracy.
- IBM Watson Discovery now includes support for ten new languages, including Bosnian, Croatian, Danish, Finnish, Hebrew, Hindi, Norwegian (Bokmål), Norwegian (Nynorsk), Serbian and Swedish. IBM has continued to add support for additional languages to help businesses build global, enterprise-grade NLP solutions.
C3.ai announced the winners of the C3.ai COVID-19 Grand Challenge. Launched on Sept. 15, the global competition encouraged developers, data scientists, students, and creative minds to build world-class data science techniques and strategies that accelerate novel COVID-19 research and drive smart and safe decision-making. The grand prize winner received $100,000. The project was titled: Combined Diagnostics – Modeling Population Heterogeneity and Personalized COVID Diagnostics. It predicts an individual’s infectious and susceptibility status and the probability of having COVID-19. The team applied the Bayesian Stochastic Expectation-Maximization method to demographics, individual health characteristics, and behavioral and geographical data to provide personalized estimates for each individual’s infectious and susceptibility statuses. (Freddy Bunbury – Carnegie Institution for Science, Nina Miolane – University of California, Santa Barbara, and Claire Donnat – University of Chicago). Six additional projects were awarded second and third place prizes.
Fetch.ai announced the launch of its CoLearn network. This collective AI learning system lets multiple parties distributed anywhere across the globe to work together to train machine learning models to detect COVID-19 patients from X-ray scans. CoLearn provides hospitals and doctors with a network in which they can use their own private data, in the form of chest X-rays, that have been labeled according to whether the patients with pneumonia have tested positive for COVID-19 serving as a rapid diagnostic tool. It can also be used to identify the severity of a patient’s condition, including recognizing the need for intubation or the need for supplemental oxygen.
Calligo launched a Machine Learning Service (MLaaS) to simultaneously address the key obstacles to the adoption of machine learning: cost, data quality, complexity, security, accuracy, and data privacy. The fully-managed service provides quick, actionable insights that solve business problems. The service is supported by Calligo’s Data Insights Platform. The platform is built upon Calligo’s own public cloud technology, CloudCore, which is purpose-built for machine learning workloads. It is highly secure and the first to be built with data privacy at its heart. On top of CloudCore sits Mind Foundry’s flexible, efficient machine learning software that delivers accurate insights fast.
Xanadu announced PennyLane, its open-source software for differentiable quantum computing, is now integrated with Amazon Braket, a fully managed quantum computing service from Amazon Web Services (AWS). Customers using Amazon Braket can use PennyLane to speed the development of variational quantum algorithms and quantum machine learning (QML) applications. PennyLane provides a powerful and flexible programming framework that makes it easy and intuitive to explore hybrid approaches to quantum computing. Together with Amazon Braket, it seamlessly integrates classical machine learning (ML) libraries with quantum hardware and simulators, giving users the power to train quantum algorithms in the same way they train neural networks.
Varada unveiled its data virtualization platform, which helps organizations instantly monetize all of their available data with a predictable and controlled budget. Using a dynamic indexing technology, the Varada Data Platform enables data teams to balance performance and cost of queries at massive scale without ceding control of their data to third-party vendors. The Varada Data Platform currently runs on AWS and supports reserved, on-demand, and spot instances. Pricing is per-node, based on a predefined scaling group. The Varada Data Platform is available on AWS Marketplace with integrated billing through AWS or via AMI (Amazon Machine Image). Enterprise support is also available from Varada.
Digital Asset announced commercial support for DAML for Azure Database and its availability through Microsoft AppSource, an online cloud marketplace providing tailored line-of-business solutions. DAML for Microsoft Azure Database is built on Digital Asset’s DAML Driver for PostgreSQL, which takes advantage of the highly-available and resilient Azure Database stack to enable businesses to automate internal multiparty workflows backed by a managed database offering they can trust.
ThoughtSpot announced ThoughtSpot One, a new product built for the cloud for business users to consume, share, and act on data-driven insights with the same ease of use as the most popular consumer apps. ThoughtSpot One radically expands the platform’s search capabilities, built and delivered for ThoughtSpot Cloud, the only fully managed SaaS platform for search and AI-driven analytics.
Comet ML, a provider of machine learning operations (MLOps) solutions, announced updates to Comet Workspaces, including the introduction of Interactive Reports, ML Templates, and the industry’s first workflow for proactively considering carbon emissions as part of the machine learning process. Comet Enterprise automates experiment and model management, automatically tracking data sets, code changes, experimentation history, and models all at scale. One key component is Comet Workspaces. Since its inception, Comet Workspaces has provided a one-stop-shop for data science and machine learning teams to consolidate, control, and collaborate on machine learning projects and experiments.
SambaNova Systems announced the availability of SambaNova Systems DataScale. Built on SambaNova Systems Reconfigurable Dataflow Architecture (RDA), SambaNova DataScale is optimized for dataflow from the algorithms to the silicon, enabling enterprises to bring new services and products to market faster than today’s state-of-the-art solutions. Also being announced was its Dataflow-as-a-Service offering, which makes the SambaNova DataScale system available via a monthly subscription service.
Cogito, the developer of AI Coaching Systems that augments professionals enabling organizations to deliver empathy at scale, announced advances in its human-aware technology. With meaningful enhancements, including a novel approach to AI called Signal-Based Machine Learning, Cogito’s coaching system understands human behavior, provides personalized, contextual guidance, and powerful insights throughout the call center ecosystem.
Real-time analytics news in brief:
NVIDIA announced the Applied Research Accelerator Program. The program, which will initially focus on robotics and autonomous machines, supports applied research on NVIDIA platforms for GPU-accelerated application deployments.
NTT DATA Services has agreed to acquire Hashmap, adding deep technical expertise with modern data platforms to support analytics, artificial intelligence, and machine learning.
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In case you missed it, here are our most recent previous weekly real-time analytics news roundups: