Quantum is developing AI software that can inspect unstructured data stored in its StorNext file system and ActiveScale object storage to identify content in videos, images and documents. The extent of this was revealed in an interview with Quantum's technical director for AI and Cloud, Plamen Minev, published in Authority magazine. Minev works in the Quantum CTO office. Quantum has already developed its AI and ML Content Enhancement Solution powered by the CatDV media asset management system and StorNext file management. This can perform object recognition within video frames, carry out speech-to-text translation, provide video and audio super-resolution, and add metadata to video and image files.

But applied correctly it can make IT infrastructure disappear. But Ronak Chokshi, who leads product marketing for InfoSight at HPE, argues that when considering how to better manage their infrastructure, tech leaders need to consider what services like Uber or Google Maps have achieved. The IT infrastructure behind the delivery of these services is immaterial to the rest of the world – except perhaps for frazzled tech leaders in other sectors who wonder how they could achieve similarly seamless operations. "The consumers don't really care how it works, as long as the service is available when needed, and it's easy to manage," he says. Or, to put another way, says Chokshi, InfoSight worries about the infrastructure, so tech teams can be more application-centric.

Machine learning and forensic tools to detect, diagnose and speed data recovery;; Corruption detection with post-attack forensics to identify last …

WekaIO's President sees the company as the Tesla of storage suppliers, and says OEM Hitachi Vantara is making inroads into the Dell EMC Isilon customer base as Weka crosses the chasm between it and general enterprise use. WekaIO's scalable, parallel and high-performance filesystem software has made its name in high-performance computing and become popular in enterprises that have HPC use cases -- such as AI, machine learning, and genomics. It's now set to cross over into more general enterprise file workloads. BMW motorcycle-riding Jonathan Martin became WekaIO's President this month. He had previously been the Chief Marketing Officer at Hitachi Vantara, serving from March 2019 to May 2021.

Sponsored Artificial Intelligence techniques have been finding their way into business applications for some time now. From chatbots forming the first line of engagement in customer services, to image recognition systems that can identify defects in products before they reach the end of the production line in a factory. But many organisations are still stuck at where to start in building machine-learning and deep-learning models and taking them all the way from development through to deployment. Another complication is how to deploy a model onto a different system than the one that was used to train it. Especially for situations such as edge deployments, where less compute power is available than in a datacentre.

WekaIO has devised a "production-ready" framework to help artificial intelligence installations to speed up their storage data transfers. The basic deal is that WekaIO supports Nvidia's GPUDirect storage with its NVMe file storage. Weka says its solution can deliver 73 GB/sec of bandwidth to a single GPU client. The Weka AI framework omprises customisable reference architectures and software development kits, centred on Nvidia GPUs, Mellanox networking, Supermicro servers (other server and storage hardware vendors are also supported) and Weka Matrix parallel file system software. Paresh Kharya, director of product management for accelerated computing at Nvidia, provided a quote: "End-to-end application performance for AI requires feeding high-performance Nvidia GPUs with a high-throughput data pipeline. Weka AI leverages GPUDirect storage to provide a direct path between storage and GPUs, eliminating I/O bottlenecks for data intensive AI applications."

Workflow-integrated storage supplier Iguazio has received $24m in C-round funding and announced its Data Science Platform. This is deeply integrated into AI and machine learning processes, and accelerates them to real-time speeds through parallel access to multi-protocol views of a single storage silo using data container tech. The firm said digital payment platform provider Payoneer is using it for proactive fraud prevention with real-time machine learning and predictive analytics. Yaron Weiss, VP Corporate Security and Global IT Operations (CISO) at Payoneer, said of Iguazio's Data Science Platform: "We've tackled one of our most elusive challenges with real-time predictive models, making fraud attacks almost impossible on Payoneer." He said Payoneer had built a system which adapts to new threats and enables is to prevent fraud with minimum false positives.

VMware is developing a cloud service to monitor software in customer deployments and tune it automatically to improve performance. This is Project Magna and its first target is vSAN in hyperconverged infrastructure. It will work like this: customers select their key performance indicator – read or write optimisation or both. Magna examines their vSAN environment and compares it to the KPI average for stored and monitored deployments. If the site is below average, Magna changes it to bring it closer to the average.

Oracle has pushed out Exadata X8, the latest iteration of its engineered system optimised for the Oracle database. Unveiled today, the Oracle Exadata Database Machine X8 introduces machine-learning capabilities drawn from the Oracle Autonomous Database. These include Automatic Indexing, which continuously tunes the database as usage patterns change. The Exadata X8 also incorporates automated performance monitoring which can determine the root cause of issues without human intervention, according to Oracle. The company said the software does this using AI combined with real-world performance triaging experience and best practices.