At its annual user conference this week, Redis Labs is disclosing the roadmap for Redis 7.0, the database pillar of Redis Enterprise, which will become generally available later in the year. The common thread among the new features and enhancements include expansion of multimodel database support; converged capabilities for managing and deploying AI/machine learning models in-database; and new features supporting stronger database consistency. The context for all this is that Redis is the most popular in-memory database, and one of the top ten ranked databases overall, according to db-Engines. Redis claims that in the AWS cloud, it is the most frequently used data platform -- at 28% of customers, outranking MySQL, PostgreSQL, DynamoDB, MongoDB, and others. And, as measured by monitoring provider DataDog, Redis is the most frequented data platform image running in Kubernetes StatefulSets.
What is AI? Everything you need to know about Artificial Intelligence On the open ocean, identifying vessels can be challenging. Governments and maritime insurers use the Automatic Identification System (AIS) to identify ships, but bad actors can easily "go dark." If a ship has deactivated its AIS beacons, there's a chance it could be involved in smuggling, piracy, illegal fishing or human trafficking. Hawkeye 360 is a data analytics company that aims to address this challenge using space-based radio frequency (RF) mapping. The six year-old company, headquartered in Herndon, Virginia, operates a constellation of commercial satellites to detect, characterize and geolocate a broad range of RF signals.
A robot that's developed something of a mythology over the years now has a new trick. Snakebot, named ground rescue robot of the year in 2017 and helping its creator win the "Oscars of automation" in 2019, can now swim. The robot consists of several actuated joints that work together to produce a range of motions. Snakebot can stand slither, roll, stand up to pull itself over obstacles, and climb a variety of objects and surfaces. CMU robotics professor Howie Choset and systems scientist Matt Travers are the brains behind Snakebot.
Sony AI and Korea University have jointly developed an artificial intelligence mapping tool called FlavorGraph that can recommend complementary ingredient pairings to help chefs come up with dishes. According to Sony AI, FlavorGraph uses AI to predict the pairing fit of two ingredients by combining information drawn from 1,561 flavour molecules found in different ingredients together with the way the ingredients have been used in millions of past recipes. "As well as relationships between food ingredients and flavour compounds that have not been explored before, the FlavorGraph research will allow greater flexibility for matching single or multiple ingredients to many others," a blog post penned by Sony AI strategy and partnership manager Fred Gifford and Korea University post-doctoral researcher Donghyeon Park said. "As the science develops and we get ever better representations of food, we should discover more and more intriguing pairings of ingredients, as well as new substitutes for ingredients that are either unhealthy or unsustainable." The development of FlavorGraph is one of the first projects to come from Sony AI's gastronomy flagship project. Launched at the end of last year, the machine learning and AI research arm of the Japanese tech conglomerate touted the project would focus on three key areas: An AI application for new recipe creation, a robotics solution that can assist chefs in the kitchen, and a community co-creation initiative.
Ocado is investing £10 million in Oxford-based start-up Oxbotica, which develops autonomy software for vehicles. Online retailer Ocado is exploring the possibility of having robots packing, transporting and delivering groceries all the way to customers' kitchens, with a new partnership designed to bring new levels of automation to the warehouse. The British e-tailer is investing £10 million ($14 million) in Oxford-based start-up Oxbotica, which develops autonomy software for vehicles, with the objective of testing different ways of integrating the technology with Ocado's hardware. Among the projects envisioned by the two firms feature autonomous vehicles travelling inside Ocado's warehouses to move orders around the buildings and surrounding yard areas, but also driverless delivery vans and even "kerb-to-kitchen" robots to facilitate what is known as last-mile logistics – the final steps between a customer's doorstep and the vehicle carrying their order. Automating these processes could cut costs significantly.
Mastercard said it will acquire Ekata for $850 million in a deal that will bolster its identity verification technology. Ekata's application programming interfaces (APIs) and tools are used by merchants, marketplaces and financial firms across multiple industries. Ekata's platform provides artificial intelligence enhanced risk scoring, indicators and data attributes. The purchase of Ekata will also bolster Mastercard's digital identity and security framework. Ekata offers a bevy of identify verification services to prevent fraud.
Google on Monday said that it's partnering with Siemens to advance AI deployments in industrial use cases. More specifically, Siemens is integrating Google Cloud data analytics and AI capabilities into its Digital Industries Factory Automation portfolio. The integration gives Google a major partner in the manufacturing space, one of six key verticals the cloud company is targeting. The integration, the companies said, should make it easier for manufacturers to manage factory data, run cloud-based AI and machine learning models on top of it, and deploy algorithms at the network edge. Over the next few months, the companies will have share more about the specific Google Cloud tools that will be integrated into the Siemens portfolio and offered as a joint solution, a Google spokesperson told ZDNet.
Adversaries are turning their focus on cheaper, easier targets within an organisation's supply chain, especially as businesses increasingly acquire software from external suppliers. In this first piece of a two-part feature, ZDNet looks at how organisations in Asia-Pacific are facing more risks even as the perimeter they need to protect extends far beyond their own networks. There had been a spate of third-party cybersecurity attacks since the start of the year, with several businesses in Singapore and across Asia impacted by the rippling effects of such breaches. Just last month, personal details of 30,000 individuals in Singapore might have been illegally accessed following a breach that targeted a third-party vendor of job-matching organisation, Employment and Employability Institute (e2i). Earlier this year, personal data of 580,000 Singapore Airlines (SIA) frequent flyers as well as 129,000 Singtel customers also were compromised through third-party security breaches.
The reason why we use the cloud so much is the bottom line: Saving money. StormForge, a start-up specializing in reducing cloud waste with machine learning (ML) and artificial intelligence (AI) has found in its recent survey that businesses waste over $17-billion a year on unused or idle cloud resources. Now, it's not that companies have an unrealistic view of what they're going to be spending. Ninety-four percent say they know, at least roughly, what their cloud spend will be each month. The bad news is they also estimate that nearly half of their cloud spend is wasted on unused or idle resources.
To say Kubernetes, everyone's top container orchestration pick, is hard to master is an understatement. Kubernetes doesn't have so much as a learning curve as it does a learning cliff. But, Canonical's MicroK8s lets you learn to climb it in your home. And, with its latest release, it's easier than ever to set up a baby Kubernetes cluster using inexpensive Raspberry Pi or NVIDIA Jetson single-board computers (SBC). MicroK8s is a tiny Kubernetes cluster platform.