Microsoft and Darktrace partner on cloud cybersecurity
has partnered with Cambridge-based AI startup and aims to provide AI-enhanced cyber security to organisations transitioning to the cloud. The partnership provides mutual customers with enterprise-scale, self-learning AI that detects and autonomously responds to cyber-threats.
This collaboration uses Darktrace’s self-learning AI for cyber security within Microsoft environments, including Microsoft 365 and cloud applications like Azure Sentinel.
The two companies are focusing on these critical areas:
- Cyber AI email security: Antigena Email, which uses Darktrace’s autonomous response technology to stop the most advanced email threats, is now hosted on Microsoft Azure and listed on Microsoft Azure Marketplace.
- Simplified and streamlined security workflows: Darktrace integrates with Azure Sentinel, with a bespoke Workbook allowing users to send and visualise Darktrace threat alerts and automated threat investigation reports inside Sentinel.
- Seamless data integration: Darktrace one-click integrations allow users to connect Darktrace’s AI detection capabilities to Microsoft Defender for endpoint.
, CEO, Microsoft UK, : “As cyber-attacks become increasingly sophisticated, AI is adding a deeper level of protection in detecting these threats. The partnership between Microsoft and Darktrace will help keep organisations secure, enabling them to focus on their core business and customers.”
Why is cloud security so important?
The COVID-19 pandemic forced many companies to move much of their business online, and while this sudden change helped protect employee safety, the rapid shift to doing business online also introduced multiple security and data protection issues.
Research conducted by shows that nearly a quarter (23%) of desktops and 17% of laptops supplied by UK employers lack security software – leaving those devices (and therefore the business) potentially vulnerable to cyber threats.
Cloud security is important for both business and personal users. Everyone wants to know that their information is safe and secure and businesses have legal obligations to keep client data secure. Security is an essential element of your cloud service and it is important to check that your service provider can provide the correct levels of security for your industry.
With the expectation that remote working is here to stay to some extent, for many businesses it is even more imperative to reinforce security awareness. Businesses can take steps including making sure security software, such as firewalls and antivirus software, are up to date, setting secure passwords, and ensuring all internet connections are secure.
Google launches Visual Inspection AI tool for manufacturers
Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped.
Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale.
How does it work?
The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.
Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI.
- Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor.
- Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps.
- Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers.
- Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
- Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.
Industry use cases
The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing.
Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”
Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture.