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Microsoft Adds Ways for Customers on AI with Azure

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Elevators that respond to voice commands, cameras that notify store managers when to restock shelves and video streams that keep tabs on everything from cash register lines to parking space availability.

Microsoft Adds Ways for Customers on AI with Azure

These are a few of the millions of scenarios becoming possible thanks to a combination of artificial intelligence and computing on the edge. Standalone edge devices can take advantage of AI tools for things like translating text or recognizing images without having to constantly access cloud computing capabilities, according to John Roach, Executive Architect, Digital Transformation Services, Microsoft.

At its Ignite digital conference, Microsoft unveiled the public preview of Azure Percept, a platform of hardware and services that aims to simplify the ways in which customers can use Azure AI technologies on the edge – including taking advantage of Azure cloud offerings such as device management, AI model development and analytics.

Roanne Sones, corporate vice president of Microsoft’s edge and platform group, said the goal of the new offering is to give customers a single, end-to-end system, from the hardware to the AI capabilities, that “just works” without requiring a lot of technical know-how.

The Azure Percept platform includes a development kit with an intelligent camera, Azure Percept Vision. There’s also a “getting started” experience called Azure Percept Studio that guides customers with or without a lot of coding expertise or experience through the entire AI lifecycle, including developing, training and deploying proof-of-concept ideas.

For example, a company may want to set up a system to automatically identify irregular produce on a production line so workers can pull those items off before shipping.

Azure Percept Vision and Azure Percept Audio, which ships separately from the development kit, connect to Azure services in the cloud and come with embedded hardware-accelerated AI modules that enable speech and vision AI at the edge, or during times when the device isn’t connected to the internet.

That’s useful for scenarios in which the device needs to make lightning-fast calculations without taking the time to connect to the cloud, or in places where there isn’t always reliable internet connectivity, such as on a factory floor or in a location with spotty service.

The Azure Percept platform makes it easy for anyone to deploy artificial intelligence on the edge. Devices include a Trusted Platform Module (center), Azure Percept Audio (left) and Azure Percept Vision (right). Photo credit: Microsoft

In addition to announcing hardware, Microsoft says it is working with third-party silicon and equipment manufacturers to build an ecosystem of intelligent edge devices that are certified to run on the Azure Percept platform, Sones said.

“We’ve started with the two most common AI workloads, vision and voice, sight and sound, and we’ve given out that blueprint so that manufacturers can take the basics of what we’ve started,” she said.

“But they can envision it in any kind of responsible form factor to cover a pattern of the world.”

Making AI at the edge more accessible

The goal of the Azure Percept platform is to simplify the process of developing, training and deploying edge AI solutions, making it easier for more customers to take advantage of these kinds of offerings, according to Moe Tanabian, a Microsoft vice president and general manager of the Azure edge and devices group.

For example, most successful edge AI implementations today require engineers to design and build devices, plus data scientists to build and train AI models to run on those devices. Engineering and data science expertise are typically unique sets of skills held by different groups of highly trained people.

“With Azure Percept, we broke that barrier,” Tanabian said. “For many use cases, we significantly lowered the technical bar needed to develop edge AI-based solutions, and citizen developers can build these without needing deep embedded engineering or data science skills.”

The hardware in the Azure Percept development kit also uses the industry standard 80/20 T-slot framing architecture, which the company says will make it easier for customers to pilot proof-of-concept ideas everywhere from retail stores to factory floors using existing industrial infrastructure, before scaling up to wider production with certified devices.

As customers work on their proof-of-concept ideas with the Azure Percept development kit, they will have access to Azure AI Cognitive Services and Azure Machine Learning models as well as AI models available from the open-source community that have been designed to run on the edge.

In addition, Azure Percept devices automatically connect to Azure IoT Hub, which helps enable reliable communication with security protections between Internet of Things, or IoT, devices and the cloud. Customers can also integrate Azure Percept-based solutions with Azure Machine Learning processes that combine data science and IT operations to help companies develop machine learning models faster.

In the months to come, Microsoft aims to expand the number of third-party certified Azure Percept devices, so anybody who builds and trains a proof-of-concept edge AI solution with the Azure Percept development kit will be able to deploy it with a certified device from the marketplace, according to Christa St. Pierre, a product manager in Microsoft’s Azure edge and platform group.

“Anybody who builds a prototype using one of our development kits, if they buy a certified device, they don’t have to do any additional work,” she said.

Security and responsibility

Because Azure Percept runs on Azure, it includes the security protections already baked into the Azure platform, the company says.

Microsoft also says that all the components of the Azure Percept platform, from the development kit and services to Azure AI models, have gone through Microsoft’s internal assessment process to operate in accordance with Microsoft’s responsible AI principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.

The Azure Percept team is currently working with select early customers to understand their concerns around the responsible development and deployment of AI on edge devices, and the team will provide them with documentation and access to toolkits such as Fairlearn and InterpretML for their own responsible AI implementations.

Ultimately, Sones said, Microsoft hopes to enable the development of an ecosystem of intelligent edge devices that can take advantage of Azure services, in the same way that the Windows operating system has helped enable the personal computer marketplace.

“We are a platform company at our core. If we’re going to truly get to a scale where the billions of devices that exist on the edge get connected to Azure, there is not going to be one hyperscale cloud that solves all that through their first-party devices portfolio,” she said. “That is why we’ve done it in an ecosystem-centric way.”

 


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What the Retail and E-commerce Sector Should Expect in 2026 in Era of AI-driven Shopping and Privacy

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In 2025, the retail and e-commerce sector continued to face intense pressure from cybercriminals. According to Kaspersky data, 14,41%* of users in the global retail sector encountered web-based threats, while 22,20% were affected by on-device attacks.

Ransomware remains a serious concern for the industry. Last year, 8,25% of retail and e-commerce companies experienced ransomware incidents, and the number of unique B2B users in the sector affected by ransomware detections rose by 152% compared to 2023, signalling a sharp escalation in targeted attacks.

Phishing also continues to be a major threat vector. Kaspersky identified 6.7 million phishing attacks targeting users of online stores, delivery services, and payment systems in 2025. More than half of these attacks (50,58%) were aimed specifically at online stores, underscoring cybercriminals’ focus on e-commerce platforms as high-value targets for fraud and data theft.

A look at 2025 cybersecurity for retail & e-commerce: Trends and what happened

A stealer with a taste for pizza delivery. Shopping and food ordering via mobile apps are routine user behaviours. However, 2025 demonstrated that even downloading a seemingly legitimate app from an official app store does not guarantee safety, nor does it ensure that user data and financial credentials will not be compromised.

Ransomware detections in the B2B sector increased due to a single dominant actor. The number of unique users in the Retail & E-commerce sector who encountered ransomware detections increased by 152% in 2025 compared to 2023 (Nov 2024 – Oct 2025 vs. Nov 2022 – Oct 2023).

The most significant growth occurred during the 2024-2025 period and is largely attributable to the rapid spread of the Trojan-Ransom.Win32. Dcryptor family, which became highly prevalent across the retail and e-commerce sector in some of the analysed markets. This malware is a trojanised ransomware variant that leverages the legitimate DiskCryptor utility to encrypt disk partitions on victim systems.

Phishing activity in the online retail segment stood out. Despite being a long-established attack technique, phishing remains highly prevalent in the context of online purchasing.

From November 2024 through to October 2025, Kaspersky products blocked 6,651,955 attempts to access phishing links targeting users of online stores, payment systems, and delivery services. Of these attempts, 50.58% targeted online shoppers, 27.3% impersonated payment systems, and 22.12% targeted users of delivery companies.

Sales seasons continue to do the work for attackers. Seasonal peaks in online shopping consistently provide attackers with predictable opportunities to scale user-focused attacks.

Periods of heightened promotional activity lower user vigilance and allow familiar phishing and spam scenarios to blend into legitimate marketing traffic, increasing their overall effectiveness.

Predictions: What retail & e-commerce cybersecurity might face in 2026

Chatbots are likely to become a common product discovery tool across online marketplaces. Unlike traditional search, conversational interfaces encourage users to share more detailed, natural-language requests, revealing preferences, constraints, and contextual information.

This shift expands the privacy attack surface, as platforms accumulate richer user profiles through chat interactions. As a result, chatbot logs may become as sensitive as transactional data, increasing the risks of over-collection, misuse, or exposure of personal information.

“Search itself is changing, including how people look for products online. In 2025, there was a gradual shift from simple keyword queries to more conversational and visual ways of finding what to buy. As these models rely on broader user input, careful handling of the data involved will remain an important consideration for maintaining user trust,” comments Anna Larkina, Web data and privacy analysis expert at Kaspersky.

Changes in taxes and trade rules might be exploited in online fraud. Modifications in taxes, import duties, and cross-border trade rules are likely to be used as lures in phishing campaigns and fraudulent online stores, promoting unrealistically cheap offers or claims of avoided fees.

As pricing and fee rules continue to evolve across markets, it may lower vigilance, increasing the effectiveness of such schemes, particularly against small and mid-sized retailers.

AI-powered shopping assistants are expected to increasingly operate outside retail platforms, embedding themselves into browsers, mobile apps, and third-party services. While designed to simplify navigation and price discovery, these tools shift data collection beyond the retailer’s perimeter, creating new and less visible privacy risks.

To function effectively, external AI shopping agents require continuous access to user behaviour, including browsing activity, search intent, location context and product interactions across multiple sites.

This enables the aggregation of detailed behavioural profiles outside the direct control of both users and retail platforms, increasing the risks of over-collection, opaque data usage, and unintended exposure.

Image-based product search might become a new challenge in privacy risks. Previously, the main privacy concern around user images in e-commerce was limited to photos voluntarily shared in product reviews.

However, image-based product search is expected to make photo uploads a routine part of the shopping experience across major retail platforms. While this feature improves product discovery, it also increases the risk of unintended exposure of personal data.

User-submitted images may contain faces, home environments, or sensitive details, such as names, phone numbers, or addresses visible on shipping labels or packaging, making secure processing, data minimisation, and limited retention critical requirements for retailers.


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Elon Musk Seeks $134Bn from OpenAI, Microsoft for ‘Wrongful Gains’

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Elon Musk, billionaire Tesla owner, has asked a United States (US) federal court to award him up to $134 billion in damages from OpenAI and Microsoft, stating that the companies earned “wrongful gains” from his early support of the artificial intelligence startup.

Elon Musk Seeks $134Bn from OpenAI, Microsoft for ‘Wrongful Gains’

Elon Musk,

This is according to a court filing, reported by Reuters.

In filings ahead of a trial expected to start in April in Oakland, California, Musk stated that OpenAI benefited between $65.5 billion and $109.4 billion from his contributions when he helped co-found the organisation in 2015, and Microsoft gained between $13.3 billion and $25.1 billion through its involvement.

He has asked a United States (US) federal court to award him up to $134 billion in damages from OpenAI and Microsoft, stating that the companies earned “wrongful gains” from his early support of the artificial intelligence startup.

This is according to a court filing, reported by Reuters.

In filings ahead of a trial expected to start in April in Oakland, California, Musk stated that OpenAI benefited between $65.5 billion and $109.4 billion from his contributions when he helped co-found the organisation in 2015, and Microsoft gained between $13.3 billion and $25.1 billion through its involvement.

Musk’s legal team argues that his early financial and strategic contributions, including approximately $38 million in seed funding, the recruitment of key personnel, and assistance in connecting founders with contacts, laid the foundation for the later success of OpenAI and Microsoft’s commercial AI efforts.

“Without Elon Musk, there’d be no OpenAI. He provided the bulk of the seed funding, lent his reputation, and taught them all he knew about scaling a business. A pre-eminent expert quantified the value of that,” Musk’s lead trial lawyer Steven Molo told Reuters.

“Just as an early investor in a startup company may realise gains many orders of magnitude greater than the investor’s initial investment, the wrongful gains that OpenAI and Microsoft have earned—and which Mr Musk is now entitled to disgorge—are much larger than Mr Musk’s initial contributions,” the filing said.

Musk, who left OpenAI’s board in 2018 and now leads AI company xAI, alleges that OpenAI violated its founding non-profit mission when it restructured to include a for-profit arm tied to Microsoft’s investment and commercial strategy.

Meanwhile, OpenAI has labelled the lawsuit “baseless” and part of a “harassment campaign” by Musk, and Microsoft’s legal team has said there is no evidence the company “aided and abetted” OpenAI in any wrongdoing.

Both companies have asked the judge to limit what Musk’s expert witness may present at trial, arguing that the damages calculations are unreliable and could mislead a jury.

According to Reuters, Musk’s filing says he may pursue punitive damages and other penalties, including a possible injunction, if the jury finds the companies liable, though it did not specify what form any injunction would take.


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Nigeria Targeted with 4,622 Cyber-attacks Per Week in December 2025

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In December 2025, organisations globally faced sustained cyber pressure, as the average number of cyber-attacks per organisation per week reached 2 027, a 1% increase from the previous month and a 9% increase from December 2024.

This is according to December 2025 Global Cyber Attack Statistics by Check Point Research, the threat intelligence arm of Check Point Software Technologies.

According to the statistics, Latin America was the hardest hit, with companies experiencing an average of 3 065 cyber-attacks per week, a 26% year-over-year increase.

In contrast, Africa saw a decline in attacks, with Nigeria (4 622 attacks per week) and Angola (4 002 attacks per week) being the most targeted countries on the continent.

The report’s findings highlight the evolving cyber threat landscape, with ransomware and GenAI-driven data risks posing significant challenges to companies worldwide.

Ransomware attacks jumped 60% year over year, with 945 publicly reported incidents in December. Qilin was the most active ransomware operator, responsible for 18% of publicly disclosed attacks.

“Ransomware continues to scale through industrialised operations, while unmanaged GenAI usage is creating widespread data exposure at enterprise level,” said Omer Dembinsky, data research manager at Check Point Research.

The report noted the education sector was the most targeted industry globally, with 4 349 cyber attacks per week; followed by government (2 666 attacks per week); and associations and non-profits (2 509 attacks per week).

The widespread adoption of GenAI tools has introduced new cyber security risks, with one in 27 GenAI prompts posing a high risk of sensitive data leakage.

Experts warn that companies must prioritise prevention-first security, real-time AI threat intelligence and strong governance over AI tools to mitigate these risks.

Hendrik de Bruin, head of security consulting at Check Point Software, added: “Strengthening ransomware resilience, deploying AI-powered prevention and enforcing clear GenAI governance will be critical to reducing cyber risk in the year ahead.”


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