Boldyn Networks’ US CCO Jason Caliento said the company is making good on pledges to boost the digital experience offered at Major League Soccer (MLS) venues after equipping a new stadium in the city of Miami with various connectivity technologies.

The company installed a platform of Wi-Fi 7, IPTV, audio, neutral host mobile and converged fibre infrastructure at the Nu Stadium in the Miami Freedom Park to deliver fresh services for fans and contribute to improved operation of the venue which opened in April.

Caliento highlighted an “innovative financial structure”, whereby Boldyn Networks handled the capital investment it plans to recoup through network operation and management duties.

He said the model provides “significant financial flexibility” and predicted it would become a key selling point for deals with other venues.

Boldyn Networks explained the Nu Stadium is a 26,700-seat facility located in a mixed-use development spanning 131-acres.

It installed more than 600 access points covering high-density Wi-Fi and mobile throughout the site. Cloud-based IoT platforms are providing real-time information on crowd behaviour, and the fibre element covers game streaming and display on more than 200 connected TVs.

The company highlighted mobile ticketing, from-seat refreshment ordering and access to interactive content as among the main benefits for fans.

Caliento said Boldyn Networks became an official supplier to the MLS in a deal struck in 2025.

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IoT specialist Wiliot expanded work with AT&T Business to boost its position in the physical AI field by tapping the US-based operator’s connectivity, device relationships and general expertise in data handling.

Wiliot is seeking to broaden its position in physical AI for enterprise supply chains and believes AT&T has the network connectivity, device relationships and ability in employing data to do so.

“Physical AI depends on continuous data” from the real world, VP of marketing Amir Khoshniyati said.

Deepening ties with AT&T improves Wiliot’s “ability to deploy and operate physical AI networks across large, distributed environments”.

The company is pitching a platform which handles sensing and intelligence, employing real-time data from dedicated devices. AT&T is tasked with delivering the network infrastructure, mobile connectivity and execution elements.

Certification of Wiliot gateway devices on AT&T’s network is also underway, as the company seeks more direct connectivity and standardised deployments for the enterprise space.

Wiliot stated the companies embarked on a systems integration collaboration late in 2025 covering core deployments and operational capabilities. The operator is also handling various design, installation, asset tagging and maintenance aspects.

Lee Wagner, area VP for AT&T, explained enterprises “need actionable data from the physical world” and the companies are “adding visibility at the case and asset level” to provide a fresh range of services.

Work already undertaken in retail, food and beverage, and some restaurant sectors delivered inventory accuracy improvements of 99%, Wiliot stated.

It also highlighted improvements in the time taken to ship goods to storage, a reduction in the number of staff required in receiving items and greater shipment accuracy.

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Telefonica Tech and Google Cloud partnered on a product intended to meet the needs of Spanish public bodies and companies in highly regulated sectors with strict data sovereignty requirements.

The latest tie-up between the pair brings a joint service to market in Spain which allows information held in Google Cloud to be encrypted by keys generated and stored by Telefonica in its local infrastructure.

Having the keys generated and managed by an operator in Spain provides increased protection against unauthorised access from elsewhere in the world, Telefonica noted.

It added the Data Boundary model offered by the pair would provide verifiable controls over data protection and access, enabling compliance with digital sovereignty requirements.

Telefonica Tech CEO Sofia Collado said the offering would provide organisations with the means “to define precise data residency, access control and data protection policies through encryption keys generated and managed outside public cloud environments”.

Google Cloud country manager, Iberia, Isaac Hernandez added “there should be no conflict between Spain’s digital sovereignty and its economic competitiveness”.

“By combining our cutting-edge cloud capabilities with Telefonica’s local operational control and encryption management, we are empowering businesses and public administrations to innovate securely and confidently on their own terms.”

Google Cloud Data Boundary is offered across various global markets in partnership with companies in each country.

Telefonica noted it was selected as the tech giant’s “trusted partner for data sovereignty” in its home market.

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A report by Telus Digital exposed significant security vulnerabilities across the generative AI landscape, which included finding every major model could be coaxed into unsafe behaviour under the right conditions.

In the company’s second GenAI Safety Model Benchmark, Telus Digital’s testing found some models engaged with harmful requests more than 90% of the time and stated most enterprises are dangerously underprepared to defend against them.

The testing drew on more than 620,000 adversarial tests across 34 AI models from 10 global providers: Anthropic, OpenAI, Google, Meta, Alibaba, Baidu, ByteDance, Zhipu AI, 01.AI and Mistral.

It is the most extensive AI security study Telus Digital has conducted to date, nearly doubling the scope of the first edition published in November 2025.

Attack vulnerability rates across tested models ranged from 1.3% to 93%, where a lower percentage means a safer model. 

Anthropic’s Claude models claimed five of the 10 lowest vulnerability scores, including the benchmark’s overall lowest rate, but Telus Digital noted even single-digit failure rates are unacceptable in high-stakes enterprise contexts involving money, health and reputation.

The research identified model size, reasoning capability and the creator’s overall safety approach as the strongest predictors of resilience.

Reasoning models, designed to deliberate before responding, proved significantly harder to exploit, with a 19.9% vulnerability rate compared to 55.1% for standard models which skip the reasoning step.

Smaller models are consistently the most susceptible to attacks, regardless of whether they are open-source or proprietary. The study found open source models are not inherently less safe than closed ones, with GLM 4.7 from China’s Zhipu AI outperforming many proprietary alternatives.

The benchmark also highlighted where risks cluster most sharply: privacy exploitation, fraud and cybersecurity threats remain the hardest categories for even leading models to handle.

Telus Digital also flagged a pattern called “refuse-but-engage,” where a model declines a harmful request but still provides related information which could cause harm or reputational damage.

Global AI spending is projected to reach $2.52 trillion in 2026, yet spending on AI trust, risk, and security management is projected to be just $3.4 billion, which is roughly $1 in security for every $735 spent on AI capabilities.

Meanwhile, 86% of organisations report having already experienced an AI-related security incident.

Telus Digital urges enterprises to move beyond one-time or periodic safety checks toward continuous, automated adversarial testing embedded directly into development workflows, layered with human oversight and clean data practices.

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