AT&S Launches Global IT Shared Service Center in Pune to Drive Digital Transformation - Related to collaborate, panel, ai-optimised, launches, edla
AT&S Launches Global IT Shared Service Center in Pune to Drive Digital Transformation
Austria-based IC substrate and PCB manufacturing leader AT&S AG on Monday launched its Global IT Shared Service Center (IT SSC) in Pune, Maharashtra, as per reports.
The new centre will support the business’s transcontinental operations across Austria, China, Malaysia, and India.
The IT SSC will create career opportunities for over 100 IT professionals in fields such as IT security, SAP, and software development by 2025-26. It aligns with AT&S’s objective to attain efficiency and technological excellence across its six manufacturing plants and nine sales offices worldwide.
“India’s deep talent pool and innovation-driven ecosystem make it the perfect location to drive agility and technological excellence across our operations,” Peter Griehsnig, AT&S AG’s chief technology officer, said at the launch event.
The Pune IT SSC will leverage India’s specialised IT expertise for innovation and service reliability.
The centre will operate through four Centres of Excellence (CoE): Security & Infrastructure, focused on strengthening cybersecurity and IT infrastructure; IT Applications, managing enterprise software and SAP solutions; Operations Technology, enhancing manufacturing and industrial IT systems; and Digital & Data, driving data-driven decision-making and digital transformation.
It is headed by [website] Raghavendra, who is responsible for delivering scalable and innovative solutions for AT&S’s global operations.
This initiative follows Indian Prime Minister Narendra Modi’s visit to Austria in July 2024, where AT&S executives met with him at the Federal Chancellery in Vienna.
AT&S has had a strong presence in India for 25 years, operating India’s largest advanced PCB export facility in Nanjangud, Mysuru.
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Keysight, Samsung, and NVIDIA Collaborate on AI-Optimised RAN Technology
US-based Keysight Technologies has partnered with Samsung and NVIDIA to develop AI models to improve radio access network (RAN) performance for 5G-advanced and 6G technologies. This collaboration enables Samsung to integrate these AI models into its virtual RAN (vRAN) software, which will be showcased at the Mobile World Congress (MWC) 2025 in Barcelona.
Developed under the AI-RAN Alliance, the initiative addresses key challenges in traditional RAN systems, such as limited throughput, high latency, and inefficient resource utilisation.
This development comes right after the business’s recent collaboration with Hyundai to complete what is claimed to be the industry’s first end-to-end reduced capability (RedCap) trial over a private 5G network.
Samsung will also unveil its first Android XR headset, Project Moohan, by integrating multimodal AI with advanced XR capabilities.
Charlie Zhang, senior VP at Samsung Research America, stated, “This collaboration marks a significant milestone as we move toward AI-native and sustainable telecommunication networks.”.
AI-based channel estimation models have demonstrated a 30% improvement in cell edge throughput during lab tests compared to conventional methods. These advancements optimise resource allocation, enhance system capacity, and reduce power consumption.
Samsung’s AI model evaluation was conducted using an end-to-end setup featuring its radio point and distributed unit (DU) on NVIDIA’s AI Aerial platform powered by the GH200 Grace Hopper Superchip.
Keysight’s Channel Emulation Solutions enabled precise testing under various conditions. Giampaolo Tardioli, GM and VP at Keysight, highlighted the transformative potential of this partnership in advancing energy-efficient networks.
Soma Velayutham, GM for AI, 5G and telecoms at NVIDIA, also emphasised the flexibility and efficiency gains unlocked by AI in signal processing pipelines. The collaboration is expected to drive innovation and accelerate the global adoption of AI-enhanced RAN technologies.
At MWC 2025, Jio Platforms Limited (JPL), along with AMD, Cisco, and Nokia, also introduced plans to develop an Open Telecom AI Platform. It offers a ‘multi-domain intelligence’ framework to introduce AI and automation to ‘every layer’ of network operations.
Even AWS has entered the game with its new cloud solutions to boost 5G networks for telecom operators.
At the same event, SynaXG (a provider of AI-RAN solutions), in collaboration with Kyocera (Japanese manufacturer), and NVIDIA claimed to have unveiled the world’s first software-defined mmWave 5G vRAN solution.
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Austria-based IC substrate and PCB manufacturing leader AT&S AG on Monday launched its Global IT Shared Service Center (IT SSC) in Pune, Maharashtra, ......
Teachmint Unveils AI-Powered Interactive Panel X2 with Google EDLA Certification
Teachmint, an edtech startup, has introduced Teachmint X2, an advanced interactive flat panel equipped with Google’s Enterprise Devices Licensing Agreement (EDLA) certification.
The device, powered by a Neural Processing Unit (NPU), integrates AI-driven functions to enhance personalised learning, real-time feedback, and intelligent automation, creating a more engaging and efficient classroom experience.
Running on Android 14, Teachmint X2 provides access to Google’s suite of applications, including Drive, Docs, and Meet. Prioritising security and AI-driven innovation, the device ensures a robust and future-ready learning environment for educators and students alike.
As a Google EDLA-certified panel, Teachmint X2 benefits from Google Play Protect’s continuous malware protection, safeguarding digital learning experiences. This certification also enables direct access to a vast library of educational applications via the Google Play Store, fostering a secure and interactive learning ecosystem.
Mihir Gupta, co-founder & CEO, Teachmint, said, “Tech in education has to start inside the classrooms. Interactive panels used as teaching devices in classrooms have traditionally lacked operating systems that are vertically designed and have missed out on the full platform strength of the Android ecosystem. To break this status quo, Teachmint X2 devices are Google EDLA and Play Protect certified.”.
Mihir further stated that with Teachmint X1, they saw massive adoption of AI in teaching methodologies through their EduAI offering. Building on this further, Teachmint X2 comes with an in-built Neural Processing Unit (NPU) that will further boost AI capabilities of the devices locally.
Similarly, SuperTron Electronics’s flagship brand, Solitaire, addresses the requirement for advanced technology in the classroom with its AI-driven interactive panel.
In an , Ramya Chatterjee, chief of the brand Solitaire, expressed, “We provide innovative technology to empower teachers and enhance their teaching experience. Our solutions are designed to simplify their work and improve learning outcomes in classrooms.”.
India’s edtech market, currently valued at $[website] billion, is expected to grow to $29 billion by 2030. AI-driven learning solutions are at the forefront of this expansion. Additionally, the interactive flat panel market is projected to reach $[website] billion by 2029, growing at a CAGR of [website], & Markets report.
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Market Impact Analysis
Market Growth Trend
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| 23.1% | 27.8% | 29.2% | 32.4% | 34.2% | 35.2% | 35.6% |
Quarterly Growth Rate
| Q1 2024 | Q2 2024 | Q3 2024 | Q4 2024 |
|---|---|---|---|
| 32.5% | 34.8% | 36.2% | 35.6% |
Market Segments and Growth Drivers
| Segment | Market Share | Growth Rate |
|---|---|---|
| Machine Learning | 29% | 38.4% |
| Computer Vision | 18% | 35.7% |
| Natural Language Processing | 24% | 41.5% |
| Robotics | 15% | 22.3% |
| Other AI Technologies | 14% | 31.8% |
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity:
Competitive Landscape Analysis
| Company | Market Share |
|---|---|
| Google AI | 18.3% |
| Microsoft AI | 15.7% |
| IBM Watson | 11.2% |
| Amazon AI | 9.8% |
| OpenAI | 8.4% |
Future Outlook and Predictions
The Launches Global Shared landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:
Year-by-Year Technology Evolution
Based on current trajectory and expert analyses, we can project the following development timeline:
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:
Innovation Trigger
- Generative AI for specialized domains
- Blockchain for supply chain verification
Peak of Inflated Expectations
- Digital twins for business processes
- Quantum-resistant cryptography
Trough of Disillusionment
- Consumer AR/VR applications
- General-purpose blockchain
Slope of Enlightenment
- AI-driven analytics
- Edge computing
Plateau of Productivity
- Cloud infrastructure
- Mobile applications
Technology Evolution Timeline
- Improved generative models
- specialized AI applications
- AI-human collaboration systems
- multimodal AI platforms
- General AI capabilities
- AI-driven scientific breakthroughs
Expert Perspectives
Leading experts in the ai tech sector provide diverse perspectives on how the landscape will evolve over the coming years:
"The next frontier is AI systems that can reason across modalities and domains with minimal human guidance."
— AI Researcher
"Organizations that develop effective AI governance frameworks will gain competitive advantage."
— Industry Analyst
"The AI talent gap remains a critical barrier to implementation for most enterprises."
— Chief AI Officer
Areas of Expert Consensus
- Acceleration of Innovation: The pace of technological evolution will continue to increase
- Practical Integration: Focus will shift from proof-of-concept to operational deployment
- Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
- Regulatory Influence: Regulatory frameworks will increasingly shape technology development
Short-Term Outlook (1-2 Years)
In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing ai tech challenges:
- Improved generative models
- specialized AI applications
- enhanced AI ethics frameworks
These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.
Mid-Term Outlook (3-5 Years)
As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:
- AI-human collaboration systems
- multimodal AI platforms
- democratized AI development
This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.
Long-Term Outlook (5+ Years)
Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:
- General AI capabilities
- AI-driven scientific breakthroughs
- new computing paradigms
These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.
Key Risk Factors and Uncertainties
Several critical factors could significantly impact the trajectory of ai tech evolution:
Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.
Alternative Future Scenarios
The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:
Optimistic Scenario
Responsible AI driving innovation while minimizing societal disruption
Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.
Probability: 25-30%
Base Case Scenario
Incremental adoption with mixed societal impacts and ongoing ethical challenges
Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.
Probability: 50-60%
Conservative Scenario
Technical and ethical barriers creating significant implementation challenges
Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.
Probability: 15-20%
Scenario Comparison Matrix
| Factor | Optimistic | Base Case | Conservative |
|---|---|---|---|
| Implementation Timeline | Accelerated | Steady | Delayed |
| Market Adoption | Widespread | Selective | Limited |
| Technology Evolution | Rapid | Progressive | Incremental |
| Regulatory Environment | Supportive | Balanced | Restrictive |
| Business Impact | Transformative | Significant | Modest |
Transformational Impact
Redefinition of knowledge work, automation of creative processes. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.
The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.
Implementation Challenges
Ethical concerns, computing resource limitations, talent shortages. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.
Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.
Key Innovations to Watch
Multimodal learning, resource-efficient AI, transparent decision systems. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.
Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.
Technical Glossary
Key technical terms and definitions to help understand the technologies discussed in this article.
Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.
platform intermediate
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