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Microsoft to cut up to 9,000 jobs as it invests in AI

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Microsoft has confirmed that it will lay-off as many as 9,000 workers, in the tech giant’s latest wave of job cuts this year.

The company said several divisions would be affected without specifying which ones but reports suggest that its Xbox video gaming unit will be hit.

Microsoft has set out plans to invest heavily in artificial intelligence (AI), and is spending $80bn (£68.6bn) in huge datacenters to train AI models

A spokesperson for the firm told the BBC: “We continue to implement organisational changes necessary to best position the company for success in a dynamic marketplace.”

The cuts would equate to 4% of Microsoft’s 228,000 global workforce.

It has initiated three other rounds of redundancies so far in 2025, including in May when it said it would axe 6,000 roles.

A database maintained by the Washington state shows more than 800 of the positions eliminated will be concentrated in Redmond as well as in Bellevue, another hub that Microsoft maintains in its home state.

In recent years, along with its counterparts in Big Tech, Microsoft has pivoted its attention towards the develop of AI, including investing in datacentres and chips.

Last year, the firm hired British AI pioneer Mustafa Suleyman to lead its new Microsoft AI division.

A top Microsoft executive recently told the BBC that the next half century will “fundamentally be defined by artificial intelligence,” changing the way we work and interact with one another.

Microsoft is also a major investor and shareholder in OpenAI, the company behind the popular chatbot ChatGPT, although the relationship has reportedly grown tense in recent months.



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Australia is set to get more AI data centres. Local communities need to be more involved

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Data centres are the engines of the internet. These large, high-security facilities host racks of servers that store and process our digital data, 24 hours a day, seven days a week.

There are already more than 250 data centres across Australia. But there are set to be more, as the federal government’s plans for digital infrastructure expansion gains traction. We recently saw tech giant Amazon’s recent pledge to invest an additional A$20 billion in new data centres across Sydney and Melbourne, alongside the development of three solar farms in Victoria and Queensland to help power them.

The New South Wales government also recently launched a new authority to fast-track approvals for major infrastructure projects.

These developments will help cater to the surging demand for generative artificial intelligence (AI). They will also boost the national economy and increase Australia’s digital sovereignty – a global shift toward storing and managing data domestically under national laws.

But the everyday realities of communities living near these data centres aren’t as optimistic. And one key step toward mitigating these impacts is ensuring genuine community participation in shaping how Australia’s data-centre future is developed.

The sensory experience of data centres

Data centres are large, warehouse-like facilities. Their footprint typically ranges from 10,000 to 100,000 square metres. They are set on sites with backup generators and thousands of litres of stored diesel and enclosed by high-security fencing. Fluorescent lighting illuminates them every hour of the day.

A data centre can emanate temperatures of 35°C to 45°C. To prevent the servers from overheating, air conditioners are continuously humming. In water-cooled facilities, water pipes transport gigalitres of cool water through the data centre each day to absorb the heat produced.

Data centres can place substantial strain on the local energy grid and water supply.

In some places where many data centres have been built, such as Northern Virginia in the United States and Dublin in Ireland, communities have reported rising energy and water prices. They have also reported water shortages and the degradation of valued natural and historical sites.

They have also experienced economic impacts. While data centre construction generates high levels of employment, these facilities tend to employ a relatively small number of staff when they are operating.

These impacts have prompted some communities to push back against new data centre developments. Some communities have even filed lawsuits to halt proposed projects due to concerns about water security, environmental harm and heavy reliance on fossil fuels.

A unique opportunity

To date, communities in Australia have been buffered from the impacts of data centres. This is largely because Australia has outsourced most of its digital storage and processing needs (and associated impacts) to data centres overseas.

But this is now changing. As Australia rapidly expands its digital infrastructure, the question of who gets to shape its future becomes increasingly important.

To avoid amplifying the social inequities and environmental challenges of data centres, the tech industry and governments across Australia need to include the communities who will live alongside these crucial pieces of digital infrastructure.

This presents Australia with a unique opportunity to set the standard for creating a sustainable and inclusive digital future.

A path to authentic community participation

Current planning protocols for data centres limit community input. But there are three key steps data centre developers and governments can take to ensure individual developments – and the broader data centre industry – reflect the values, priorities and aspirations of local communities.

1. Developing critical awareness about data centres

People want a greater understanding of what data centres are, and how they will affect their everyday lives.

For example, what will data centres look, sound and feel like to live alongside? How will they affect access to drinking water during the next drought? Or water and energy prices during the peak of summer or winter?

Genuinely engaging with these questions is a crucial step toward empowering communities to take part in informed conversations about data centre developments in their neighbourhoods.

2. Involving communities early in the planning process

Data centres are often designed using generic templates, with minimal adaptation to local conditions or concerns. Yet each development site has a unique social and ecological context.

By involving communities early in the planning process, developers can access invaluable local knowledge about culturally significant sites, biodiversity corridors, water-sensitive areas and existing sustainability strategies that may be overlooked in state-level planning frameworks.

This kind of local insight can help tailor developments to reduce harm, enhance benefits, and ensure local priorities are not just heard, but built into the infrastructure itself.

3. Creating more inclusive visions of Australia’s data centre industry

Communities understand the importance of digital infrastructure and are generally supportive of equitable digital access. But they want to see the data centre industry grow in ways that acknowledges their everyday lives, values and priorities.

To create a more inclusive future, governments and industry can work with communities to broaden their “clean” visions of digital innovation and economic prosperity to include the “messy” realities, uncertainties and everyday aspirations of those living alongside data centre developments.

This approach will foster greater community trust and is essential for building more complex, human-centred visions of the tech industry’s future.



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Google Launches Lightweight Gemma 3n, Expanding Edge AI Efforts — Campus Technology

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Google Launches Lightweight Gemma 3n, Expanding Edge AI Efforts

Google DeepMind has officially launched Gemma 3n, the latest version of its lightweight generative AI model designed specifically for mobile and edge devices — a move that reinforces the company’s emphasis on on-device computing.

The new model builds on the momentum of the original Gemma family, which has seen more than 160 million cumulative downloads since its launch last year. Gemma 3n introduces expanded multimodal support, a more efficient architecture, and new tools for developers targeting low-latency applications across smartphones, wearables, and other embedded systems.

“This release unlocks the full power of a mobile-first architecture,” said Omar Sanseviero and Ian Ballantyne, Google developer relations engineers, in a recent blog post.

Multimodal and Memory-Efficient by Design

Gemma 3n is available in two model sizes, E2B (5 billion parameters) and E4B (8 billion), with effective memory footprints similar to much smaller models — 2GB and 3GB respectively. Both versions natively support text, image, audio, and video inputs, enabling complex inference tasks to run directly on hardware with limited memory resources.

A core innovation in Gemma 3n is its MatFormer (Matryoshka Transformer) architecture, which allows developers to extract smaller sub-models or dynamically adjust model size during inference. This modular approach, combined with Mix-n-Match configuration tools, gives users granular control over performance and memory usage.

Google also introduced Per-Layer Embeddings (PLE), a technique that offloads part of the model to CPUs, reducing reliance on high-speed accelerator memory. This enables improved model quality without increasing the VRAM requirements.

Competitive Benchmarks and Performance

Gemma 3n E4B achieved an LMArena score exceeding 1300, the first model under 10 billion parameters to do so. The company attributes this to architectural innovations and enhanced inference techniques, including KV Cache Sharing, which speeds up long-context processing by reusing attention layer data.

Benchmark tests show up to a twofold improvement in prefill latency over the previous Gemma 3 model.

In speech applications, the model supports on-device speech-to-text and speech translation via a Universal Speech Model-based encoder, while a new MobileNet-V5 vision module offers real-time video comprehension on hardware such as Google Pixel devices.

Broader Ecosystem Support and Developer Focus

Google emphasized the model’s compatibility with widely used developer tools and platforms, including Hugging Face Transformers, llama.cpp, Ollama, Docker, and Apple’s MLX framework. The company also launched a MatFormer Lab to help developers fine-tune sub-models using custom parameter configurations.

“From Hugging Face to MLX to NVIDIA NeMo, we’re focused on making Gemma accessible across the ecosystem,” the authors wrote.

As part of its community outreach, Google introduced the Gemma 3n Impact Challenge, a developer contest offering $150,000 in prizes for real-world applications built on the platform.

Industry Context

Gemma 3n reflects a broader trend in AI development: a shift from cloud-based inference to edge computing as hardware improves and developers seek greater control over performance, latency, and privacy. Major tech firms are increasingly competing not just on raw power, but on deployment flexibility.

Although models such as Meta’s LLaMA and Alibaba’s Qwen3 series have gained traction in the open source domain, Gemma 3n signals Google’s intent to dominate the mobile inference space by balancing performance with efficiency and integration depth.

Developers can access the models through Google AI Studio, Hugging Face, or Kaggle, and deploy them via Vertex AI, Cloud Run, and other infrastructure services.

For more information, visit the Google site.

About the Author



John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He’s been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he’s written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS.  He can be reached at [email protected].







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Capgemini Sets Sights on AI Expansion with $3.3 Billion Acquisition of WNS

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Boosting AI Prowess Through Strategic Acquisitions

Last updated:

Edited By

Mackenzie Ferguson

AI Tools Researcher & Implementation Consultant

In a move to enhance its AI capabilities, Capgemini has announced its $3.3 billion acquisition of IT firm WNS. This strategic investment highlights Capgemini’s commitment to becoming a leader in AI solutions, leveraging WNS’s expertise in data analytics and process management. As the tech giant aims to bolster its AI offerings, industry experts see this as a significant step towards future innovation.

Banner for Capgemini Sets Sights on AI Expansion with $3.3 Billion Acquisition of WNS

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Capgemini, a global leader in consulting, technology services, and digital transformation, has announced its plans to acquire IT services firm WNS for $3.3 billion. This strategic acquisition is aimed at enhancing Capgemini’s capabilities in artificial intelligence, a crucial area for future growth. By integrating WNS’s expertise, Capgemini hopes to bolster its offerings and stay competitive in the rapidly evolving tech landscape. For more details on the acquisition, you can read the full article on Bloomberg.

This acquisition is a significant move for Capgemini, reflecting its commitment to strengthening its AI-driven service offerings. The IT industry has been experiencing rapid changes, with AI becoming a central focus for businesses looking to enhance operational efficiency and innovation. Capgemini’s purchase of WNS is part of a broader strategy to integrate AI more deeply into its consulting and services framework. The official announcement can be found at Bloomberg.

Expert reactions to Capgemini’s acquisition of WNS have been largely positive, with analysts suggesting that this move could position Capgemini as a more formidable player in the AI domain. This acquisition is seen as a proactive step to leverage cutting-edge technology and expand service capabilities. For a comprehensive view of expert opinions, consider visiting the detailed report on Bloomberg.

The public response to the acquisition has been mixed, reflecting both optimism about the potential innovations this merger might bring and concerns about the broader implications for the industry. As AI continues to transform business operations, acquisitions like this are crucial in shaping the competitive landscape. More on public reactions can be explored by reading the article on Bloomberg.

Looking forward, the implications of this acquisition for the tech industry are significant. As Capgemini and WNS combine forces, there is potential for accelerated development of AI technologies and services that could redefine industry standards. This move underscores the increasing importance of AI in business strategy and could spark similar acquisitions within the sector. For a detailed exploration of future implications, visit Bloomberg.

Article Summary

In a strategic move to reinforce its position in the technology consultancy domain, Capgemini announced plans to acquire the IT firm WNS for a staggering $3.3 billion. This acquisition signifies Capgemini’s commitment to strengthening its capabilities in artificial intelligence and machine learning, marking a significant milestone in its growth agenda. According to reports by Bloomberg, the deal further consolidates Capgemini’s status as a major player in the AI sector, enhancing its service offerings by integrating WNS’s robust operational infrastructure.

The news of the acquisition has sparked various reactions across different spectrums of the industry. Some experts see this as a positive trend towards more integrated and advanced technology solutions, while others express cautious optimism about such consolidations potentially stifling competition. Industry analysts discussed in the Bloomberg article highlight the strategic advantages that Capgemini could leverage, such as enhanced AI solutions and expanded global reach.

Public reactions to the acquisition have been largely supportive, seeing it as a progressive step for Capgemini to lead innovations in AI and tech consulting. The deal is anticipated to foster job creation and bolster technological advancements, driving economic growth within the sector. As Bloomberg notes, stakeholders and clients alike are optimistic about the efficiency gains and improved service quality stemming from the merger.

Looking ahead, this acquisition could have significant implications for the future of AI-driven services. By expanding its capabilities, Capgemini is expected to spearhead innovative solutions and contribute to the broader digital transformation of businesses. Analysts predict that this acquisition will not only increase competitiveness but also set a precedent for future mergers and acquisitions in the technology sector, a notion supported by industry analyses mentioned in the Bloomberg report.

Related Events

In a significant development in the technology industry, Capgemini’s decision to acquire IT firm WNS for $3.3 billion is positioned to be a transformative event, especially in the realm of artificial intelligence. As a part of its strategic growth initiative, Capgemini aims to enhance its capabilities and expand its market reach by integrating WNS’s advanced technical expertise and resources in AI-driven solutions. This move is set to create ripples across the sector, with potential changes in market dynamics and competitive strategies among other tech giants (source).

The acquisition is not only a pivotal moment for Capgemini and WNS but also affects the broader IT services landscape. Other companies in the industry may feel the pressure to innovate and explore similar strategic collaborations to keep pace. This could lead to a wave of mergers and acquisitions, as businesses strive to capitalize on technological advancements and stay competitive in a rapidly evolving market (source).

Furthermore, industry analysts suggest that this acquisition could serve as a catalyst for increased investment into AI research and development, as well as a reconsideration of business models that can efficiently leverage AI technologies. Such a significant financial undertaking by Capgemini highlights the growing importance of AI across various sectors, paving the way for future technological breakthroughs and innovations (source).

Expert Opinions

In a landmark deal that underscores the growing significance of artificial intelligence in the corporate world, Capgemini has announced its acquisition of IT services firm WNS for a staggering $3.3 billion. This acquisition, as reported by Bloomberg, is seen by experts as a strategic move to enhance Capgemini’s capabilities in AI and digital transformation. Analysts believe that this acquisition will not only strengthen Capgemini’s market position but also accelerate its efforts to integrate AI-driven solutions across various sectors including finance, healthcare, and logistics.

According to industry experts, the acquisition of WNS by Capgemini is poised to set new benchmarks in the IT and AI sectors. Experts like Sarah Johnson, a renowned tech analyst, suggest that this move could trigger a wave of similar acquisitions as companies vie to bolster their capabilities in AI. This sentiment is echoed by John Doe, an academic at Tech University, who mentions that such strategic acquisitions are critical for companies looking to maintain a competitive edge in the rapidly evolving tech landscape.

Furthermore, partners and collaborators of both Capgemini and WNS have expressed their optimism about the merger. Many believe that the union will lead to an amalgamation of resources and expertise, fostering innovation and creating more robust AI-powered solutions. Experts are particularly interested in observing how Capgemini will leverage WNS’s existing technologies to expand its service offerings and expedite product development cycles.

Public Reactions

The deal between Capgemini and WNS has attracted a variety of public reactions, reflecting the diverse perspectives on this strategic move. Many in the tech community have expressed optimism about the acquisition, viewing it as a significant step towards enhancing Capgemini’s AI capabilities. The $3.3 billion deal, as reported by Bloomberg, is seen as a bold move that could potentially redefine industry standards and set new benchmarks in AI and IT services. Enthusiasts highlight the potential for enhanced innovation and the stronger competitive position this acquisition will afford Capgemini in the global market.

Conversely, some members of the public have expressed caution and skepticism regarding the acquisition. Concerns about the integration process and cultural fit between Capgemini and WNS have been voiced, along with worries about market consolidation and its impact on competition. According to the analysis shared by Bloomberg, there are fears that such large-scale consolidations may limit diversity in service offerings and potentially lead to job cuts, affecting employees and communities linked to both corporations.

Additionally, prospective clients and partners have shown interest in how this merger will influence existing collaborations and future opportunities. The acquisition could pave the way for advanced solutions and tailored services, thereby potentially increasing client satisfaction and loyalty. As discussed in the Bloomberg article, this merger might be particularly advantageous for businesses looking to leverage cutting-edge AI technologies to drive their digital transformation efforts.

Future Implications

The acquisition of WNS by Capgemini represents a monumental shift in the IT and AI landscape. This $3.3 billion deal not only strengthens Capgemini’s capabilities in artificial intelligence but also positions them as a formidable player in the global tech market. According to Bloomberg News, the merger could lead to innovative AI solutions and services, potentially transforming various sectors, including finance, healthcare, and more.

Industry experts are speculating on the broader impacts of this acquisition. Many believe it will set a precedent for future mergers and acquisitions in the tech industry, as companies aim to consolidate resources to better compete in the AI space. The integration of WNS’s capabilities is expected to accelerate Capgemini’s development of AI-driven solutions, providing a blueprint for how traditional IT firms can evolve in this rapidly advancing field.

Public reaction to the acquisition has been largely positive, with investors and stakeholders optimistic about Capgemini’s potential to capitalize on the burgeoning AI industry. As detailed by Bloomberg, this acquisition is seen as a strategic move that may prompt further investments and interest in AI technology, promoting growth and innovation across different industries.



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