Siemens announced on Wednesday its acquisition of US software firm Dotmatics for $5.1 billion, aiming to enhance its AI capabilities for drug discovery.
The German company described the deal as complementary to its expansion into Life Sciences, positioning itself in a market increasingly reliant on digital transformation to meet growing medical needs.
Siemens expects Dotmatics to generate $100 million annually in the mid-term, rising to $500 million in the long run, and said the acquisition would be immediately profitable. The transaction is set to be completed in the first half of next year.
Founded in 2005, Dotmatics employs 800 people and specialises in AI-driven R&D software designed to accelerate drug research. This move follows Siemens’ recent $10 billion purchase of another AI-powered US software firm, Altair Engineering.
As Siemens’ industrial software faces slowing demand, its digital division has been driving revenue growth instead of its traditional factory automation products. The company, Germany’s second-largest by market value, continues expanding its software portfolio to capitalise on AI-driven innovations.
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While President Trump’s tariffs on goods dominate headlines, a more consequential battle is brewing over digital services. US tech giants like Meta, Google, and Amazon wield unparalleled global dominance in this sector.
In just-in-time analysis, Jovan Kurbalija argues that Trump’s fixation on traditional trade levers (steel, cars) overlooks a critical vulnerability for the United States: the use of digital services taxes (DSTs) and regulatory pressure by the EU and other trading partners to counterbalance new US tariff.
The collapse of OECD-led multilateral tax negotiations in 2024 has triggered a resurgence of unilateral DSTs, from Canada’s retroactive levy to India’s expanded ‘equalization levy’ and revived EU proposals for bloc-wide digital taxes.
Kurbalija analyses how digital taxation redefines trade diplomacy, with implications ranging from recalibrated leverage (host nations exploiting US tech dependence) to governance gaps (WTO rules ill-equipped for digital disputes). It poses new challenges for digital diplomacy, AI negotiations, and internet governance.
He warns that failure to address this ‘invisible trade war’ could escalate tit-for-tat measures, jeopardizing both physical goods trade and the digital economy. The rise of data and sovereignty will be inevitable.
Ultimately, the piece underscores a paradigm shift: in the 21st-century economy, algorithms, and data flows are as strategically vital as steel beams—and more impactful for economic well-being and global prosperity.
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Claude for Education, launched by Anthropic, introduces a specialised AI for higher education, aiming to support universities in teaching, learning, and administration.
The initiative includes key features like Learning mode, full campus access for top universities, and partnerships with organisations like Internet2 and Instructure to integrate AI into academic tools.
Learning mode helps students develop critical thinking by guiding them through problems with Socratic questioning instead of providing direct answers. It also offers templates for research and study.
Key academic partnerships include Northeastern University, London School of Economics, and Champlain College, all of which will benefit from campus-wide access to Claude. These partnerships ensure AI’s responsible integration and accessibility for all students.
New student programs, such as the Claude Campus Ambassadors and API credit initiatives, provide opportunities for students to engage with and build on AI tools.
The launch also coincides with efforts to integrate AI into the academic plans of institutions like Northeastern University, which is pioneering AI adoption in higher education with its ‘Northeastern 2025’ initiative.
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Chinese smartphone maker Honor has unveiled a $10 billion investment plan aimed at advancing AI technologies across its product ecosystem. The announcement was made by CEO James Li at the Mobile World Congress in Barcelona, where he outlined the company’s ambition to evolve beyond smartphones and expand into AI-powered PCs, tablets, and wearables.
The major funding initiative comes as Honor prepares for a public listing, following a shareholder restructuring completed in December. While a date for the IPO has yet to be confirmed, the company appears to be positioning itself as a key player in China’s AI race, spurred by growing domestic interest in large language models like those developed by DeepSeek.
Despite slipping to fourth place in China’s smartphone market last year, Honor continues to receive strong backing from the Shenzhen local government. Support has included R&D funding, tax incentives, and assistance with international expansion. The company’s strategic pivot to AI reflects broader trends in China’s tech sector, as firms seek to integrate smart features into a wider range of consumer devices.
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Bill Gates has predicted that AI will reduce work hours significantly, with two-day work weeks becoming a reality in the next decade.
His vision contrasts with views in India, where figures like Narayana Murthy and S.N. Subrahmanyan argue for longer work hours instead of reducing them, believing they are crucial for economic growth.
However, Harsh Goenka and Harish Mariwala, who focus on ambition and productivity instead of hours worked, have a different take. They stress the importance of quality instead of quantity in work hours.
Studies, such as those from Iceland and New Zealand, suggest that reduced working hours can lead to higher productivity and a better work-life balance.
In Iceland, trials reducing weekly hours from 40 to 35 saw workers feeling more energised and less stressed, while New Zealand’s Perpetual Guardian found that employees completed tasks in fewer hours, raising engagement and reducing stress.
Despite Gates’ prediction, the idea of working only two days a week seems extreme, especially considering his past work ethic.
Gates himself worked long hours instead of fewer ones during his early career, fearing mistakes could cost him his company, but he acknowledges that AI and technology have shifted the landscape.
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AI may seem like a modern marvel, but its foundations stretch back to early 20th-century philosophical thought—particularly to the Lwów–Warsaw School of Philosophy. In a recent blog by Jovan Kurbalija, Executive Director of Diplo, he highlights how this influential movement, established by Kazimierz Twardowski and active between the world wars, made groundbreaking contributions to logic, semantics, and analytical philosophy—fields that underpin today’s AI systems.
Despite being overshadowed by more famous contemporaries like the Vienna Circle, the Lwów–Warsaw School cultivated thinkers whose work continues to shape how machines process language and make decisions. Among the most influential figures was Alfred Tarski, whose formal definition of truth laid the groundwork for natural language processing (NLP), enabling AI to understand and generate human language.
Another key contributor, Jan Łukasiewicz, developed many-valued logic—a system that goes beyond simple true/false decisions and allows machines to reason through uncertainty, essential in complex tasks like autonomous driving or medical diagnostics. The school’s importance isn’t just technical.
Its strong emphasis on analytical rigour also offers tools for navigating AI’s growing ethical concerns—ranging from fairness in algorithmic decisions to broader questions about consciousness and societal impact. Though these philosophical aspects are less often discussed, they’re crucial for ensuring AI development remains responsible and aligned with human values.
The intellectual legacy is rarely acknowledged in mainstream AI history. Yet, as Kurbalija emphasises, AI’s roots are deeper and more diverse than we often realise. Revisiting the Lwów–Warsaw School highlights how past ideas can still guide us in shaping the technologies of tomorrow.
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In Shenzhen, a quiet breakthrough is unfolding in autism rehabilitation as AI-powered tools begin to transform how young children receive therapy.
At a local centre, a therapist guides a three-year-old boy through speech exercises, while an AI system documents progress and instantly generates a tailored home-training plan, offering much-needed support to both therapists and families.
China faces a severe shortage of autism therapists, with only around 100,000 professionals serving a community of over 10 million individuals, including 3 million children.
Traditional diagnosis and treatment rely on time-consuming behavioural assessments. Now, AI is streamlining this process.
Centres like Dami & Xiaomi, in partnership with Amazon Web Services, have developed RICE AI, a system trained on over 80 million behavioural data points to generate faster, personalised interventions and even custom visual materials for home learning.
By dramatically reducing workloads and enhancing precision, AI is helping to close the gap in early intervention and support.
More facilities are following suit, with efforts underway to unify and open-source these tools across the country. As one mother tearfully recalled her autistic son’s first spoken word, the emotional impact of this technological shift was clear, AI is not replacing care, but deepening it.
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The startup Emergence AI has launched a new no-code platform that allows users to generate custom AI agents simply by describing tasks in natural language.
These agents can then autonomously create other, more specialised agents to complete complex work, in real time and without requiring human coding expertise.
The system, which the company calls a breakthrough in ‘recursive intelligence’, checks its registry of agents for task compatibility. If existing agents aren’t suitable, new ones are created instantly to handle the job.
These can also anticipate related tasks, boosting automation across enterprise operations. Emergence AI claims the platform can seamlessly orchestrate collaboration among multiple agents, bringing a new level of efficiency to data transformation, migration, analytics, and even code generation and verification.
Users can select from a range of major large language models including OpenAI’s GPT-4.5, Anthropic’s Claude, and Meta’s Llama. Enterprises can also integrate their own models.
With safety and oversight in mind, Emergence AI has built in access controls, performance verification tools, and human review processes to ensure responsible deployment. Pricing has yet to be disclosed, but interested parties are encouraged to contact the firm directly.
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Qualcomm has acquired MovianAI, the generative AI division of Vietnam’s VinAI, in a move aimed at enhancing its capabilities across smartphones, PCs, and automotive technologies.
The US chipmaker described the acquisition as a strategic step to fuel future innovation in AI, with particular emphasis on customised models and advanced engineering.
MovianAI brings expertise in machine learning, computer vision, and natural language processing. Qualcomm highlighted the value of adding ‘high-calibre talent’ to its engineering team, with MovianAI’s founder and CEO Hung Bui, who previously worked at Google DeepMind, set to join the company.
Bui stated that his team is eager to contribute to Qualcomm’s mission of scaling foundational AI breakthroughs across industries.
Qualcomm has a two-decade history of working with Vietnamese companies, particularly in 5G, IoT, and AI development. While the financial terms of the deal remain undisclosed, Vietnamese outlet VNExpress International reported that Qualcomm has acquired a 65 per cent stake in MovianAI.
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Joelle Pineau, the Vice President of AI research at Meta, announced she will be leaving the company by the end of May, after nearly eight years with the organisation.
Pineau, who joined Meta in 2017, has overseen key AI initiatives, including the FAIR research unit, PyTorch, and the Llama AI models.
In a LinkedIn post, Pineau reflected on her time at Meta, mentioning the creation of groundbreaking AI projects such as PyTorch, FAISS, and Roberta.
She expressed gratitude for the opportunity to work alongside top AI researchers, with the aim of accelerating innovation through open-source contributions.
Pineau, also a professor at McGill University, stated that after her departure, she plans to take some time to reflect before pursuing new ventures. Her departure comes as Meta intensifies its focus on AI, including the recent launch of its Meta AI chatbot in Europe.
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