Tech
Meta Launches Muse Spark, Its First Major AI Model in Nine Months
Meta has unveiled its first major AI model in nine months, following a $14.3 billion (€12.24 billion) investment spree and executive hiring push to rival OpenAI and Google. The American tech company introduced the model, called Muse Spark, on Wednesday, claiming it is faster and smarter than its previous technologies.
The company, founded by Mark Zuckerberg, invested $14.3 billion in Scale AI in June 2025 and recruited its CEO and co-founder, Alexandr Wang, to oversee Meta Superintelligence Labs, which houses teams working on foundational AI models. Zuckerberg also embarked on a hiring campaign, bringing in executives from competitors including OpenAI, Anthropic, and Google.
In a blog post, Meta said, “Over the last nine months, Meta Superintelligence Labs rebuilt our AI stack from the ground up, moving faster than any development cycle we have run before. This initial model is small and fast by design, yet capable enough to reason through complex questions in science, math, and health. It is a powerful foundation, and the next generation is already in development.”
Muse Spark is positioned as a significant upgrade over Meta’s last major release, Llama 4, launched in April 2025. The company highlighted that the model excels in advanced reasoning, particularly in scientific, mathematical, and medical queries. To improve its health advice capabilities, Meta worked with over 1,000 physicians to curate training data, aiming for more accurate and comprehensive responses.
The AI model will power the company’s digital assistant in the Meta AI app and website, with planned integration across Facebook, Instagram, WhatsApp, Messenger, and the Ray-Ban Meta AI glasses. A “contemplating mode” will gradually roll out, allowing multiple AI agents to reason in parallel on complex tasks. Meta’s technical blog noted this feature is designed to compete with high-level reasoning in models such as Gemini Deep Think and GPT Pro.
Zuckerberg emphasized on social media that Meta aims to build AI products that “don’t just answer your questions but act as agents that do things for you.” Unlike conventional chatbots, these AI agents operate autonomously, gathering information based on user preferences to assist without direct human commands.
One notable shift for Meta is the move away from open-source AI models. Unlike earlier releases, Muse Spark is not available for public download, meaning access to the technology is currently restricted. The company said the model is initially available only in the United States.
Muse Spark underscores Meta’s aggressive push into the competitive AI market, combining extensive investment, executive recruitment, and technical innovation to challenge the dominance of established players like OpenAI and Google.
Tech
European Governments Move to Cut Dependence on Palantir Amid Rising Security and Privacy Concerns
Tech
Microsoft Unveils In-House AI Models and Quantum Breakthrough as Tech Giant Moves to Reduce External Dependence
Microsoft has taken a major step toward reducing its reliance on external artificial intelligence partners, unveiling seven in-house AI models at its Build 2026 developer conference in San Francisco. The move signals a strategic shift as the company seeks greater control over its AI stack while its key investee firms prepare for high-profile public listings.
Satya Nadella, Microsoft’s chief executive, told attendees that the industry is entering a new phase in which companies must do more than simply consume frontier AI systems. “We believe the time has come for every company to move from consuming a frontier model to fully participating at the frontier,” he said.
At the centre of the announcement is MAI-Thinking-1, Microsoft’s first reasoning model built entirely from scratch using commercially licensed data and without distillation from external systems. The model includes 35 billion active parameters and a 256,000-token context window, designed for complex reasoning tasks, coding, and long-form instruction handling.
Microsoft also introduced MAI-Code-1-Flash, a coding-focused model integrated into GitHub Copilot and Visual Studio Code, aimed at converting natural language prompts into functional software code. The company said these tools will run on Azure infrastructure, allowing it to reduce costs currently paid to external model providers and potentially offer cheaper services to developers.
Mustafa Suleyman, chief executive of Microsoft AI, said internal testing suggested strong performance gains. After optimisation for consulting firm McKinsey, he said the new models outperformed OpenAI’s GPT-5.5 in quality while offering what Microsoft estimates as up to ten times better cost efficiency, based on scaled public pricing comparisons.
In independent evaluations conducted by Surge, Microsoft’s third-party rating partner, MAI-Thinking-1 was reportedly preferred over Anthropic’s Claude Sonnet 4.6, while matching Claude Opus 4.6 on coding benchmarks.
Alongside its AI announcements, Microsoft revealed progress in quantum computing. The company’s new Majorana 2 chip is said to be 1,000 times more stable than its predecessor, extending qubit lifespan from milliseconds to an average of 20 seconds. While still far from practical deployment, Microsoft believes this marks a meaningful step toward scalable quantum machines.
Zulfi Alam, corporate vice president of Microsoft Quantum, said the company aims to deliver a commercially useful quantum system by 2029, though current prototypes contain only 12 qubits, far short of the millions required for full-scale systems.
The announcements come as Microsoft’s AI partners move toward public markets. Anthropic has filed confidentially for an IPO following a major funding round valuing it at $965 billion, while OpenAI is also preparing a filing. Microsoft has invested heavily in both companies, committing billions of dollars while integrating their models into Azure.
The new direction suggests Microsoft is positioning itself to compete directly with its own partners, as the race for dominance in advanced AI and next-generation computing intensifies.
Tech
Estonia’s AI Education Model Draws Attention as Europe Debates Digital Learning
As European governments weigh how to integrate artificial intelligence into classrooms and allocate funding for digital literacy, Estonia’s approach to AI education is gaining attention as a practical and structured model.
The Baltic nation’s AI Leap programme is designed not only to teach students how to use artificial intelligence tools but also to strengthen critical thinking and teacher involvement at a time when AI is becoming deeply embedded in everyday learning.
Concerns have grown across Europe that while students are increasingly comfortable using AI tools, many struggle to evaluate or question the information these systems generate. Educators and employers have raised concerns that overreliance on chatbots and automated tools could weaken analytical thinking and increase vulnerability to misinformation.
Estonia has chosen to address this challenge directly rather than attempting to limit student exposure to AI.
According to the AI Leap programme, between 64% and 90% of Estonian students were already using AI tools before the initiative began. Programme organisers argued that ignoring this reality could undermine learning and reasoning skills.
The initiative aims to train 48,000 students and 6,700 teachers over two years in a country with a population of just 1.36 million.
The programme has two primary goals: helping teachers adapt to AI-assisted education and encouraging students to develop responsible, thoughtful AI habits.
To support this effort, Estonia has introduced several key measures. Teachers participate in study circles that meet monthly to develop teaching methods and exchange experiences. A central online platform provides educational resources, videos, self-assessment tools and discussion forums.
More than 4,000 teachers are also receiving premium access to advanced AI platforms such as ChatGPT and Gemini to support lesson planning and classroom preparation.
One of the programme’s most distinctive features is a Socratic-style chatbot designed to guide students rather than provide direct answers. The chatbot encourages questioning, self-management and contextual thinking, helping students assess AI-generated information instead of accepting it automatically.
The programme also includes debate leagues, creative arts projects and student-led initiatives aimed at encouraging discussion and experimentation with AI beyond formal classroom settings.
Estonia has placed strong emphasis on management and implementation. School principals oversee local delivery, while nine regional managers coordinate activities across seven educational regions. The initiative operates through a public-private partnership, with the government providing half of the funding and private partners contributing the remainder.
Technology companies, educators and researchers are involved in designing and testing tools tailored to Estonia’s education system.
Education analysts say Estonia’s strategy highlights a broader lesson for Europe: AI literacy may depend less on limiting technology and more on teaching students how to use it thoughtfully, critically and responsibly.
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