Lonestar and Phison have successfully launched the first-ever lunar data centre infrastructure aboard a SpaceX Falcon 9 rocket. The mission, set to land on the moon on March 4, is a joint venture to send Phison’s Pascari solid-state drives (SSDs), packed with data from various clients, to the lunar surface. The companies plan to expand this infrastructure, with ambitions to scale up to a petabyte of storage in the coming years.
The idea of building a data centre on the moon originated in 2018, driven by the need for secure, off-Earth storage to safeguard against climate disasters and cyber-attacks. Lonestar’s CEO, Chris Stott, noted that data has become as valuable as oil, if not more precious. The SSDs were rigorously tested for space readiness, ensuring their durability for long-term use without the possibility of on-site repairs.
This mission is just the beginning, as Lonestar and Phison aim to revolutionise data storage with nearly limitless capacity and energy efficiency in space. As AI-driven demand for data storage continues to rise, this lunar project could set the stage for future space-based infrastructure, promising a new era in data management.
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Inception, a Palo Alto-based startup founded by Stanford professor Stefano Ermon, has unveiled an innovative AI model based on diffusion technology. Unlike traditional large language models that generate text sequentially, Inception’s diffusion-based model can produce large blocks of text in parallel, making it up to 10 times faster and more cost-efficient. The company claims its model offers similar capabilities to existing LLMs but with significantly improved performance.
The diffusion model operates differently from the typical approach of LLMs, which generate text word by word. Instead, it starts with a rough estimate and refines the output all at once, allowing for faster processing. Ermon, who has been researching this technology for years at Stanford, believes it will revolutionise AI by enabling more efficient use of computational resources, particularly GPUs. Inception already boasts several Fortune 100 companies as clients, attracted by its promise to reduce AI latency and costs.
Inception’s model can handle various tasks, including code generation and question answering, and is designed for flexible deployment options such as API, on-premises, and edge devices. This breakthrough technology is expected to lead to more accessible and scalable AI solutions, positioning Inception at the forefront of AI development.
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ElevenLabs, a Palo Alto-based AI startup valued at $3.3 billion, has introduced its first stand-alone speech-to-text model, Scribe. The company, which is better known for its audio-generation capabilities, now aims to disrupt the speech detection market by providing a faster and more accurate alternative to existing models like Whisper and Deepgram. Scribe supports over 99 languages, with top accuracy in more than 25, including English, French, and Spanish.
The new AI model has already outperformed competitors like Google’s Gemini 2.0 Flash and OpenAI’s Whisper Large V3 in benchmark tests. It also includes features like speaker diarisation, accurate subtitles, and sound event tagging, which could appeal to customers in media and content creation. While Scribe currently only works with pre-recorded audio, ElevenLabs plans to release a real-time version soon.
Priced at $0.40 per hour of transcribed audio, Scribe offers a competitive rate, though some rivals currently offer lower prices. With this move into speech-to-text, ElevenLabs is positioning itself to expand its AI offerings and challenge established players in the field.
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Amazon has unveiled Alexa+, a major upgrade to its voice assistant, integrating advanced AI to enhance interactions.
The new version can process multiple prompts in sequence, store user preferences, and manage tasks such as making reservations and sending reminders. AI-powered improvements aim to make Alexa more conversational and responsive.
The company has invested heavily in the technology, incorporating AI models through its Bedrock platform. Startup Anthropic contributed to development, with its Claude AI underpinning Alexa+.
The service will be free for Amazon Prime members, while non-Prime users will pay $19.99 per month. A phased rollout begins in March.
Alexa+ will integrate seamlessly with Amazon devices, including Ring doorbells, allowing users to access video recordings and control smart home features. It can also analyse documents, helping users understand contracts and regulations.
Industry competition remains strong, with Apple and Google also enhancing their voice assistants through AI.
Amazon hopes the overhaul will boost engagement, as Alexa usage had declined due to limited advancements. The company’s stock rose 1.7% following the announcement, reflecting investor confidence in the AI-driven update.
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China’s embrace of DeepSeek’s AI models has expanded beyond tech companies into everyday household appliances. The startup, based in Hangzhou, has seen a surge of support from Chinese manufacturers, with home appliance giants such as Haier, Hisense, and TCL Electronics announcing plans to incorporate DeepSeek’s AI models into their products. These appliances, already equipped with voice-activated commands, are set to become even smarter with DeepSeek’s models, which promise greater accuracy and functionality.
DeepSeek has made waves in the AI sector this year, with its large language models competing against Western systems but at a fraction of the cost. This has sparked immense pride in China, where the company is seen as a testament to the country’s growing tech capabilities in the face of US efforts to limit its advancements. The company’s founder, Liang Wenfeng, has received significant recognition from Chinese authorities, and DeepSeek is expected to soon release its next-generation R2 reasoning model.
The impact of DeepSeek’s technology is already being felt across industries. From robotics to smart appliances, its AI models offer improved precision in tasks such as obstacle avoidance in robot vacuum cleaners. These devices are expected to better understand complex commands, like ‘Gently wax the wooden floor in the master bedroom but avoid the Legos,’ making everyday life more efficient and intuitive.
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Baidu is set to launch the next generation of its Ernie AI model, the Ernie 4.5, in mid-March. This upgraded version will feature improved reasoning capabilities and enhanced multimodal functions, allowing it to process and integrate a variety of data formats, including text, images, audio, and video. Baidu also plans to make the Ernie 4.5 series open source from June 30, marking a significant shift in its approach to AI development.
The Chinese tech giant has faced fierce competition in the AI race, particularly from the rising startup DeepSeek, whose models are seen as rivals to leading US systems at a much lower cost. Despite claiming that Ernie’s performance is comparable to OpenAI’s GPT-4, Baidu has struggled to gain widespread adoption of its AI model. The emergence of DeepSeek has further complicated Baidu’s aspirations in the sector, leading the company to reassess its strategy.
Baidu’s CEO, Robin Li, who once advocated for keeping AI models closed-source, has acknowledged the success of DeepSeek and other competitors. He now views the open-source approach as essential for the future of AI development. This shift comes as Baidu continues to compete with other tech giants, including Alibaba, which recently announced its plans to make its video and image-generating AI model, Wan 2.1, open source.
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The European Commission has approved Nokia’s $2.3 billion acquisition of US-based Infinera, confirming the deal raises no competition concerns.
The approval was granted unconditionally, as the combined company will hold only a moderate share of the optical transport equipment market.
Nokia’s takeover of Infinera, announced last June, will make it the second-largest player in optical networking with a 20% market share, trailing Huawei.
Western firms have struggled to compete in China, giving Huawei a dominant position in the sector.
Nomagic, a fast-growing Polish startup, has secured $44 million in funding to develop its robotic arms used in logistics operations like picking, packing, and moving. The company plans to use this investment to expand its technology and business, aiming to sell its robots in North America. Nomagic’s technology, which uses AI and automation software, has already gained significant traction in industries like e-commerce and pharmaceuticals, with a 220% growth in annual recurring revenue last year.
The funding round, led by the European Bank for Reconstruction and Development (EBRD), highlights the growing importance of robotics in rebuilding industrial competitiveness in Europe. Nomagic’s approach focuses on software rather than hardware, enabling its robotic arms to perform across various use cases with ease. This strategy sets it apart from other robotics companies and positions it to capitalise on the increasing demand for automation.
Nomagic’s competitors, such as Covariant, are also seeing success in the field, with Amazon hiring Covariant’s founders and licensing its technology. Industry leaders like Nvidia and SoftBank are also investing in robotic technology, underscoring the potential of this growing market. With government backing and increasing private investment, robotics is playing a key role in modernising logistics and manufacturing industries.
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Estonia has launched a new initiative aimed at preparing students and teachers for the age of AI. The ‘AI Leap’ programme will provide access to popular AI chatbots, including an educational version of ChatGPT, to help build digital skills. Starting in September 2025, the programme will involve 20,000 high school students and 3,000 teachers, with plans to expand to vocational schools and an additional 38,000 students and 3,000 teachers in 2026.
Education Minister Kristina Kallas emphasised that Estonia’s economic competitiveness depends on how well the country adapts to AI, ensuring young people are equipped for the future. As part of the initiative, Estonia will also invest in teacher training to support the integration of AI in classrooms.
The programme is a public-private partnership, with negotiations underway with major AI companies, including OpenAI and Anthropic. OpenAI has expressed its pride in collaborating with Estonia to bring ChatGPT Edu to the education system, aiming to better prepare students for the workforce. Estonia’s use of AI in education is seen as a model that other countries may follow as the EU pushes to increase digital skills across Europe by 2030.
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British universities have been urged to reassess their assessment methods after new research revealed a significant rise in students using genAI for their projects. A survey of 1,000 undergraduates found that 88% of students used AI tools like ChatGPT for assessments in 2025, up from 53% last year. Overall, 92% of students now use some form of AI, marking a substantial shift in academic behaviours in just a year.
The report, by the Higher Education Policy Institute and Kortext, highlights how AI is being used for tasks such as summarising articles, explaining concepts, and suggesting research ideas. While AI can enhance the quality of work and save time, some students admitted to directly including AI-generated content in their assignments, raising concerns about academic misconduct.
The research also found that concerns over AI’s potential impact on academic integrity vary across demographics. Women, wealthier students, and those studying STEM subjects were more likely to embrace AI, while others expressed fears about getting caught or receiving biased results. Despite these concerns, students generally feel that universities are addressing the issue of academic integrity, with many believing their institutions have clear policies on AI use.
Experts argue that universities need to adapt quickly to the changing landscape, with some suggesting that AI should be integrated into teaching rather than being seen solely as a threat to academic integrity. As AI tools become an essential part of education, institutions must find a balance between leveraging the technology and maintaining academic standards.
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