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— scientists at EPFL have collected and curated MammAlps, the first richly annotated, multi-view, multimodal wildlife behaviour dataset in collaboration with the Swiss National Park. MammAlps is designed to train AI models for species and behaviour recognition tasks, and ultimately to help researchers understand animal behaviour better. This work could make conservation efforts faster, cheaper, and smarter. MammAlps was developed by Valentin Gabeff, a PhD student at EPFL under the supervision of Professors Alexander Mathis and Devis Tuia, together with their respective research teams.
— MammAlps brings a new standard to wildlife monitoring: a full sensory snapshot of animal behaviour across multiple angles, sounds, and contexts. It also introduces a "long-term event understanding" benchmark, meaning scientists can now study not just isolated behaviours from short clips, but broader ecological scenes over time—like a wolf stalking a deer across several camera views.
— The researchers set up nine camera traps that recorded more than 43 hours of raw footage over the course of several weeks. The team then meticulously processed it, using AI tools to detect and track individual animals, resulting in 8.5 hours of material showing wildlife interaction. They labeled behaviors using a hierarchical approach, categorizing each moment at two levels: high-level activities like foraging or playing, and finer actions like walking, grooming, or sniffing. This structure allows AI models to interpret behaviors more accurately by linking detailed movements to broader behavioral patterns.
— To provide AI models with richer context, the team supplemented video with audio recordings and captured "reference scene maps" that documented environmental factors like water sources, bushes, and rocks. This addition al data enables better interpretation of habitat-specific behaviours. "By incorporating other modalities alongside video, we've shown that AI models can better identify animal behaviour," explains Alexander Mathis. "This multi-modal approach gives us a more complete picture of wildlife behaviour."
— "Speakers at the weekend event talked about how AI can seek out deeper, universal values that humanity hasn't even been privy to, and that machines should be taught to pursue 'the good', or risk enslaving an entity capable of suffering."
— The process was developed by MIT mechanical engineering graduate student Alex Kachkine, who restores paintings via traditional hand-painting techniques as a hobby.
— Amazon CEO Andy Jassy has called generative AI a "once-in-a-lifetime type of business opportunity." The investment in North Carolina will create roughly 500 jobs in the state, Amazon said.
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— Leading this monumental round is none other than SoftBank. Joining SoftBank are Microsoft, Coatue, Altimeter, and Thrive Capital. The funding is to help in more research, scaling computer infrastructure, and delivering more powerful AI tools, says OpenAI.
— "The story of Browser Use began at ETH Zurich's Student Project House accelerator, founded by Magnus Müller and Gregor Zunic. Their journey, starting in 2024 during their master’s degrees in data science, reflects a blend of academic rigor and entrepreneurial spirit. Müller’s prior experience in web scraping combined with Zunic's data science expertise proved to be a potent mix. Their breakthrough idea was to leverage data science principles to guide browser actions, effectively teaching AI agents how to interact with websites programmatically. The rapid development of a Browser Use demo in just five weeks, followed by its open-sourcing, speaks volumes about the team's capabilities and the immediate appeal of their solution. Being part of Y Combinator's prestigious Winter 2025 batch further validates their innovative approach and potential for growth."
— "Browser Use gained significant traction thanks to its integration into Butterfly Effect's viral Manus tool. This Chinese startup leveraged Browser Use to power Manus, showcasing the practical applications and effectiveness of the technology in real-world scenarios. The virality of Manus significantly amplified awareness of Browser Use, propelling it into the spotlight and attracting wider developer interest."
— Alibaba touted its new model, QwQ-32B, in an online statement as delivering "exceptional performance, almost entirely surpassing OpenAI-o1-mini and rivaling the strongest open-source reasoning model, DeepSeek-R1." OpenAI-o1-mini is the American company's cost-efficient reasoning model released last year.
— The release of Alibaba's new AI model comes a day after the launch of a "general AI agent" called Manus by another company. A video on the website dedicated to Manus says the software can carry out complex, multi-step tasks such as screening resumés and creating a website. According to Reuters, Manus is the creation of Chinese company Monica. The video also says the AI agent is more advanced than a chatbot because it doesn't only generate ideas but delivers tangible results, such as producing a report recommending properties to buy based on specific criteria.
