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10 Best AI Collaboration Tools (February 2025)

Unite.AI

The following tools use artificial intelligence to streamline teamwork from summarizing long message threads to auto-generating project plans so you can focus on what matters. For example, Miros AI can instantly create mind maps or diagrams from a prompt, and even auto-generate a presentation from a collection of sticky notes.

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Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A Closed-Loop Framework for Automating Scientific Research with Iterative Feedback

Marktechpost

Researchers want to create a system that eventually learns to bypass humans completely by completing the research cycle without human involvement. Several research environments have been developed to automate the research process partially. Such developments could raise productivity and bring people closer to tough challenges.

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10 Best AI Note-Taking Apps (February 2025)

Unite.AI

Key features of Fathom: Fast AI Summaries: Generates meeting summaries within 30 seconds of meeting completion, so you get instant post-meeting notes. Beyond transcription, Otter provides automated summarization and smart highlights that help users review lengthy meetings quickly. Visit Otter 4. Fireflies.ai Visit Avoma 6.

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HARPA AI Review: How I Finally Tamed My Tab Overload

Unite.AI

Verdict HARPA AI automates tasks securely in your browser with over 100 commands and support for top AI models. Pros and Cons Automates routine online tasks to free up time for more complex projects. Combines AI with web automation for things like content creation, email management, and SEO optimization.

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Retrain ML models and automate batch predictions in Amazon SageMaker Canvas using updated datasets

AWS Machine Learning Blog

You can now retrain machine learning (ML) models and automate batch prediction workflows with updated datasets in Amazon SageMaker Canvas , thereby making it easier to constantly learn and improve the model performance and drive efficiency. Automating this process provides efficiency, scalability, and timely decision-making.

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Additionally, it poses a security risk when handling sensitive data, making it a less desirable option in the age of automation and digital security.

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Prioritizing employee well-being: An innovative approach with generative AI and Amazon SageMaker Canvas

AWS Machine Learning Blog

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Complete the following steps: Choose Prepare and analyze data. Complete the following steps: Choose Run Data quality and insights report. Choose Create.