π Faculty Announcement - New Computational Linguistics Faculty Member
This article announces the appointment of Kanishka Misra as a new computational linguistics faculty member at UT Linguistics. It also encourages prospective PhD students to apply to work with him.
Key Points:
β’ Kanishka Misra joins UT Linguistics faculty.
β’ He is a great mentor for PhD students.
β’ Prospective students are encouraged to apply.
π Resources:
β’ Kanishka Misra β - UT Austin Computational Linguistics Faculty
β’ UT Linguistics β - Department of Linguistics at University of Texas at Austin
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π€ Evaluation Methodology - Variance in Small Datasets
This article discusses the variance in an evaluation methodology using four samples per question for relatively small datasets. A plot demonstrating the results is included.
Key Points:
β’ Investigates variance in evaluation methodology.
β’ Uses four samples per question.
β’ Results suggest four samples are sufficient for most conclusions.
π Resources:
β’ M. BalunoviΔ β - Author of the analysis.
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π Streamlit Application - Course Resource Display
This article showcases a Streamlit application use case: displaying course lectures, tutorials, resources, and FAQs. The example includes multi-page applications with additional information sections.
Key Points:
β’ Streamlit effectively displays course resources.
β’ Multi-page applications enhance organization.
β’ Includes sections for contact information and further resources.
π Resources:
β’ Streamlit β - Open-source Python library for building web applications.
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β¨ Anime Character Profile - Eri Shiina
This article provides a profile of Eri Shiina, a character from Angel Beats!. It highlights her mysterious past and personality traits.
Key Points:
β’ Eri Shiina is a mysterious kunoichi from Angel Beats!.
β’ She has resided in the afterlife for over 100 years.
β’ She possesses a serious demeanor but enjoys cute things.
π Resources:
β’ Angel Beats! β - Anime series featuring Eri Shiina.
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π‘ Indian Council of Historical Research - Scam Investigation
This article reports on a Rs 14 crore scam at the Indian Council of Historical Research (ICHR), involving the organization's history rewriting efforts.
Key Points:
β’ Rs 14 crore scam at the ICHR.
β’ Public funds misused without proper checks.
β’ Contracts awarded to associates of the Sangh.
π Resources:
β’ Scroll.in β - News website reporting on the investigation.
β’ Article Link β - Scroll.in's investigation.
π€ React useEffect Hook - useEffectOnDepChange
This article describes a custom React hook, useEffectOnDepChange, designed to run a useEffect only when a specific dependency changes, preventing execution on component mount.
Key Points:
β’ Custom hook for controlling useEffect execution.
β’ Runs only when specified dependency changes.
β’ Avoids unnecessary executions on component mount.
π Resources:
β’ React β - JavaScript library for building user interfaces.
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π€ AI Report Analysis - ChatGPT Growth and User Base
This article summarizes key findings from a comprehensive AI report, focusing on ChatGPT's rapid growth and its significant user base in India.
Key Points:
β’ ChatGPTβs user base grew 8x in 2.5 years.
β’ Reached 800 million monthly users.
β’ India has the largest user base (14%).
π Resources:
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π‘ Satire and Reality - Interview Setting Analogy
This article uses an anecdote about an interview setting to illustrate the blurring lines between satire and reality in modern society.
Key Points:
β’ Anecdote of an interview setting.
β’ Highlights the absurdity of the situation.
β’ Illustrates the difficulty in creating satire due to the absurdity of real-life events.
π Resources:
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π€ AI Model Training - Synthetic Data and AI Agents
This article discusses the use of synthetic data and AI agents in training Microsoft's open-source Phi-4 model.
Key Points:
β’ Leverages synthetic data for model training.
β’ Uses AI agents to create contextual training data.
β’ Innovative approach to data curation.
π Resources:
β’ Microsoft Phi-4 Model β - (Placeholder - a specific link to the research paper is needed)
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π‘ Venture Capital Performance - Top Quartile Funds
This article discusses the performance disparity among venture capital funds, highlighting the significant underperformance of non-top-quartile funds.
Key Points:
β’ Non-top-quartile VC funds destroy money for LPs.
β’ Consistent top-quartile performance is unpredictable.
β’ Risk of significant losses exists.
π Resources:
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