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There was much praise for Dr Helen Webster's @scholastic_rat LearnHigher resource at #ALDcon23, The Three Domains of Critical Reading. You can download it for free: https://shorturl.at/cBLOT . If you use this resource, please leave a review. #LoveLD #CriticalReading #LearnHigher
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We love this write-up from edWeb.net about our last webinar where we brought together experts to dive into the components of the reading brain in relation to fluency and comprehension! It makes it easy to access the main take-aways. https://hubs.li/Q02ygW_R0
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I've shared these 'Introduction to Degrowth' slides before, but they needed a little update. I've recently come across an 'Internationalist' perspective on degrowth that these slides didn't include and I felt it was remiss of me to not have included it. So, I've added slides 21, 22 and 31 to this deck to redress my error. A big thanks to Nathalie Roy 🌍🌱, Matthias Schmelzer, Tonny Nowshin and Gabriel Trettel Silva for their work in this area. For anyone wanting to use this document, please feel free. It is downloadable from this post. #degrowth #globaljustice
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Using Citavi and NVivo 14 can help you overcome common obstacles in your literature review. ✍️ With Citavi and NVivo, you can: 🔎 Manage Information Overload 🔎 Synthesize Information 🔎 Boost Credibility 🔎 Integrate Directly in Word and more! See how integrating Citavi and NVivo can help you accelerate your literature review: https://bit.ly/3R7uwHV 👀 #literaturereview #writingtips #researchpaper #writingsoftware #academicchatter #phdchat
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A wonderful set of slides for your next discussion group! #degrowth #postgrowth
I've shared these 'Introduction to Degrowth' slides before, but they needed a little update. I've recently come across an 'Internationalist' perspective on degrowth that these slides didn't include and I felt it was remiss of me to not have included it. So, I've added slides 21, 22 and 31 to this deck to redress my error. A big thanks to Nathalie Roy 🌍🌱, Matthias Schmelzer, Tonny Nowshin and Gabriel Trettel Silva for their work in this area. For anyone wanting to use this document, please feel free. It is downloadable from this post. #degrowth #globaljustice
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Creative Lead, UW-Madison Master of Science in Design Innovation | Speculative Futures. Pataphysics. Design Research. Design Fiction. Regenerative Design.
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I've shared these 'Introduction to Degrowth' slides before, but they needed a little update. I've recently come across an 'Internationalist' perspective on degrowth that these slides didn't include and I felt it was remiss of me to not have included it. So, I've added slides 21, 22 and 31 to this deck to redress my error. A big thanks to Nathalie Roy 🌍🌱, Matthias Schmelzer, Tonny Nowshin and Gabriel Trettel Silva for their work in this area. For anyone wanting to use this document, please feel free. It is downloadable from this post. #degrowth #globaljustice
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As the RBA release ‘poor’ GDP growth rate news today for Australia, it’s a shame to see the reporting without any human or plantary constraints context. The evidence continues to mount for alternative way to measure global performance, one that respects natures and its limits (which includes us humans as we are not separate) Erin Remblance has produced an amazing document sharing key data points for our planetary context and a valid alternative economic outlook in degrowth. I encourage you all to read and challenge the assumptions you hold about how you live your life and business decisions are made. Courage is needed to challenge the systems that govern us and approach the future with hope and imagination. It is very easy with continued cost pressures, rising houses and an uncertain risk landscape to feel overwhelmed. I once read an thought provoking business book who’s author measured success by the numbers of days they got to go work in shorts and bare feet, an act that made them feel good. How would you measure success if the sole focus was your wellbeing? #challengeassumptions #sustainablewellbeing
I've shared these 'Introduction to Degrowth' slides before, but they needed a little update. I've recently come across an 'Internationalist' perspective on degrowth that these slides didn't include and I felt it was remiss of me to not have included it. So, I've added slides 21, 22 and 31 to this deck to redress my error. A big thanks to Nathalie Roy 🌍🌱, Matthias Schmelzer, Tonny Nowshin and Gabriel Trettel Silva for their work in this area. For anyone wanting to use this document, please feel free. It is downloadable from this post. #degrowth #globaljustice
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AI PO/PM @ SAP | NUS Alumni Ventures & Garnet Ventures Co-Founder | Double Degree, SAFe®, Generative AI, Innovation
Just completed this insightful course on Building and Evaluating Advanced Retrieval Augmented Generation (RAG) applications. Delving into sentence window retrieval, automerging, and aspects like question-answer relevance, grounding, cost, and latency, I've come to appreciate the depth and still much JTBD in this field. This ties perfectly with the latest from OpenAI. As people get hands-on experience with OpenAI's Assistants API Beta, it is a game-changer for building AI assistants. More than just executing instructions, functionalities like Retrieval, Code Interpretation and Function Calling are built in. This is already a game changer for all the various use cases that are already in development all over the world. Yet, the integration of these capabilities raises some existing considerations to be figured out. Ensuring confidence and reducing uncertainty in AI responses are crucial. Equally important are explainability - understanding AI decision-making, privacy - safeguarding user data, fairness - mitigating biases, and toxicity - avoiding harmful interactions. Addressing these aspects is vital in developing AI applications that are not only powerful but safe and ethical. I am hopeful. How has your experience been with the pace of innovation? #AI #TechEthics #Innovation
Do you want to expand your knowledge of the latest techniques in Retrieval Augmented Generation? Join our latest course, Building and Evaluating Advanced RAG Applications, built in collaboration with TruEra and LlamaIndex. This new course equips you with tools to build production-ready RAG applications. You’ll learn: ➡️ Two advanced retrieval methods: sentence-window retrieval and auto-merging retrieval. ➡️ Evaluation and experiment tracking to optimize your RAG pipeline performance. ➡️ The RAG evaluation and comparison triad: Context Relevance, Groundedness, and Answer Relevance. Enroll now: https://hubs.la/Q02blFqN0
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Excited to share my completion of DeepLearning.AI Building and Evaluating Advanced RAG (Retrieval Augumented Generation) course! This journey has equipped me with invaluable knowledge and skills in the exciting field of next-generation language models. Exploration of RAG Pipelines: I delved into building robust RAG pipelines, leveraging the power of OpenAI GPT-3.5-Turbo for response generation for the questions and Hugging Face's BGE Small English v 1.5 model (BAAI/bge-small-en-v1.5) for efficient embedding creation, BAAI/bge-reranker-base specialized reranker model further enhances performance by precisely scoring and selecting the most relevant retrieved documents, ensuring the LLM has access to the highest quality information for generating accurate and informative responses. This combination ensures accurate context representation, crucial for top-quality retrieval and generation. Mastering RAG Training Metrics: I explored the RAG Triad metrics: Answer Relevance, Context Relevance, and Groudedness. These metrics provide a comprehensive evaluation framework, ensuring generated responses are relevant, grounded in factual information, and address the user's query effectively. Additionally, I gained expertise in utilizing TruLens, a novel tool that assesses model responses based on ethical parameters like honesty, harmlessness, and helpfulness. Advanced Retrieval Techniques: I explored two cutting-edge retrieval methods: Sentence Window Retrieval and Auto Merging Retrieval. Sentence Window Retrieval: This innovative approach tackles the issue of limited context by dividing the input into smaller chunks, allowing the LLM to access a broader scope of information before and after the query sentence. This leads to improved contextual understanding and enhanced response quality. Auto Merging Retrieval: This technique utilizes a sophisticated tree-based merging algorithm to optimize the retrieval process and enhance response generation efficiency. By focusing on the most relevant information, it reduces redundancy and improves overall performance. Where Auto Merging Retrieval can be complimentary to Sentence Window Retrieval technique Auto Merging Retrieval complements Sentence Window Retrieval by efficiently focusing the LLM's attention on the most relevant information within the wider context window provided by Sentence Window Retrieval, especially beneficial for large datasets, time-sensitive applications, and reducing noise. I'm incredibly grateful to DeepLearning.AI Andrew Ng Jerry Liu Anupam Datta LlamaIndex TruEra for offering this exceptional course. The acquired knowledge and skills will undoubtedly prove invaluable in my career as I navigate the ever-evolving landscape of large language models and explore their numerous potential applications. #RAG #DeepLearning #LLMs #NaturalLanguageProcessing #AI #CourseCompletion #AdvancedRetrievalTechniques
Do you want to expand your knowledge of the latest techniques in Retrieval Augmented Generation? Join our latest course, Building and Evaluating Advanced RAG Applications, built in collaboration with TruEra and LlamaIndex. This new course equips you with tools to build production-ready RAG applications. You’ll learn: ➡️ Two advanced retrieval methods: sentence-window retrieval and auto-merging retrieval. ➡️ Evaluation and experiment tracking to optimize your RAG pipeline performance. ➡️ The RAG evaluation and comparison triad: Context Relevance, Groundedness, and Answer Relevance. Enroll now: https://hubs.la/Q02blFqN0
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