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A New Study from Korea Introduces a Deep Learning-Based Approach to Screen for Autism and Symptom Severity Using Retinal Photographs
A recent study introduces a potential game-changer in diagnosing autism spectrum disorder (ASD) by utilizing retinal photographs and advanced deep-learning algorithms. The study showcases outstanding performance metrics, with the algorithms accurately distinguishing between individuals with ASD and typical development. This approach offers a more objective and accessible method for ASD screening and could mark a…
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A Surgeon’s Reflections on Artificial Intelligence
As an oncologic surgeon and AI researcher, I observe a growing gap between clinical practice and AI research. Despite the disruptive potential of AI in healthcare, the lack of clinician involvement and top-down market strategies hinder its effectiveness. To truly innovate in healthcare, we need an interdisciplinary approach and a new generation of doctors skilled…
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The Just Right Size for Agile Teams
The text discusses the optimal size for Scrum teams and the advantages of small teams, recommending 4 to 5 members based on research and practical reasoning. It emphasizes the benefits of small teams in terms of efficiency, communication, and productivity, counterbalancing the potential need for larger teams in certain urgent situations.
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Images altered to trick machine vision can influence humans too
A series of experiments published in Nature Communications showed evidence of systematic influence on human judgments by adversarial perturbations.
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9 Effective Techniques To Boost Retrieval Augmented Generation (RAG) Systems
In 2023, advancements in NLP saw the emergence of ChatGPT and other Large Language Models, making fine-tuning LLMs easier. The demand for personalized RAGs surged across industries, with a need for tailored solutions. Techniques to enhance RAG efficiency include enhancing data quality, optimizing index structure, adding metadata, aligning query with documents, mixed retrieval, ReRank, prompt…
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SW/HW Co-optimization Strategy for LLMs — Part 2 (Software)
The text discusses the growing significance of software in the landscape of Large Language Models (LLMs) and outlines emerging libraries and frameworks enhancing LLM performance. It emphasizes the critical challenge of reconciling software and hardware optimizations for LLMs and highlights specific software tools and libraries catering to LLM deployment. Emerging hardware and memory technologies are…
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Nobel Prize winner warns against studying STEM subjects
Nobel laureate Sir Christopher Pissarides cautions against rushing into STEM education due to AI’s impact on job markets. He emphasizes AI’s potential to replace STEM jobs and suggests a shift towards roles requiring empathy and creativity. Pissarides is part of The Institute for the Future of Work, aiming to navigate the changes AI brings to…
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This AI Research Introduces TinyGPT-V: A Parameter-Efficient MLLMs (Multimodal Large Language Models) Tailored for a Range of Real-World Vision-Language Applications
TinyGPT-V is a novel multimodal large language model aiming to balance high performance with reduced computational needs. It integrates a 24G GPU for training and an 8G GPU/CPU for inference, leveraging Phi-2 language backbone and pre-trained vision modules for efficiency. The unique architecture delivers impressive results, showcasing promise for real-world applications.
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Meet KwaiAgents: A Generalized Information Seeking Agent System based on Large Language Models LLMs
Recent advances in AI and NLP have led to the development of KwaiAgents, an information-seeking agent system based on Large Language Models (LLMs). It comprises KAgentSys, KAgentLMs, and KAgentBench, demonstrating improved performance compared to existing open-source systems. Additionally, the Meta-Agent Tuning framework ensures effective performance with less sophisticated LLMs.
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IBM AI Cheif Says No Computer Science Degree Needed in Tech Soon
Matthew Candy, IBM’s global managing partner for generative AI, predicts that a computer science degree may soon be unnecessary in the tech industry, with AI enabling non-coders to innovate. He highlights a shift towards creativity and innovation over technical expertise but acknowledges concerns about job redundancy due to AI advancements. This signals a significant change…