Sat.May 25, 2024

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Effective Prompting with A Handful of Fundamentals

Eugene Yan

Description of post here (150 chars)

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Could “Robot-Phobia” Worsen the Hospitality Industry’s Labor Shortage?

Unite.AI

The hospitality industry has grappled with a severe labor shortage since the COVID-19 pandemic. As businesses struggle to find enough workers to meet the growing demand, many have turned to robotic technology as a potential solution. However, a recent study conducted by Washington State University suggests that the introduction of robots in the workplace may inadvertently exacerbate the labor shortage due to a phenomenon known as “robot-phobia” among hospitality workers.

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Microsoft Research Introduces Gigapath: A Novel Vision Transformer For Digital Pathology

Marktechpost

Digital pathology converts traditional glass slides into digital images for viewing, analysis, and storage. Advances in imaging technology and software drive this transformation, which has significant implications for medical diagnostics, research, and education. There is a chance to speed up advancements in precision health by a factor of ten because of the present generative AI revolution and the parallel digital change in biomedicine.

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The GenAI TR/Lexis Study – Stanford Replies ‘We Were Denied Access’

Artificial Lawyer

Following a request for comment on the controversial study ‘Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools’, conducted by the Human-Centred AI group.

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

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This AI Research from the University of Chicago Explores the Financial Analytical Capabilities of Large Langauge Models (LLMs)

Marktechpost

GPT-4 and other Large Language Models (LLMs) have proven to be highly proficient in text analysis, interpretation, and generation. Their exceptional effectiveness extends to a wide range of financial sector tasks, including sophisticated disclosure summarization, sentiment analysis, information extraction, report production, and compliance verification.

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Elia: An Open Source Terminal UI for Interacting with LLMs

Marktechpost

People who work with large language models often need a quick and efficient way to interact with these powerful tools. However, many existing methods require switching between applications or dealing with slow, cumbersome interfaces. Some solutions are available, but they come with their own set of limitations. Web-based interfaces are common but can be slow and may not support all the models users need.

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How to Log out of Gemini AI 

Ofemwire

Logging out of Gemini AI is just a three-step process. Within a few seconds, you’re done. However, most users don’t know what logging out of Gemini AI actually means. You won’t be among those users because you’ll know what it means. In this article, you’ll learn how to log out of Gemini AI, what doing that means, and more.

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Uni-MoE: A Unified Multimodal LLM based on Sparse MoE Architecture

Marktechpost

Unlocking the potential of large multimodal language models (MLLMs) to handle diverse modalities like speech, text, image, and video is a crucial step in AI development. This capability is essential for applications such as natural language understanding, content recommendation, and multimodal information retrieval, enhancing the accuracy and robustness of AI systems.

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Beyond the Frequency Game: AoR Evaluates Reasoning Chains for Accurate LLM Decisions

Marktechpost

Large Language Models (LLMs) have driven remarkable advancements across various Natural Language Processing (NLP) tasks. These models excel in understanding and generating human-like text, playing a pivotal role in applications such as machine translation, summarization, and more complex reasoning tasks. The progression in this field continues to transform how machines comprehend and process language, opening new avenues for research and development.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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MIT Researchers Propose Cross-Layer Attention (CLA): A Modification to the Transformer Architecture that Reduces the Size of the Key-Value KV Cache by Sharing KV Activations Across Layers

Marktechpost

The memory footprint of the key-value (KV) cache can be a bottleneck when serving large language models (LLMs), as it scales proportionally with both sequence length and batch size. This overhead limits batch sizes for long sequences and necessitates costly techniques like offloading when on-device memory is scarce. Furthermore, the ability to persistently store and retrieve KV caches over extended periods is desirable to avoid redundant computations.

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EleutherAI Presents Language Model Evaluation Harness (lm-eval) for Reproducible and Rigorous NLP Assessments, Enhancing Language Model Evaluation

Marktechpost

Language models are fundamental to natural language processing (NLP), focusing on generating and comprehending human language. These models are integral to applications such as machine translation, text summarization, and conversational agents, where the aim is to develop technology capable of understanding and producing human-like text. Despite their significance, the effective evaluation of these models remains an open challenge within the NLP community.

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Enhancing Neural Network Interpretability and Performance with Wavelet-Integrated Kolmogorov-Arnold Networks (Wav-KAN)

Marktechpost

Advancements in AI have led to proficient systems that make unclear decisions, raising concerns about deploying untrustworthy AI in daily life and the economy. Understanding neural networks is vital for trust, ethical concerns like algorithmic bias, and scientific applications requiring model validation. Multilayer perceptrons (MLPs) are widely used but lack interpretability compared to attention layers.

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A Paradigm Shift: MoRA’s Role in Advancing Parameter-Efficient Fine-Tuning Techniques

Marktechpost

Parameter-efficient fine-tuning (PEFT) techniques adapt large language models (LLMs) to specific tasks by modifying a small subset of parameters, unlike Full Fine-Tuning (FFT), which updates all parameters. PEFT, exemplified by Low-Rank Adaptation (LoRA), significantly reduces memory requirements by updating less than 1% of parameters while achieving similar performance to FFT.

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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Transparency in Foundation Models: The Next Step in Foundation Model Transparency Index FMTI

Marktechpost

Foundation models are central to AI’s influence on the economy and society. Transparency is crucial for accountability, competition, and understanding, particularly regarding the data used in these models. Governments are enacting regulations like the EU AI Act and the US AI Foundation Model Transparency Act to enhance transparency. The Foundation Model Transparency Index (FMTI) introduced in 2023 evaluates transparency across 10 major developers (e.g.

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