Sat.May 25, 2024

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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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Effective Prompting with A Handful of Fundamentals

Eugene Yan

Description of post here (150 chars)

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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.

AI 61
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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.

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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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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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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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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.

NLP 119
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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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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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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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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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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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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 Speak The Language Of Financial Success In Product Management

Speaker: Jamie Bernard

Success in product management goes beyond delivering great features - it’s about achieving measurable financial outcomes that resonate across the organization. By connecting your product’s journey with the company’s financial success, you’ll ensure that every feature, release, and innovation contributes to the bottom line, driving both customer satisfaction and business growth.

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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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