Sat.Nov 02, 2024

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Jamba 1.5: Hybrid Mamba-Transformer Model for Advanced NLP

Analytics Vidhya

Jamba 1.5 is an instruction-tuned large language model that comes in two versions: Jamba 1.5 Large with 94 billion active parameters and Jamba 1.5 Mini with 12 billion active parameters. It combines the Mamba Structured State Space Model (SSM) with the traditional Transformer architecture. This model, developed by AI21 Labs, can process a 256K effective […] The post Jamba 1.5: Hybrid Mamba-Transformer Model for Advanced NLP appeared first on Analytics Vidhya.

NLP 200
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Anthropic Launches Visual PDF Analysis in Latest Claude AI Update

Unite.AI

In a significant advancement for document processing, Anthropic has unveiled new PDF support capabilities for its Claude 3.5 Sonnet model. This development marks a crucial step forward in bridging the gap between traditional document formats and AI analysis, enabling organizations to leverage advanced AI capabilities across their existing document infrastructure.

AI 189
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Deploying Custom Detectron2 Models with a REST API: A Step-by-Step Guide.

Towards AI

Author(s): Gennaro Daniele Acciaro Originally published on Towards AI. An image generated using Midjourney In the life of a Machine Learning Engineer, training a model is only half the battle. Indeed, after obtaining a neural network that accurately predicts all the test data, it remains useless unless it’s made accessible to the world. Model deployment is the process of making a model accessible and usable in production environments, where it can generate predictions and provide real-time insig

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39 Lessons from Industry ML Conferences in 2024

Eugene Yan

ML systems, production & scaling, execution & collaboration, building for users, conference etiquette.

ML 102
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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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Leopard: A Multimodal Large Language Model (MLLM) Designed Specifically for Handling Vision-Language Tasks Involving Multiple Text-Rich Images

Marktechpost

In recent years, multimodal large language models (MLLMs) have revolutionized vision-language tasks, enhancing capabilities such as image captioning and object detection. However, when dealing with multiple text-rich images, even state-of-the-art models face significant challenges. The real-world need to understand and reason over text-rich images is crucial for applications like processing presentation slides, scanned documents, and webpage snapshots.

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Cornell Researchers Introduce QTIP: A Weight-Only Post-Training Quantization Algorithm that Achieves State-of-the-Art Results through the Use of Trellis-Coded Quantization (TCQ)

Marktechpost

Quantization is an essential technique in machine learning for compressing model data, which enables the efficient operation of large language models (LLMs). As the size and complexity of these models expand, they increasingly demand vast storage and memory resources, making their deployment a challenge on limited hardware. Quantization directly addresses these challenges by reducing the memory footprint of models, making them accessible for more diverse applications, from complex natural langua

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OpenAI Launches ChatGPT Search

Towards AI

Last Updated on November 2, 2024 by Editorial Team Author(s): Get The Gist Originally published on Towards AI. Plus: Claude AI Gets Desktop App This member-only story is on us. Upgrade to access all of Medium. Welcome to Get The Gist, where every weekday we share an easy-to-read summary of the latest and greatest developments in AI — news, innovations, and trends — all delivered in under 5 minutes!

OpenAI 67
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This AI Paper Explores New Ways to Utilize and Optimize Multimodal RAG System for Industrial Applications

Marktechpost

Multimodal Retrieval Augmented Generation (RAG) technology has opened new possibilities for artificial intelligence (AI) applications in manufacturing, engineering, and maintenance industries. These fields rely heavily on documents that combine complex text and images, including manuals, technical diagrams, and schematics. AI systems capable of interpreting both text and visuals have the potential to support intricate, industry-specific tasks, but such tasks present unique challenges.

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25 Simple Concepts We’re Tired of Explaining Again and Again

Flipboard

25 Simple Concepts We’re Tired of Explaining Again and Again

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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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Promptfoo: An AI Tool For Testing, Evaluating and Red-Teaming LLM apps

Marktechpost

Promptfoo is a command-line interface (CLI) and library designed to enhance the evaluation and security of large language model (LLM) applications. It enables users to create robust prompts, model configurations, and retrieval-augmented generation (RAG) systems through use-case-specific benchmarks. This tool supports automated red teaming and penetration testing to ensure application security.

LLM 88
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Meta AI Releases Sparsh: The First General-Purpose Encoder for Vision-Based Tactile Sensing

Marktechpost

Tactile sensing plays a crucial role in robotics, helping machines understand and interact with their environment effectively. However, the current state of vision-based tactile sensors poses significant challenges. The diversity of sensors—ranging in shape, lighting, and surface markings—makes it difficult to build a universal solution. Traditional models are often developed and designed specifically for certain tasks or sensors, which makes scaling these solutions across different applications

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KVSharer: A Plug-and-Play Machine Learning Method that Shares the KV Cache between Layers to Achieve Layer-Wise Compression

Marktechpost

In recent times, large language models (LLMs) built on the Transformer architecture have shown remarkable abilities across a wide range of tasks. However, these impressive capabilities usually come with a significant increase in model size, resulting in substantial GPU memory costs during inference. The KV cache is a popular method used in LLM inference.

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Enhancing Artificial Intelligence Reasoning by Addressing Softmax Limitations in Sharp Decision-Making with Adaptive Temperature Techniques

Marktechpost

The ability to generate accurate conclusions based on data inputs is essential for strong reasoning and dependable performance in Artificial Intelligence (AI) systems. The softmax function is a crucial element that supports this functionality in modern AI models. A major component of differentiable query-key lookups is the softmax function, which enables the model to concentrate on pertinent portions of the input data in a way that can be improved or learned over time.

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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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Researchers at KAUST Use Anderson Exploitation to Maximize GPU Efficiency with Greater Model Accuracy and Generalizability

Marktechpost

Escalation in AI implies an increased infrastructure expenditure. The massive and multidisciplinary research exerts economic pressure on institutions as high-performance computing (HPC) costs an arm and a leg. HPC is financially draining and critically impacts energy consumption and the environment. By 2030, AI is projected to account for 2% of global electricity consumption.

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Multi-Scale Geometric Analysis of Language Model Features: From Atomic Patterns to Galaxy Structures

Marktechpost

Large Language Models (LLMs) have emerged as powerful tools in natural language processing, yet understanding their internal representations remains a significant challenge. Recent breakthroughs using sparse autoencoders have revealed interpretable “features” or concepts within the models’ activation space. While these discovered feature point clouds are now publicly accessible, comprehending their complex structural organization across different scales presents a crucial resea

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Decoding Arithmetic Reasoning in LLMs: The Role of Heuristic Circuits over Generalized Algorithms

Marktechpost

A key question about LLMs is whether they solve reasoning tasks by learning transferable algorithms or simply memorizing training data. This distinction matters: while memorization might handle familiar tasks, true algorithmic understanding allows for broader generalization. Arithmetic reasoning tasks could reveal if LLMs apply learned algorithms, like vertical addition in human learning, or if they rely on memorized patterns from training data.

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iP-VAE: A Spiking Neural Network for Iterative Bayesian Inference and ELBO Maximization

Marktechpost

The Evidence Lower Bound (ELBO) is a key objective for training generative models like Variational Autoencoders (VAEs). It parallels neuroscience, aligning with the Free Energy Principle (FEP) for brain function. This shared objective hints at a potential unified machine learning and neuroscience theory. However, both ELBO and FEP lack prescriptive specificity, partly due to limitations in standard Gaussian assumptions in models, which don’t align with neural circuit behaviors.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.