Sat.Nov 02, 2024

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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 105
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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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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 184
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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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Precision in Motion: Why Process Optimization Is the Future of Manufacturing

Speaker: Jason Chester, Director, Product Management

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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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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 244
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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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Support Vector Machines Math Intuitions

Towards AI

Last Updated on November 3, 2024 by Editorial Team Author(s): Fernando Guzman Originally published on Towards AI. Support Vector Machines, or SVM, is a machine learning algorithm that, in its original form, is utilized for binary classification. The SVM model seeks to determine the optimal separation line between two classes, understood as the best margin between these classes, as demonstrated in the following example: SVM Example by OSCAR CONTRERAS CARRASCO As shown in the image, we have a sepa

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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.

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Smart Tools & Strong Teams: A People-First Approach to AI in Sales

Speaker: Matt Sunshine, CEO at The Center for Sales Strategy

AI isn’t replacing salespeople—it’s empowering them. The most forward-thinking sales organizations are using AI to enhance human performance rather than eliminate it. From coaching and messaging to prospecting and pipeline accountability, artificial intelligence is giving managers and SDRs the new tools they need to work smarter, sell better, and close more.

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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 204
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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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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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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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AI-Enabled Robotics Software for Manufacturing Automation: Speeding Time-to-Value

Robots are a cornerstone of a smart factory, automating a wide range of manufacturing tasks that are monotonous, physically straining, or even hazardous. However, real-world robotics deployments have not lived up to the revolutionary potential the industrial sector had originally envisioned. Robot implementations are typically confined to specific applications, carry high costs, and are time-consuming.

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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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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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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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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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New Research-Backed Strategies to Empower Managers as Culture & Engagement Leaders

Speaker: Beth Sunshine, SVP, Up Your Culture

When culture isn’t consistently lived out across the organization, engagement suffers—and it often starts with a disconnect at the top. In this session, Beth Sunshine, SVP of Up Your Culture at The Center for Sales Strategy, will reveal how HR and executive leaders can close the gap between vision and execution by equipping frontline and mid-level managers to become culture carriers.