Unite.AI

NOVEMBER 2, 2024

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

AI AI Automation Artificial Intelligence 184

Eugene Yan

NOVEMBER 2, 2024

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

ML 192

ML 192

Towards AI

NOVEMBER 2, 2024

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

OpenAI ChatGPT AI AI 105

Marktechpost

NOVEMBER 2, 2024

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

Robotics 85

Robotics AI AI Automation 85

Speaker: Jesse Hunter and Brynn Chadwick

Today’s buyers expect more than generic outreach–they want relevant, personalized interactions that address their specific needs. For sales teams managing hundreds or thousands of prospects, however, delivering this level of personalization without automation is nearly impossible. The key is integrating AI in a way that enhances customer engagement rather than making it feel robotic.

AI

Towards AI

NOVEMBER 2, 2024

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

Neural Network 105

Neural Network Machine Learning Computer Vision AI Engineer 105

Flipboard

NOVEMBER 2, 2024

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

Explainability 65

Explainability Machine Learning 65

Analytics Vidhya

NOVEMBER 2, 2024

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

NLP Large Language Models Python 244

Towards AI

NOVEMBER 2, 2024

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

Machine Learning 111

Machine Learning Algorithm AI AI 111

Marktechpost

NOVEMBER 2, 2024

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.

Large Language Models 92

Large Language Models ML AI AI 92

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

LLM

Marktechpost

NOVEMBER 2, 2024

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

Algorithm 90

Algorithm Large Language Models Machine Learning Natural Language Processing 90

Marktechpost

NOVEMBER 2, 2024

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.

Large Language Models 88

Large Language Models AI AI Artificial Intelligence 88

Marktechpost

NOVEMBER 2, 2024

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

LLM AI Tools Large Language Models Automation 88

Marktechpost

NOVEMBER 2, 2024

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.

Artificial Intelligence 82

Artificial Intelligence Artificial Intelligence Neural Network Computer Vision 82

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Marktechpost

NOVEMBER 2, 2024

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

Natural Language Processing 82

Natural Language Processing Large Language Models LLM ML 82

Marktechpost

NOVEMBER 2, 2024

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.

Neural Network 79

Neural Network ML AI AI 79

Marktechpost

NOVEMBER 2, 2024

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.

Algorithm 78

Algorithm ML Large Language Models Artificial Intelligence 78

Marktechpost

NOVEMBER 2, 2024

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.

Neural Network 43

Neural Network Machine Learning Algorithm ML 43

Speaker: Alexa Acosta, Director of Growth Marketing & B2B Marketing Leader

Marketing is evolving at breakneck speed—new tools, AI-driven automation, and changing buyer behaviors are rewriting the playbook. With so many trends competing for attention, how do you cut through the noise and focus on what truly moves the needle? In this webinar, industry expert Alexa Acosta will break down the most impactful marketing trends shaping the industry today and how to turn them into real, revenue-generating strategies.

Automation