Sat.Sep 14, 2024

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Pixtral-12B: Mistral AI’s First Multimodal Model

Analytics Vidhya

Introduction Mistral has released its very first multimodal model, namely the Pixtral-12B-2409. This model is built upon Mistral’s 12 Billion parameter, Nemo 12B. What sets this model apart? It can now take both images and text for input. Let’s look more at the model, how it can be used, how well it’s performing the tasks […] The post Pixtral-12B: Mistral AI’s First Multimodal Model appeared first on Analytics Vidhya.

AI 291
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AI-Powered Automated Pentesting: Protecting your Business from Cyber Attacks

Aiiot Talk

As technology and artificial intelligence advance in 2024 and beyond, cybersecurity threats will unfortunately keep pace. In a world where “deepfakes” are already hard to discern from real videos, businesses now need to up their game to defend against genuine (and hard to detect) virtual attacks. “ According to IBM, the global average cost of a data breach is a staggering $4.88 million making up-to-date cybersecurity measures imperative for businesses of all sizes.

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How to Access the OpenAI o1 API?

Analytics Vidhya

Introduction OpenAI’s o1 series models represent a significant leap in large language model (LLM) capabilities, particularly for complex reasoning tasks. These models engage in deep internal thought processes before responding, making them excellent at solving intricate problems in science, mathematics, and programming. This article will guide you through the key features of the OpenAI o1 […] The post How to Access the OpenAI o1 API?

OpenAI 283
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OneGen: An AI Framework that Enables a Single LLM to Handle both Retrieval and Generation Simultaneously

Marktechpost

A major challenge in the current deployment of Large Language Models (LLMs) is their inability to efficiently manage tasks that require both generation and retrieval of information. While LLMs excel at generating coherent and contextually relevant text, they struggle to handle retrieval tasks, which involve fetching relevant documents or data before generating a response.

LLM 127
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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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15 Most Frequently Asked Questions About LLM Agents

Analytics Vidhya

Introduction Large language model (LLM) agents are advanced AI systems that use LLMs as their central computational engine. They have the ability to perform specific actions, make decisions, and interact with external tools or systems autonomously. This allows them to handle complex tasks that require complex reasoning, unlike standard LLMs, which primarily focus on text-generation-based […] The post 15 Most Frequently Asked Questions About LLM Agents appeared first on Analytics Vidhya.

LLM 262

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How to Prompt on OpenAI’s o1 Models and What’s Different From GPT-4

Marktechpost

OpenAI’s o1 models represent a newer generation of AI, designed to be highly specialized, efficient, and capable of handling tasks more dynamically than their predecessors. While these models share similarities with GPT-4, they introduce notable distinctions in architecture, prompting capabilities, and performance. Let’s explore how to effectively prompt OpenAI’s o1 models and highlight the differences between o1 and GPT-4, drawing on insights from OpenAI’s documentation and usage guidelines.

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Nvidia Open Sources Nemotron-Mini-4B-Instruct: A 4,096 Token Capacity Small Language Model Designed for Roleplaying, Function Calling, and Efficient On-Device Deployment with 32 Attention Heads and 9,216 MLP

Marktechpost

Nvidia has unveiled its latest small language model, Nemotron-Mini-4B-Instruct , which marks a new chapter in the company’s long-standing tradition of innovation in artificial intelligence. This model, designed specifically for tasks like roleplaying, retrieval-augmented generation (RAG), and function calls, is a more compact and efficient version of Nvidia’s larger models.

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Piiranha-v1 Released: A 280M Small Encoder Open Model for PII Detection with 98.27% Token Detection Accuracy, Supporting 6 Languages and 17 PII Types, Released Under MIT License

Marktechpost

The Internet Integrity Initiative Team has made a significant stride in data privacy by releasing Piiranha-v1 , a model specifically designed to detect and protect personal information. This tool is built to identify personally identifiable information (PII) across a wide variety of textual data, providing an essential service at a time when digital privacy concerns are paramount.

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Advancing Social Network Analysis: Integrating Stochastic Blockmodels, Reciprocity, and Bayesian Approaches

Marktechpost

The use of relational data in social science has surged over the past two decades, driven by interest in network structures and their behavioral implications. However, the methods for analyzing such data are underdeveloped, leading to ad hoc, nonreplicable research and hindering the development of robust theories. Two emerging approaches, blockmodels and stochastic models for digraphs, offer promising solutions.

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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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FutureHouse Researchers Introduce PaperQA2: The First AI Agent that Conducts Entire Scientific Literature Reviews on Its Own

Marktechpost

Artificial intelligence (AI) is transforming the way scientific research is conducted, especially through language models that assist researchers with processing and analyzing vast amounts of information. In AI, large language models (LLMs) are increasingly applied to tasks such as literature retrieval, summarization, and contradiction detection. These tools are designed to speed up the pace of research and allow scientists to engage more deeply with complex scientific literature without manuall

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gsplat: An Open-Source Python Library for Gaussian Splatting

Marktechpost

Gaussian Splatting is a novel 3D rendering technique representing a scene as a collection of 3D Gaussian functions. These Gaussians are splatted, or projected, onto the image plane, enabling faster and more efficient rendering of complex scenes compared to traditional methods like neural radiance fields (NeRF). It particularly effectively renders dynamic and large-scale scenes with high visual quality.

Python 110
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Optimizing Large-Scale Sentence Comparisons: How Sentence-BERT (SBERT) Reduces Computational Time While Maintaining High Accuracy in Semantic Textual Similarity Tasks

Marktechpost

Researchers have focused on developing and building models to process and compare human language in natural language processing efficiently. One key area of exploration involves sentence embeddings, which transform sentences into mathematical vectors to compare their semantic meanings. This technology is crucial for semantic search, clustering, and natural language inference tasks.

BERT 110
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Assessing the Capacity of Large Language Models to Generate Innovative Research Ideas: Insights from a Study with Over 100 NLP Experts

Marktechpost

Research idea generation methods have evolved through techniques like iterative novelty boosting, multi-agent collaboration, and multi-module retrieval. These approaches aim to enhance idea quality and novelty in research contexts. Previous studies primarily focused on improving generation methods over basic prompting, without comparing results against human expert baselines.

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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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Ebay Researchers Introduce GraphEx: A Graph-based Extraction Method for Advertiser Keyphrase Recommendation

Marktechpost

Keyphrase recommendation in e-commerce advertising faces significant challenges, particularly in balancing relevance and effectiveness for sellers and advertisers. The primary issue lies in recommending keyphrases that are relevant to items and represent actual user queries, crucial for targeted advertising. This problem has been approached as an Extreme Multi-Label Classification (XMC) task, utilizing search logs to map items to multiple queries.

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ClimDetect: A New Benchmark Dataset for Testing AI Models in Detecting Climate Change Signals

Marktechpost

Detecting and attributing temperature increases due to climate change is vital for addressing global warming and shaping adaptation strategies. Traditional methods struggle to separate human-induced climate signals from natural variability, relying on statistical techniques to identify specific patterns in climate data. Recent advances, however, have utilized deep learning to analyze large climate datasets and uncover complex patterns.

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Top 9 Different Types of Retrieval-Augmented Generation (RAGs)

Marktechpost

Retrieval-Augmented Generation (RAG) is a machine learning framework that combines the advantages of both retrieval-based and generation-based models. The RAG framework is highly regarded for its ability to handle large amounts of information and produce coherent, contextually accurate responses. It leverages external data sources by retrieving relevant documents or facts and then generating an answer or output based on the retrieved information and the user query.