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Introduction Having the correct tools and platforms is crucial for learning and innovation in the constantly changing field of artificial intelligence. AI playgrounds offer a great opportunity to test advanced models and technologies without needing a lot of money. If you’re a scientist, creator, or fan, these play areas offer various features for different purposes. […] The post Top 10 Free AI Playgrounds For You to Try in 2024 appeared first on Analytics Vidhya.
Last Updated on July 22, 2024 by Editorial Team Author(s): Vatsal Saglani Originally published on Towards AI. Image by DALL-E 3 Disclaimer: This implementation of GraphRAG is inspired by the paper From Local to Global: A Graph RAG Approach to Query-Focused Summarization by Darren Edge et. al. The code is not entirely similar to the paper’s codebase, though the prompts for certain tasks are taken from the paper’s codebase.
Introduction In data science, having the ability to derive meaningful insights from data is a crucial skill. A fundamental understanding of statistical tests is necessary to derive insights from any data. These tests allow data scientists to validate hypotheses, compare groups, identify relationships, and make predictions with confidence. Whether you’re analyzing customer behavior, optimizing algorithms, […] The post 5 Statistical Tests Every Data Scientist Should Know appeared first
In the rapidly developing field of Artificial Intelligence, it is more important than ever to convert unstructured data into organized, useful information efficiently. Recently, a team of researchers introduced the Neo4j LLM Knowledge Graph Builder , an AI tool that can easily address this issue. This potential application creates a text-to-graph experience by utilizing some great machine-learning models to transform unstructured text into an extensive knowledge graph.
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Last Updated on July 22, 2024 by Editorial Team Author(s): Vatsal Saglani Originally published on Towards AI. Part 1: Introduction to GraphRAGImage by DALL-E 3 Disclaimer: This implementation of GraphRAG is inspired by the paper From Local to Global: A Graph RAG Approach to Query-Focused Summarization by Darren Edge et. al. The code is not entirely similar to the paper’s codebase, though the prompts for certain tasks are taken from the paper’s codebase.
Language models (LMs) have become fundamental in natural language processing (NLP), enabling text generation, translation, and sentiment analysis tasks. These models demand vast amounts of training data to function accurately and efficiently. However, the quality and curation of these datasets are critical to the performance of LMs. This field focuses on refining the data collection and preparation methods to enhance the models’ effectiveness.
Language models (LMs) have become fundamental in natural language processing (NLP), enabling text generation, translation, and sentiment analysis tasks. These models demand vast amounts of training data to function accurately and efficiently. However, the quality and curation of these datasets are critical to the performance of LMs. This field focuses on refining the data collection and preparation methods to enhance the models’ effectiveness.
Author(s): Reza Yazdanfar Originally published on Towards AI. Time Series Time series is one of the most challenging lines of work in machine learning, and this has made researchers less reluctant to work on it. However, solving time series tasks like anomaly detection, time series forecasting, … are vital in a wide variety of industries and could save tons of money.
Optimal transport is a mathematical discipline focused on determining the most efficient way to move mass between probability distributions. This field has wide-ranging applications in economics, where it is used to model resource allocation; in physics, to simulate particle dynamics; and in machine learning, where it aids in data alignment and analysis.
Author(s): Ryan Nguyen Originally published on Towards AI. AI-Generated Image Hello everyone, I’m back after a busy few months since my last blog post (6 months and 13 days exactly). It has been busy for me for the last couple of months as I’ve been working on an AI-powered solution with multi-agent AI integrated with Slack for internal use. The project has been a great success, with over 150 employees using it since launch and it has answered more than 1,000 questions so far.
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling the creation of language agents capable of autonomously solving complex tasks. However, the development of these agents faces significant challenges. The current approach involves manually decomposing tasks into LLM pipelines, with prompts and tools stacked together.
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.
Created Using DALL-E Next Week in The Sequence: Edge 415: Our series about autonomous agents dives into procedural memory. We review Microsoft’s JARVIS-1 memory-augmented agent adn dive into the Zep framework for memory management in LLMs. Edge 416: We deep dive into Apple’s amanzing 4M-21 multimodal model. You can subscribe to The Sequence below: TheSequence is a reader-supported publication.
The semantic capabilities of modern language models offer the potential for advanced analytics and reasoning over extensive knowledge corpora. However, current systems need more high-level abstractions for large-scale semantic queries. Complex tasks like summarizing recent research, extracting biomedical information, or analyzing internal business transcripts require sophisticated data processing and reasoning.
ChatGPT-Generated Exam Answers Dupe Profs Looks like college take-home tests are destined to suffer the same fate as the Dodo bird. Instructors at a U.K. university learned as much after a slew of take-home exams featuring answers generated by ChatGPT passed with flying colors — all while evading virtually any suspicions of cheating. Observes writer Richard Adams: “Researchers at the University of Reading fooled their own professors by secretly submitting AI-generated exam answers th
Nexusflow has released Athene-Llama3-70B , an open-weight chat model fine-tuned from Meta AI’s Llama-3-70B. Athene-70B has achieved an Arena-Hard-Auto score of 77.8%, rivaling proprietary models like GPT-4o and Claude-3.5-Sonnet. This marks a significant improvement from its predecessor, Llama-3-70B-Instruct, which scored 46.6%. The enhancement stems from Nexusflow’s targeted post-training pipeline, designed to improve specific model behaviors.
The guide for revolutionizing the customer experience and operational efficiency This eBook serves as your comprehensive guide to: AI Agents for your Business: Discover how AI Agents can handle high-volume, low-complexity tasks, reducing the workload on human agents while providing 24/7 multilingual support. Enhanced Customer Interaction: Learn how the combination of Conversational AI and Generative AI enables AI Agents to offer natural, contextually relevant interactions to improve customer exp
Human reviewers or LLMs are often the only options for evaluating free-form material. However, their evaluation can be inaccurate and the process is time-consuming, costly, and arduous. The relief from this manual work comes with prompt engineering or the development of a unique optimization procedure, which is necessary for LLM evaluations to function as intended.
Arcee AI introduced Arcee-Nova , a groundbreaking achievement in open-source artificial intelligence. Following their previous release, Arcee-Scribe, Arcee-Nova has quickly established itself as the highest-performing model within the open-source domain. Evaluated on the same stack as the OpenLLM Leaderboard 2.0, Arcee-Nova’s performance approaches that of GPT-4 from May 2023, marking a significant milestone for Arcee AI and the AI community at large.
Llama-3-Nephilim-v3-8B and llama-3-Nephilim-v3-8B-GGUF are two innovative models released on Hugging Face. Although these models were never explicitly trained for roleplay, they exhibit remarkable capability in this domain, highlighting the potential of “found art” approaches in AI development. The creation of these models involved merging several pre-trained language models using mergekit, a tool designed to combine the strengths of different models.
Large Language Models (LLMs) have been widely discussed in several domains, such as global media, science, and education. Even with this focus, measuring exactly how much LLM is used or assessing the effects of created text on information ecosystems is still difficult. A significant challenge is the growing difficulty in differentiating texts produced by LLMs from human-written texts.
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
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