AskNews
What is AskNews?
AskNews is a news platform that provides human editorial boosted by AI-powered insights to minimize bias and build a transparent view of current events. It offers diverse news coverage, real-time event tracking, chat with AI assistant, and developer tools for integrating news context into applications.
How to use AskNews?
To use AskNews, explore curated stories, try the chat feature, or use the API for integrating rich news context into applications.
AskNews's Core Features
Human editorial boosted by AI-powered insights
Diverse news coverage from around the world
Real-time event tracking
Chat with AI assistant
Developer tools for news integration
AskNews's Use Cases
Stay up-to-date with diverse news from around the world
Integrate rich news context into applications
Chat with AI assistant for news-related tasks
FAQ from AskNews
Is AskNews completely free to use?
What kind of news sources does AskNews index?
AskNews Discord
Here is the AskNews Discord: https://discord.gg/5QkTSm94ha. For more Discord message, please click here(/discord/5qktsm94ha).
AskNews Company
AskNews Company name: Emergent Methods, LLC .
AskNews Pricing
AskNews Pricing Link: https://my.asknews.app/plans
AskNews Reviews (1)
John Brown
July 11 2024
AskNews Pricing
Free Tier
Free
Access to the news API for as little as $0.005 per call
Paid Plans
Starting from $0.005 per call
Pay as you go for higher-volume usage
For the latest pricing, please visit this link: https://my.asknews.app/plans
Analytic of AskNews
AskNews Website Traffic Analysis
Geography
Top 1 Regions
AskNews Discord Users Analysis
Latest user counts
AskNews Launch embeds
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Social Listening
What is RAG? Building Better LLM Systems with Qdrant
Large Language Models (LLMs) often struggle to keep up with new information. So, how can we fix this? In this video, discover how Retrieval-Augmented Generation (RAG) integrates real-time data from vector databases like Qdrant to ensure accurate and relevant answers instantly. Join us as we explore fundamental RAG concepts, including indexing, chunking, embedding, retrieving, and generating data. AskNews is able to create smart predictions with Qdrant as its vector database. Try it out yourself: https://asknews.app/ More questions about how this works? Join our GenAI and Vector Search community on Discord: https://discord.gg/qdrant
Production-scale RAG for Real-Time News Distillation - Robert Caulk | Vector Space Talks #015
🎤 Meet our guest speaker: - Robert Caulk, Founder at Emergent Methods Title: "Production-scale Retrieval Augmented Generation for Real-Time News Distillation" Abstract: This talk aims to map out the cluster architecture at Emergent Methods for our AskNews.app deployment. We aim to explain how we process over 1 million news articles per day for fast real-time RAG consumption. In particular, we will discuss the roles and interactions of four open-source software packages, including a cluster orchestration software (Flowdapt), a vector database (Qdrant), an LLM server (vLLM), and an embedding server (TEI). This combination of services allows us to infuse a mixture of LLMs with the latest news, and to deploy an enriched chat to thousands of users simultaneously in a public-facing application. We will highlight the role of Qdrant for some of its indispensable features, including efficient batch upserting, fast search on millions of vectors, easy filtering, and multi-node scaling. Finally, we will discuss the key roles that Flowdapt plays for orchestrating production-scale RAG across a variety of services in real-time, including the importance of configurability, scheduling, and resource management. We will conclude with our thoughts on why we believe the incorporation of these tools at the foundation level of a start-up is a huge advantage in comparison to the big tech companies from the 2010s. Talk Takeaways: How we process over 1 million news articles by combining Flowdapt, Qdrant, vLLM, and TEI. Why Qdrant is indispensable for production-scale RAG. How Flowdapt improves deployability, configurability, scaling, scheduling, and resource management. Why new start-ups have a huge tech-stack advantage over 2010 era tech companies. Robert's Bio: Robert is a scientist by trade, dedicating his career to a variety of open-source projects that range from large-scale artificial intelligence to discrete element modeling. He is currently working with a team at Emergent Methods to adaptively model over 1 million news articles per day, with a goal of reducing media bias and improving news-awareness. -------------------------------------------------------------------------------- Connect with Robert and Emergent Methods: https://www.linkedin.com/in/rcaulk/ https://emergentmethods.ai https://asknews.app Connect with Demetrios: https://www.linkedin.com/in/dpbrinkm/ Follow Qdrant: https://www.linkedin.com/company/qdrant/ https://twitter.com/qdrant_engine Join the Qdrant Discord server: https://discord.gg/W4PejyMMKu
Catching Bad Guys using Graph Entity Resolution with Paco Nathan
Our guest is Paco Nathan, a Principal Developer Relations Engineer at Senzing.com (and listed as an “evil mad scientist” on LinkedIn). Paco works a lot within developer communities and tech events, and tries to provide many pointers to learning materials, industry analysis, and connect with many people. He presents talks, workshops, and hands-on tutorials about entity-resolved knowledge graph practices, and the related AI use cases which are downstream. Episode Notes Speaker Resources: * Neo4j+Senzing Tutorial: https://bit.ly/3AvKneU * When GraphRAG Goes Bad: A Study in Why you Cannot Afford to Ignore Entity Resolution (Dr. Clair Sullivan): https://www.linkedin.com/pulse/when-graphrag-goesbad-study-why-you-cannot-afford-ignore-sullivan-7ymnc/ * Paco’s NODES 2024 session: https://bit.ly/48sCSlD * Graph Power Hour: https://www.youtube.com/playlist?list=PL9-tchmsp1WMnZKYti-tMnt_wyk4nwcbH T* omaz Bratanic on GraphReader: https://towardsdatascience.com/implementing-graphreader-with-neo4j-and-langgraph-e4c73826a8b7 Tools of the Month: * Neo4j GraphRAG Python package: https://pypi.org/project/neo4j-graphrag/ * Spring Data Neo4j: https://spring.io/projects/spring-data-neo4j * Entity Linking based on Entity Resolution tutorial: https://github.com/louisguitton/spacy-lancedb-linker https://github.com/DerwenAI/strwythura * AskNews (build news datasets) https://asknews.app/ * The Sentry https://atlas.thesentry.org/azerbaijan-aliyev-empire/ Announcements / News: Articles: * Neo4j Developer Blog https://bit.ly/3LcYx6q Videos: * NODES 2023 playlist https://youtube.com/playlist?list=PL9Hl4pk2FsvUu4hzyhWed8Avu5nSUXYrb&si=8_0sYVRYz8CqqdIc Events * All Neo4j events: https://bit.ly/3Lb1Kn3 * (Nov 5) Conference (virtual): XtremeJ https://xtremej.dev/2024/schedule/ * (Nov 7) Conference (virtual): NODES 2024 https://bit.ly/47VqQkp * (Nov 8) Conference (Austin, TX, USA): MLOps World https://mlopsworld.com/ * (Nov 12) Conference (Baltimore, MD, USA): ISWC https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589a52/summary * (Nov 13) Meetup (Seattle, WA, USA): Puget Sound Programming Python (PuPPY) - Talk night Rover https://www.meetup.com/psppython/events/303896335/?eventOrigin=group_events_list * (Nov 14) Meetup (Seattle, WA, USA): AI Workflow Essentials (with Pinecone, Neo4J, Boundary, Union) https://lu.ma/75nv6dd3 * (Nov 14) Conference (Reston, VA, USA): Senzing User Conference https://senzing.com/senzing-event-calendar/ * (Nov 18) Meetup (Cleveland, OH, USA): Cleveland Big Data mega-meetup https://www.meetup.com/Cleveland-Hadoop/ * (Nov 19) Chicago Java User Group (Chicago, IL, USA): https://cjug.org/cjug-meeting-intro/#/ * (Dec 3) Conference (London, UK): Linkurious Days https://resources.linkurious.com/linkurious-days-london * (Dec 10) Meetup (London, UK): ESR meetup in London by Neural Alpha * (Dec 11-13) Conference (London, UK): Connected Data London https://2024.connected-data.london/
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