AskNews
Was ist AskNews?
AskNews ist eine Nachrichtenplattform, die menschliche Redaktionen durch KI-gestützte Erkenntnisse unterstützt, um Voreingenommenheit zu minimieren und einen transparenten Blick auf aktuelle Ereignisse zu schaffen. Es bietet eine vielfältige Nachrichtenberichterstattung, Echtzeit-Ereignisverfolgung, Chat mit KI-Assistenten und Entwicklertools zur Integration von Nachrichtenkontexten in Anwendungen.
Wie benutzt man AskNews?
Um AskNews zu verwenden, erkunden Sie kuratierte Geschichten, probieren Sie die Chat-Funktion aus oder verwenden Sie die API, um reichen Nachrichtenkontext in Anwendungen zu integrieren.
AskNews's Hauptmerkmale
Menschliche Redaktion durch KI-gestützte Erkenntnisse
Vielfältige Nachrichtenabdeckung aus der ganzen Welt
Echtzeit-Ereignisverfolgung
Chat mit KI-Assistenten
Entwicklertools für die Nachrichtenintegration
AskNews's Anwendungsfälle
Bleiben Sie auf dem Laufenden mit vielfältigen Nachrichten aus der ganzen Welt
Integrieren Sie reichen Nachrichtenkontext in Anwendungen
Chatten Sie mit KI-Assistenten für nachrichtenbezogene Aufgaben
FAQ von AskNews
Ist AskNews komplett kostenlos zu benutzen?
Welche Art von Nachrichtenquellen indexiert AskNews?
AskNews Discord
Hier ist der AskNews Discord: https://discord.gg/5QkTSm94ha. Für weitere Discord-Nachrichten klicken Sie bitte hier(/de/discord/5qktsm94ha).
AskNews Unternehmen
AskNews Firmenname: Emergent Methods, LLC .
AskNews Preise
AskNews Preislink: https://my.asknews.app/plans
AskNews Bewertungen (1)
John Brown
Juli 11 2024
AskNews Preise
Gratis-Stufe
Kostenlos
Zugang zu Nachrichten-API für so wenig wie $0,005 pro Abruf
Bezahlte Pläne
Ab $0,005 pro Abruf
Bezahlen Sie bei höherem Volumenverbrauch
Die aktuellen Preise finden Sie unter diesem Link: https://my.asknews.app/plans
Analyse von AskNews
AskNews Website-Traffic-Analyse
Geografischer Verkehr
Top 1 Regionen
AskNews Discord-Benutzeranalyse
Latest user counts
AskNews Einbettungen starten
Verwenden Sie Website-Badges, um die Unterstützung Ihrer Community für Ihren Toolify-Launch zu fördern. Sie lassen sich einfach auf Ihrer Homepage oder in der Fußzeile einbetten.
Alternative von AskNews
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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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