RAG

Intel Unleashes Enterprise AI with Gaudi 3, AI Open Systems Strategy and New Customer Wins

Retrieved on: 
tisdag, april 9, 2024
Technology, Semiconductor, Software, Networks, Internet, Hardware, Electronic Design Automation, Data Management, Consumer Electronics, Artificial Intelligence, Cloud, UEC, Google Cloud, Bosch, Algorithm, GPU, Face, Ultra, CtrlS, LLM, DataStax, FP16, Xeon, Silicon, SGX, Original equipment manufacturer, Cohesity, H100, Anomaly, Advent International, Vision, Fermentation, TERA, Kx Systems, Memory, RAG, Running, SAP, Cancer, Food, IBM, VMware, Nvidia, Credit, Dell Technologies, SAM, NPU, Red Hat, HPE, Vision transformer, Intel, Motivation, Infosys, Trust, MinIO, Supermicro, CLIP, TEE, BF16, Workflow, Data center, Ecosystem, Multimedia, MariaDB

The Intel Gaudi 3 AI accelerator will power AI systems with up to tens of thousands of accelerators connected through the common standard of Ethernet.

Key Points: 
  • The Intel Gaudi 3 AI accelerator will power AI systems with up to tens of thousands of accelerators connected through the common standard of Ethernet.
  • Intel Gaudi 3 promises 4x more AI compute for BF16 and a 1.5x increase in memory bandwidth over its predecessor.
  • Intel outlined its strategy for open scalable AI systems, including hardware, software, frameworks and tools.
  • In addition to the Intel Gaudi 3 accelerator, Intel provided updates on its next-generation products and services across all segments of enterprise AI.

Denodo Partners with Google Cloud on the Future of Enterprise Innovation with New Data Virtualization and Generative AI Integration

Retrieved on: 
måndag, april 8, 2024
Software, Networks, Data Analytics, Internet, Artificial Intelligence, Data Management, Professional Services, Technology, Cloud, Google Cloud, Organization, Health, Partnership, GOOGLE, RAG, Education, Bias, Indiana University, LLM, CLOUD, Telecommunications, Data management

GOOGLE CLOUD NEXT, Booth 1362 - Denodo , a leader in data management, announced a new integration of the Denodo Platform with Google Cloud’s Vertex AI as part of its partnership.

Key Points: 
  • GOOGLE CLOUD NEXT, Booth 1362 - Denodo , a leader in data management, announced a new integration of the Denodo Platform with Google Cloud’s Vertex AI as part of its partnership.
  • Powered by data virtualization , the Denodo Platform will work with Google Cloud to empower joint customers to drive innovative solutions by combining advanced logical data management capabilities with cutting-edge generative AI services while providing access to state-of-the-art large language models (LLM).
  • “Generative AI can significantly improve how businesses operate and benefit virtually every industry,” said Ritika Suri, Technology Partnerships director, at Google Cloud.
  • “This latest integration further sets the stage for enterprises to redefine the boundaries of innovation by unlocking new levels of business value through the power of data and generative AI.

Neo4j Partners with Google Cloud to Launch New GraphRAG Capabilities for GenAI Applications

Retrieved on: 
tisdag, april 9, 2024
Cloud, Knowledge, Flex, Synthetic media, GDC, Google Cloud, Organization, Dun & Bradstreet, Environment, Partnership, RAG, PDF, SAN, Dun, Google Cloud Storage, IDE, Data management, Hallucination, Cloud computing, API, Language, BigQuery, Generative, Satellite navigation device

SAN MATEO, Calif., April 9, 2024 /PRNewswire/ -- Neo4j®, the world's leading graph database and analytics company, announced new native integrations with Google Cloud that dramatically speed up Generative AI application development and deployment across several crucial stages. The results solve a problem for enterprises that struggle with complexity and hallucinations when building and deploying successful GenAI applications requiring real-time, contextually rich data and accurate, explainable results. The integrations are available now.

Key Points: 
  • Developers can easily apply GraphRAG techniques with knowledge graphs to ground LLMs for accuracy, context, and explainability, enhancing GenAI innovation.
  • Neo4j's vector search, GraphRAG, and conversational memory capabilities integrate seamlessly through LangChain and Neo4j AuraDB with Google Cloud.
  • Neo4j in 2023 was the only native graph vendor to launch native product integrations with GenAI features in Google Cloud Vertex AI platform.
  • "GraphRAG with Neo4j and Google Cloud enables enterprises to move from GenAI development to deployment much faster and see value from their production use cases.

Neo4j Partners with Google Cloud to Launch New GraphRAG Capabilities for GenAI Applications

Retrieved on: 
tisdag, april 9, 2024
Cloud, Knowledge, Flex, Synthetic media, GDC, Google Cloud, Organization, Dun & Bradstreet, Environment, Partnership, RAG, PDF, SAN, Dun, Google Cloud Storage, IDE, Data management, Hallucination, Cloud computing, API, Language, BigQuery, Generative, Satellite navigation device

SAN MATEO, Calif., April 9, 2024 /PRNewswire/ -- Neo4j®, the world's leading graph database and analytics company, announced new native integrations with Google Cloud that dramatically speed up Generative AI application development and deployment across several crucial stages. The results solve a problem for enterprises that struggle with complexity and hallucinations when building and deploying successful GenAI applications requiring real-time, contextually rich data and accurate, explainable results. The integrations are available now.

Key Points: 
  • Developers can easily apply GraphRAG techniques with knowledge graphs to ground LLMs for accuracy, context, and explainability, enhancing GenAI innovation.
  • Neo4j's vector search, GraphRAG, and conversational memory capabilities integrate seamlessly through LangChain and Neo4j AuraDB with Google Cloud.
  • Neo4j in 2023 was the only native graph vendor to launch native product integrations with GenAI features in Google Cloud Vertex AI platform.
  • "GraphRAG with Neo4j and Google Cloud enables enterprises to move from GenAI development to deployment much faster and see value from their production use cases.

Pinecone Launches Partner Program to Bring More Companies Into the AI Stack

Retrieved on: 
måndag, april 8, 2024
RAG, Vectorization, AI, Technology strategy, Workflow, Metadata, Ecosystem, Marketing

NEW YORK, April 8, 2024 /PRNewswire/ -- Pinecone , the vector database company making AI knowledgeable, announced the launch of the Pinecone Partner Program.

Key Points: 
  • NEW YORK, April 8, 2024 /PRNewswire/ -- Pinecone , the vector database company making AI knowledgeable, announced the launch of the Pinecone Partner Program.
  • The program lets software providers become part of the critical AI ecosystem by offering streamlined access to the market-leading vector database inside their products.
  • Expanded and streamlined access for developers to the vector database inside their existing tools will dramatically accelerate successful deployments of AI applications.
  • "Developers want a simple workflow even if their projects are incredibly ambitious," said Edo Liberty, Founder & CEO of Pinecone.

IDTechEx Analyzes the Impact of Large Language Models on the Material Development Landscape

Retrieved on: 
måndag, april 8, 2024
Microsoft, Players, Informatics, HR, Organization, Software as a service, Science, RAG, Knowledge, News, First officer (aviation), LLM, PwC, Investment, ChatGPT, Microsoft Excel, Language, Book, Data, Catalysis, Software

A common approach is to use machine learning models trained on databases of material structures and properties, which then capture the underlying structure-property relationship.

Key Points: 
  • A common approach is to use machine learning models trained on databases of material structures and properties, which then capture the underlying structure-property relationship.
  • Large Language Models (LLMs) like the GPT3.5/4 models behind ChatGPT and Microsoft's Copilot use similar tactics to model language: in 2024, their power to enhance material development is becoming clear.
  • This can make the activities of a SaaS firm look more like a consulting outfit, reducing the capacity to scale.
  • The role of a materials informatics firm is to connect the expertise of materials scientists and data scientists/engineers to drive material development.

IDTechEx Analyzes the Impact of Large Language Models on the Material Development Landscape

Retrieved on: 
måndag, april 8, 2024
Microsoft, Players, Informatics, HR, Organization, Software as a service, Science, RAG, Knowledge, News, First officer (aviation), LLM, PwC, Investment, ChatGPT, Microsoft Excel, Language, Book, Data, Catalysis, Software

A common approach is to use machine learning models trained on databases of material structures and properties, which then capture the underlying structure-property relationship.

Key Points: 
  • A common approach is to use machine learning models trained on databases of material structures and properties, which then capture the underlying structure-property relationship.
  • Large Language Models (LLMs) like the GPT3.5/4 models behind ChatGPT and Microsoft's Copilot use similar tactics to model language: in 2024, their power to enhance material development is becoming clear.
  • This can make the activities of a SaaS firm look more like a consulting outfit, reducing the capacity to scale.
  • The role of a materials informatics firm is to connect the expertise of materials scientists and data scientists/engineers to drive material development.

Pryon Selected for the 2024 CB Insights AI 100 List

Retrieved on: 
fredag, april 5, 2024
Intelligence, RAG, Lightning, Pain, CB Insights, Research, Face, Netflix, AI, Online shopping

RALEIGH, N.C., April 5, 2024 /PRNewswire/ -- CB Insights today named Pryon, a leader in Retrieval Augmented Generation (RAG) solutions, to its eighth-annual AI 100, showcasing the 100 most promising private AI companies of 2024. This year's winners are recognized for tackling some of the hardest challenges in scaling AI across industries, and Pryon, having pioneered best-in-class RAG solutions, earned its spot on the list for its capabilities to increase productivity through AI applications.

Key Points: 
  • RALEIGH, N.C., April 5, 2024 /PRNewswire/ -- CB Insights today named Pryon , a leader in Retrieval Augmented Generation (RAG) solutions, to its eighth-annual AI 100 , showcasing the 100 most promising private AI companies of 2024.
  • "AI is taking off at lightning speed, and it's not just big tech companies at the forefront of it," said Deepashri Varadharajan, director of AI research at CB Insights.
  • "Our AI 100 winners – many of them early-stage startups, some with very small teams – are pushing the boundaries of AI in everything from game development and battery design to agentic AI systems."
  • For more information about Pryon, please visit https://pryon.com
    For the full list of the most promising artificial intelligence startups of 2024, please visit https://www.cbinsights.com

Zilliz Introduces Milvus 2.4 with GPU Indexing Support for CAGRA

Retrieved on: 
onsdag, mars 20, 2024
GPU, Acceleration, RAPIDS, RAG, Graphics processing unit, NVIDIA, Video game

Building on Zilliz’s commitment to innovation, Milvus 2.4 enhances GPU indexing capabilities since the introduction of GPU IVF-Flat and GPU IVF-PQ indexes last year.

Key Points: 
  • Building on Zilliz’s commitment to innovation, Milvus 2.4 enhances GPU indexing capabilities since the introduction of GPU IVF-Flat and GPU IVF-PQ indexes last year.
  • GPU Indexing represents a significant milestone in vector database technology, propelling Milvus 2.4 further ahead of traditional CPU-based indexes like HNSW.
  • Leveraging the power of GPU acceleration, Milvus 2.4 delivers remarkable performance gains, particularly under large datasets, ensuring lightning-fast search responses and unparalleled efficiency for developers.
  • “Bringing GPU acceleration to Milvus 2.4 with cuVS will improve a broad range of generative AI applications built on vector search, including NVIDIA NeMo Retriever.”
    In addition to GPU Indexing, Milvus 2.4 introduces support for GPU-based brute force search, further enhancing recall performance without sacrificing speed.

Kinetica Delivers Real-Time Vector Similarity Search

Retrieved on: 
onsdag, mars 20, 2024
Cloud, Synthetic media, ANN, OLAP, Gen, Algorithm, GPU, SQL, General partnership, RAG, SAN, Motion, Anomaly, LLM, Architecture, RAFT, Acceleration, Index, Language, NVIDIA, ANSI, Generative, Weather, Cryptocurrency

SAN JOSE, Calif., March 20, 2024 (GLOBE NEWSWIRE) -- Kinetica, the real-time GPU-accelerated database for analytics and generative AI, today unveiled at NVIDIA GTC the industry’s only real-time vector similarity search engine that can ingest vector embeddings 5X faster than the previous market leader, based on the popular VectorDBBench benchmark. Under the hood Kinetica uses NVIDIA RAPIDS RAFT to harness the power of the GPU for vector similarity search. With Kinetica’s best-in-class combined data and query latency for vector embedding pipelines, large language models (LLM) can immediately augment their results with new information via embeddings as soon as they are generated, without delays at scale.

Key Points: 
  • Under the hood Kinetica uses NVIDIA RAPIDS RAFT to harness the power of the GPU for vector similarity search.
  • High performance vector similarity search at speed and scale - Kinetica vectorization enables vector similarity search (exact nearest neighbor) at speed and scale even without an index.
  • Hybrid vector search combines similarity search with time-series, spatial, graph & OLAP through SQL - Build more powerful Generative AI applications by combining vector similarity search with filters, joins, aggregations, etc.
  • “By taking advantage of NVIDIA RAPIDS vector search, Kinetica can offer higher throughput, lower latency and faster index builds for Gen AI applications.”
    Kinetica’s vector similarity search is now available in Kinetica 7.2 for users of Kinetica Cloud Dedicated, Developer Edition, and Kinetica Enterprise.