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Demand Builds for Third-Party GenAI Development Services
The emergence of generative AI is easily the biggest tech story of 2023, as products like ChatGPT have captured the imaginations of consumers and business leaders alike. We’re currently in the experimentation phase of Read more…
Inside AWS’s Plans to Make S3 Faster and Better
As far as big data storage goes, Amazon S3 has won the war. Even among storage vendors whose initials are not A.W.S., S3 is the defacto standard for storing lots of data. But AWS isn’t resting on its laurels with S3, a Read more…
Why Samsara Picked Ray to Train AI Dashcams
When the engineers at Samsara began building their first smart dashcam several years ago, they found themselves using a series of different frameworks to collect data from the IoT devices, train the machine learning mode Read more…
Mastering Data Modeling: Insights from a Data Product Developer
Let's not deny it; we've all been captivated by the elegant symmetry of Data Products. If you haven't encountered them yet, you might be living under a rock. But don't worry, before we delve into advanced solutions, let' Read more…
Rockset Primes Database for Massive Vector Serving
Rockset today unveiled new vector database capabilities, such as the addition of approximate nearest neighbor (ANN) search and native support for LlamaIndx and LangChain, that it says will help companies efficiently scal Read more…
News In Brief
GenAI Debuts Atop Gartner’s 2023 Hype Cycle
Gartner released the 2023 version of its hype curve for emerging technology yesterday, and as expected, generative AI was given the most prominent seat, right at the peak of inflated expectations. But does GenAI have the Read more…
Track Data Product Health and Reliability with Monte Carlo’s Latest Dashboard
Monte Carlo has announced a new capability in its observability suite, the Data Product Dashboard. The new dashboard gives data teams a window into the health and reliability of the tables, training sets, and other as Read more…
Proactive CIOs Embrace Generative AI Despite Risks: MIT and Databricks Report
A new report from MIT Technology Review Insights and Databricks found the most proactive CIOs are decisively embracing generative AI as part of an enterprise-wide strategy, despite its risks. “The Great Acceleration Read more…
DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
DataStax just announced the general availability of its vector search capability in Astra DB, its DBaaS built on Apache Cassandra. Vector search is a must-have capability for building generative AI applications. In ma Read more…
TikTok Parent Open Sources Real-Time Data Warehouse
You might not yet be a major TikTok influencer, but you can still analyze data like TikTok’s parent company, ByteDance, which recently released its real-time data warehouse architecture as open source. ByConity, the Read more…
This Just In
Jan 25, 2024 |
SUNNYVALE, Calif., Jan. 25, 2024 — Google Cloud and Hugging Face today announced a new strategic partnership that will allow developers to utilize Google Cloud’s infrastructure for all Hugging Face services, and will enable training and serving of Hugging Face models on Google Cloud. Read more…
Jan 19, 2024 |
REDWOOD CITY, Calif., Jan. 19, 2024 — Equilar is proud to introduce Equilar RainMaker, available on Snowflake Marketplace. Equilar RainMaker is an app native to the Snowflake Data Cloud that is designed to operationalize valuable customer relationship data and accelerate growth opportunities. Read more…
Jan 16, 2024 |
NEW YORK, Jan. 16, 2024 — Pinecone has announced a new vector database that lets companies build more knowledgeable AI applications: Pinecone serverless. Read more…
Jan 12, 2024 |
SAN FRANCISCO, Jan. 12, 2024 — The OpenTofu community is excited to announce the general availability of OpenTofu, the open source fork of Terraform, now a production-ready project under the Linux Foundation. Read more…
Jan 8, 2024 |
IRVINE, Calif., Jan. 8, 2024 — Syntiant Corp., a leader in edge AI deployment, today announced results of its first optimizations that reduce the computational footprint of leading large language model (LLM) architectures, enabling these massive neural networks to run on cloud-free, always-on devices at the edge of networks. Read more…
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