Tag
Databricks introduces Lakebase LTAP architecture that stores Postgres data in Parquet on S3, enabling transactions and analytics on a single copy of data without CDC or mirroring.
Unconventional AI, led by former Databricks AI chief Naveen Rao, claims their oscillator-based computer architecture can reduce AI inference power consumption by up to 1,000x, demonstrated with their first image-generation model Un0.
A seed-stage YC startup, Wafer AI, is competing in the inference speed race, with Databricks achieving 392 token/s on GLM-5.2, topping Artificial Analysis.
A Twitter thread highlights key takeaways from a Latent.Space podcast episode with Databricks co-founders, covering why Databricks beat Snowflake, the rise of metaharners, Neon's success, HTAP via LTAP, MosaicML's fate, and maintaining startup culture in a large company.
Databricks introduces Agent Mode API for Genie Agent, providing a new interface for building and managing AI agents on the platform.
Grok models from xAI are now available on Databricks Agent Bricks, enabling enterprises to build AI agents with their data.
Omnigent is an open-source meta-harness by Databricks that lets you run a team of AI agents (Claude Code, Codex, Cursor, Pi, and your own) in one live session for coding.
Databricks launches LTAP (Lake Transactional/Analytical Processing), a new architecture that unifies OLAP and OLTP on a single copy of data in the lake, eliminating ETL pipelines and powered by Lakebase. This provides a single governed foundation for operational, analytical, and streaming data in the AI application era.
Databricks launched Omnigent, a meta-harness for combining, controlling, and sharing AI agents, validating the meta-harness approach.
A Databricks tech lead argues that multi-agent AI systems fail not due to model intelligence but due to lack of coordination, framing 50+ agents as a distributed systems problem where parallelism is easy but shared coherence is difficult.
Ali Ghodsi, CEO of Databricks, argues that Zoom has a massive opportunity to build an AI-first product using its vast repository of meeting videos and transcripts, potentially disrupting traditional enterprise SaaS by automating data entry and coordination.
Databricks introduces GPT-5.5 for enterprise agent workflows, achieving state-of-the-art on the OfficeQA Pro benchmark with a 46% error reduction over GPT-5.4.
An analysis of three new Postgres-compatible cloud databases—Snowflake Postgres, Databricks Lakebase, and Azure HorizonDB—highlighting their distinct architectures and the vendor lock-in implications for enterprise data platforms.
This article explains how Databricks' Lakebase architecture achieves a 5x improvement in Postgres write throughput by disabling Full Page Writes (FPW) and leveraging stateless compute with distributed storage.
OpenAI partners with Databricks to release the GPT-5.5 model, achieving a 46% reduction in error rate in agent frameworks, becoming the only model to exceed 50% on benchmarks, with significant improvements in parsing quality and function calling capabilities.