Search: “sql”

Today, we’re excited to announce the general availability of our next-generation Storage-optimized Z4D machine series in Google Compute Engine with both Virtual Machine (VM) and bare-metal instances.

Reinforcement learning (RL) has been a keystone of modern LLM post-training, but it demands large training clusters and access to model internals that external customers can't have with proprietary mo

The volume of data being generated today brings both opportunity and massive operational complexity. Most teams that operate at scale don't discover issues until they appear on an invoice — and by the

Introduction The landscape of software supply chain security has undergone a significant shift. Recent campaigns demonstrate that sophisticated threat actors are systematically targeting the engineeri

AIOps (Artificial Intelligence for IT Operations) merges AI and machine learning with comprehensive observability to automate event correlation, root‑cause analysis, anomaly detection, incident respon

As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN

arXiv:2609.15779v1 Announce Type: new Abstract: Data agents aim to fulfill natural-language instructions over heterogeneous data, including tables, files, and databases. However, data agents face a ch

arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach

arXiv:2609.11286v1 Announce Type: new Abstract: Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This p

arXiv:2607.18029v2 Announce Type: replace-cross Abstract: Researchers need to answer ad-hoc questions about the contents of domain-specific archives but often lack the expertise to write structured qu

arXiv:2609.09671v1 Announce Type: cross Abstract: When an agent writes code, the development framework becomes the control system for a non-deterministic worker. Spec-first, agent-driven frameworks ha

arXiv:2609.09853v1 Announce Type: new Abstract: LLM agents for enterprise systems of record cannot be evaluated on customer production data, and no existing substitute provides ground truth. We presen

I have been a dwarfstar fan for awhile and I really liked glm 5.3 flash but needed it to be materially faster to feel good using it. In the screenshot you can see the outcome of using the model with a

arXiv:2609.04199v1 Announce Type: cross Abstract: Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduce

arXiv:2609.02106v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly explore many candidate states of relational data in parallel, each of which should remain isolated, rep

arXiv:2609.00460v1 Announce Type: new Abstract: Recent Relational Deep Learning architectures have been proposed as foundation models for multi-table relational data, yet they impose constrained neigh

arXiv:2609.01292v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) has become a powerful paradigm for learning from multi-tabular data. However, manually defining RDL prediction tasks is

arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente

arXiv:2608.28963v1 Announce Type: cross Abstract: The number of knowledge graph databases has increased significantly with the proliferation of knowledge graph technologies. Knowledge graphs enable th

Data pipelines are the backbone of the modern enterprise, yet a barrier to entry exists for orchestrating them, making this critical capability unavailable to many data professionals. Following our an

arXiv:2608.23992v1 Announce Type: cross Abstract: Large language model (LLM) agents invoke external tools to retrieve and reason over information beyond pretrained knowledge. The Model Context Protoco

arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the

arXiv:2608.21208v1 Announce Type: cross Abstract: This paper investigates cross-agent specification portability using Oracle-to-PostgreSQL migration as a controlled software transformation task. The s

arXiv:2608.18105v1 Announce Type: cross Abstract: StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured quer

Every data team knows the moment. Someone opens a table, sees a column called cust_seg_flg, and has to go ask around to find out what it means, whether it's safe to use, and whether anyone has already

arXiv:2608.13004v1 Announce Type: new Abstract: Knowledge-base question answering (KBQA) systems rely on effective retrieval and reasoning mechanisms to generate accurate answers from external knowled

For organizations deploying AI agents at scale, there’s often a critical divide between structured and unstructured data. While large language models (LLMs) excel at parsing text documents, emails, an

CISO role evolution is accelerating as cyber resilience emerges as a defining benchmark of security success and AI forces enterprises to rethink not just how they defend against attacks, but how quick

In the modern data landscape, query performance tuning and managing system price-performance is challenging, especially as the number of agentic workloads increase. Even for experienced developers and

In today’s retail environment, shoppers expect highly personalized product discovery experiences and conversational assistance that feels genuine, natural, and genuinely helpful. Today, successful pro

arXiv:2607.29064v1 Announce Type: cross Abstract: Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclea

Businesses want to quickly and safely deploy AI agents to drive revenue, mitigate risk, and optimize capital, all without disrupting mission-critical ERP systems. And to power AI agents, you need more

For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (they

arXiv:2607.23322v1 Announce Type: new Abstract: Instruction tuning has become the standard method for adapting large language models to follow human intent, yet existing instruction datasets are domin

arXiv:2509.21028v4 Announce Type: replace Abstract: We introduce SciTrek, a synthetic question-answering dataset for assessing and improving long-context numerical reasoning in large language models (

In Google Cloud, Identity and Access Management (IAM) helps you maintain access control over your cloud resources and operations. While it includes other features, this is its primary purpose. If you

AlloyDB is a fully managed, PostgreSQL-compatible database service built for your most demanding enterprise workloads. It combines the best of open source PostgreSQL with Google’s advanced technology,

datasette code-frequency chart on GitHub Out of curiosity I decided to see if I could find a useful illustration of the impact of coding agents and Opus 4.5 class models on my own output. The best I'v

The automotive industry is at a pivotal crossroads as it hits the gas on adopting new technology. The era of the traditional connected vehicle has shifted into the age of the software-defined vehicle

AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% ac

Businesses run on fast decisions, but the teams who hold the answers are often buried under a backlog of routine requests, leaving users waiting in line for insights they need now. Today, we are bring

Written by: Jordan Jones Introduction Google Threat Intelligence Group (GTIG) has conducted an in-depth analysis of a .NET backdoor, tracked as STOCKSTAY, that has been continually developed and deplo

Release: datasette-agent 0.2a0 Highlights from the release notes: Tools can now ask the user questions mid-execution. Tools that declare a context parameter receive a ToolContext object, and await con

I didn't have early access to today's Claude Fable 5 release, but I've spent the past ~5.5 hours putting it through its paces. My initial impressions are that this is something of a beast. It's slow,

arXiv:2606.07923v1 Announce Type: cross Abstract: With the advent of Large Language Models (LLMs), many database systems introduced semantic operators that enabled analytical queries over unstructured

arXiv:2606.04646v1 Announce Type: cross Abstract: Many real-world questions over business, legal, and scientific corpora are natural-language versions of database-style queries over records latent in