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Unlocking the Power of the TPU Stack: Introducing our new Developer Hub
Google Cloud has launched the TPU Developer Hub, an educational resource for model builders, optimizers, and developers working with TPU infrastructure and its supporting software stack. It organizes guidance across the developer lifecycle, covering pre-training, post-training, and inference, with material on hardware architecture, infrastructure consumption modes, and software capabilities including specialized compiler technology and XLA. Resources also address PyTorch migration and deployment, XProf-based tracing and observability, multi-chip parallelism, Pallas kernels, KV cache offloading, networking, and security for distributed workloads. The hub combines interactive Colabs, open-source code recipes, and deep-dive documentation, with content intended for both manual browsing and AI-assisted development. Its stated purpose is to help users select appropriate TPU infrastructure, diagnose bottlenecks, optimize model performance, and move from concepts toward production through practical, regularly updated guidance.
Enhance Security and Trust: New Session Metadata in Sign in with Google
Sign in with Google now provides verified applications with two OpenID Connect session metadata claims, auth_time and amr, in ID tokens. auth_time records the last successful Google authentication time, distinguishing session freshness from token issuance, while amr is a JSON array identifying authentication methods such as pwd, mfa, hwk, swk, tel, and sms. The claims are available across Android, iOS, and web client and server applications, and can support audit logging, step-up authentication based on session age, and authorization rules requiring stronger methods for sensitive operations. Verified applications request them through the standard OIDC claims parameter without significantly changing an existing Sign in with Google authentication flow.
What a difference 10 years of open source makes
ClickHouse marks ten years since becoming open source under the Apache 2.0 license, crediting more than 2,600 contributors and a decade of monthly releases for its growth into one of the world’s most widely deployed analytical databases. Recent engineering work spans joins, updates and deletes, JSON, full-text search, vector search, query acceleration, integrations, and developer tooling. Join-focused changes made the TPC-H SF100 workload 26× faster between versions 22.4 and 26.4, while statistics-based reordering reduced one six-table query from 3,903.7 seconds to 2.7 seconds. The project also publishes open benchmarks, including ClickBench, JSONBench, CostBench, and PostgresBench, with scripts, configurations, data, and results intended for independent validation. Its next phase continues to emphasize community contributions and broader ways to use ClickHouse.
From hobby to real world: integrating the hard stuff with agents
The post documents building a production-oriented leaderboard for open-source Stripe Projects applications, where users submit projects, share links, and vote. Unlike an earlier transcription app, this project required authentication, multiple database tables, hosting, and controls limiting unauthenticated users to one vote per project. The agent initially selected Supabase for database and auth and Vercel for hosting, then added Upstash Redis after an in-memory rate limiter proved unsuitable for serverless enforcement. Supabase's two-emails-per-hour authentication limit prompted a human-directed migration to Clerk, after the agent proposed an unsuitable Twilio solution. The resulting MVP used five resources across four providers, took more than a day, and received separate security and performance audits before review.
Databricks announces 2026 global partner awards
Databricks announced its 2026 Partner Awards at Data + AI Summit, recognizing more than 65 achievements across its global partner network of over 8,000 organizations. The awards cover consulting and system integrators, independent software vendors, technical champions, learning and enablement, industry categories, and product-focused contributions. Accenture/Avanade received Global Partner of the Year for an eighth consecutive year, citing more than 15,000 trained practitioners, 9,500+ certified resources, and over 1,000 joint engagements. Other cited results include Capgemini’s Unity Catalog migration of 25,000 tables, 10,000 notebooks, and 2 petabytes across 150+ countries, while Kraken Technologies reduced data-processing costs eightfold and cut load times from three days to eight hours using Databricks and Delta Sharing. The announcement frames the winners’ work as supporting data and AI adoption through software, services, integrations, and consulting.
Announcing New OpenSharing and Marketplace capabilities for the AI era
Databricks announces new OpenSharing and Marketplace capabilities aimed at sharing data, AI assets, and partner applications without moving data. OpenSharing, a Linux Foundation project and evolution of Delta Sharing, adds vendor-neutral sharing for Agent Skills, AI models, unstructured data, Iceberg clients, Lakebase tables and change data feed, plus governed multi-cloud connectivity and agentic sharing through Genie Agent Sharing. The release also introduces identity resolution in Databricks Clean Rooms, where partners such as LiveRamp and Acxiom can work against protected first-party data without seeing raw customer records. Third-party apps are now available through Databricks Marketplace, allowing customers to deploy them in their workspaces without separate infrastructure, while providers gain distribution. Marketplace Commit Drawdown lets customers use existing Databricks universal commits to acquire Marketplace data and AI solutions.
Skip the learning curve: rethinking data migration for real outcomes
Data migrations are presented as high-risk, costly initiatives whose technical completion can delay adoption and strategic value, especially during infrequent warehouse transitions. The proposed alternative combines migration, modernization, and value creation in parallel, using experienced specialized partners and AI-enabled automation for code conversion, data-quality validation, and pipeline modernization. Rather than lifting and shifting legacy workloads, teams are urged to simplify architectures, retire unnecessary components, reduce technical debt, and align data with business needs while validating progress continuously. Progressive decommissioning reduces the “double-bubble” period in which old and new systems run together, helping costs fall as workloads move instead of waiting for final completion. The Migrate & Modernize Program connects organizations with partners, and the post reports faster cutovers, reduced migration costs, and complex workloads entering production ahead of schedule among early participants.
Salesforce signs definitive agreement to acquire Fin
Salesforce has signed a definitive agreement to acquire Fin for approximately $3.6 billion, with closing expected in the fourth quarter of Salesforce’s fiscal year 2027. Fin says it began as Intercom 15 years ago and, nearly four years ago, shifted toward modern LLMs to create and define the Customer Agents category. The companies plan to join forces, with Salesforce’s resources intended to help bring Fin to more consumers, while Fin says little will practically change for customers: the author will remain CEO and Des Traynor will continue running R&D. The announcement also points to recent work including the Apex model and the Operator internal agent, and describes the deal as a pivotal moment for Fin’s employees, founders, and leadership team.
How Wayfair cut ML model costs by 90% (twice!) with Cursor
Wayfair’s Applied Research team used Cursor to automate and parallelize experiments for a product-tag validation model that checked attributes against images, descriptions, and reviews. The model was accurate but too expensive to run across the catalog. In December 2025, five researchers standardized the dataset and evaluation benchmark, then built and tested 110 distinct variants in four days; the winning architecture reduced inference costs by 94%, improved precision, and became the production baseline. In March 2026, the team benchmarked against that baseline, ran 140+ new experiments, and added genetic-algorithm searches, achieving another 90% cost reduction. The workflow used 20+ parallel agents, desktop and CLI surfaces, and cloud agents, leaving researchers to formulate hypotheses, interpret results, and choose candidates while Cursor implemented, ran, and measured variants.
How to Rent a Car in Grand Rapids, Michigan
Renting a car in Grand Rapids can provide flexible transportation around the city and for trips to nearby areas, including for travelers arriving at Gerald R. Ford International Airport. Uber Rent lets users compare vehicles from rental companies in the Uber app or online, with choices including economy cars and SUVs; available suppliers may include Budget, Hertz, and Avis, depending on location. The booking process covers entering pickup and drop-off details, reserving a vehicle, collecting it with a matching driver’s license and physical credit card, and returning it to the listed location. Renters must be at least 18, while a Young Driver Fee may apply under 25; personal insurance is not required, though supplier-provided options are available, and additional conditions may appear in the reservation terms.
How to Rent a Car in Fayetteville, North Carolina
Renting a car in Fayetteville, North Carolina, can provide mobility for airport arrivals, city-center work, local errands, and trips to surrounding areas. The guide describes using Uber Rent through the Uber app or online to book available sedans, SUVs, and other models from rental companies such as Budget, Hertz, and Avis, with availability varying by location. It recommends matching vehicle type and rental duration to the trip, while reviewing rates, mileage, and additional fees, then outlines reservation, pickup, payment, and drop-off steps. Renters must be at least 18, present a valid license matching the reservation, and bring a physical credit card in the primary driver's name; under-25 renters may pay a Young Driver Fee, and rental companies can offer insurance and protection plans.
How to Rent a Car in Spokane, Washington
Renting a car in Spokane can provide flexibility for city travel, work visits, longer stays, and drives to nearby destinations. Uber Rent lets travelers browse, compare, and book vehicles from rental companies in the Uber app or online, with options including compact cars, SUVs, and same-day or advance reservations. The booking flow covers entering pickup and drop-off details, completing payment either in advance or at the rental counter, collecting the vehicle with a valid driver’s license and physical card, and returning it to the stated location. The source says renters must be at least 18, while a Young Driver Fee may apply under 25; personal insurance is not required, though suppliers may offer protection plans, and requirements can vary by vehicle and supplier.
How to Rent a Car in Peoria, Arizona
Renting a car in Peoria, Arizona, is presented as an option for local transportation, regional trips, and travel from Phoenix Sky Harbor International Airport (PHX). Uber Rent lets users compare and book vehicles from participating rental companies, including Budget, Hertz, and Avis, through the Uber app or online, although availability varies by location. The booking process covers entering pickup and dropoff details, reserving a vehicle, collecting it with a driver’s license and payment method, and returning it to the listed location; reservation details appear in the app and confirmation email. The source advises matching vehicle type and rental duration to the trip, reviewing base rates and extra fees, and checking requirements such as a minimum age of 18, a physical credit card in the primary driver’s name, and supplier-specific conditions.
How to Rent a Car in Bakersfield, California
Renting a car in Bakersfield can provide flexibility for city travel, trips beyond the city, airport arrivals through Meadows Field Airport (BFL), business stays, or extended visits. The guide describes using Uber Rent to browse, compare, and book vehicles from rental companies, with options ranging from sedans to SUVs and reservations available through the Uber app or online. It outlines choosing a vehicle based on trip purpose, space, rental duration, and budget, then covers reserving, picking up, and returning the car while keeping booking details in the app and confirmation email. Requirements include being at least 18, presenting a matching valid driver’s license and physical credit card, and reviewing supplier-specific conditions; personal car insurance is not required, though protection plans may be offered at pickup.
What is Document AI?
Document AI uses machine learning, natural language processing (NLP) and optical character recognition (OCR) to extract, classify and understand information from structured, semi-structured and unstructured documents. Unlike OCR alone, it interprets layout and context, turning files such as invoices, contracts and emails into structured, actionable data through ingestion, OCR, layout parsing, entity extraction, classification, validation and, when needed, human review. Modern systems add large language models for summarization, document Q&A and zero-shot extraction, but hallucination risk makes validation and human oversight essential, particularly in regulated settings. The guide also describes Databricks Document Intelligence, which processes and stores documents alongside organizational data under Unity Catalog, using AI Functions, Variant and Lakeflow Jobs to create governed, queryable workflows without moving data between systems.
Product updates: VM Sandboxes, Lower latency routing, RBAC, and more
Modal also announced several product updates including VM Sandboxes in alpha, lower latency regional routing, and role-based access control. VM Sandboxes, currently in alpha, are a new VM runtime that runs a real Linux kernel, supporting Docker containers and Linux features like eBPF, systemd, cgroups, and custom filesystem mounts for better I/O performance. Regional routing lets Functions run in US West, EU West, or Asia Pacific South instead of default US East with a single setting, lowering latency and keeping data in-region. RBAC is now available for Team and Enterprise plans, with Environments as security boundaries and read-only defaults via Restricted Environments, tied into Audit Logs. Other updates include domain allowlisting, named images, volume subdirectory mounts, readiness probes, configurable snapshot TTLs with a 30-day default, SDK updates, and a partnership with Anthropic for Claude Managed Agents.
Teaching Sidekick to say no: automated data curation with LLM judge consensus
Sidekick’s customer-segmentation skill was fine-tuned on tens of thousands of successful, de-identified production queries, so it generated zero-result queries instead of refusing impossible requests such as finding customers by occupation. A small Toloka dataset of roughly 600 standard queries and 602 refusal annotations became a seed for four frontier LLM judges, which were calibrated against human-labeled examples and required to agree on both verdict and reasoning. The pipeline used mutually exclusive categories to resolve conflicting labels, filtered disagreements for human review, and fed accepted examples from later production traffic back into fine-tuning. With automated curation, the segmentation pass rate rose from 0.762 to 0.798 versus naive merging, while manual validation measured 86.3% refusal accuracy and a 4.6% false-positive rate. The resulting flywheel is being applied to other Sidekick skill models and data-quality problems.
Ten years of ClickHouse in open source
ClickHouse’s tenth-anniversary history describes its path from an internal web-analytics experiment to an open-source analytical database with more than 2,000 contributors. The original problem was processing rapidly growing, real-time logs while answering flexible reports quickly; tested MySQL extensions and standalone analytical databases did not meet the stated scale of 100 billion records per day and 500 columns. The project built column-oriented storage, lightweight compression, custom aggregation structures, background merges, and query support for grouping, aggregation, filtering, and sorting. Released publicly on June 15, 2016, ClickHouse is presented as a level-three open-source project with public contribution guidelines, code review, testing, CI, documentation, and a roadmap, while contributors receive credit even when implementations are substantially rewritten.
Cisco Talos empowers threat researchers while reducing TCO by 75% with ClickHouse Cloud
Cisco Talos operates a threat-intelligence reputation service that classifies file hashes from Cisco product telemetry, enabling researchers to make security decisions about benign and potentially malicious artifacts. Previously, a custom pipeline moved data from Databricks Delta and S3 through EKS, where staging and aggregated tables supported an API; the self-managed design retained about a petabyte of compressed, replicated data on 32 high-compute nodes. The team rebuilt the system in four phases, using Terraform, SSO/SAML, sharded ClickPipes for a 12-month backfill, shadow traffic, and a validated cutover to ClickHouse Cloud on AWS. The resulting architecture uses EventBridge, SQS, ClickPipes, SharedMergeTree, object storage, and AWS PrivateLink, delivering less than a minute of queue lag, zero data loss, a 100% response match across more than 1,000 hashes, zero downtime, roughly 90% lower storage costs, and about 75% lower TCO while reclaiming over 300 engineer hours annually.
How API changes flow into Stripe's developer products
Stripe describes how API changes are propagated across its developer-product suite, including SDKs in seven languages and three release channels, the CLI, Shell, API Explorer, API Reference, changelog, and internal tools. Historically, v1 workflows used OpenAPI or a Ruby-based DSL while v2 APIs used protobuf-based DSLs and an internal API specification, forcing teams to maintain parallel generators and leaving some products without v2 support. Stripe chose OpenAPI as a shared representation and built a pipeline whose generated artifacts are tailored by variant, release phase, and API version, with vendor extensions carrying Stripe-specific metadata. Automated validation, OpenAPI diffs, pre-release comparisons, versioned snapshots, and downstream publishing now connect API definition changes to documentation, code samples, SDK and CLI releases, while older v1 versions remain difficult to regenerate with newly added metadata.
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