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Uber
a global technology platform that connects people who need a ride or delivery with independent drivers and couriers through a smartphone app.
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Piloting estimated earnings per active hour on trip requests
Uber’s pilot, now ended, tested an estimated earnings per active hour badge on trip requests for some drivers in select cities. The badge appeared on Trip Radar and Exclusive requests, while drivers still received upfront fares and were paid per trip, not by the hour. Active time covered driving to pickup, waiting for the rider, and completing the trip, excluding time spent online between requests. The estimate divided the upfront fare by estimated pickup, one-minute average pickup wait, and trip time, then scaled the per-minute amount to 60 minutes. Uber described it as a comparison benchmark, but noted that timing estimates use historical data and traffic conditions, actuals can vary, and the figure is not a guarantee.
Beyond Prediction: Solving the Multiple Knapsack Problem at Scale: How Uber Optimizes Incentives
Uber’s Tarot platform frames incentive allocation as a Multiple Knapsack Problem (MKP), replacing FIFO contention handling and reactive budget management. It combines segmentation, budget pacing, uplift predictions, multi-objective value scoring, and a plug-and-play optimizer coordinated by an orchestrator. For each run, Tarot forms user-lever opportunities, predicts incremental ROI and cost, reconciles available budget, and selects assignments under team, business, and concurrency constraints before publishing them to domain services. The initial HiGHS linear programming approach took more than 24 hours to find a feasible solution for 100,000 users and one lever, while CP-SAT solved the same dataset in minutes and handled millions of users across multiple levers within stated SLA timeframes. The result is a production architecture that moves beyond heuristics by combining constraint programming with budget pacing, while future work targets automated exploration and model feedback.
Autonomous vehicles are coming to more cities
Uber is introducing autonomous vehicles (AVs) on its app in selected sections of Atlanta, Austin, Dallas, and Las Vegas, as part of a hybrid marketplace that includes both AVs and drivers. Availability is limited by geography and time of day, monitored during each rollout, and expected to change over time. Riders requesting UberX, Uber Comfort, or Uber Comfort Electric may be matched with an AV and can adjust app settings to increase their chances; some trips may initially include a specialist from an autonomous partner who can take over if needed. The company says AVs are intended to complement drivers, helping meet demand during busy periods or where fewer drivers are available. Uber expects minimal driver impact and says expanding rider engagement will create more opportunities for drivers.
App-based Worker Notice of Rights (Seattle)
Uber’s Notice of Rights describes protections and information available to app-based workers using its platform for delivery work in Seattle, Washington, under Seattle Bill CB 120294 and Seattle Municipal Code Chapter 8.37. It lists guaranteed minimums of $0.47 per engaged minute, $0.80 per engaged mile, and $5.34 per offer, along with required information before accepting an offer. Workers may decide when to be available and whether to accept, reject, or cancel delivery offers, and are protected from retaliation for exercising covered rights. The notice also covers tip and fraudulent-use policies, cancellation reasons, complaint or civil-action rights, and access for up to three years to information required under Sections 8.37.070(B) and (C); Uber directs workers to Customer Support for those records.
Fast Copy-On-Write within Apache Parquet for Data Lakehouse ACID Upserts
Large-scale lakehouse upserts can become slow and resource-intensive, especially in Apache Hudi copy-on-write mode, where affected files are read, modified, and rewritten in full. The approach adds a Parquet row-level secondary index mapping records to files and row IDs, allowing updates to locate the specific data pages containing changed records. During copy-on-write, related pages are updated while unrelated pages are copied as byte buffers, avoiding decompression, re-encoding, and record reassembly for skipped data. Benchmarks using TPC-DS sales data, Spark jobs with matching vCore and memory settings, and update rates from 5% to 50% found significantly faster speeds than traditional approaches, including Delta Lake’s default configuration. The authors plan to integrate the row-level index and fast copy-on-write into Apache Hudi for use cases such as incremental ingestion, data deletion, and CDC.
We’ve improved Destination Mode to get you better matches
Destination Mode has been updated to prioritize trip requests that move drivers toward a chosen destination while accounting for added time and distance. Drivers can choose Flexible route, which widens the search area for more opportunities but may lengthen arrival, or Faster route, which limits requests to trips directly on route for potentially quicker arrival but fewer offers. To use it, drivers search for a place in Driver App, enable Destination Mode, select a route, and accept trips. Destination Mode can be used twice daily, with a session starting on an Exclusive trip request; drivers can decline or cancel up to two Exclusive offers on Faster or three on Flexible before the session ends, and those offers still affect Acceptance Rate. Delivery requests remain unfiltered, and the mode cannot be enabled at airports.
Lessons from Building a First-Pass AI PRD Reviewer at Uber
Uber built an AI-powered PRD Evaluator to help product managers strengthen drafts before they enter structured checkpoint and approval forums. Starting with a PRD, it gathers linked documents, decks, meeting notes, prior experiments, cross-functional artifacts, and Uber-specific context, then classifies the proposal to calibrate review depth. It assesses opportunity and hypothesis, product scope, user experience and impact, and metric and data rigor, producing a launch-readiness scorecard with prioritized gaps, evidence, replacement-text suggestions, and a “start here” fix. Early internal use by dozens of PMs helped surface blind spots, test unsupported headroom assumptions, identify adjacent-system effects, and improve experiences within existing scope. The team’s lessons emphasize decision frameworks, broader context, hard boundaries, prioritization, and preserving human judgment for final approval.
Upgrading M3DB from v1.1 to v1.5
Uber upgraded M3DB from v1.1 to v1.5 after three years on its previous open-source deployment, seeking a repeatable rollout process for a roughly 100-cluster, 5,500-node environment. The effort addressed scale-specific validation: offline benchmarks measured correctness, latency, success rates, bootstrap and tick durations, and persistence across restarts and replacements, while online shadow testing compared sampled production traffic between old and new versions. Within each cluster, upgrades were limited to one node at a time because writes used a two-thirds majority quorum. A rollout-related read-quorum incident exposed missing replica data; the cause was bootstrap misconfiguration, corrected by using “exclude_commitlog,” since production workloads did not employ WAL. Production then showed significantly lower memory usage and improved node bootstrap times, supporting continued, data-driven upgrades and contributions to M3DB's benchmarking and documentation.
Zero-Growth Stack, Real Gains: How Stack Allocation Can Save 10% CPU in Go
At Uber, repeated Go goroutine stack expansion consumed substantial CPU in a service whose stack-memory usage remained low, making memory a viable trade-off. Go starts goroutines with 2KB stacks and doubles them when needed, copying the previous stack; the post also notes that adaptive stack sizing and stack shrinking can add runtime cost. Uber patched the runtime, disabled adaptive sizing and shrinking, and used profile-guided analysis of pprof traces plus assembly-derived function stack usage to choose a static power-of-two starting size. For the profiled service, the analyzer identified about 19KB of required stack usage, leading to a 32KB setting instead of 2KB. After deployment, stack-growth CPU fell from close to 10% to below 1%, while most instances used about 50MB of stack and a few reached 200MB.
The 5 Layers Every Cloud Commitment Depends On
Long-term hyperscale cloud commitments are presented as distributed-systems problems with expensive consequences when physical assumptions are wrong. The post proposes a dependency sequence across regional and availability-zone topology, power architecture, fit-for-purpose compute, SKU qualification, and network design. It compares application-observable latency with bare-metal RTT, uses power consumption as a migration check, and argues that workload characteristics should drive memory-to-core ratios, silicon generations, instance families, and routing choices rather than provider defaults. It also explains why zone placement, inter-zone and inter-region transfer, and egress pricing affect quorum latency, reliability, and economics, while noting that cross-region traffic may require explicit justification. The conclusion is that these constraints compound over the commitment unless teams manage architectural drift, with software and contracting layers addressed separately.
Next-gen transit: Votran’s innovative model for multimodal partnership
Volusia County Transit Services (Votran) has partnered with RATP Dev, Spare, and Uber Transit to unify demand-responsive transportation for more than half a million Volusia County residents. The VoTran On Demand app, powered by Spare, brings together the Transportation Disadvantaged program, VoRide microtransit, and other options alongside traditional fixed-route and paratransit services. Votran uses a mixed fleet of dedicated vehicles and Uber’s non-dedicated driver network to improve on-time performance, enable same-day trips, and reduce the cost of serving low-density areas. In zones such as Ponce Inlet, the app can request an Uber ride for local travel or connect riders to a suitable fixed bus route for destinations outside the zone, offering a model for balancing coverage and efficiency across a 1,100-plus-square-mile county.
How Ansible® Automation Powers the Uber Corporate Network at a Global Scale
Uber’s corporate network spans offices across six continents and around 5,000 devices, creating a configuration-management problem involving continuous updates, regional variation, and hardware from multiple vendors. The post explains why Uber uses Ansible for on-premises network configuration while Terraform handles cloud provisioning and Puppet manages configuration on running machines. Its Daily Nightly Enforcement workflow backs up each region’s running configuration to a private GitHub repository, gathers device facts, renders vendor-specific golden configurations through inventory variables and Jinja templates, and pushes them overnight, with failures triggering alerts. Inventory groups encode desired state across regions, functions, and operating systems, while custom roles, formatters, cleanup jobs, and occasional Ansible or Python modules address scale and vendor-specific gaps. The conclusion says this automation makes the diverse network manageable, stable, updated, and ready for daily use, although some hardware still requires other portals.
City of Boston Delivery Insurance Addendum January 9, 2026
Effective January 9, 2026, this City of Boston addendum describes insurance Portier, LLC and/or Schleuder, LLC maintains for delivery services performed under its agreements. For motorized bicycles below 30 mph and transportation modes requiring registration under M.G.L. c. 90, § 1A, coverage is $50,000/$100,000/$50,000 while available before matching, then $1 million for death, bodily injury, and property damage after accepting a request until delivery completion or cancellation; physical-damage coverage may apply with a $2,500 deductible when personal comprehensive and collision coverage exists. For electric bicycles below 30 mph, accepted-trip coverage is $50,000/$100,000/$30,000. No other periods are covered, personal policies may exclude delivery activity, and the Company may verify insurance information.
Validating Bounding Box Annotations
Video bounding-box annotations can contain ID swaps and position jumps that degrade training data for object-tracking models, especially when long videos are split among annotators and later merged. Uber's system runs in uLabel, combining visual, motion, and coordinate features from an 11-frame sliding window with an XGBoost classifier trained on synthetic anomalies from six open-source datasets. It scores each frame for error probability, then groups predictions with frame-index and confidence clustering into regions that operators can review, fix, or dismiss. The current iteration prioritizes jump and ID-swap detection, while freeze and scale/aspect errors remain planned for future releases; the deployed workflow is intended to reduce the cost and time of sequential edit-review while processing client data statelessly without retaining it or using it to train models.
Massachusetts Driver Benefits
In June 2024, Uber reached an agreement with Massachusetts Attorney General Andrea Campbell that adds protections and benefits for independent Massachusetts Uber Rides drivers. For Rides trips beginning in Massachusetts, drivers are guaranteed $34.48 per hour of active time, calculated over two-week periods, with supplemental payments when trip fares and included incentives fall short. Beginning November 1, 2024, drivers can accrue up to 40 hours of paid sick leave annually at $21.22 per hour, subject to the stated accrual and claiming rules. The post also describes occupational accident insurance, Paid Family Medical Leave payments, a portable health fund with quarterly eligibility, and account-deactivation appeals. It explains how active time, sick leave, guaranteed earnings, and health-fund participation are viewed or claimed through Uber’s systems and related administrators.
Using Uber at Louis Armstrong New Orleans International Airport
Louis Armstrong New Orleans International Airport (MSY) handled more than 10 million passengers in 2015, a nearly 9% increase from the previous year, making preparation useful for travelers. The post recommends Uber as an alternative to parking, with uberX or uberXL available and pickup at the Ground Transportation Center on the first floor of the short-term parking garage. After collecting luggage and selecting a vehicle, riders should follow the airport signs; drivers wait at designated parking spots, and riders can call if they have trouble connecting. Additional resources cover terminal maps, traffic, flight status, airport updates, TSA guidelines, and security wait times. It also points visitors toward the French Quarter, Jean Lafitte National Historical Park and Preserve, and Casamento’s, noting attractions, trails, historical sites, gumbo, and an oyster loaf sandwich.
Where to Celebrate Valentine's Day in Pittsburgh
Pittsburgh’s Valentine’s Day guide pairs restaurant suggestions with movies, concerts, creative courses, or a cooking class, allowing couples to mix and match stops. Dinner options include Dish Osteria and Bar’s daily-changing classic Italian menu, Morcilla’s shareable Spanish pintxos, Kaya’s Caribbean-inspired dishes, and Everyday Noodles’ soups, dim sum, and soup dumplings. Events range from films at the Manor Theatre and February concerts at Mr. Smalls Funhouse and Club Cafe to multi-week courses at Manchester Craftsmen’s Guild and a February 11 class at Habitat, which includes lunch and an apron. The practical notes include making reservations at Morcilla, arriving early for a Club Cafe table, and scheduling Uber between destinations for convenience.
New Atlanta Stadium ride guide: Getting there
Uber’s guide explains transportation options for events at Atlanta’s new Mercedes-Benz Stadium, which it says will host more than 100 events that year. It recommends combining Uber with MARTA: riders can use promo code MARTA2MBS for 50% off eligible uberX or uberPOOL trips to and from select stations, within specified event windows. The discount has exclusions, a maximum value of $10, and applies to up to five rides per event in select Atlanta areas while supplies last; the guide lists dates and times ranging from September 7 through January 8. For direct stadium trips, Uber advises using designated pickup points, avoiding Northside Drive, verifying the vehicle and license plate, and using features such as upfront fares and Split Fare.
Perfect Date Ideas in Manhattan for Valentine's Day
Manhattan is presented as a Valentine’s Day destination for couples seeking either elaborate experiences or quieter, indulgent ways to spend the evening. The recommendations range from a Hornblower Cruise’s New York City Lights Dinner at Pier 40, with filet mignon and landmark views, to dancing at the vintage Jane Ballroom and rooftop views across the Hudson. For a celestial theme, Hayden Planetarium offers a hand-holding setting where Neil deGrasse Tyson guides visitors through astronomy. The Library at the NoMad Hotel pairs Old World décor, books, and more than 250 bottles of bubbly, while AMC Loews on West 84th Street offers reclining seats that convert into love seats for a movie night. Together, the suggestions cover waterfront dining, dancing, stargazing, champagne, and a cozy film.
5 Beaches in Close Proximity to NYC
The article recommends five beach escapes near New York City, combining public transportation with Uber rides to reach destinations beyond much of the city’s less inviting coastline. Orient Beach State Park offers eight miles of Gardiner’s Bay shoreline, undeveloped acreage, nature trails, and views of Shelter Island. Fort Tilden pairs a pristine Queens shoreline with former military structures and art installations, while Robert Moses State Park provides a less crowded Fire Island setting with picnic areas, mini-golf, surfing, and fishing. Jones Beach adds a broad, popular barrier-island destination with sports, a nature center, concerts, and quieter sand beyond its facilities. Sherwood Island State Park in Connecticut supplies a quieter mix of sand, woods, wetlands, picnicking, and salt-marsh trails.
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