Monday, September 29, 2025

Ultralytics YOLO26

YOLO26: A better, faster, smaller YOLO model

Ultralytics on 25 Sep 2025 shared more information about YOLO26


Here’s an overview of the computer vision tasks supported by YOLO26:

  • Object detection: YOLO26 can identify and locate multiple objects within an image or video frame.
  • Instance segmentation: Going a step beyond detection, YOLO26 can generate pixel-perfect boundaries around each object it identifies. 
  • Image classification: The model can analyze an entire image and assign it to a specific category or label.

  • Pose estimation: YOLO26 can detect keypoints and estimate poses for humans as well as other objects.

  • Oriented bounding boxes (OBB): The model can detect objects at any angle, which is especially useful for aerial, drone, and satellite imagery, where items like buildings, vehicles, or crops may not be aligned with the image frame.

  • Object tracking: YOLO26 can be used to track objects across video frames or real-time streams.

In fact, the smallest version of YOLO26, the nano model, now runs up to 43% faster on standard CPUs, making it especially well-suited for mobile apps, smart cameras, and other edge devices where speed and efficiency are critical.

Here’s a quick recap of YOLO26’s features and what users can look forward to:

  • DFL removal: We removed the Distribution Focal Loss module from the model’s architecture. Regardless of the object sizes in an image, YOLO26 can place tailored bounding boxes while running more efficiently.
  • End-to-end NMS-free inference: YOLO26 adds an optional mode that doesn’t need Non-Maximum Suppression (NMS), a step normally used to remove duplicate predictions, making deployment simpler and faster for real-time use.
  • ProgLoss and STAL: These improvements make training more stable and significantly boost accuracy, especially for detecting small objects in complex scenes.
  • MuSGD optimizer: YOLO26 uses a new optimizer that combines the strengths of two training optimizers (Muon and SGD), helping the model learn faster and reach higher accuracy.

Simplifying deployment with Ultralytics YOLO26 

Whether you are working on mobile apps, smart cameras, or enterprise systems, deploying YOLO26 is simple and flexible. The Ultralytics Python package supports a constantly growing number of export formats, which makes it easy to integrate YOLO26 into existing workflows and makes it compatible with almost any platform. 

A few of the export options include TensorRT for maximum GPU acceleration, ONNX for broad compatibility, CoreML for native iOS apps, TFLite for Android and edge devices, and OpenVINO for optimized performance on Intel hardware. This flexibility makes it straightforward to take YOLO26 from development to production without extra hurdles.

Another crucial part of deployment is making sure models run efficiently on devices with limited resources. This is where quantization comes in. Thanks to its simplified architecture, YOLO26 handles this exceptionally well.  It supports INT8 deployment (using 8-bit compression to reduce size and improve speed with minimal accuracy loss) as well as half-precision (FP16) for faster inference on supported hardware. 

Most importantly, YOLO26 delivers consistent performance across these quantization levels, so you can rely on it whether it’s running on a powerful server or a compact edge device.

Documentation:

https://docs.ultralytics.com/models/yolo26/

 Please read more on Ultralytics blog

https://www.ultralytics.com/blog/meet-ultralytics-yolo26-a-better-faster-smaller-yolo-model

PostgreSQL 18 Released

 

PostgreSQL 18 Released

on 2025-09-25 PostgreSQL group released version 18
postgresql 18 is the lateset and best version introduced ever.
internal benchmarks of postgress group demonstrated a better performance of x3 times in certains scenario.

PostgreSQL 18 improves performance for workloads of all sizes through a new I/O subsystem that has demonstrated up to 3× performance improvements when reading from storage, and also increases the number of queries that can use indexes. 


This release makes major-version upgrades less disruptive, accelerating upgrade times and reducing the time required to reach expected performance after an upgrade completes. Developers also benefit from PostgreSQL 18 features, including virtual generated columns that compute values at query time, and the database-friendly uuidv7() function that provides better indexing and read performance for UUIDs. PostgreSQL 18 makes it easier to integrate with single-sign on (SSO) systems with support for OAuth 2.0 authentication.


PostgreSQL previously relied on operating system readahead mechanisms to accelerate data retrieval. However, because operating systems lack insight into database-specific access patterns, they cannot always anticipate what data will be required, leading to suboptimal performance in many workloads.

PostgreSQL 18 introduces a new asynchronous I/O (AIO) subsystem designed to address this limitation. AIO lets PostgreSQL issue multiple I/O requests concurrently instead of waiting for each to finish in sequence. This expands existing readahead and improves overall throughput. AIO operations supported in PostgreSQL 18 include sequential scans, bitmap heap scans, and vacuum. Benchmarking has demonstrated performance gains of up to 3x in certain scenarios.


The new io_method setting lets you toggle between the AIO methods, including worker and io_uring, or you can choose to maintain the current PostgreSQL behavior with the sync setting. There are now more parameters to consider tuning with AIO, which you can learn more about in the documentation.

Faster upgrades, better post-upgrade performance

A key PostgreSQL feature is the generation and storage of statistics that help PostgreSQL select the most efficient query plan. Before PostgreSQL 18, these statistics didn't carry over on a major version upgrade, which could cause significant query performance degradations on busy systems until the ANALYZE finished running. PostgreSQL 18 introduces the ability to keep planner statistics through a major version upgrade, which helps an upgraded cluster reach expected performance more quickly after the upgrade.

Additionally, pg_upgrade, a utility that performs major version upgrades, includes several enhancements in PostgreSQL 18, such as faster upgrades when a database contains many objects like tables and sequences. 

This release also lets pg_upgrade process its checks in parallel based on the settings of the --jobs flag, and adds the --swap flag that swaps upgrade directories instead of copying, cloning, or linking files.

Query and general performance enhancements

PostgreSQL 18 further accelerates query performance with features that automatically make your workloads faster. This release introduces "skip scan" lookups on multicolumn B-tree indexes that improve execution time for queries that omit an = condition on one or more prefix index columns. It can also optimize queries that use OR conditions in a WHERE to use an index, leading to significantly faster execution. There are also numerous improvements for how PostgreSQL plans and executes table joins, from boosting the performance of hash joins to allowing merge joins to use incremental sorts. PostgreSQL 18 also supports parallel builds for GIN indexes, joining B-tree and BRIN indexes in supporting this capability.

This release also builds on PostgreSQL support for hardware acceleration, including support for ARM NEON and SVE CPU intrinsics for the popcount function, which is used by the bit_count and other internal capabilities.

Enhancing the developer experience

PostgreSQL 18 introduces virtual generated columns that compute values at query time instead of storing them. This is now the default option for generated columns. Additionally, stored generated columns can now be logically replicated.

This release adds the capability to access both the previous (OLD) and current (NEW) values in the RETURNING clause for INSERTUPDATEDELETE and MERGE commands. PostgreSQL 18 also adds UUIDv7 generation through the uuidv7() function, letting you generate random UUIDs that are timestamp-ordered to support better caching strategies. PostgreSQL 18 includes uuidv4() as an alias for gen_random_uuid().

PostgreSQL 18 adds temporal constraints -- constraints over ranges -- for both PRIMARY KEY and UNIQUE constraints using the WITHOUT OVERLAPS clause, and on FOREIGN KEY constraints using the PERIOD clause.

Finally, PostgreSQL 18 makes it easier to create the schema definition of a foreign table using the definition of a local table with the CREATE FOREIGN TABLE ... LIKE command.

Authentication and security features

PostgreSQL 18 introduces oauth authentication, which lets users authenticate using OAuth 2.0 mechanisms supported through PostgreSQL extensions. Additionally, PostgreSQL 18 includes validation for FIPS mode, and adds the ssl_tls13_ciphers parameter for configuring server-side TLS v1.3 cipher suites.

This release deprecates md5 password authentication, which will be removed in a future release. If you require PostgreSQL password-based authentication, use SCRAM authentication. PostgreSQL 18 also supports SCRAM passthrough authentication with both postgres_fdw and dblink for authenticating to remote PostgreSQL instances. Additionally, pgcrypto now supports SHA-2 encryption for password hashing.

Replication

PostgreSQL 18 supports reporting logical replication write conflicts in logs and in the pg_stat_subscription_stats view. Additionally, CREATE SUBSCRIPTION now defaults to using parallel streaming for applying transactions, which can help improve performance. The pg_createsubscriber utility now has an --all flag so you can create logical replicas for all databases in an instance with a single command. PostgreSQL 18 also lets you automatically drop idle replication slots to help prevent storing too many write-ahead log files on a publisher.

Maintenance and observability

PostgreSQL 18 improves its vacuum strategy by proactively freezing more pages during regular vacuums, reducing overhead and helping in situations that require aggressive vacuums.

PostgreSQL 18 adds more details to EXPLAIN, which provides information about query plan execution, and as of this release now automatically shows how many buffers (the fundamental unit of data storage) are accessed when executing EXPLAIN ANALYZE. Additionally, EXPLAIN ANALYZE now shows how many index lookups occur during an index scan, and EXPLAIN ANALYZE VERBOSE includes CPU, WAL, and average read statistics. PostgreSQL 18 includes more info in pg_stat_all_tables on time spent on vacuum and related operations, as well as per-connection statistics on I/O and WAL utilization.

Other notable changes

Databases initialized with PostgreSQL 18 initdb now have page checksums enabled by default. This can affect upgrades from non-checksum enabled clusters, which would require you to create a new PostgreSQL 18 cluster with the --no-data-checksums option when using pg_upgrade.


PostgreSQL 18 also introduces a new version (3.2) of the PostgreSQL wire protocol, the first new protocol version since PostgreSQL 7.4 (2003). libpq still uses version 3.0 by default while clients (e.g., drivers, poolers, proxies) add support for the new protocol version.


Please read more on their following post:

https://www.postgresql.org/about/news/postgresql-18-released-3142/

Java™ SE Development Kit 25

JDK 25

JDK 25 reached General Availability on 16 September 2025. 

Production-ready binaries under the GPL are available from Oracle

JDK 25 is a long-term support (LTS) release from most vendors. For a complete list of the JEPs integrated since the previous LTS release, JDK 21, please see here.

Binaries from openJDK are available here:

https://jdk.java.net/25/

https://openjdk.org/projects/jdk/25/

Release notes from Oracle

https://www.oracle.com/java/technologies/javase/25-relnote-issues.html


🚀 What JDK 25 brings

Major new additions / enhancements:

  • Compact Object Headers (JEP 519): reduces object header size for many objects on 64-bit platforms → lower memory and better heap density. Java Code Geeks+1

  • Scoped Values (JEP 506): a safer/more efficient alternative to ThreadLocal for context propagation, especially with virtual threads. Java Tech Online+1

  • Flexible Constructor Bodies (JEP 513): allows code before super()/this() in constructors. HappyCoders.eu

  • Compact Source Files & Instance Main Methods (JEP 512): lets you write simpler top-level code without class boilerplate (good for learning, quick scripts). Java Tech Online

  • Primitive Types in Patterns (JEP 507, preview): pattern matching now supports primitives (int, double, etc.). Baeldung on Kotlin+1

  • Performance & runtime enhancements:

    • Generational Shenandoah GC (JEP 521) becomes supported. Java Code Geeks

    • JDK Flight Recorder (JFR) improvements: better CPU-time profiling, method timing & tracing. Java Tech Online+1

  • Security / cryptography: Key Derivation Function API (JEP 510) finalised to support modern cryptograpic workflows. JDK Builds

  • Module import declarations (JEP 511): easier modular code reuse/imports. Java Tech Online

  • JDK 25 is also an LTS release. OpenJDK+1

What this means for you:

  • Significant runtime and memory improvements: if you manage large scale Java services you’ll likely benefit from Compact Object Headers, improved GC, and profiling tools.

  • More expressive language features continue to expand.

  • Better support for modern concurrency/context propagation (via Scoped Values) which ties into virtual threads.

  • If you build frameworks or libraries, features like Module Import Declarations may reduce boilerplate for users.

  • The migration path from 21 → 25 is relevant because many new features are production-ready (no longer preview) so you may want to plan early.


📋 Side-by-side comparison

CategoryJDK 21JDK 25
StatusLTS (Sep 2023)LTS (Sep 2025)
Major concurrency additionVirtual threads finalised HowToDoInJava+1Scoped Values finalised; further concurrency ecosystem improvements Java Code Geeks+1
Language expressivenessRecord patterns, switch pattern matching, sequenced collections Baeldung on KotlinAdds flexible constructors, primitive types in patterns (preview), compact source files Java Tech Online
Performance / runtimeImproved JVM generally, new APIsCompact object headers, generational Shenandoah GC, better profiling tools Java Code Geeks
Cryptography/securityKEM API introduced InfoWorldKey Derivation Function API final, better security readiness JDK Builds
Library & toolingGood improvementsModule import declarations, further enhancements in tooling and observability Java Tech Online
Preview features statusMany preview (string templates, unnamed classes) Baeldung on KotlinSome features still preview/incubator (primitive types in patterns) Java Tech Online
Migration / production readinessVery production-ready at releaseAlready production-ready for many features, but some still in preview – evaluate accordingly

Anthropic introducing Claude Sonnet 4.5 & Claude Haiku 4.5

Claude Haiku 4.5 gives users a new option for when they want near-frontier performance with much greater cost-efficiency. For example, Sonnet 4.5 can break down a complex problem into multi-step plans, then orchestrate a team of multiple Haiku 4.5s to complete subtasks in parallel.

https://www.anthropic.com/news/claude-haiku-4-5

benchmark link



Anthropic introducing Claude Sonnet 4.5

Claude Sonnet 4.5 is the best coding model in the world. It's the strongest model for building complex agents. It’s the best model at using computers. And it shows substantial gains in reasoning and math.

In Claude Code, Anthropic added checkpoints—one of our most requested features—that save your progress and allow you to roll back instantly to a previous state. We've refreshed the terminal interface and shipped a native VS Code extensionAnthropic added a new context editing feature and memory tool to the Claude API that lets agents run even longer and handle even greater complexity. In the Claude apps, we've brought code execution and file creation (spreadsheets, slides, and documents) directly into the conversation. And we've made the Claude for Chrome extension available to Max users who joined the waitlist last month.

They also giving developers the building blocks they uses themselves to make Claude Code. Anthropic calling this the Claude Agent SDK. The infrastructure that powers our frontier products—and allows them to reach their full potential—is now yours to build with.


see more on Anthropic following post:

https://www.anthropic.com/news/claude-sonnet-4-5


The Claude Agent SDK

Anthropic spent more than six months shipping updates to Claude Code, so they know what it takes to build and design AI agents. According to Anthropic They solved hard problems: how agents should manage memory across long-running tasks, how to handle permission systems that balance autonomy with user control, and how to coordinate subagents working toward a shared goal.

The Engine and The Network: How NVIDIA's New Hardware Is Powering the AI Future and 6G

  The Engine and The Network: How NVIDIA's New Hardware Is Powering the AI Future and 6G The era of simply training bigger AI models is ...