AI video generators in 2026 allow anyone to create high-quality videos from text prompts, images, or scripts in just minutes.
This guide explains how the technology works, compares the leading tools on the market, and highlights their strengths, limitations, and best use cases to help you choose the right solution for your creative or business needs.
After the unexpected divorce between LeCun and Meta, there is a lot of talk that the dead-end in LLM progress will be overcome through the physics of the world. That is, having a neural network work with physical data from the surrounding environment will allow the model to acquire meaning and an understanding of its actions. LeCun has a foundational paper that nobody is going to read. So, I'll summarize it as best I can. Essentially, the idea is that the current trajectory of LLM development is doomed. As long as they are predicting the next token, real understanding — the emergence of real meaning — is impossible. LeCun proposes training neural networks on physical world data, assuming that building a model of it will allow the system to discard details and focus on meaning.
I agree with LeCun that using world data will partially solve the data scarcity problem. But here I see a problem that engineers might not understand. A physical model of the world is actually much poorer than human knowledge. Newton described the entire infinite number of possible falls with a few lines of formulas. I doubt LeCun wants to spend billions of dollars on this wonderful deduction.
This article reviews the November 2025 CommitFest.
For the highlights of the previous two CommitFests, check out our last posts: 2025-07, 2025-09.
Planner: eager aggregation
Converting COUNT(1) and COUNT(not_null_col) to COUNT(*)
Parallel TID Range Scan
COPY … TO with partitioned tables
New function error_on_null
Planner support functions for optimizing set-returning functions (SRF)
SQL-standard style functions with temporary objects
BRIN indexes: using the read stream interface for vacuuming
WAIT FOR: waiting for synchronization between replica and primary
Logical replication of sequences
pg_stat_replication_slots: a counter for memory limit exceeds during logical decoding
pg_buffercache: buffer distribution across OS pages
pg_buffercache: marking buffers as dirty
Statistics reset time for individual relations and functions
Monitoring the volume of full page images written to WAL
New parameter log_autoanalyze_min_duration
psql: search path in the prompt
psql: displaying boolean values
pg_rewind: skip copying WAL segments already present on the target server
pgbench: continue running after SQL command errors
In the IT crowd, it’s common to mock HR for their weird terminology and attempts to assess a “rich inner world” instead of clean code. But when a senior starts tearing juniors apart in code reviews to the point where they end up crying in the bathroom, nobody’s laughing anymore.
We pit two archetypes against each other: the “toxic genius” and the “human glue”. Which one is dead weight, and which one is the load-bearing structure of the project? You might not like the answer.
Hey, Habr! Ivan Glinkin is here again, head of the hardware research group from the Bastion team.
"A flash drive with a combination lock," "a flash drive with hardware encryption," "an encrypted USB drive," and finally, the proper term — "Cryptographic Module". An encrypted USB flash drive goes by many names, but the core concept remains the same.
The purpose of such a device is to protect sensitive information from unauthorized access at both the software and hardware levels through encryption, anti-tampering mechanisms, and various other safeguards. But are these secure USB drives really as reliable as they're made out to be, or is it all just smoke and mirrors?
We decided to look past the marketing claims and conduct our own investigation, attempting to crack several of these devices using hardware reverse engineering. We attempted to extract data, identify the encryption algorithms used, physically open the drives, and read their memory chips.
The results were quite interesting. Read on for the details.
Imagine having a personal AI agent running on your computer. It can read files, run commands, automate tasks, and remember your workflows. In this guide, you will learn how to run OpenClaw with Ollama locally and choose the best local LLM models.
This article is not about Puppeteer being a bad tool. Puppeteer is excellent. And competent TLS fingerprinting will bypass most defenses. But there is a class of tasks where even a perfect network stack won't save you — because detection has long since landed at the level of rendering engine behavior. Let's take a look at how Cloudflare and Akamai expose you through WebGL and Canvas, and why “clean” code no longer works.
There are things in the IT industry whose even existence has become a beautiful myth.
The knowledge described in this article is extremely rare, as it has previously been held by individuals with an academic degree, special training, and, most importantly, access to the necessary equipment.
I recorded a short video showing how to build a complete feature using Claude Code Agent Teams. Even if you're not using Agent Teams, the general approach still applies, making this a useful watch for anyone getting started with Claude Code or curious about this new experimental feature. In the video, I set up an "umbrella" project that brings together two repositories and multiple components: a Java App built with Google ADK (Spring Boot), a Front End App, and a Command Line utility. As part of the demo, the utility is extended with an "api" command that exposes it via the AG-UI protocol, allowing clients to connect to it directly.
Link to the video https://youtu.be/FekjxvNSpyg in the case embed does not work.
Since there are so many great command line AI assistants, including the marvellous Opencode, I thought I was going to stop developing Gaunt Sloth. However, because I control the code and it is so small and LangChain.js-based, I still find myself reaching for it regularly for quick prototypes and other tasks.
https://github.com/Galvanized-Pukeko/gaunt-sloth-assistant/
The last thing I needed was to use it with a very minimal system prompt and without any vendor-provided defaults, so here comes a new config parameter: noDefaultPrompts. This enforces no fallback to default system prompts, which means if your project config does not define a system prompt, it will be completely blank.
Example config
{
"llm": {
"type": "groq",
"model": "openai/gpt-oss-120b"
},
"noDefaultPrompts": true
}
Another new feature, introduced for experiments, is the api command, which currently supports the AG-UI protocol. Calling gsloth api ag-ui will make Gaunt Sloth listen for incoming connections.
{
"llm": {
"type": "openai",
"model": "gpt-4o-mini"
},
"streamOutput": true,
"commands": {
"api": {
"port": 3000,
"cors": {
"allowOrigin": "http://localhost:5555",
"allowMethods": "POST, GET, OPTIONS",
"allowHeaders": "Content-Type, Accept"
}
}
}
}A client implementation and demo setup are available at the link below. https://github.com/Galvanized-Pukeko/galvanized-pukeko-ai-ui
How we transformed stressful manual releases into a dependable, one-click process using GitOps and automation. 50+ modules, auditors and regulators—in a single template that scaled across more than 30 services. No magic, an engineering discipline.
Hello, fellow developers!
Anyone who designs multilayer printed circuit boards in KiCad has faced the need, during routing, to leave large areas free of copper polygons (whether connected to nets or not) for schematic or other reasons. On outer layers, this isn't a big problem. On inner layers, it's a bit different. While it might be fine from a topology perspective, it's not ideal from a manufacturing point of view.
Today, we want to share a plugin we developed to solve this problem. It's a tool for automatically filling free areas on a PCB with non-current-carrying copper elements, either square or round, of a configurable size.
Why is this needed?
At first glance, an empty area on a board is just bare laminate without copper. But for the manufacturer and the end-user of the device, this has two important consequences.
Your service has just published a message to RabbitMQ — and then, right at commit time, the database transaction rolls back. The classic distributed-systems nightmare: ghost data, broken consistency, and hours lost to debugging. Usually you fight this with tricky custom code, two-phase commits, or just… crossing your fingers. But what if a PostgreSQL rollback could automatically “roll back” the message too, putting it back into the queue without you writing a single extra line? Here’s how that works.
Every prompt is a gamble. Your AI writes code that compiles, looks right, and silently breaks things you already built. Tests catch it before your users do. The best part? Your AI can write the tests for you.
~206 символов. Добавил "compiles, looks right" из A для конкретики, убрал "And here's the thing" на более кликбейтное "The best part?".
Добавить в начало статьи?
Design documentation is a crucial part of the UX workflow that unfortunately often gets looked upon as something not worthy of wasting time and effort on. Meanwhile, it is the most trustworthy way of bringing order to the process and sharing all the details about the product development with everyone involved. Basically, it is a set of documents that record all the steps, details, descriptions and explanations of every action and decision taken and performed while creating the product.
Let’s discuss its goals, components and ways of effective integration into the typical UX design workflow.
Before creating our future messenger, we need to decide on the technology we'll use for its development. Among web development tools for single-page applications (SPAs), Angular and React are clear favorites. I won't dwell on the advantages of each of these tools, but will focus on Angular, as I've previously conducted research on non-classical virtualized lists and found that it handles this task better than React.
In this article, our team shares how artificial intelligence and modern analytics tools have shaped the way our projects are built, tested, and optimized — from code to player experience.
Artificial intelligence isn’t just hype for us — it’s a practical, everyday part of how we build and improve our projects. AI empowers us to accelerate development, improve reliability, personalize experiences, and make smarter decisions based on real player behavior. Below, we walk through how AI is integrated into key parts of our platform.
We continue our series of articles reviewing changes in PostgreSQL 19. This time we'll look at what emerged from the September 2025 CommitFest.
The highlights from the first July CommitFest are available here: 2025-07.
GROUP BY ALL
Window functions: NULL value handling
Event triggers in PL/Python
More precise error message for incorrect routine parameter names
random: random date/time within a specified range
base64url format for encode and decode functions
New debug_print_raw_parse parameter
The log_lock_waits parameter is now enabled by default
pg_stat_progress_basebackup: backup type
vacuumdb: collecting statistics on partitioned tables
Buffer cache: using clock-sweep algorithm to find free buffers
Fake table aliases in queries
We're launching a new series of articles covering the changes coming up in PostgreSQL 19. This first article focuses on the events from last summer's July CommitFest.
Connection service file in libpq parameter and psql variable
regdatabase: a type for database identifiers
pg_stat_statements: counters for generic and custom plans
pg_stat_statements: FETCH command normalization
pg_stat_statements: normalizing commands with parameter lists in IN clauses
EXPLAIN: Memoize node estimates
btree_gin: comparison operators for integer types
pg_upgrade: optimized migration of large objects
Optimized temporary table truncation
Planner: incremental sort in Append and MergeAppend nodes
Domain constraint validation no longer blocks DML operations
CHECKPOINT command parameters
COPY FROM: skipping initial rows
pg_dsm_registry_allocations: dynamic shared memory (DSM) usage
Build the project as follows:
This command is for downloading from GitHub: https://github.com/rexglue/rexglue-sdk
Warning: You can download a pre-built .exe file, which will allow you to decompile the game in C++ (but building it is unlikely). Furthermore, versions are updated frequently, and the latest versions (with more instructions) are worth building.
Prepare the necessary directory.
Specify it as REXSDK in the global variables.
Sometimes the project won't compile in x64, so it's worth adding these lines to CMakeList.txt.
Enable Windows developer mode to download the necessary packages.
And in the /thirdparty/libsmpack folder, enter the following commands.
Then the necessary updates for the package will be downloaded.
Try adding additional parameters here. If it doesn't compile, then:
And finish the build:
Testing
To test the tool, use the following commands:
Add it to the assets/default.xex folder (you'll need to create it and add it to the project that rexglue will create).
This video can be useful for installing clang-cl and preparing default.xex from an Xbox 360 ISO image (which was dumped).
The program will display all missing instructions and replace them with placeholders (but it's best to create an issue with the required instructions, and once they're implemented, return to the project).
Don't forget to support the developers with well-deserved stars and share with your friends. Also, subscribe so you don't miss the next part, which will explain how to run the recompiled project.