Mark your calendars, Hollow Knight: Silksong fans! The latest patch is here, and it’s bringing some major improvements that you won’t want to miss. The game’s Steam public beta branch has just been updated to Patch 1.0.28954, and it’s all about making the gaming experience better for everyone, especially our Chinese-speaking friends.

You might remember that the initial Simplified Chinese translation wasn’t exactly a hit with players. Some even joked that it read like a Wuxia novel! Well, Team Cherry heard your feedback, and they’ve been working hard to make things right. The new patch introduces a work-in-progress Simplified Chinese translation that’s set to replace the old one. But remember, this is just the beginning. Team Cherry is encouraging all Chinese-speaking players to share their thoughts on the new translation – whether it’s about clarity, style, or anything else – via the game’s bug report form.

But that’s not all, folks! This patch also brings a bunch of other fixes to make your gaming experience even smoother. Here’s what you can expect:

– Improved Controller Support: The team has switched to Unity’s Input System, which means better controller support and working rumble features for various controllers. Plus, more controllers will be recognized, so you can game your way!
– Bug Fixes Galore: From Styx not giving rosaries to Hornet’s plasmified state clearing at the wrong times, Team Cherry has been busy squashing those pesky bugs.
– Tweaks and More Tweaks: The team has been making smaller tweaks and fixes all around the game to make sure everything runs as smoothly as possible.

So, what are you waiting for? Dive back into the world of Hollow Knight: Silksong and enjoy the improved gaming experience! And remember, your feedback is crucial, so don’t hesitate to share it with Team Cherry. Happy gaming!

Hoover HW3 Wet and Dry Vacuum: Two-Minute Review

Looking for a budget-friendly wet-dry vacuum that packs a punch? The Hoover HW3 is here to save the day! This nifty little machine delivers impressive cleaning power at a price that won’t break the bank. Designed for hard floors, it combines a wet roller to scrub away dirt with powerful suction to pull up solid debris.

On test, the Hoover HW3 tackled spillages of all kinds with ease. From soy sauce to dry cereal, oats, and even sticky Marmite spread, it wiped and sucked away mess with minimal effort. Its battery life is on par with the rest of the market, maneuverability is good, and the self-clean mode takes care of everyday maintenance.

Now, the design of the water tanks could use a bit of improvement – filling the clean one can be a bit fiddly, and both tanks occasionally failed to clip in properly. But these are minor nit-picks in an otherwise stellar performer.

So, should you buy the Hoover HW3 wet-dry vacuum?

If you’re on a budget and looking for a wet-dry vacuum that ticks all the boxes for everyday cleaning, the Hoover HW3 is a no-brainer. It’s affordable, effective, and a great choice for the average household.

However, if you’re dealing with hardcore cleaning needs, like grease, you might want to consider investing in a pricier model with more advanced features like hot water self-cleaning or steam functions.

Hoover HW3 Review: Price & Availability

List price: £249
Launched: August 2025
Available: UK

The Hoover HW3 launched in summer 2025 and is available in the UK direct from Hoover, as well as via various third-party retailers such as Currys and John Lewis. At the time of writing, it was widely discounted to £199.

Even at full price, that’s extremely affordable for a wet-dry vacuum. Pricier models offer features such as dirt detection and hot water in the self-clean cycle, but in terms of the basics, you’re more than covered here.

For a slightly higher price, you could pick up a Shark HydroVac Cordless, which offers a similar feature-set but also comes with a “Freshen mode” for area rugs. At the premium end of the market, there are models like the Tineco Floor One S7 Pro and Dyson WashG1, which offer additional modes and features, but at a significantly higher price point.

Value for money score: 4.5 out of 5

Hoover HW3 Specs

– Type: Cordless wet-and-dry vacuum (corded also available)
– Cleaner size (H x L x W): 44.5 x 10.6 x 9.4in / 113 x 27 x 24cm
– Weight (empty): Confirming
– Clean water tank volume: 0.55L
– Dirty water tank volume: 0.55L
– Max runtime: 40mins
– Recharge time: 4hrs 30mins
– Suction power: 16,000Pa
– Modes: Vacuum only, vacuum+mop, Max
– Self-clean cycle: Yes, cold water and cold air

Hoover HW3 Wet and Dry Vacuum Review: Design

The Hoover HW3 is a cordless wet-dry cleaner with button controls and a screen for info. It has two main modes: vacuum-and-mop and vacuum-only, plus a Max mode for extra suction. The self-clean function uses cold water and cool air.

Controls are positioned on the top of the handle, within easy reach while cleaning. There are three buttons: On/Off, Max, and a third button for switching modes. A secret fourth button sits on the bottom corner of the handle for launching the self-clean cycle.

A screen on top of the motor section displays battery life and troubleshooting icons. The clean and dirty water tanks clip to the front and back of the machine, but the design could be improved for easier filling and clipping.

Design score: 4 out of 5

Hoover HW3 Wet and Dry Vacuum Review: Performance

The Hoover HW3 excels at cleaning solid and liquid spills, even sticky stains like Marmite. It’s simple but effective to use, with clear verbal and visual cues. Setup was a bit of a trial and error due to unclear instructions, but once up and running, the vacuum performed exceptionally well.

It propels itself forwards when switched on, making it easy to drive, and maneuvers well around furniture. The mopping was even and left a light sheen of water that dried within around five minutes. The self-clean mode is solid, using cold water and cool air to clean and dry the roller.

Performance score: 4 out of 5

Hoover HW3 Review: Battery Life

The Hoover HW3 promises 40 minutes of cleaning on a single charge in standard vac-mop mode, and my tests confirmed this figure. It’s in line with the wet-dry competition, but the recharge period is long at four and a half hours.

Battery life score: 4 out of 5

So, if you’re in the market for a budget-friendly wet-dry vacuum that cleans like a pro, the Hoover HW3 should be at the top of your list. It’s affordable, effective, and a great choice for the average household. Happy cleaning!

The Samsung Galaxy S26 Pro might just be a letdown for photography enthusiasts. According to the latest leak from reliable source Erencan Yilmaz (via NotebookCheck), the ‘Pro’ model seems to be sticking with the same camera setup as its predecessors. Here’s what we know so far:

📸 Same Old, Same Old: The Galaxy S26 Pro is rumored to sport the same 50MP ISOCELL GN3 sensor for its main camera as the Galaxy S25, which has been around since the Galaxy S22. The telephoto camera (10MP S5K3K1) and ultra-wide lens (12MP IMX564) are also carryovers from the S22 series, and the front-facing camera (12MP S5K3LU) hasn’t changed since the S23.

💥 Battery Boost, But… The leak suggests a 4,300mAh battery, which is a step up from the S25’s 4,000mAh. But the potential Exynos 2600 chipset might not be as powerful as the Snapdragon 8 Elite Gen 5 expected in other 2026 flagships. US buyers might get the Snapdragon version, though.

📅 Mark Your Calendars: We’ll find out more in January or February. But with these uninspiring leaks and rumors of the Galaxy S26 Edge’s cancellation, 2026 might not be Samsung’s shining year.

Stay tuned to TechRadar for more updates! And while you’re at it, follow us on Google News, TikTok, and sign up for our WhatsApp updates for all things tech.

💡 Vibe Coding: The New Kid on the Block
Vibe coding is the latest buzz in software development. It’s a fun, fast way to use generative AI to sketch out an app idea and whip up a prototype in minutes. But here’s the thing: while it’s great for app development, it’s just the tip of the iceberg for businesses.

Why Vibe Coding Isn’t Enough
Vibe coding can help you build an app, but it won’t help you rethink your business, reimagine how work gets done, or scale transformation across your enterprise. That’s where vibe transformation comes in.

🌟 Introducing Vibe Transformation
Vibe transformation is when you start with a clear business outcome you want to achieve, then use generative AI tools to deliver on that outcome through full-blown business reinvention. It’s not about generating code; it’s about redesigning your apps and processes to operate faster, deliver better experiences, and adapt on the fly.

How Vibe Transformation Works
1. You import documents, videos, and specs detailing your requirements or legacy apps you want to replace.
2. The platform combines your descriptions with industry best practices to deliver a vision of what your workflows and customer engagement should look like.
3. You get a working prototype to test drive and refine.

Why Vibe Transformation is Game-Changing
Vibe transformation bridges the gap between strategy and execution. It rapidly turns business objectives into prototypes, fostering faster alignment and innovation across the organization.

🚧 Why Vibe Coding Alone Falls Short
For complex enterprise apps, vibe coding hits limits quickly. It can’t handle the complexity of compliance, security, or data governance. It can’t anticipate how changes might ripple across systems or customer journeys.

🏢 Vibe Transformation: Built for Enterprise
Vibe transformation brings structure and scale to app development. It combines the creativity of generative AI with the guardrails of enterprise-grade platforms. It generates systems that are resilient, secure, and ready for what’s next.

💡 The Bottom Line
AI isn’t just changing how we code; it’s enabling us to reimagine business. The real opportunity isn’t vibe coding; it’s vibe transformation. It’s where the energy of generative AI meets the rigor of enterprise process and application design to drive real, resilient change.

🚨 Breaking News! 🚨 Over 40 billion records, including sensitive emails and banking notices, were left exposed online, leaving millions of people vulnerable. Here’s what we know so far:

The Big Picture:
– Security researcher Jeremiah Fowler stumbled upon a massive, unsecured database belonging to Indian marketing giant Netcore Cloud Pvt. Ltd.
– The database, weighing a whopping 13 terabytes, was left open without any password protection, allowing anyone with an internet connection to access it.

What Was Exposed?
Fowler found a treasure trove of sensitive information, including:
– Emails and IP addresses
– Banking activity notices
– Employment-related messages and account verification emails
– Marketing messages and healthcare notifications
– Partial account numbers and records marked as ‘confidential’

The Company Behind the Breach:
Netcore is a major player in the marketing scene, providing cloud-based tools for businesses to communicate with customers across various digital channels. With offices worldwide, they serve over 6,500 customers, including big names like Flipkart, Disney Hotstar, and McDonald’s.

What Happened Next?
Fowler reached out to Netcore, and they swiftly secured the database. However, it’s still unknown how long the data was exposed or if any malicious actors accessed it before Fowler did.

Stay Informed:
– Keep an eye on our tech news for more updates on this story.
– For tips on protecting your digital identity, check out our guide to the best authenticator apps and password managers.

Ever wished you could effortlessly convert complex, multilingual documents—packed with dense layouts, tiny scripts, formulas, charts, and handwriting—into clean, structured Markdown or JSON? Baidu’s PaddlePaddle team has just made that wish a reality with their latest release, PaddleOCR-VL (0.9B), a vision-language model designed for end-to-end document parsing across various elements, supporting a whopping 109 languages.

How does it work, you ask?

PaddleOCR-VL operates in two stages. First, PP-DocLayoutV2 performs page-level layout analysis, identifying and categorizing regions, and predicting reading order. Then, PaddleOCR-VL-0.9B takes over, recognizing elements based on the detected layout. The final outputs are aggregated into easy-to-use Markdown and JSON formats.

At its core, PaddleOCR-VL-0.9B combines a NaViT-style (Native-resolution ViT) dynamic-resolution vision encoder with the ERNIE-4.5-0.3B language model. This innovative setup allows it to handle dense, multi-column, mixed text-graphic pages with lower latency and memory usage, making it perfect for real-world deployments.

But how does it perform?

PaddleOCR-VL achieves state-of-the-art results on OmniDocBench v1.5 and competitive or leading scores on v1.0, covering overall quality and sub-tasks. It also shows complementary strength on other benchmarks, including in-house evaluations for handwriting, tables, formulas, and charts.

Why should you care?

This release is a game-changer because it merges a NaViT-style dynamic-resolution visual encoder with the lightweight ERNIE-4.5-0.3B decoder, delivering state-of-the-art page-level document parsing and element-level recognition at practical inference costs. It supports 109 languages, including small scripts and complex page layouts, making it a powerful tool for document intelligence across the globe.

Ready to dive in?

Check out the Technical Paper, Model on Hugging Face, and Technical details. For hands-on resources, head over to the GitHub Page for Tutorials, Codes, and Notebooks. Stay updated by following them on Twitter, joining their 100k+ ML SubReddit, subscribing to their Newsletter, and even joining them on Telegram!

In a groundbreaking move, a joint team from Google Research, Google DeepMind, and Yale has unveiled C2S-Scale 27B, a revolutionary 27-billion-parameter foundation model for single-cell analysis, built on the Gemma-2 platform. This model transforms complex single-cell RNA-seq (scRNA-seq) profiles into “cell sentences”—ordered lists of gene symbols—that language models can understand and parse.

Here’s what makes C2S-Scale 27B a game-changer:

1. Understanding the Model: C2S-Scale converts high-dimensional expression vectors into text by ranking genes and emitting the top-K symbols as a gene-name sequence. This representation aligns single-cell data with standard LLM toolchains, enabling tasks like cell-type prediction, tissue classification, and biological Q&A to be phrased as text prompts and completions.

2. Training and Release: C2S-Scale-Gemma-2-27B is built on Gemma-2 27B (decoder-only Transformer), trained on Google TPU v5, and released under CC-BY-4.0. The training corpus aggregates over 800 public scRNA-seq datasets spanning 57 million cells (human and mouse) with associated metadata and textual context.

3. The Key Result: An Interferon-Conditional Amplifier – The research team found a compound, silmitasertib (CK2 inhibitor), that boosts antigen presentation (MHC-I program) only in immune-context-positive settings—i.e., primary patient samples with low interferon tone—while having negligible effect in immune-context-neutral cell-line data. In lab tests, the combination of silmitasertib and low-dose interferon produced a marked, synergistic increase in antigen presentation (≈50% in their assays).

4. Key Takeaways:
– C2S-Scale 27B (Gemma-2) encodes scRNA-seq profiles as textual “cell sentences,” enabling LLM-native single-cell analysis workflows.
– In a two-context virtual screen (>4,000 compounds), the model predicted an interferon-conditional amplifier: CK2 inhibition (silmitasertib) boosts MHC-I antigen-presentation only with low-dose IFN.
– Wet-lab tests confirmed the prediction, with ~50% antigen-presentation increase for silmitasertib+IFN versus either alone.

5. Editorial Comments: C2S-Scale 27B is a significant step for LLMs in biology, enabling text-native screening across thousands of compounds to propose context-dependent pathways that may convert immune-“cold” tumors toward visibility. However, all evidence is preclinical and bench-scale, so consider it “hypothesis-generating AI” for now.

Check out the Technical Paper, Model on Hugging Face, GitHub Page, and Technical details. For tutorials, codes, and notebooks, visit our GitHub Page. Follow us on Twitter, join our 100k+ ML SubReddit, subscribe to our Newsletter, and join us on Telegram for more updates!

Ever thought about how much thought we give to cables when setting up our home cinema? Yeah, me neither. I mean, as long as they support our fancy tech, who cares, right? Wrong! I’m here to tell you how some affordable HDMI cables turned my home cinema from ‘good’ to ‘wow’!

I’ve got a pretty sweet setup – an 83-inch LG G5 OLED TV and a full Sonos speaker package. We’re talking Arc Ultra, Era 300s for surrounds, Sub 3, and even some Era 100s. But here’s the thing, no matter how great your tech is, ugly cables can ruin the vibe. I’m talking about those sneaky HDMI cables hanging down behind the screen, snaking their way into the TV bench. They were killing my floating TV illusion!

Enter: the humble HDMI cable. I picked up a couple of 3-meter Ugreen HDMI 2.1 cables during a Prime Day sale for just AU$22 each. They arrived, I got to work, and let me tell you, LG’s cable management system is a game changer! With the extra length, I was able to run the cables through the TV stand, up through cut outs, along the rear panel, and into the HDMI ports. Voila! No more dangling cables, just a sleek, floating TV.

And the best part? This simple upgrade cost me less than $24 / £28 / AU$44. So, if you’re looking to take your home cinema to the next level, don’t overlook the power of a good cable. Your space (and your eyes) will thank you!

🚀 Why Traditional AI Testing Isn’t Enough

Agentic AI systems, those that act and make decisions, are complex beasts. They’re unpredictable, context-dependent, and bound by policies. Current quality assurance methods—like unit tests or simple prompts—just don’t cut it. They can’t expose multi-turn vulnerabilities or provide solid audit trails. Developer teams need more: realistic conversations, explicit policy checks, and machine-readable evidence to confidently release their AI agents.

🌟 Introducing Rogue – The AI Testing Revolution

Qualifire AI has just open-sourced Rogue, a Python framework that evaluates AI agents over the Agent-to-Agent (A2A) protocol. Rogue transforms business policies into executable scenarios, engages in multi-turn interactions with target agents, and generates deterministic reports perfect for CI/CD and compliance reviews.

💻 Getting Started with Rogue

Prerequisites:
– `uvx` (install using `uv` installation guide if not already installed)
– Python 3.10+
– An API key for an LLM provider (e.g., OpenAI, Google, Anthropic)

Installation:
– Quick Install (Recommended):
“`
# TUI
uvx rogue-ai
# Web UI
uvx rogue-ai ui
# CLI / CI/CD
uvx rogue-ai cli
“`
– Manual Installation:
1. Clone the repository:
“`
git clone https://github.com/qualifire-dev/rogue.git
cd rogue
“`
2. Install dependencies using `uv sync` or `pip install -e .`
3. Optionally: Set up your environment variables in a `.env` file.

Running Rogue
Rogue works on a client-server architecture. The default behavior starts the Rogue server in the background and launches the Terminal User Interface (TUI) client. You can also run specific modes like Server, TUI, Web UI, or CLI.

Example: Testing the T-Shirt Store Agent
Rogue comes with a simple example agent that sells T-shirts. You can use it to see Rogue in action. Here’s how:

1. Install example dependencies using `uv sync –group examples` or `pip install -e .[examples]`.
2. Start the example agent server in a separate terminal.
3. Configure Rogue in the UI to point to the example agent.
4. Run the evaluation using either the TUI or Web UI mode.

Where Rogue Fits: Practical Use Cases
– Safety & Compliance: Validate data handling, refusal behavior, and secret-leak prevention.
– E-Commerce & Support: Enforce discounts, refund rules, and tool-use correctness.
– Developer/DevOps: Assess code-mod and CLI copilots for workspace confinement and unsafe command prevention.
– Multi-Agent Systems: Verify planner-executor contracts and interoperability.
– Regression & Drift Monitoring: Detect behavioral drift and enforce policy-critical pass criteria.

What is Rogue, and Why Should Agent Dev Teams Care?
Rogue is an end-to-end testing framework that evaluates AI agents’ performance, compliance, and reliability. It turns business context and risk into structured tests with clear objectives and success criteria. Rogue provides streaming observability and deterministic artifacts, making it an invaluable tool for agent development teams.

Under the Hood: How Rogue Is Built
Rogue operates on a client-server architecture, with multiple interfaces connecting to the core evaluation logic running in the backend server.

Summary
Rogue helps developer teams test agent behavior as it runs in production. It turns written policies into concrete scenarios, exercises those scenarios over A2A, and records what happened with transcripts you can audit. The result is a clear, repeatable signal you can use in CI/CD to catch policy breaks and regressions before they ship.

Find Rogue on GitHub
Thanks to the Qualifire team for their thought leadership and support in creating this article.