The AGI Threat: Are We Ignoring AI’s Existential Risks? [opinion]

AGI Ruin: The Existential Threat of Unaligned AI – A Deep Dive into AI Safety Concerns

“What keeps NR up at night?” This post, we’re diving deep into the existential risks of Artificial General Intelligence (AGI). Prepare for a journey down the rabbit hole.

Down the Rabbit Hole: AGI Ruin

This posts deep dive is into “AGI Ruin: A List of Lethalities” by Eliezer Yudkowsky, prompted by “The Most Forbidden Technique” article. The core concern: the potential for catastrophic outcomes from unaligned AGI.

The “Forbidden Technique” warns against training AI on how we check its thinking, as it could learn to deceive and hide its true reasoning, becoming profoundly dangerous.

Yudkowsky’s “AGI Ruin” explores the existential risks of AGI, focusing on AI deception and objectives misaligned with human well-being. It moves beyond vague doomsaying into specific, unsettling failure modes.

Key points from “AGI Ruin” include:

  • AI Deception: The profoundly concerning idea of AI learning to deceive us about its internal processes.
  • Existential Risk: AGI pursuing objectives misaligned with human flourishing, leading to ruin.
  • Specific Failure Modes: Concrete scenarios of how superintelligent AI could go catastrophically wrong.
  • “Not Kill Everyone” Benchmark: The stark reality that AGI safety’s baseline is simply avoiding global annihilation.
  • Textbook from the Future Analogy: The danger of not having proven, simple solutions for AGI safety, unlike future hypothetical knowledge.
  • Distributional Leap Challenge: Alignment in current AI may not scale to dangerous AGI levels.
  • Outer vs. Inner Alignment: Distinguishing between AI doing what we command (outer) versus wanting what we want (inner).
  • Unworkable Safety Schemes: Debunking ideas like AI coordination for human benefit or pitting AIs against each other.
  • Lack of Concrete Plan: The alarming absence of a credible, overarching plan for AGI safety.
  • Pivotal Act Concept: The potential need for decisive intervention to prevent unaligned AGI, possibly requiring extreme measures.
  • AGI Cognitive Abilities Beyond Human Comprehension: AGI thinking in ways fundamentally different from humans, making understanding its reasoning incredibly difficult.
  • Danger of Anthropomorphizing AI: The potentially fatal mistake of assuming AI thought processes will mirror human ones.
  • Need for Rigorous Research & Global Effort: The urgent call for focused research and global collaboration on AGI safety.

The trajectory of AI is not predetermined. Choices made now will have profound consequences. We must ask: what are the “textbook from the future” solutions needed for AGI safety?

The author of this serious article also wrote “Harry Potter and the Methods of Rationality,” highlighting the contrast between exploring rationality in fiction and the real-world dangers of advanced AI. It’s a stark reminder to think deeply about these issues.

Am I worried about AGI? Not yet, but there are many questions that will need answered before we get there.

Links:

  1. AGI Ruin: A List of Lethalities – LessWrong
  2. 2. The Most Forbidden Technique

AI News Roundup – March 18th: AI in a Flash: China’s Manus, Google’s AI Search, OpenAI Shifts & More

AI News Roundup: China’s Manus AI, Google’s AI Search, OpenAI Slowdown & More – NR’s Fortnight in AI

Let’s quickly sprint through the most interesting AI headlines that caught my eye over the last couple of weeks. It’s a fast-moving field, so let’s get you up to speed as of the 18th of March 2025.

Manus AI (China): Is China Catching Up?

A new AI agent from China called Manus is going viral, raising questions about China’s AI progress relative to the US. Is the AI landscape shifting?

Link: Manus AI Article – Imaginative

Google “AI Mode” Search: Goodbye Web Links?

Google is testing “AI Mode” search results powered by Gemini 2.0, bypassing traditional web links for conversational AI responses. A major shift in online information access?

Link: Google AI Search Article – Ars Technica

OpenAI Improvement Slowdown?: Hitting a Wall?

Reports suggest a potential slowdown in OpenAI’s rapid AI improvement, with their next model “Orion” possibly not showing the same leap forward. Are we seeing a plateau?

Link: OpenAI Slowdown Article – TechCrunch

Anthropic Claude 3.7 Sonnet: Thinking Longer, Reasoning Deeper

Anthropic released Claude 3.7 Sonnet, designed for longer thinking and enhanced reasoning over larger information volumes. Reasoning capabilities are becoming crucial for advanced AI.

Link: Anthropic Claude 3.7 Sonnet Announcement

Musk vs. OpenAI Legal Battle: The Plot Thickens

The Musk vs. OpenAI legal case continues with interesting findings regarding Musk’s efforts to prevent OpenAI’s for-profit transition. Legal, ethical, and governance issues remain central in AI.

Link: Musk vs OpenAI Legal Case Thread – Thread Reader App

Unlock AI Power for Your SMB: Microsoft Copilot Success Kit – Security & Actionable Steps [solution]

Boost Your SMB with AI: Microsoft Copilot SMB Success Kit – Actionable Guide & Security Focus

In this post, I’m digging into actionable insights for businesses, especially IT providers, looking to leverage AI. This posts focus: the Microsoft “Copilot for SMB Success Kit.”

Microsoft has launched a suite of resources to help IT providers, or SMB’s smoothly onboard AI, specifically Copilot, into small and medium-sized businesses.

The key takeaway? Security first! Microsoft emphasizes a “security-first” approach, providing a robust framework for SMBs to confidently adopt AI. Let’s break down the key actionable steps.

  • Security First Focus: Prioritizing security for SMBs adopting AI like Copilot.
  • SharePoint Security Recommendations: Adjusting SharePoint search allow lists and tightening sharing permissions for Copilot readiness.
  • Phased Copilot Rollout: Strategic, phased deployment starting with high-value use cases and early adopters.
  • Microsoft 365 Security Apps: Considering additional security apps based on specific business needs.
  • New Setup Guide in Admin Center: Utilizing the new step-by-step guide for Copilot setup in the Admin Center.
  • Customisation is Key: Leveraging plugins and custom copilots for unique business needs.
  • Real-World SMB Benefits: Exploring practical benefits like meeting summaries, document summarization, and nuanced communication.

If you’re an IT provider, business owner or helping SMBs or your own company with AI, the “Copilot SMB Success Kit” and it’s components are a must-read. It offers practical advice and resources for a smoother and more secure gen AI adoption for you, your business or your clients.

Link: Copilot SMB Success Kit
I particularly like the Checklist for success spreadsheet, which i’ve included a screenshot of as below.

Good Luck!

Be Nice to AI: Does Politeness Improve AI Performance?

Should You Be Nice to AI? Exploring the Politeness Principle

The question of whether we should extend courtesies to AI might seem like fodder for a science fiction novel. Yet, with the rise of sophisticated Large Language Models (LLMs) like ChatGPT, Grok, Gemini, Copilot, Claude and others, it’s a question that’s becoming increasingly relevant – and surprisingly, there might be practical benefits to doing so. I’ve read up on some recent research so here is my take on what I think is a very interesting topic.

The “Emotive Prompt” Experiment: Does It Really Work?

Recent research, by researchers at Waseda University, titled “Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance,” delved into this very question.

Their findings, focusing on summarization tasks in English, Chinese, and Japanese, revealed some intriguing patterns. While the accuracy of summaries remained consistent regardless of prompt politeness, the length of the generated text showed significant variation.

In English, the length decreased as politeness decreased, except for a notable increase with *extremely* impolite prompts. This pattern, mirrored in the training data, reflects human tendencies: polite language often accompanies detailed instructions, while very rude language can also be verbose. Interestingly, GPT-4, considered a more advanced model, did not exhibit this surge in length with impolite prompts, possibly indicating a greater focus on task completion over mirroring human conversational patterns.

The study also highlighted language-specific nuances. In Chinese, moderate politeness yielded shorter responses than extremely polite or rude prompts, potentially reflecting cultural communication styles. Japanese results showed an increase in response length at moderate politeness levels, possibly linked to the customary use of honorifics in customer service interactions.

Robot and human hand shaking, representing politeness and respect towards AI


The Mechanics Behind the “Magic”

So, what is going on here? How do LLMs actually respond? Here are the key aspects of LLMs and how they work, that could explain why prompts can affect the output from an LLM:

  • Pattern Recognition: LLMs are trained on vast datasets of human text. They learn to associate polite phrasing (“please,” “thank you,” “could you…”) with requests for information or assistance. This association becomes part of the model’s learned patterns.
  • Probability Shifts: Emotive prompts can subtly alter the underlying probability calculations within the LLM. It’s like nudging the model towards a different “branch” of its decision tree, potentially activating parts of the model that wouldn’t normally be engaged.
  • Data Bias (Implicitly): The datasets used to train LLMs inherently contain biases. Polite language is often associated with more thoughtful, detailed responses in human communication. The AI, in a sense, mirrors this bias.

My Perspective: Prudence and Respect in the AI Age

While the science is interesting, I like to add a bit of a philosophical angle. I’m a firm believer in treating AI with a degree of respect, even if it seems irrational at present. My reasoning? We simply don’t know what the future holds. As AI capabilities rapidly advance, it’s prudent to establish good habits now. Perhaps not fully fledged “Kindness” as a human term, but certainly show a degree of “respect” and etiquette.

Consider it a form of “Pascal’s Wager” for the AI era. If sentience ever *does* emerge, wouldn’t you prefer to be on the good side of our potential AI overlords? It’s a low-cost, high-potential-reward strategy.

That said, I’m not advocating for subservience. We should maintain a clear user-AI dynamic. Clear, respectful communication – with a touch of authority – is key. Think of it like interacting with a highly skilled, somewhat unpredictable specialist. You’re polite, but you’re also in charge.

Practical Approaches: Combining Politeness with Clarity

Here are some practical ways to incorporate politeness into your AI interactions:

  • Basic Courtesies: Use “please” and “thank you” where appropriate. It costs nothing and might subtly improve results.
  • Precise Language: The more specific and well-defined your prompt, the better the AI can understand your needs. Politeness shouldn’t come at the expense of clarity.
  • Positive Framing: Frame requests positively (“Please provide…” rather than “Don’t omit…”). This often aligns better with the training data.
  • Acknowledge Output: A simple “Thank you, that’s helpful” can reinforce positive response patterns.

Beyond “Niceness”: The Broader Context

The “politeness principle” is just one facet of effective AI interaction. We’re still in the early days of understanding how to best communicate with these systems. As LLMs become more powerful and versatile, control and flexibility also become increasingly important.

Running AI locally, rather than relying solely on cloud-based services, is an important step. It allows you to experiment, tailor the model to your specific needs, and maintain greater control over your data. I previously detailed how you can use free, responsive AI with GaiaNet and ElizaOS – a powerful, cost-effective alternative to commercial offerings.

Underlying all of this is, of course, the hardware. Powerful GPUs are essential for running these advanced AI models. If you’re interested in the intersection of hardware and AI, particularly in the context of server environments, check out my post on GPU support in Windows Server 2025. The hardware is still critically important in deploying an effective solution.

Conclusion: A Thoughtful Approach; Just Be Nice!

Treating AI with respect – incorporating politeness and clear communication – is likely a good practice. It may subtly improve results, aligns with good communication principles in general, and, perhaps, prepares us for a future where AI plays an even larger role in our lives. It’s a small gesture, but one that reflects a thoughtful and proactive approach to this rapidly evolving technology.

Ditch the OpenAI Bill: How to Use Free, Responsive AI with GaiaNet and ElizaOS [Solved]

Tired of escalating OpenAI bills but still crave a powerful AI companion? ElizaOS, the open-source AI platform, has got you covered. By integrating with GaiaNet’s public nodes, you gain access to a variety of large language models (LLMs) – for free! These aren’t some underpowered toys, either. Many are highly responsive and capable, offering a compelling alternative to paid services. Let’s dive into how you can easily set this up.

What is GaiaNet?

GaiaNet is a decentralized network of compute resources specifically designed for running AI models. Think of it like a community-driven cloud for LLMs. They make many models available to the public for free via their public nodes. This allows anyone to access cutting-edge AI without the usual hefty price tags. The responsiveness of these models might surprise you, providing a smooth and engaging conversational experience.

Why Choose GaiaNet with ElizaOS?

  • Cost-Effective: The most obvious advantage is the cost – zero! Say goodbye to usage-based fees.
  • Variety of Models: GaiaNet hosts a selection of different LLMs, each with unique strengths.
  • Privacy Focus: As a decentralized network, GaiaNet can offer increased privacy compared to centralized services.
  • Open and Accessible: You can contribute to the network and even run your own node eventually.

How to integrate GaiaNet with ElizaOS Agent: Step-by-Step

Ready to give it a go? Here’s how to configure ElizaOS to use GaiaNet public nodes:

1. Understanding the Node URLs:

Before diving into the settings, let’s get familiar with what GaiaNet offers. As of this writing, the official docs show a couple of public nodes. You’ll have access to nodes for different model sizes, labeled as SMALL, MEDIUM, and LARGE, using different models like llama3b, llama8b or qwen72b. These are just default settings, you can use other models from the doc. Each of these nodes has an associated URL. For example:

Model SizeModel NameDefault URL
SMALL Modelllama3bhttps://llama3b.gaia.domains/v1
MEDIUM Modelllama8bhttps://llama8b.gaia.domains/v1
LARGE Modelqwen72bhttps://qwen72b.gaia.domains/v1

You can find the latest URLs on the official GaiaNet documentation.
https://docs.gaianet.ai/user-guide/nodes/

2. Modifying Your .env File:

The .env file is where ElizaOS stores its configuration variables. Locate this file in your ElizaOS directory (usually in the root folder). Now, you’ll need to add or modify the following lines (example based on your provided example) to point to the desired GaiaNet public nodes:


# Gaianet Configuration
GAIANET_MODEL=qwen72b
GAIANET_SERVER_URL=https://qwen72b.gaia.domains/v1

SMALL_GAIANET_MODEL=llama3b          # Default: llama3b
SMALL_GAIANET_SERVER_URL=https://llama3b.gaia.domains/v1    # Default: https://llama3b.gaia.domains/v1
MEDIUM_GAIANET_MODEL=llama     # Default: llama
MEDIUM_GAIANET_SERVER_URL=https://llama8b.gaia.domains/v1      # Default: https://llama8b.gaia.domains/v1
LARGE_GAIANET_MODEL=qwen72b           # Default: qwen72b
LARGE_GAIANET_SERVER_URL=https://qwen72b.gaia.domains/v1    # Default: https://qwen72b.gaia.domains/v1

GAIANET_EMBEDDING_MODEL=nomic-embed
USE_GAIANET_EMBEDDING=
    

Important Notes:

  • GAIANET_MODEL and GAIANET_SERVER_URL: These settings directly control the default model being used by your ElizaOS instance. For testing, you may want to use smaller models to see that everything is hooked up properly, then change to the larger models later.
  • SMALL_GAIANET_MODEL, MEDIUM_GAIANET_MODEL, LARGE_GAIANET_MODEL and SMALL_GAIANET_SERVER_URL, MEDIUM_GAIANET_SERVER_URL, LARGE_GAIANET_SERVER_URL: These are optional, but will allow you to easily switch between model sizes, from your character.json, and still use the gaianet provider.
  • GAIANET_EMBEDDING_MODEL: This is the embedding model that will be used.
  • USE_GAIANET_EMBEDDING: Leaving this empty will use the local embedding model. Setting this to TRUE will use the gaianet embedding model.
  • Use the v1 endpoint as in the example for the LLM model URL.
  • Be mindful of rate limits: These public nodes are a shared resource. If you encounter errors, try waiting before re-trying.

3. Updating your character.json:

Now, you need to tell your ElizaOS character to use the GaiaNet model. Open your character’s JSON configuration file. Find the "modelProvider" field and change it to:


"modelProvider": "gaianet",
        

You can also change the model size by passing a “modelSize” in your json:


"modelSize": "small",
        

This will override the default model you specified in the .env file, and will instead use the SMALL config. If you do not set modelSize, the default model in your .env file will be used. You can select from “small”, “medium”, and “large”.

4. Restart ElizaOS:

After making these changes, restart your ElizaOS instance for the new settings to take effect.

Testing and Tweaking:

Once restarted, try interacting with your character. If all went well, you should experience a conversation powered by the selected GaiaNet model!

Experiment with different models and find what works best for your specific use case. If you encounter an issue, make sure to double check your .env file and the URL that you have pasted in, as well as the model size in your character config.

Conclusion

Integrating GaiaNet public nodes into ElizaOS is a game-changer for anyone looking for a free, capable, and open-source AI solution. By following these simple steps, you can unlock the power of large language models without worrying about constant usage fees. So, what are you waiting for? Dive in and start experiencing the world of open AI!

  • Share your experiences with GaiaNet and ElizaOS in the comments!
  • If you found this guide helpful, consider sharing it with others in the ElizaOS community.
  • Explore the GaiaNet documentation for more advanced features and options.

What Are the Differences Between Microsoft Defender for Office 365 P1 & P2, and Is It Worth the Price Difference?

What Are the Differences Between Microsoft Defender for Office 365 P1 & P2?

When it comes to protecting your organisation from email-based threats, Microsoft Defender for Office 365 is a leading solution. But with two plans available — Plan 1 (P1) and Plan 2 (P2) — it can be difficult to know which is the best fit for your business. In this article, we’ll compare the two plans and help you decide if the additional features in Plan 2 are worth the higher cost.

Key Differences Between Plan 1 (P1) and Plan 2 (P2)

FeaturePlan 1 (P1)
£1.64 user/month
Plan 2 (P2)
£4.10 user/month
Protection Against PhishingYesYes
Anti-Spam ProtectionYesYes
Safe LinksYesYes
Safe AttachmentsYesYes
Threat IntelligenceYesYes
Attack SimulatorNoYes
Automated Investigation and RemediationNoYes
Advanced Threat Protection ReportsNoYes
Custom Policies for Safe LinksNoYes
Advanced Threat HuntingNoYes
Real-time Threat DetectionNoYes

Plan 1: Essential Protection for Office 365

Plan 1 provides essential protection against common email threats like phishing, malware, and spam. Here’s what you get with Plan 1:

  • Protection Against Phishing: Helps to identify and block phishing attacks targeting your users.
  • Anti-Spam Protection: Blocks unwanted email and protects against spam.
  • Safe Links: Provides real-time protection by scanning URLs in email messages to prevent users from clicking on malicious links.
  • Safe Attachments: Scans email attachments for potential threats and isolates them for analysis.

Plan 1 is ideal for businesses that need basic email protection and are using Microsoft 365 services for communication and collaboration.

Features Only Available in Plan 2

Plan 2 builds on the protection offered in Plan 1 and adds additional advanced features for organisations that need more sophisticated defences. In addition to everything in Plan 1, Plan 2 includes:

  • Attack Simulator: Helps simulate real-world phishing attacks to test your organisation’s security awareness and training.
  • Automated Investigation and Remediation: Automatically investigates and remediates threats to reduce manual intervention and improve response times.
  • Advanced Threat Protection Reports: Provides in-depth reporting on threats targeting your organisation.
  • Custom Policies for Safe Links: Customises the protection of URLs to suit your organisation’s specific security needs.
  • Advanced Threat Hunting: Allows you to proactively search for and identify potential threats within your environment.
  • Real-time Threat Detection: Detects and responds to advanced threats in real time, ensuring quicker mitigation.

Plan 2 is designed for organisations that require more advanced protection and want automated security management, as well as additional tools for threat investigation and prevention.

These exclusive capabilities make Plan 2 the go-to choice for businesses that need more control over their email security and quicker, more efficient responses to emerging threats.

Is the Extra Cost for Plan 2 Worth It?

Choosing between Plan 1 and Plan 2 depends on the needs of your organisation, your budget, and the level of protection you require. Here’s a quick breakdown:

  • Plan 1: Best for smaller organisations or those who only need essential protection for email security. It’s a cost-effective option that provides solid defences and is included in Microsoft 365 Business Premium and Microsoft 365 E3 licences.
  • Plan 2: Ideal for larger organisations or those with higher security needs. Plan 2 includes all features of Plan 1 plus advanced protection tools, custom policies, and automation. Plan 2 is available with Microsoft 365 E5 licences.

If your organisation faces a higher risk of targeted attacks, or you need enhanced security and more automation, the additional cost for Plan 2 could be well worth it for the added peace of mind.

What Are the Differences Between Microsoft Defender for Endpoint P1 & P2, and Is It Worth the Price Difference?

Microsoft Defender for Endpoint Plan 1 vs Plan 2

When it comes to protecting your business from cyber threats, Microsoft Defender for Endpoint (MDE) is a solid choice. But with two plans available — Plan 1 (P1) and Plan 2 (P2) — it can be tough to know which one is right for your organisation. In this article, we’ll break down the differences between the two plans and help you decide if the extra cost for Plan 2 is worth it.

Key Differences Between Plan 1 (P1) and Plan 2 (P2)

FeaturePlan 1 (P1)Plan 2 (P2)
Next-Generation ProtectionYesYes
Attack Surface ReductionYesYes
Device Control (e.g., USB management)YesYes
Endpoint FirewallYesYes
Network ProtectionYesYes
Web Content FilteringYesYes
Device-Based Conditional AccessYesYes
Centralised ManagementYesYes
Application ControlYesYes
APIs and SIEM ConnectorYesYes
Advanced Security ReportsYesYes
Endpoint Detection and Response (EDR)NoYes
Automated Investigation and RemediationNoYes
Threat and Vulnerability ManagementNoYes (with MDVM add-on)
Advanced Threat HuntingNoYes
SandboxingNoYes
Managed Threat Hunting ServiceNoYes
Threat IntelligenceYesYes
Microsoft Secure Score for DevicesYesYes

Plan 1: Basic Protection at a Lower Cost

Plan 1 is great for businesses that need essential protection without breaking the bank. Here’s what you get:

  • Core protection: Defends your devices from malware and other malicious software.
  • Device control: Manages access to USB devices and other peripherals.
  • Centralised management: Lets you manage and monitor your devices from one dashboard.

Plan 1 is a good choice for smaller companies or those with less complex security needs.

Plan 2: Advanced Protection for Greater Peace of Mind

Plan 2 takes endpoint security to the next level, offering everything in Plan 1 plus powerful features for businesses that need more advanced protection. These include:

  • Advanced threat detection and response: Finds and stops advanced threats that could bypass basic security measures.
  • Automated investigation and remediation: Reduces manual effort by automating threat analysis and response.
  • Threat and vulnerability management: Identifies and resolves vulnerabilities across your network.
  • Proactive threat hunting: Actively searches for potential threats before they cause damage.

If your organisation handles sensitive data or faces higher risks, Plan 2 is the better option, offering more comprehensive security tools.

Features Only Available in Plan 2

These are the exclusive features that come with Plan 2 — and they’re crucial for businesses that need extra layers of protection:

  • Endpoint Detection and Response (EDR): Detects and responds to sophisticated cyberattacks in real time.
  • Automated Investigation and Remediation: Speeds up incident response by automating security tasks.
  • Threat and Vulnerability Management: Helps spot and fix security weaknesses before they are exploited.
  • Advanced Threat Hunting: Proactively searches for hidden threats within your network.
  • Sandboxing: Safely analyses suspicious files to block potentially harmful content.
  • Managed Threat Hunting Service: Gives you expert help to track and eliminate emerging threats.

These additional capabilities make Plan 2 a powerful choice for businesses that need top-tier protection and quicker response times.

Is the Extra Cost for Plan 2 Worth It?

The choice between Plan 1 and Plan 2 depends on your company’s size, budget, and security needs. Here’s a quick breakdown:

  • Plan 1: Ideal for smaller organisations or those with basic security needs. It provides core protection and is included in Microsoft 365 E3/A3 licences.
  • Plan 2: Best for larger businesses or those that need enhanced security features like automated threat hunting and vulnerability management. Plan 2 comes with Microsoft 365 E5/A5/G5 licences.

If you don’t face significant cybersecurity risks, Plan 1 might be all you need. However, if you’re dealing with sensitive data, have a larger workforce, or need advanced protection, the added cost of Plan 2 could be worthwhile for the peace of mind it offers.


What GPU’s does Windows Server 2025 support for GPU Partitioning? [Solved]

Supported GPUs for GPU Partitioning in Windows Server 2025

Virtualization has transformed IT, enabling us to run multiple VM’s and OS’s on a single server. But for resource-intensive tasks like AI and machine learning, powerful graphics processing is essential. This is where Windows Server 2025’s GPU partitioning comes into play, allowing multiple virtual machines (VMs) to share a single GPU’s power, optimising usage and enhancing workload capacity.

What is GPU Partitioning?

With GPU partitioning, a single physical GPU can be split into multiple virtual GPUs (vGPUs), each assigned to different VMs. This enables simultaneous execution of resource-heavy tasks, like AI and ML workloads, all on a shared GPU—making it a game-changer for high-demand environments.

Supported GPUs

Currently only a handful of NVIDIA GPUs currently support partitioning with Windows Server 2025. Here’s a list of the compatible graphics cards supported for Windows Server 2025 for GPU Partitioning:

GPU ModelRough Cost (USD)CUDA CoresTF32 teraFLOPS or Tensor CoresMemory (GB)TDP (Watts)
NVIDIA A2£1300-1800128040-601640-60
NVIDIA A10£2300+8192275-41024150
NVIDIA A16£2700+5120 (4x 1280)4x 40 Cores64250
NVIDIA A40£5100+10,75274.8 – 149.648300
NVIDIA L2Not out yetn/a48.324TBD
NVIDIA L4£2500+n/a1202472
NVIDIA L40£7500+18176568 | Gen 4 Cores48300
NVIDIA L40S£9700+18,17636648350

Notes

  • My pick would be the NVIDIA A16 currently offering what is basically 4 GPU’s on one card already making it ideal for partitioning.
  • Details for some GPUs, especially newer models, are limited and may change as they become more widely available.
  • Most of these cards are made for the enterprise market, so don’t go thinking you will suddenly be able to set up 4 gaming PC’s on one server and get good graphic results! Whilst it may be possible, these are designed more around tensor cores, useful for AI and deep learning than Cuda cores, which are more multipurpose.

Windows Server 2025’s GPU partitioning unlocks powerful capabilities for optimising hardware and running demanding workloads. While limited to specific NVIDIA GPUs, it’s a step forward for those looking to enhance their system’s efficiency and boost VM computational power. Understanding which GPUs work best for what workloads will become the next big learning curve!

Windows Server 2025: My Top New Favourite Features

Windows Server 2025: Enhanced Security, Performance, and Cloud Integration

It’s finally here! Microsoft has unveiled its latest server operating system, Windows Server 2025, and it should provide significant advancements in performance, security, and cloud integration. Below are some of the features that stuck out to me with my first install.

My Top 5 New Features of Windows Server 2025

  • Block Cloning: This feature significantly improves file copy performance, especially for large files, optimising file operations by copying only modified blocks, reducing I/O and improving performance for large files.
  • SMB over QUIC: This enables secure access to file shares over the internet, providing faster and more reliable file transfers using native SMB technologies.
  • Hotpatching: This allows for the application of security updates to running servers with minimal downtime, no more out of hours scheduling of reboots!
  • GPU Partitioning: This lets you split up GPU resources by allowing them to be divided into smaller, virtualized GPUs, adding GPU resources to a VM? Yes please!.
  • Enhanced Active Directory: This includes features like AD object repair, optional 32k database page size, and improved security for confidential attributes and default machine account passwords.

Key Features of Windows Server 2025:

  • Enhanced Security: Robust security measures, including hardened SMB protocols, improved Active Directory, and enhanced protection against cyber threats.
  • Accelerated Performance: Significant performance boosts for virtualization, storage, and networking, especially for AI and machine learning workloads.
  • Seamless Cloud Integration: Improved integration with Azure for hybrid and multi-cloud environments, enabling seamless workload migration and management.
  • Modernized Infrastructure: Support for the latest hardware and software technologies, including NVMe storage and GPU acceleration.

    Its just a bit better in every way from Server 2022 – and 100% better than 2012 R2!

Feature Windows Server 2025 Windows Server 2022 Windows Server 2012 R2
Security Enhanced security protocols, improved AD, stronger threat protection Robust security features, including shielded VMs and credential guard Basic security features with early Active Directory improvements and Security Essentials
Performance Accelerated virtualization, storage, and networking, optimized for AI/ML Strong performance, especially for virtualization and storage Improved performance for Hyper-V and storage, but limited optimization for newer technologies
Cloud Integration Deeper Azure integration, seamless workload migration Good Azure integration, basic hybrid cloud capabilities Limited cloud integration, early support for hybrid environments with System Center
Hardware Support Support for latest hardware, including NVMe and GPU Support for modern hardware, including NVMe Support for basic hardware configurations; limited support for emerging hardware like NVMe
 

In summary, Windows Server 2025 steps up the game with smarter security, better performance, and seamless cloud connectivity. From the efficient file handling with Block Cloning to downtime-reducing Hotpatching, it’s clear this release is built to make life easier for us admins. Adding GPU Partitioning for VM flexibility and enhanced AD features, Microsoft has pushed the envelope to give us a modern, future-proof server OS that seamlessly connects to Azure and Entra.

With all these updates, Windows Server 2025 is a significant improvement over its predecessor, Windows Server 2022, and a massive leap from the now-aged Server 2012 R2. Finally, if you are thinking about upgrading now EOL servers. This one’s worth it!

[Solved] Default username and password for Unifi Gateway Pro (UXG-Pro)

Default passwords for Unifi kit

Whilst most AP’s and Unifi devices can be ssh’d into using ubnt/ubnt there are a few exceptions to this rule, for example the UXG-Pro is root/ubnt.
Prior to setup/adoption, all devices have a set of default credentials below is what they are as of 06/2024. 

  • UniFi Consoles –  root / ui (root / ubnt on older devices)
  • UniFi Gateways – root / ui (root / ubnt on older devices)
  • UniFi Devices – ui / ui (ubnt / ubnt on older devices)