Designed for Modern IT Departments

Let’s be honest — a couple of years ago, most people didn’t even know what “LLM” meant. Fast forward to 2025, and large language models are everywhere. In apps. In browsers. In business tools. They’re writing code, solving math problems, analyzing data, and even helping doctors, lawyers, and writers do their jobs better (or faster).

But not all LLMs are created equal. Some are massive, built to handle just about anything. Others are lean and focused. And while OpenAI’s ChatGPT brought this space into the mainstream, the landscape today is full of contenders—each with its own strengths, quirks, and use cases.

So, who’s leading the pack in 2025? Let’s walk through the real heavy-hitters.

Claude (Anthropic)

Think of Claude as the helpful, rule-following type. It’s built on a “constitutional AI” framework, meaning it tries to stay useful without going off the rails. The newer Claude Opus 4 and Sonnet 4 models? Surprisingly good at following instructions, writing code, and even juggling long tasks. Some developers swear by its memory system and ability to link up with tools like IDEs or file APIs. It’s also learning how to “use a computer” more like a person. Wild.

Gemini & Gemma (Google)

Google didn’t just stop at Bard. They spun up Gemini—a seriously powerful multimodal engine that handles text, audio, video, images—you name it. Gemini 2.5 Pro and Flash are optimized for long-form input and fast responses, respectively. For the open-source crowd, Gemma fills that space nicely with models that run locally or on cloud platforms. Clean, scalable, and deeply integrated into Google’s ecosystem.

GPT Family (OpenAI)

Still the gold standard for many. GPT-3 and 3.5 laid the groundwork. GPT-4 took things up a notch. And GPT-4o? That’s where it gets conversational. With voice, vision, and ultra-low response times, it’s like chatting with something genuinely human. No surprise it powers most of ChatGPT now, even on the free tier.

Mistral (Mistral AI)

A bit of a rising star. The Mistral Large and Pixtral models are gaining traction fast. They’re fast, open, and surprisingly versatile across languages and coding tasks. The May 2025 release of Mistral Medium 3 added even more firepower—multimodal, big-context, and built for frontier-level tasks.

LLaMA (Meta)

Meta’s LLaMA series made open-source AI cool again. The LLaMA 4 line—Scout, Maverick, Behemoth—is powerful and widely adopted. Some of the most popular community models are based on it (like Vicuna). These models are everywhere now, from local setups to research labs.

DeepSeek & DBRX

If reasoning is your thing—math, logic, chains of thought—DeepSeek is one to watch. DBRX, on the other hand, is Databricks’ entry into the scene. It’s a mixture-of-experts model that’s shown impressive benchmarks in code and reasoning. Fast, efficient, and enterprise-ready.

Grok (xAI)

This one’s quirky—in a good way. Built by Elon Musk’s xAI team, Grok comes with “Think” and “DeepSearch” modes. So it doesn’t just answer—it breaks things down, reflects, and researches. It runs on a monster of a supercomputer called Colossus. Whether that’s overkill or genius… well, depends who you ask.

Why It All Matters

Let’s not sugarcoat it: the LLM space is moving *fast*. Features that felt like science fiction last year are now standard. Multimodal inputs, million-token context windows, code generation, real-time interactivity—it’s all happening now.

And it’s not just about chatbots. These models are powering medical analysis tools, legal assistants, customer service bots, and whole new classes of digital agents. Some are open. Some closed. Some tiny and nimble. Others? Absolute giants.

But one thing’s clear: the way we interact with machines—how we write, learn, build, and decide—is being rewritten in real time.

Remember when macro-based malware was everywhere? Word docs with “Enable Content” buttons that turned out to be Trojan horses for ransomware, keyloggers, and all sorts of nasty surprises?

For a while, Microsoft managed to shut that party down. Starting in 2022, macros in files downloaded from the internet were blocked by default. No more instant infections from a single careless click. Things got quieter.

But now? With legacy versions of Office reaching the end of their support lifecycles, we’re seeing an unexpected side effect: macros are creeping back into the threat landscape.

When Old Software Sticks Around, So Do Old Problems

Let’s be honest — not every organization jumps on new versions of Office the moment they launch. Some are still using Office 2013 or earlier, either out of habit, cost savings, or because some critical internal system just won’t work with newer builds.

That’s where the danger lies. These older versions don’t have Microsoft’s newer macro-blocking features. No Smart App Controls. No default sandboxing. Just the old-school “trust or don’t trust” model — and attackers know exactly how to exploit that.

Phishing campaigns are catching on. Files disguised as invoices, reports, or meeting notes are back in circulation, weaponized with VBA macros that run the moment a user clicks that innocent-looking “Enable” prompt.

Why Are Macros Still a Thing?

Because they work. Simple as that.

They’re flexible, deeply embedded into Office, and they let attackers do a lot with very little. Launch PowerShell? Easy. Reach out to a C2 server? Sure. Write persistence to the registry? No problem.

And with a little social engineering, macros still trick people — especially in sectors where documents move fast and scrutiny is low.

Microsoft 365 Has Better Protection — But Adoption Is Uneven

Microsoft wants everyone in the cloud, and sure, Office 365 and its web-based tools do have stronger default security controls. But the reality is, not every org is ready (or willing) to make the switch.

The result? A patchwork of environments. Some users are on hardened Office installs. Others are stuck with older local deployments that haven’t seen a security update in years. For attackers, it’s obvious where to aim.

What Security Teams Should Do (Besides Panic)

If moving off legacy Office is on the roadmap but not yet reality, here’s how to buy some breathing room:

– Use Group Policy to block all macros in files from external sources.

– Set up mail filters that detect and isolate suspicious Office attachments.

– Watch for behavior — not just files. A macro spawning PowerShell should always be a red flag.

– Help users understand that “Enable Content” isn’t just a button. It’s a decision.

Final Thought

Just because macro-based malware went quiet doesn’t mean it disappeared. The threat was always there — it just lost its edge for a while. Now, with older Office versions hanging around and security gaps reopening, it’s finding new ground to grow.

Patching, upgrading, and educating might not be glamorous. But they’re what stands between your org and a very old, very familiar problem that’s suddenly back in style.

Here’s the uncomfortable truth: if you’ve got anything exposed to the internet, it’s already been scanned. Maybe even poked, mapped, or added to someone’s list. These days, “you could be a target” isn’t the story. You already were. And probably will be again — today, tomorrow, next week.

That’s why patching isn’t just another checkbox. It’s frontline defense. And in 2025, falling behind on updates isn’t a risk — it’s an open invitation.

Threats Move Fast. Slower Teams Pay the Price.

It takes hours — sometimes minutes — for attackers to jump on a newly disclosed vulnerability. Some don’t even wait for public announcements; they’re working off leaked info, automated crawlers, and dark web chatter. The window for patching? It’s getting smaller. In some cases, it barely exists.

Still, a lot of orgs are lagging. Maybe they rely on legacy systems that break under updates. Maybe it’s the fear of downtime. Maybe it’s just too many tools and too little time. Whatever the reason, the result’s the same — exposure.

And attackers? They don’t care why you’re behind. They only care that you are.

Burnout Is Real — But So Is the Tech to Fix It

Nobody loves the endless stream of updates. Patch fatigue is real, especially when you’re juggling OS patches, third-party software, and firmware — often across multiple environments.

But there’s hope. Smarter automation, better asset tracking, and tools that prioritize what actually matters are helping teams breathe again. No more guessing which patches to apply first. No more hunting for rogue machines running outdated versions.

It’s not about patching everything, all the time. It’s about patching what counts, before it bites you.

Visibility Is Everything

If you can’t see it, you can’t fix it — plain and simple. That’s why so many companies are shifting back to basics: proper inventories, up-to-date asset management, and real-time monitoring for missing patches.

And honestly? Some of the scariest vulnerabilities aren’t the zero-days. They’re the ones sitting there for months, untouched, because nobody realized the software was even still running.

Old Tech, Old Problems

Legacy systems are a pain. They’re fragile. They’re critical. And they often can’t be patched at all. Attackers know that, and they go looking for them.

So what do you do? You isolate. You segment. You throw up virtual firewalls, watch the traffic like a hawk, and — if you’re lucky — make a plan to replace them someday.

Until then, they’re your weak spot. And you know it.

In 2025, Patch Management Is Everyone’s Problem

It’s not just an IT issue anymore. Security cares. Risk teams care. Auditors definitely care. Patching is now tied to compliance, incident response, and even insurance. More and more companies are tracking patch times like uptime — as a metric that actually matters.

It’s not about being perfect. It’s about being better than “exploitable.”

Final Thought

Patching isn’t glamorous. It won’t win awards. But it keeps businesses standing. In a world where threats are constant, patches are your quickest — and often last — line of defense.

So yeah. Patch early. Patch often. And if you can’t? At least know what’s out there, and don’t pretend it can wait.

Data Center Power Challenges Are Reshaping Enterprise IT

As AI continues to grow, powering enterprise data centers is becoming more difficult than building them. The problem is no longer just about space or servers — it’s about how to deliver and manage much larger amounts of power in a smart, safe, and efficient way.

For hyperscalers like AWS or Google, the issue is finding enough power at all — sometimes even considering building dedicated power plants. But for most enterprises, the challenge is more about managing extreme power density inside racks and rooms that weren’t designed for it.

Why Power Use Is Rising Fast

Today’s racks can draw up to 1 megawatt — compared to just 150 kW a few years ago. This spike is driven by three key factors:

• CPUs are more power-hungry, growing from 200W to 500W+.
• AI workloads rely on GPUs, with multiple accelerators in each server, each using close to 1 kW.
• Tight integration and higher density reduce latency, which is critical for AI training.

AI models need constant, high-speed data movement between chips. That’s why components are packed tightly, which raises both power and cooling demands.

New Rack Designs and Power Layouts

To handle the extra load, some companies are moving power systems out of the racks themselves. Instead, they use external power units that feed several racks at once. This frees up space, supports denser compute, and reduces delays between components.

But managing this setup isn’t easy. Most enterprise data centers were built around far lower power needs, and there are no standard solutions yet for 1 MW racks. Every setup is a custom job, often pushing the limits of current designs.

Skills Are Becoming a Bottleneck

Many IT staff were trained for traditional setups — low-voltage, simpler equipment. But with these new demands, more advanced electrical knowledge is now required. In some cases, technicians may even need electrician-level certifications to safely install and maintain systems.

There’s a clear skills gap: most current certifications don’t go far enough for today’s power requirements, and trained professionals are in short supply.

What Needs to Change

To keep up, the industry needs to adapt in several ways:

• IT teams must level up their skills, especially in power and safety.
• Vendors should simplify infrastructure, making it easier to manage and scale.
• Automation tools need to handle more tasks, reducing pressure on staff.

There’s no one-size-fits-all answer yet. But smarter designs, better training, and improved tools can help data centers handle the growing demands of AI and high-density compute.

Power Is Now a Core Strategy

Power is no longer just a background concern — it’s a core part of data center planning. Companies that ignore it risk hitting limits fast. But those that address power early — from design to staffing — will be better prepared for what’s coming next.