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This Week’s Forward »

A new addition to the newsletter that will include some unique thoughts and insights-

AI hits an inflection point as government and reality catch up. From regulation to market expectations, the enterprise realization that generative AI can make an impact is starting to materialize. The latest Gartner Hype Cycle for Infrastructure and Operations shows generative AI moving quickly into the ‘drink’ of technology adoption.

Why?

Multiple reasons:

• AI Regulation is starting to take shape

• AI vendors are hitting the typical innovation roadblocks, but the market is unforgiving, creating doubt for businesses

• Solutions are slow to be realized, and return on investment (ROI) is slower than expected

Gartner Hype Cycle for Infrastructure and Operations for 2024 highlights that generative AI is moving off-peak, toward the trough of disillusionment.

Is this a blip? Is this temporary and the hype will continue? Time will tell, but it feels like just another day in AI.

🔥Top Stories🔥

🔥Experts assess the EU's AI Act

As the EU's AI Act prepares to come into force tomorrow, industry experts are weighing in on its potential impact.

🔥NVIDIA and Meta CEOs: Every business will ‘have an AI’

As AI continues to evolve and integrate into various aspects of our lives, the insights shared by these industry leaders provide a glimpse into a future where AI assistants are as commonplace as websites and social media accounts.

🔥Enterprise AI adoption soars almost 90 percent

For some time now AI has been the go-to technology to enable informed decision making, accelerate innovation, and enhance experiences for both employees and customers.

📈Trending News📈

📈Can ChatGPT-4o Be Trusted With Your Private Data?

📈Are we prepared for ‘Act 2’ of gen AI?

📈The convergence of human and machine in transforming business

📈Meta to 10x training compute infrastructure for Llama 4

📈Google’s Gemini 1.5 Pro dethrones GPT-4o

📈Hugging Face offers inference as a service powered by Nvidia NIM

✖️Enterprise AI @Nutanix✖️

✖️ Debo Dutta Talks on the latest data platform trends, rising AI apps, and cloud dynamics

✖️ Unleashing the Power of AI with Nutanix GPT-in-a-Box and Red Hat OpenShift AI

The thoughts, opinions, viewpoints, and concepts shared here are the sole property of endofline.cloud and are not affiliated with any other company or publication.

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🔥Top Stories🔥

🔥Open-Source AI Models Create Parity with Proprietary Model Leader

Silicon Valley shook as open-source AI models Llama 3.1 and Mistral Large 2 match industry leaders. Open-source artificial intelligence has reached a watershed moment, challenging the long-held dominance of proprietary systems and promising to reshape the AI landscape, especially in how enterprises deploy their AI strategies.

🔥Are You Ready to Deploy AI? C-Suite Leaders Chime In

82% of C-suite and other senior executives agree that “scaling AI or generative AI use cases to create business value is a top priority for our organization.” The number-one challenge in achieving that AI readiness, survey respondents say, is data integration and pipelines (45%). Asked about challenging aspects of data integration, respondents named four: managing data volume, moving data from on-premises to the cloud, enabling real-time access, and managing changes to data.

📈Trending News📈

📈Why Enterprise AI Needs Connected Clouds

📈Day-2 AI: Examples from the Retail Industry

📈Only 6% of organizations have held off on generative AI, Capgemini says

📈Cutting-Edge Infrastructure Best Practices for Enterprise AI Data Pipelines

📈Gartner: How to Calculate Business Value and Cost for Generative AI Use Cases

✖️Enterprise AI @Nutanix✖️

✖️ Cisco Compute Hyperconverged with Nutanix GPT-in-a-Box

The thoughts, opinions, viewpoints, and concepts shared here are the sole property of endofline.cloud and are not affiliated with any other company or publication.

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🔥Top Stories🔥

🔥How Your CEO Is Thinking About AI

The annual Gartner CEO and Senior Business Executive Survey probed how leaders are reacting to the highly visible rise of AI, particularly GenAI. We found that CEOs are bullish on the technology’s potential, but may not have a fully baked plan for realizing its promises.

📈Trending News📈

📈Powerful AI Models Get Smaller: Mistral AI and NVIDIA Unveil Mistral NeMo 12B, a Cutting-Edge Enterprise AI Model

📈The Global Race for AI Dominance Shifts Gears: Nvidia, ASML, and other chip stocks tumbled following reports of potential moves that could negatively impact the sector.

📈Cheat Sheet for AI Terminology: AI is changing everything, so get up to speed on what these terms mean and how they can help your business.

📈AI training data is running out - what’s next? The first wave of AI innovation is over. Here’s what comes next as businesses themselves, not closed-source AI companies, need ownership and control of their proprietary models.

📈Gartner predictions about GenAI beyond 2024

✖️Enterprise AI @Nutanix✖️

✖️Nutanix releases DataRobot solutions documentation

The thoughts, opinions, viewpoints, and concepts shared here are the sole property of endofline.cloud and not affiliated with any other company or publication.

LLMs are the driving force behind today’s GenAI hype. Trained on billions or trillions of pieces of data context, these models can do everything from giving you advice on your current mood to helping you discover new types of dad jokes. And why it’s really cool for the average person interfacing with OpenAI’s ChatGPT, Anthropic’s Claude, or any of the thousands of LLMs available right now, as a business you may want to reconsider a LARGE language model in favor of a small one. An SLM (small language model)

LLM vs. SLM

So let’s go back; wayyyy back. Back to the suit-fitted, dress attire of yesteryear. Back when huge banks of computers filled rooms and floors as a single entity that was accessed through retro-futuristic terminals. My favorite concept of this? The original Tron:

The ‘Master Control Program’, MCP for short, was the AI villain that controlled and assimilated other programs from across the world for Encom. It naturally spoke with humans and was eventually felled by Tron, a security program that ended the MCPs reign.

Ahhh, Sci-fi.

Modern LLMs aren’t that different than the MCP they’re all-knowing and centers of massive amounts of machine-trained data, pre-canned and tuned to naturally convey information as you or I would in a casual conversation.

Also like the MCP, an LLM can be a security and privacy risk when tied to business data and applications. When connected to these components, an internal or external threat actor can coax an LLM to forgo its guardrails or query sensitive data.

When Flynn, the rightfully disgruntled ex-employee, forged access to the MCP through current employees, he was whisked away to a digital world inside the mainframe. Though not as profound, unauthorized access to critical company IP (intellectual property) is made to be just as easy with an LLM using GenAI (generative AI).

So remember like, 200 words ago about that term SLM? Imagine if Tron’s premise was an AI that only had access to, say, laser schematics and data to improve the digitizing of matter. Nothing extra. Ok, maybe some dad jokes, because as a laser technician I’d love some mid-day funnies:

Ok, that was bad, but I think you get it. Our ‘Laser Chicken SLM’ specializes in a very focused dataset and task: Understanding Encom’s laser schematics and telling laser dad jokes. This smaller attack surface doesn’t prevent someone like the MCP from compromising its information, but what IS compromised is much less than a large model. Also, an attacker would have to compromise other, adjacent SLMs to get deeper context or secrets. When you separate AI models, this provides better security hygiene and makes model management more aligned to knowledge buckets or tasks inside a business rather than one large model for everything.

The GenAI Edge with SLMs: Less Power, Less Hardware, Less Headaches

AI models are the result of huge amounts of data and processing power (compute) trained and compiled for millions of GPU hours. Accessing this trained data also takes large amounts of computing on the user side. When you run a chatbot for example, it has a cost to interact with an AI model; a compute operation to query or infer using a GPU card, or a newer CPU with AI capabilities. Models can only handle a certain number of words or characters at a time. These are called tokens. The combination of compute and tokenization costs may show up to an end user as “AI slow down” where a question may go unanswered, time out, or not function. Nothing is free.

These days many users of AI are not close to AI compute operations. Most are remote at the network edges on a myriad of devices performing an array of tasks. Sure, a company could spend large amounts of capital on compute resources for AI, but why? With SLMs and private cloud platforms designed for the edge, you can save money, time, and resources.

Imagine you’re a hybrid legal worker whose expertise and main role is to identify and correct incorrect language in business contracts. You paid for OpenAI ChatGPT and turned off prompt sharing, but a new mandate stipulates you must use internal AI resources to protect company IP.

Ugh. What are you going to do?

Enter the SLM. Small, specialized, powerful. It is 1/10 the size or even smaller than a typical LLM. It can run locally on your MacBook or on a slimmed-down edge server with optimized GPU hardware or even GPU-less with AI CPUs that include powerful natural language processing extensions.

You can use an SLM to help a legal professional find and understand duplicate contexts and problematic language, or trigger a workflow to bring in other people simply based on a keyword.

Your IT dept may even need to allow you to be part of the testing for these SLMs. But a series of tickets and back-and-forth communication can be clunky. Imagine a world where a few clicks can find, swap, and implement a new SLM. A good starting point to find SLMs is a list like this on Hugging Face.

Still, the challenge remains how quickly IT can qualify in, or qualify out, a particular model. This is where a private cloud platform with deep AI roots and self-service comes to save the day.

A Private Cloud Data Platform; Nutanix GPT-in-a-Box 2.0

Ok, ok, this is a plug but hear me out.

AI for your business is much more than GPUs and the latest LLM; It’s about data, lifecycle management, and enterprise-scale; It’s about private and security operations that are identical whether you’re on-premises or in the public cloud; It’s about making your IT wizards into AI wizards. Most importantly, it’s about choice: The choice to deploy something today without fear it will be obsolete tomorrow and the ability to adapt, to evolve.

Nutanix was born on the notion that a resilient and scalable data platform was critical to a business. It’s since evolved to spread this message beyond the datacenter into public clouds. The explosion of AI only reinforces this idea: You must control your data; no small print, no cloud contracts, no promises, just good old-fashioned ownership.

Data control now becomes the deciding factor for GenAI. In reality, most organizations will not create their LLMs or SLMs, but use an open-source model or pay for a specialized model from a trusted vendor. This means deploying an AI app should be easy, secure, and interchangeable. It should be simple.

Nutanix GPT-in-a-Box 2.0 is a private cloud solution that includes your choice of hardware, software, and data services for GenAI; Think of it like a box of everything you need to run AI applications including GPUs, CPUs, memory, storage, networking, and a single pane of glass dashboard to control it all. Now imagine you can combine these boxes into clusters of servers across data centers or clouds. What you enact or change in a single location also changes everywhere else.

Cool, right?

But what about GenAI itself? You know, the model management, development, and testing? An LLM/SLM isn’t enough. There’s probably no budget to find ‘AI specialists’. Heck, even if you did, these days it would just be someone like me who has used AI enough to be dangerous :-) There must be a way to retrain technologists into AI experts, and with GPT-in-a-Box 2.0 there is.

Nutanix AI Endpoint and NVIDIA NIM

Nutanix AI Endpoint will be a native container-based workflow ‘engine’ that allows you to search and download validated LLM/SLM models from HuggingFace, or upload your own model. An API creator is built in that, within a couple of clicks, you can tie an enterprise-grade API to your model. Not the right model? No worries, simply remove the connection, download a new model, and tie the same API to the new model. Pretty slick.

For NVIDIA AI Enterprise users, the Nutanix AI Endpoint’s engine is under development and will be able to be ‘swapped’ for NVIDIA NIM, a set of containers that create a microservices infrastructure based on NVIDIA’s latest offering. Similar to the native engine in the Nutanix AI Endpoint, the option to run NVIDIA NIM provides a choice depending on your business requirements or outcomes.

And this is just the beginning.

Future engines will be able to be swapped into Nutanix GPT-in-a-Box 2.0 providing you exactly what you need to make GenAI yours.

Back to our legal user example from before-

Now imagine if your IT dept had GPT-in-a-Box 2.0 with AI Endpoint. Testing SLMs would be easy, seamless, and straightforward. Not the right model? Open source license constraints? Just grab a new model, repoint, and test. It’s painting a future of GenAI model management for large, small, or whatever comes next.

Are SLMs the Future of Enterprise AI?

Surprise, the answer is yes, AND no.

Enterprises must consider the diversity of problems GenAI could solve and balance that with what should be tackled. SLMs are a great solution for exploring AI as a way to improve the little things.

Again, with our legal example, providing AI as a tool, not a replacement, will enhance user productivity. An SLM is an impactful way to validate AI without a heavy capital investment in hardware, software, or talent. Partnering with a trusted vendor that ensures your success unlocks this goal. Nutanix provides solutions from the edge to the public cloud, allowing you to buy exactly what you need today and expand tomorrow when needed. Imagine getting an SLM up and running in minutes with all the data and workflows in your control. Thats Nutanix.

AI is Changing, So you Should Too

What you’re doing or even conceiving of today with GenAI WILL change, and will do so soon. We’re at the very beginning of its impact on business. The risk is choosing a solution or a direction that may not be supported or even exist, tomorrow. Yet waiting for things to shake out isn’t an option either. The advantages AI brings are too impactful. So what do you do?

Find a solution that enables choice, one that can adapt. Focus on:

A strong but upgradable hardware platform

A software-defined approach for data and applications ensuring they can operate anywhere

A platform where AI isn’t just a focus, it’s the reason

Flexibility is key when the outcome of a journey is unknown, and GenAI has just charted a path for us all.

But, a word of caution: AI shouldn’t change everything.

The goal of any GenAI initiative should be to augment the human aspect, not replace it. AI, like any new and advanced technology, will undoubtedly replace some of the jobs humans do today much like centralized hearing replaced chimney sweeps, or automated phone line switching replaced switchboard operators. Overall, the majority of jobs can be aided by leveraging AI to automate mundane tasks leaving humans to do what they do best- imagine, create, and thrive.

End of line.

Learn more about Nutanix, GPT-in-a-Box, and NVIDIA at nutanix.com/ai

Disclaimer: These thoughts are my own and not reflective of anything related to Nutanix.

1. LCM Customs! Sleek New Pre-Upgrade / Update Checks

2. Foundation Joins the Party: Upgrade Nutanix Foundation in Parallel to Other Upgrades with LCM

3. New Platform-Wide Secure ESXi Upgrade Support in LCM

4. Inventory Checks at Ludicrous Speed

5. LCM Final Mentions

Here’s a description on how LCM fits into the Nutanix ecosystem:

Let me bring you into my life with my 8-year-old in a nutshell:

“Dad!” … “DAAAADDDD!”

I shouldn’t assume anything with kids, but it becomes almost automatic.

“Yes?”

“Check you texts!”

She’s snickering as I switch apps and see her emoji face requesting more time on Roblox.

Multiple things go through my head when I see this:

1. What time is it?

2. How much screen time has she had today?

3. Is it a school day?

4. Am I doing something I need to focus on that more time would help me accomplish?

5. Where’s her mother, lol

I take inventory: 7:10 pm on a Wednesday, 50min until bed, and I’m on Reddit as my wife puts my toddler down.

I brace for it: The incoming barrage and attempt to convince me WHY she needs more time, sometimes followed by a tantrum. She’s mine so that Hulk is lurking right below the surface, which when unleashed, turns my logical brain into a primordial soup of emotion. Not great to get to an 8-year-old’s level.

I deny the request and send a signature gif of my reaction:

“DAAAADDDDD WHYYY?!”

Before I can answer, I hear her laughing-a good sign. And. Here. We. Go! The Apple iMessage text bubbles start churning as we get into a GIF war.

“Get yer pitchforks!”

So before I start getting blasted by the infinite gradient of the online consortium of we-know-what’s-best-a-crew, I understand where I sit inside the circle of parental judgment.

I won’t bother with statistics to prove my point (though this article from the Mayo Clinic is pretty good), but here are a few anecdotes from a viewpoint of a new world as I see it, and honestly, it comes back to a fundamental of how we learn: Trust but verify.

• Deny screens?

  • Denying screens these days feels like social suicide and borderline irresponsible. The bottom line is they’ll get it from somewhere - a friend, etc. Closing off this ubiquitous part of our lives only creates a ‘rubber band’ of pent-up energy to navigate a digital landscape that’s extremely dangerous without guidance and help.

• Allow All screens?

  • This is giving up, plain and simple. I don’t see any difference between this and denying everything, this just backloads the issues whilst denying everything frontloads the drama. Regardless, unfettered access has its risks. Sure, many live in an Instagram/Facebook society where their lives are cataloged from everything they eat down to their kids’ interactions multiple times a day.
    
    The effect is a child who sees a screen as a normal outlet for their lives (not bad), but human nature takes over, and not managing what they’re doing puts them at risk of destroying their lives online in the future.
    
    It’s also easy to get out of parenting this way.

• Put effort into managing screens?

  • Not a perfect solution and it will cut DEEP into your personal solitude, but providing digital guardrails ensures some KEY things:

    • Starting young, this creates a necessity to come to you for their digital needs.

    • It creates rhetoric between you and them on what they’re doing

    • It helps you understand their technology abilities (no more, “Not my Billy! He doesn’t even know what a (insert device) is!”

    • Most importantly, it creates a feedback mechanism for them to explore somewhat safely.

This next part isn’t cheap, nor can I say it’s for everyone, but I have landed on a decent system. I’ve tried Amazon’s and now Apple’s controls. I also am an ‘expert’ (lmao) on Chromebooks and Nintendo Switches.

We moved from Amazon to Apple because, well:

1. My wife and I have iPhones, and so do our extended family and good friends.

2. It is more secure with things like encrypted iMessage, recovery options in case of an incident, health alerts, contact controls, screen controls, etc.

3. The parental controls are streamlined into the iOS software - no extra apps to download and manage.

4. We wanted to expand our daughter’s ability to communicate with her family (we live away from all of them) but without opening her up to the world.

5. We see an Apple Watch in her future with cellular far before she gets a phone-call text, without social media and web capabilities anywhere.

So get your pitchforks, post-COVID, this world is undeniably connected. I’d rather navigate it WITH my kids than at a distance.

But what’s in store?

“Into the unknown!”

God, ‘Frozen’ got it right. (Apologies for bringing that into your head. If you know, you know.)

Looking forward requires us to look backward. Consider this:

• The iPhone has been out a bit less than 16 years (2007)

• The public cloud’s rise to dominance only started around 10 years ago (2013).

• COVID hit the world three years ago (2020) requiring many to work remotely for months. Even today, hybrid work is the norm.

In fewer years than most of us have been alive, we’ve seen a transformation only compared to the rise of the internet. And before that, the rise of digital computation.

We’re hitting an exponential stride leaving linear growth behind. What does this mean for our children and ourselves? In reality, the foundational technologies of the next 20 years are already in motion.

Ever wonder why common technologies like the microwave or air travel seem to have stagnated in our minds when we compare them to social media or the smartphone? It’s a compounded cycle of exponential adoption built on previous innovations.

Sooner, not later, this model will ‘tip’, and new inventions we’ve not heard of will already be predominant and ubiquitous.

Case in point, ChatGPT, the AI chatbot that was released in November of 2022, only to have 100M users interface with it just two months later in January 2023.

These advances should be unleashing humankind from menial tasks, but instead are being exploited through socioeconomic models like capitalism allowing those with the means to grow more powerful.

We stand at a precipice for our existence: Do we allow ourselves to become enslaved by the very technology we’ve created to liberate us? Or do we let go and refocus on the greater unknown?

I think frequently of the Kardashev scale on our place in breaking through its model. I wonder how many other civilizations strewn across our young universe have also gotten to this point; only ~14 billion years old with a life span of trillions of years to go. Are we on a trajectory to become stellar dust and join the others? Or are we something more? Is the more? Are there others?

And here I sit, contemplating a digital request from my daughter, a few feet away to interact with a digital world on a device that didn’t exist a few years ago.

It’s time we teach responsibility. It’s time we enable ourselves to do more.

End of line.

Through those windows the steep gulley rises suddenly to meet our rear property. Hidden among the salal and blackberry thickets, some clearings pierce through the wilds to provide a semblance of order. Here, you can meet the forest and behold the terrain as it clings to the earth.

Rising up suddenly from this deluge are numerous madrona trees identified by their contrasting bark of gold and red. Unique to these are a trait where the majority of a madrona is near leaf-less and branch-less except for the very top. Non-deciduous by nature, their leaves are always green, but the tree itself requires a salty maritime climate to thrive. Some are new, some are old. The old ones are gray lifeless. Like large crooked canes they reach to the sky and have no leaves. Many have had their tops sheered off due to wind and time and stand like great thick sticks in mud.

These winter months tend to merge and melt together with only events to separate the time from week to week. Your sense of presence becomes distorted and compressed. Then, even as spring emerges, all memory of this epoch is shelved and a new season takes hold with instant benefits thwarting any thoughts of dismay.

And I remain, an observer to denote.

As my years roll on, I notice a kinship to how my brain works like these seasons. I compress monotony longing for a spark of life only to deride said opportunity because I’d rather dwell on its insignificance or shew it to the past thinking another will reveal itself. There will be other seasons, I say; other canvases; other days. And so, my justification turns to inaction creating a rot of living.

Is that harsh? Is it too condemning of my disposition? Perhaps, and yet I am an observer careening towards an empty end. Perfection has become my enemy. Why dream? Why hope? Why reach? A subtle depression, this mindset is relentless.

As I recall this madness, a small sliver takes hold. A speck of gold at the bottom of a forgotten barrel. I would not have found it without a total descent to the bottom. And yet, here it is, a radical and nuanced glimmer. I know what I must do.

I vow a reform to embrace the warmth of happiness. And not a faux whisper, but a total approach to stay true to the cause. I’ve feared this pursuit, because, like the onslaught of wild surrounding my home, I’ve denied my being thinking all is sabotaged in irony. But this is false.

The beauty of the winter isn’t the hope of the rise of spring, it’s the solemn desire to remain and refocus, to reflect and renew.