As data centers grow to run larger artificial intelligence (AI) models to feed a breakneck adoption rate, the electricity needed to power vast numbers of GPU-filled servers is skyrocketing.

The compute capacity needed to power AI large language models (LLMs) has grown four to five times per year since 2010, and that includes the biggest models released by OpenAI, Meta, and Google DeepMind, according to a study by Epoch AI, a research institute investigating key AI trends.

AI service providers such as Amazon Web Services, Microsoft, and Google have been on the hunt for power providers to meet the growing electricity demands of their data centers, and that has landed them squarely in front of nuclear power plants. The White House recently announced plans to support the development of new nuclear power plants as part of its initiative to increase carbon-free electricity or green power sources.

AI as energy devourer

The computational power required for sustaining AI’s rise is doubling roughly every 100 days, according to the World Economic Forum (WEF). At that rate, the organization said, it is urgent for the progression of AI to be balanced “with the imperatives of sustainability.”

“The environmental footprint of these advancements often remains overlooked,” the Geneva-based, nongovernmental organization think tank stated. For example, to achieve a tenfold improvement in AI model efficiency, the computational power demand could surge by up to 10,000 times. The energy required to run AI tasks is already accelerating with an annual growth rate between 26% and 36%.

“This means by 2028, AI could be using more power than the entire country of Iceland used in 2021,” the WEF said.

Put simply, “AI is not very green,” said Jack Gold, principal analyst with tech industry research firm J. Gold Associates.

Large language models (LLMs), the algorithmic foundation for AI, train themselves on vast amounts of data scoured from the internet and other sources. It is the process of training AI models (i.e., LLMs) and not the act of chatbots and other AI tools offering users answers based on that data — known as “inference” — that requires the overwhelming majority of compute and electrical power.

And, while LLMs won’t be training themselves 100% of the time, the data centers in which they’re located require that peak power always be available. “If you turn on every light in your house, you don’t want them to dim. That’s the real issue here,” Gold said.

“The bottom line is these things are taking a ton of power. Every time you plug in an Nvidia H100 module or anyone’s GPU for that matter, it’s a kilowatt of power being used. Think about 10,000 of those or 100,000 of those, like Elon Musk wants to deploy,” Gold said.

The hunt for power heats up

As opposed to adding new green energy to meet AI’s power demands, tech companies are seeking power from existing electricity resources. That could raise prices for other customers and hold back emission-cutting goals, according The Wall Street Journal and other sources. 

According to sources cited by the WSJ, the owners of about one-third of US nuclear power plants are in talks with tech companies to provide electricity to new data centers needed to meet the demands of an artificial-intelligence boom.

For example, Amazon Web Services is expected to close on a deal with Constellation Energy to directly supply the cloud giant with electricity from nuclear power plants. An Amazon subsidiary also spend $650 million to purchase a nuclear-powered data center from Talen Energy in Pennsylvania, and it plans build 15 new data centers on its campus that will feed off that power, according to Pennsylvania-based The Citizen’s Voice.

One glaring problem with bringing new power online is that nuclear power plants can take a decade or more to build, Gold said.

“The power companies are having a real problem meeting the demands now,” Gold said. “To build new plants, you’ve got to go through all kinds of hoops. That’s why there’s a power plant shortage now in the country. When we get a really hot day in this country, you see brownouts.”

The available energy could go to the highest bidder. Ironically, though, the bill for that power will be borne by AI users, not its creators and providers. “Yeah, [AWS] is paying a billion dollars a year in electrical bills, but their customers are paying them $2 billion a year. That’s how commerce works,” Gold said.

“Interestingly enough, Bill Gates has an investment in a smallish nuclear power company that wants to build next-generation power plants. They want to build new plants, so it’s like a mini-Westinghouse,” Gold said. “He may be onto something, because if we keep building all these AI data centers, we’re going to need that power.”

“What we really need to do is find green AI, and that’s going to be tough,” Gold added.

Amazon said it has firmly set its sights on renewable energy for its future and set a goal to reach net-zero carbon emissions by 2040, ten years ahead of the Paris Agreement. The company, which is the world’s largest purchaser of renewable energy, hopes to match all of the electricity consumed by its operations with 100% renewable energy by 2025. It’s already reached 90%, according to a spokesperson.

“We’re also exploring new innovations and technologies and investing in other sources of clean, carbon-free energy. Our agreement with Talen Energy for carbon-free energy is one project in that effort,” the Amazon spokesperson said in an email response to Computerworld. “We know that new technology like generative AI will require a lot of compute power and energy capacity both for us and our customers — so while we’ll continue to invest in renewable energy, we’ll also explore and invest in other carbon-free energy sources to balance, including nuclear.

“There isn’t a one-size-fits-all solution when it comes to transitioning to carbon-free energy, and we believe that all viable and scalable options should be considered,” the spokesperson said.

AI as infrastructure planner

The US Department of Energy (DOE) is researching potential problems that may result from growing data center energy demands and how they may pose risks to the security and resilience of the electric grid. The agency is also employing AI to analyze and help maintain power grid stability.

The DOE’s recently released AI for Energy Report recognized that “AI itself may lead to significant load growth that adds burden to the grid.” At the same time, a DOE spokesperson said, “AI has the potential to reduce the cost to design, license, deploy, operate, and maintain energy infrastructure by hundreds of billions of dollars.”

AI-powered tools can substantially reduce the time required to consolidate and organize the DOE’s disparate information sources and optimize their data structure for use with AI models.

The DOE’s Argonne Lab has initiated a three-year pilot project with multiple work streams to assess using foundation models and other AI to improve siting, permitting, and environmental review processes, and help improve the consistency of reviews across agencies.

“We’re using AI to help support efficient generation and grid planning, and we’re using AI to help understand permitting bottlenecks for energy infrastructure,” the spokesperson said.

The future of AI is smaller, not bigger

Even as LLMs run in massive and expanding data centers run by the likes of Amazon, IBM, Google, and others are requiring more power, there’s a shift taking place that will likely play a key role in reducing future power needs.

Smaller, more industry- or business-focused algorithmic models can often provide better results tailored to business needs.

Organizations plan to invest 10% to 15% more on AI initiatives over the next year and a half compared to calendar year 2022, according to an IDC survey of more than 2,000 IT and line-of-business decision makers. Sixty-six percent of enterprises worldwide said they would be investing in genAI over the next 18 months, according to IDC research. Among organizations indicating that genAI will see increased IT spending in 2024, internal infrastructure will account for 46% of the total spend. The problem: a key piece of hardware needed to build out that AI infrastructure — the processors — is in short supply.

LLMs with hundreds of billions or even a trillion parameters are devouring compute cycles faster than the chips they require can be manufactured or upscaled; that can strain server capacity and lead to an unrealistically long time to train models for a particular business use.

Nvidia, the leading GPU maker, has been supplying the lion’s share of the processors for the AI industry. Nvidia rivals such as Intel and AMD have announced plans produce new processors to meet AI demands.

“Sooner or later, scaling of GPU chips will fail to keep up with increases in model size,” said Avivah Litan, a vice president distinguished analyst with Gartner Research. “So, continuing to make models bigger and bigger is not a viable option.”

Additionally, the more amorphous data LLMs ingest, the greater the possibility of bad and inaccurate outputs. GenAI tools are basically next-word predictors, meaning flawed information fed into them can yield flawed results. (LLMs have already made some high-profile mistakes and can produce “hallucinations” where the next-word generation engines go off the rails and produce bizarre responses.)

The solution is likely that LLMs will shrink down and use proprietary information from organizations that want to take advantage of AI’s ability to automate tasks and analyze big data sets to produce valuable insights.

David Crane, undersecretary for infrastructure at the US Department of Energy’s Office of Clean Energy, said he’s “very bullish” on emerging designs for so-called small modular reactors, according to Bloomberg.

“In the future, a lot more AI is going to run on edge devices anyways, because they’re all going to be inference based, and so within two to three years that’ll be 80% to 85% of the workloads,” Gold said. “So, that becomes a more manageable problem.”

This article was updated with a response from Amazon.

Around and around Starliner goes, and when it comes down, nobody knows. What we do know is that thanks to poor development and engineering, Boeing’s stock will come down soon.

I remember a time when Boeing was one of the top American companies. Indeed, it was the very model of a modern technology enterprise. Then things changed. In 1997, after its merger with McDonnell Douglas, the company prioritized financial engineering over actual engineering and MBAs over aeronautic engineers.

Thereafter, one questionable decision after another was made, and corners were cut. The result? A once-proud American manufacturer is now better known for fatal crashes of its 737 Max 8 planes in 2017 and 2018 and this year’s explosive midflight loss of a 737 Max 9 door plug. These are the results of bad engineering and lousy quality assurance.

Now, as I write this, I see that Boeing’s Starliner spaceship remains parked at the International Space Station. When will it come down bearing its astronauts, Butch Wilmore and Suni Williams? I don’t know. They certainly don’t know. None of us know.

Just don’t say they’re stranded. Boeing’s vice president for its Commercial Crew Program, Mark Nappi, insists, “We’re not stuck on the ISS.” Uh, folks, they’re stranded, and the astronauts are stuck.

I doubt very much that they’ll be coming down on Starliner. Just getting to ISS, five of Starliner’s 28 thrusters stopped working due to helium leaks. NASA engineers got four thrusters to work again … and discovered four more leaks. That’s five known leaks to date.

While the astronauts get more time in space than they ever planned, down here on Earth at NASA’s White Sands Test Facility in New Mexico, they’re testing an identical thruster to work out what’s going on and how to fix it.

I wish them luck. Personally, you couldn’t get me back on Starliner for love or money. I worked at NASA’s Goddard Space Flight Center (GSFC) mission control during the Challenger disaster. That was more than bad enough.

Instead, I suggest the astronauts hitch a ride with the SpaceX Dragon Crew-9, which is still docked at ISS.  

This episode may be the straw that will break Boeing’s back.

Lessons for tech leaders

What does all this have to do with your business and technology? A lot.

What your company does may not be a matter of life and death, but your customers still expect you to do your best for them, not your stockholders. For too long, businesses have labored under the delusion that shareholder wealth is more important than the creation of stakeholder value.

The result is that companies prioritize their next quarter’s results over the overall health of their business. Specifically, Boeing didn’t just cut the fat from its teams; it also cut and outsourced its muscle. Financial engineering should never trump actual engineering. 

For example, quality assurance went out the window. Instead of testing, testing, and then testing again, Boeing neglected this fundamental principle of both software and hardware engineering. Make sure you don’t.

In particular, if something is mission-critical, treat it that way!

Take, for example, the very fuselages of the 737s. In 2005, Boeing cut costs by selling its Witchica-based manufacturing site to Onex, a private equity firm that buys struggling businesses, slashes costs, and resells them. There went years of experience and a quality-first culture.

That plant would re-emerge as Spirit AeroSystems, Boeing’s third-party manufacturing partner. Whether Boeing overseeing its quality assurance would have improved anything is an open question, but there can be no doubt that Spirit’s products were shoddy and second-rate under a cost-saving mandate.

Never, ever outsource mission-critical work. What Boeing used to do best was engineering and manufacturing. I don’t know what your company does best, but neglecting your expertise to cut costs is a fool’s move.

Now Boeing has repurchased Spirit for about $8.3 billion. The company finally has figured out it can’t fix its problems without fixing its fundamental manufacturing problems. Somehow, I think Boeing would have done better if it’d never spun out its major manufacturing side in the first place.

The moral of the story? Never let MBAs driven by the bottom line take over an engineering company building airplanes and spaceships. The same’s true for your company. Yes, make profits for your owners, but never forget that long-term success comes from putting quality work for your customers first.

More by Steven J. Vaughan-Nichols:

• What happens when genAI vendors kill off their best sources?
• The end of non-compete agreements is a tech job earthquake
• Return-to-office initiatives or stealth layoffs? Why not both?

Content distribution network Cloudflare is making it simpler for customers who have had enough of badly behaved bots to block them from their website.

It’s long been possible to prevent well-behaved bots from crawling your corporate website by adding a “robots.txt” file listing who’s welcome and who isn’t — and content distribution networks such as Cloudflare offer visual interfaces to simplify the creation of such files.

But faced with the arrival of a new generation of badly behaved AI bots, scraping content to feed their large language models, Cloudflare has introduced an even quicker way to block all such bots with one click.

“The popularity of generative AI has made the demand for content used to train models or run inference on skyrocket, and although some AI companies clearly identify their web scraping bots, not all AI companies are being transparent,” Cloudflare staff wrote in a blog post.

According to authors of the post, “Google reportedly paid $60 million a year to license Reddit’s user generated content, Scarlett Johansson alleged OpenAI used her voice for their new personal assistant without her consent, and most recently, Perplexity has been accused of impersonating legitimate visitors in order to scrape content from websites. The value of original content in bulk has never been higher.”

Last year, Cloudflare introduced a way for any of its customers, on any plan, to block specific categories of bots, including certain AI crawlers. These bots, said Cloudflare, observe requests in sites’ robots.txt files, and do not use unlicensed content to train their models, nor gather to feed for retrieval-augmented generation (RAG) applications.

To do this it identifies bots by their “user-agent string” — a kind of calling card presented by browsers, bots and other tools requesting data from a web server.

“Even though these AI bots follow the rules, Cloudflare customers overwhelmingly opt to block them. We hear clearly that customers do not want AI bots visiting their websites, and especially those that do so dishonestly,” the post said.

The top four AI webcrawlers visiting sites protected by Cloudflare were Bytespider, Amazonbot, ClaudeBot and GPTBot, it said. Bytespider, the most frequent visitor, is operated by ByteDance, the Chinese company that owns TikTok. It visited 40.4% of protected websites, and is reportedly used to gather training data for its large language models (LLMs), including those that support its ChatGPT rival Doubao. Amazonbot is reportedly used to index content to help Amazon’s Alexa’s chatbot answer questions, while ClaudeBot gathers data for Anthropic’s AI assistant Claude.

Blocking bad bots

Blocking bots based on their user-agent string will only work if such bots tell the truth about their identity — but there are signs that not all do, or not all the time.

In such cases, other measures will be necessary — and enterprises’ main recourse against unwanted web scraping is normally reactive: pursue legal action, according to Thomas Randall, director of AI market research at Info-Tech Research Group.

“While some software applications exist for web scraping prevention (such as DataDome and Cloudflare), these can only go so far: if an AI bot is rarely scraping a site, the bot may still go undetected,” he said via email.

To justify legal action against the operators of bad bots, enterprises will need to do more than claim that the bot didn’t leave when asked.

The best course of action, Randall said, is for “enterprises to hide intellectual property or other important information behind a membership paywall. Any scraping done behind the paywall is liable for legal action, reinforced with a clear restrictive copyright license on the site. The organization must, therefore, be prepared to legally follow through. Any scraping done on the public site is accepted as part of the organization’s risk tolerance.”

Randall noted that if organizations have the resources to go further, they could consider rate-limiting connections to their site, temporarily automatically blocking suspicious IP addresses, limiting information on why access has been blocked to a message such as “For help, contact support via [email protected]” in order to force a human interaction, and double-checking how much of their websites are available on their mobile site and apps.

“Ultimately, scraping cannot be stopped, but hindered at best,” he said.

Losing your phone is one of the most stressful predicaments of modern-day life. We’ve all been there: You pat your pocket, swiftly scan every surface in sight — then suddenly feel your heart drop at the realization that your Android device and all of its contents (including, potentially, all sorts of sensitive company-connected materials) are no longer in your control.

There’s certainly no scenario in which losing your phone is a good thing. (Understatement of the century, I realize.) But with the advanced and just recently upgraded phone-finding system now built into Android at the operating system level, seeking out and then managing a missing device is more manageable than ever. And despite what some security suite services may try to convince you, you don’t need any third-party software to do it.

Android’s native Find My Device system can precisely pinpoint any Android device — phone, tablet, watch, you name it. It also works with a new series of special AirTag-like trackers that can be attached to keys, briefcases, and other important items. And it’ll show you your device’s exact location on an interactive map and — when relevant — give you tools to remotely ring it, lock it, or wipe it entirely and send all of its data to the digital beyond.

Best of all? You have to do shockingly little to get it up and running. It’s mostly just a matter of confirming that the system is active and then remembering how to tap into it if and when the need ever arises.

So take a few minutes now to learn the ins and outs of how the new Find My Device network on Android works and what it takes for your devices to be discoverable. Then, if you ever have that heart-dropping moment, your phone will be 100% ready — and so will you.

[Get Googley goodness in your inbox every Friday with my free Android Intelligence newsletter. Three new things to know and try each Friday!]

Find My Device on Android, part I: Preparation

Most reasonably recent Android phones should be actively enrolled in Google’s Find My Device Android network by default, but there are a few critical settings that are worth double-checking to confirm everything’s connected.

First, head into the Location section of your Android device’s system settings and make sure the toggle at the top of the screen is turned on. If it isn’t, Android won’t be able to access your phone’s GPS and thus won’t be able to perform any Find My Device-related location functions.

Next, pull up the Google section of your phone’s system settings and scroll down to the line labeled “Find My Device.” Tap that, then make sure the “Use Find My Device” toggle on the screen that comes up next is activated. And last but not least, tap “Find your offline devices” and consider which of the available options seems most suitable for you and your future finding purposes.

JR Raphael, IDG

All set? Good. Now, let’s break down what your options are when that dreaded moment becomes reality.

Find My Device on Android, part II: Action

The best part about Android’s Find My Device system is that, being a Google product, it’s easily accessible from almost anywhere. If you ever can’t find your phone, choose the most convenient option and go, go, go:

1. Use the Find My Device Android app on another phone or tablet

Got an Android tablet — or maybe a secondary phone for some specific purpose? Install the Find My Device Android app on it. In fact, go ahead and do that on all your active Android devices this minute so the app will be there and ready in case you ever need it. As long as you’re signed into the same Google account on the secondary device as you are on your primary phone, finding your phone will be as simple as opening the app, confirming your Google password, and then selecting your phone from the list on the app’s main screen.

JR Raphael, IDG

From there, you’ll see your phone’s last known location on a zoomable map. And you’ll be able to ring it — for a full five minutes at a time, even if it’s set to silent — and optionally lock it or erase it as needed.

No secondary Android device? No problem: If you have a friend or family member with an Android phone or tablet nearby, kindly ask them to install the Find My Device app onto their device. Open it and find the option to sign in as a guest. Type in your Google account credentials, and then take a deep breath: Everything you need to find your phone will be right at your fingertips.

(Side note: The Find My Device Android app is strictly about finding a missing device — nothing more. It doesn’t actually have to be on your device in order for the device itself to be discoverable.)

2. Pull up Android’s Find My Device website in a browser

If you don’t have another Android device handy, you can still get to Android’s Find My Device function from any web browser — on a laptop or desktop computer or even an iPhone or iPad.

The main Android Find My Device site is at google.com/android/find. It’s basically identical to what you’ll get in the Find My Device Android app:

JR Raphael, IDG

You can also find an alternate version of the Android Find My Device function within Google’s My Account site. That site provides the same basic info but seems to go back further in your device history — so if you’re looking for a device you haven’t used in a while and that device doesn’t come up on the main Android Find My Device site, you might give it a whirl to see if it shows up there.

And that, my friend, is all there is to it. Consider yourself protected — and you know what? Go get yourself a cookie. You’ve earned it.

Want even more Googley knowledge? Come check out my free Android Intelligence newsletter to get three new things to know and try in your inbox every Friday.

More Android tips:

• 30 out-of-sight Android app shortcuts worth surfacing
• Supercharge your Android lock screen — no Android 15 required
• 6 secret settings for a smarter Chrome Android setup

Independent experts have urged businesses to think carefully before relying on third-party support for security patches once Windows 10 reaches its end of life in October 2025.

Upgrading from Windows 10 may be challenging for some businesses, because many older PCs may not meet the minimum system requirements for Windows 11. Some software or applications may not be compatible with Windows 11, forcing users to stick with Windows 10 or find alternatives.

In addition, point-of-sale (POS) terminals running Windows 10 may be difficult to upgrade, presenting a particular challenge for IT professionals in the retail and hospitality sectors.

As with the retirement of previous versions of Windows, Microsoft is offering enterprises extended support for Windows 10. For commercial customers and small businesses, this comes in at $61 per device in the first year, doubling to $122 per Windows 10 device in year two and $244 per device for the third and final year.

Organizations using cloud-based update management enjoy cost savings, with prices of $45 per user with up to five devices in the first year. There’s a big discount for educational institutions, which can get extended support for a total of $7 over the maximum of three years.

Microsoft’s Extended Security Updates offers monthly critical and important security updates to Windows 10 but without access to any new features and only for up to three years.

Micro-patching alternative

Acros, a Slovenian company specializing in security updates, announced Wednesday that it will offer enterprise users of Windows 10 extended support under its 0patch brand for up to five years at a lower cost than Microsoft.

For medium and large organizations, 0patch Enterprise includes central management, multiple users and roles, and comes in at €35 (around $38) per device per year, excluding tax. A cut down version pitched at small business and individuals, 0patch Pro, costs €25 plus tax per device per year.

0patch uses a system of “micro-patches” to address critical vulnerabilities, an approach touted as faster and offering a lower potential for system instability. The vendor has previously offered extended support for Windows 7 and Windows 8.

The company said it may offer fixes for vulnerabilities that Microsoft leaves unpatched, while also providing patches for non-Microsoft products (such as Java runtime, Adobe Reader etc.), as explained in a blog post.

Gauging risk to reward

Rich Gibbons, head of market development at IT asset management specialist Synyega, noted that third-party support is an established part of the enterprise software market.

“Businesses regularly bring in third parties to help patch and maintain their legacy Oracle, SAP, and IBM estates, and while it’s not as common with Microsoft, it’s still a legitimate option, and one worth assessing,” Gibbons said.

“Purchasing extended support packages from Microsoft is expensive and will only go up in price each year. It’s therefore little wonder that more cost-effective options like those offered by 0patch are beginning to gain traction,” Gibbons added.

He advised companies to conduct a full risk-reward analysis to understand if the cost savings are worth selecting alternatives like 0patch rather than purchasing extended support from Microsoft or biting the bullet and upgrading their systems.

Leaving Microsoft’s ecosystem

Javvad Malik, lead security awareness advocate at KnowBe4, also urged companies to be careful about opting for third-party support rather than facing the financial and operational burdens of a significant overhaul.

“The viability of turning to a third-party for extended support, as opposed to embarking on the arguably Herculean task of retooling apps and refreshing hardware to embrace Windows 11, is, on the surface, an attractive proposition,” Malik told Computerworld. “However, engaging with a third party for security patches introduces a layer of dependency beyond the control of Microsoft’s established ecosystem.”

Malik warned that relying on extended support for an extended period might make it more difficult to upgrade in the future.

“Upgrading from one version to the next is relatively simple when considering upgrading two or more versions up from the current version of any software. So, the cost of delaying an upgrade needs to be evaluated in totality, and not just as a comparison to an upgrade today,” Malik advised.

In response to this criticism, 0patch co-founder Mitja Kolsek told Computerworld that deferring a costly Windows upgrade can be beneficial, while admitting that enterprises have to move on eventually.

“While an upgrade may eventually be inevitable for functional and compatibility reasons, we’re making sure that you’re not forced to upgrade because of security flaws that the vendor won’t fix anymore,” Kolsek explained. “At the same time, five years is a long time and a lot can happen — maybe you’ll be able to skip a version, or start using some other tool altogether.”

From the editors of Computerworld, this enterprise buyer’s guide helps IT and business staff understand what the various types of business projectors can do for their organizations and how to choose the right solution.

News that VMware’s former End User Computing (EUC) division is now officially called Omnissa — and that reference to the former was mentioned only in a footnote in the firm’s press release — is not surprising at all, said Shannon Kalvar, research director of virtual client computing at IDC.

Yesterday marked the official launch of the new organization, now owned by Menlo Park, Calif.-based KKR. The global investment firm paid $4 billion for VMware’s EUC division in a deal announced in late February, only a few months after Broadcom’s $69 billion acquisition of VMware was finalized. The EUC division purchase included Horizon, a desktop and application virtualization platform, and Workspace One, a unified endpoint management platform for the enterprise.

Instead of dwelling on the past, the Omnissa executive team, which includes Shankar Iyer as the firm’s CEO and who formerly headed up the VMware EUC division, has an opportunity to “come out and really lay out a vision for end user computing in an era where companies are increasingly very much digital and becoming AI driven,” Kalvar said.

“By that, I don’t mean all the excitement about LLMs,” he added. “But there have been tremendous advancements in hundreds of different kinds of models for predictive and interpreted analytics, for all kinds of things,” he said.

There is, he said, also an opportunity to say, “OK, we are stable now, but we can go further, we can do more.”

John Annand, practice lead at Info-Tech Research Group, said that as “Broadcom has continued its attempts to mend fences following the acquisition of VMware, we now finally know the outcome of the division they did not want to take into the new partnership.”

Annand described Omnissa as a company that is “aggressively looking to retain the former VMware client base by appealing to the goodwill VMware used to have in both the enterprise and reseller partner space. Senior staff in operations, engineering, marketing, product, and, of course, the new CEO, Shankar Iyer, are all familiar faces for those who took the EUC track at past VMWorld conferences.”

Combine these staff choices, he said, with the “vision and value statements, and the messaging seems clear: ‘We will be the company you used to like doing business with.’”

Omnissa is “wasting no time reaching out to industry analysts to schedule briefings and invite us to attend their Omnissa Live conference” on July 23, Annand said.

“I imagine over the next 20 days, in the lead-up to their conference, we’ll begin to get a sense of their partner program and pricing models. Certainly, these are topics that are foremost on the minds of former VMware customers. And whatever goodwill Omnissa hopes to retain will depend on a large part of how they respond to these questions.” 

Position-wise, said Annand, “this is a great time for them, and it makes a lot of sense for them to move quickly. Citrix recently had to go back to the well in order to raise some more cash and is aggressively ‘evaluating’ its customer portfolio, which is to say focusing on strategic ones at the expense of nonstrategic ones. And while Microsoft continues to reimagine what an entirely cloud-native desktop experience might look like, enterprises need solutions that work with existing software and devices today and not just into the future.”

Annand added that the need for desktop and app virtualization, as well as end-user device management, “has not gone away by any means. Zero-trust and security requirements across all the different form factors, manufacturers, and operating systems we put in front of workers these days have exponentially increased the operational complexity of enterprise IT.”

The challenge for Omnissa will be, he said, “do they bring the same bag of well-rehearsed tricks to the party, or can they, without legacy VMware hanging around their necks, do something truly innovative? If not, then at least we’ll have some competition as Microsoft continues to win the EUC space by default.”

Forrester principal analyst Naveen Chhabra noted in an email, “Companies that use VMware EUC products and plan to continue to do so will have to deal with Omnissa for continued support unless they need no more vendor support. Support is critical for most large organizations for functionality, performance, and security reasons.”

Chhabra noted that VMware customers have had to navigate a lot of change, first adjusting to the Broadcom acquisition and then to EUC division’s sale to KKR. And they’re not done yet.

“Omnissa is a new company, new leadership. Clients will have to learn how to work with a new company, new policies, new roadmap, new licensing,” he said. “So it is not going to be as easy or straightforward as one may want or like. There are credible alternatives from vendors like HCL, Microsoft, IBM, and Ivanti, but, as always, transition/migration is not going to be pain-free.”

China aims to be among the first countries to begin developing standards for the future of brain-computer interfaces with the establishment of a new technical committee by its Ministry of Industry and Information Technology specifically for this purpose.

The ministry’s Brain-Computer Interface Standardization Technical Committee is currently fielding opinions and ideas on various issues associated with the technology and standards that the country already has set for its development, according to a press release published online by the Ministry.

These include developing and revising basic standards not only for the technology’s technical aspects, but also to hammer out issues around ethics and safety — which become increasingly more critical as technology that pushes boundaries for human-machine interaction advance.

The newly formed standards committee is currently soliciting comments regarding topics such as the “typical paradigms” of brain-computer interfaces; input and output interfaces such as brain information collection and preprocessing; and brain information encoding and decoding, data communication, and data visualization.

It’s also formulating and revising technical standards and test specifications for brain-computer interfaces in various fields, including medical, health, education, industry, and consumer electronics. It also will consider ethics and safety aspects such as the safety of emerging interface systems, as well as clinical applications of them.

Organizing standards leadership

Overall, the standards effort will attempt to create some kind of organization around stakeholders involved in China’s domestic brain-computer interface industry, including those in academia, research, and the tech industry itself.

The ultimate goals are “to focus on the hot spots of the industry and the needs of industry development, accelerate the research on the roadmap for the standardization of brain-computer interfaces, clarify the key directions and research and development priorities of brain-computer interface standardization, and coordinate and promote the formulation of brain-computer interface standards,” according to the release.

People have until July 30 to share their comments with the Science and Technology Department of the Ministry during the public announcement period.

The move supports China’s previously revealed three-year plan to establish itself as a global leader in computing standards, particularly for emerging technologies such as artificial intelligence. China is vying to strengthen its position in its ongoing technology race with the US and other nations taking the lead in tech that’s pushing the boundaries of how humans interact with machines.

Ethics to play a key role

While many technology standards efforts focus on interoperability, stewards for technologies such as AI and brain-computer interfaces — which push the boundaries of human-machine interaction — have a more pressing set of concerns, noted Brad Shimmin, chief analyst, AI & Data Analytics at Omdia. China’s new committee and groups such as the Institute of Electrical and Electronics Engineers (IEEE) in the US that seek to clarify these emerging standards will need to put ethical and safety considerations at the forefront of their agendas, he said.

“These organizations will be tasked with the difficult task of providing ethical guidance, providing a sustainable foundation upon which innovators can build solutions, as well as placing constraints on research and experimentation,” Shimmin said. “Such efforts can help to accelerate innovation while also ensuring that funded research conforms to the current socio-political expectations of the host country.”

Even with standards bodies such as the IEEE, the United States has historically encouraged aggressive research and experimentation with new technologies — up to a point, Shimmin noted. In the US, for example, Elon Musk’s brain-computer interface company Neuralink is currently in human trials with its surgically implanted brain chip, though it hit a snag this week when the second patient who was to receive the chip bowed out for medical reasons. As these trials evolve, however, organizations like the National Institutes of Health will continue to collaborate with lawmakers so they can step in to limit potentially dangerous research, he said.

Still, countries that can take a lead on the standardization of methods, interface mechanics, or materials used in creating human brain-computer interfaces, as well as the consideration of ethical issues, can “fuel national pride” that in turn drives investment in innovation and an influence on the global stage, Shimmin noted.

“Any country able to set the tone for highly impactful areas of innovation … can to a great degree shape the future of influence in that market, drawing in talented researchers and investors,” he said.

Still, no matter what standards bodies decide about human brain-computer interfaces, the pace of the technology will likely move very slowly — at least in the US, given that any meaningful use or market application will have to be approved by medical and healthcare regulators, experts said. This may give China’s standards efforts an edge if they are not limited by such a rigorous approval structure.