As the adoption of generative artificial intelligence (genAI) continues to soar, the infrastructure to support that growth is currently running into a supply and demand bottleneck.

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 genAI will see increased IT spending in 2024, infrastructure will account for 46% of the total spend. The problem: a key piece of hardware needed to build out that AI infrastructure is in short supply.

The breakneck pace of AI adoption over the past two years has strained the industry’s ability to supply the special high-performance chips needed to run the process-intensive operations of genAI and AI in general. Most of the focus on processor shortages has been on the exploding demand for Nvidia GPUs and alternatives from various chip designers such as AMD, Intel, and the hyperscale datacenter operators, according to Benjamin Lee, a professor in the Department of Computer and Information Science at the University of Pennsylvania.

“There has been much less attention focused on exploding demand for high-bandwidth memory chips, which are fabricated in Korea-based foundries run by SK Hynix,” Lee said.

Last week, SK Hynix said its high-bandwidth memory (HBM) products, which are needed in combination with high-performance GPUs to handle AI processing requirements, are almost fully booked through 2025 because of high demand. The price of HBMs has also recently increased by 5% to 10%, driven by significant premiums and increased capacity needs for AI chips, according to market research firm TrendForce.

HBM chips are expected to account for more than 20% of the total DRAM market value starting in 2024, potentially exceeding 30% by 2025, according to TrendForce Senior Research Vice President Avril Wu. “Not all major suppliers have passed customer qualifications for [high-performance HBM], leading buyers to accept higher prices to secure stable and quality supplies,” Wu said in a research report.

Why GPUs need high-bandwidth memory

Without HBM chips, a data center server’s memory system would be unable to keep up with a high-performance processor, such as a GPU, according to Lee. HBMs are what supply GPUs with the data they process. “Anyone who purchases a GPU for AI computation will also need high-bandwidth memory,” Lee said.

“In other words, high-performance GPUs would be poorly utilized and often sit idle waiting for data transfers. In summary, high demand for SK Hynix memory chips is caused by high demand for Nvidia GPU chips and, to a lesser extent, associated with demand for alternative AI chips such as those from AMD, Intel, and others,” he said.

“HBM is relatively new and picking up a strong momentum because of what HBM offers — more bandwidth and capacity,” said Gartner analyst Gaurav Gupta. “It is different than what Nvidia and Intel sell. Other than SK Hynix, the situation for HBM is similar for other memory players. For Nvidia, I believe there are constraints, but more associated with packaging capacity for their chips with foundries.”

While SK Hynix is reaching its supply limits, Samsung and Micron are ramping up HBM production and should be able to support the demand as the market becomes more distributed, according to Lee.

The current HBM shortages are primarily in the packaging from TSMC (i.e., chip-on-wafer-on-substrate or CoWoS), which is the exclusive supplier of the technology. According to Lee, TSMC is more than doubling its SOIC capacity and boosting capacity for CoWoS by more than 60%. “I expect the shortages to ease by the end of this year,” he said.

At the same time, more packaging and foundry suppliers are coming online and qualifying their technology to support NVIDIA, AMD, Broadcom, Amazon, and others using TSMC’s chip packaging technology, according to Lee.

Nvidia, whose production represents about 70% of the global supply of AI server chips, is expected to generate $40 billion in revenue from GPU sales this year, according to Bloomberg analysts. By comparison, competitors Intel and AMD are expected to generate $500 million and $3.5 billion, respectively. But all three are ramping production as quickly as possible.

Nvidia is tackling the GPU supply shortage by increasing its CoWoS and HBM production capacities, according to TrendForce. “This proactive approach is expected to cut the current average delivery time of 40 weeks in half by the second quarter [of 2024], as new capacities start to come online,” TrendForce report said in its report. “This expansion aims to alleviate the supply chain bottlenecks that have hindered AI server availability due to GPU shortages.”

Shane Rau, IDC’s research vice president for computing semiconductors, said that while demand for AI chip capacity is very high, markets are adapting. “In the case of server-class GPUs, they’re increasing supply of wafers, packaging, and memories. The increased supply is key because, due to their performance and programmability, server-class GPUs will remain the platform of choice for training and running large AI models.”

Chipmakers scramble to meet the demand for AI

Global spending on AI-focused chips is expected to hit $53 billion this year — and to more than double over the next four years, according to Gartner Research. So it’s no surprise that chipmakers are rolling out new processors as quickly as they can.

Intel has announced its plans for chips aimed at powering AI functions with its Gaudi 3 processors, and has said its Xeon 6 processors, which can run retrieval augmented generation (RAG) processes, will also be key. The Gaudi 3 GPU was purpose-built for training and running massive large language models (LLMs) that underpin genAI in data centers.

Meanwhile, AMD in its most recent earnings call, touted its MI300 GPU for AI data center workloads, which also has good market traction, according to IDC Group Vice President Mario Morales, adding that the research firm is tracking over 80 semiconductor vendors developing specialized chips for AI.

On the software side of the equation, LLM creators are also developing smaller models tailored for specific tasks; they require fewer processing resources and rely on local, proprietary data — unlike the massive, amorphous algorithms that boast hundreds of billions or even more than a trillion parameters.

Intel’s strategy going forward is similar: it wants to enable genAI on every type of computing device, from laptops to smart phones. Intel’s Xeon 6 processors will include some versions with onboard neural processing units (NPUs or “AI accelerators”) for use in workstations, PCs and edge devices. Intel also claims its Xeon 6 processors will be good enough to run smaller, more customized LLMs.

Even so, without HBMs, those processors would likely struggle to keep up with genAI’s high performance demands.

CIO.com (a sister publication) had an intriguing story about ChatGPT and a potential conflict with the European Union’s GDPR rules. The sad reality is that although the story accurately describes the EU issue, the GDPR kerfuffle amounts to barely a rounding error when it comes to generative AI (genAI) and how it is obliterating all compliance rules — especially those involving privacy.

Enterprise IT leaders have never had an especially strong mastery of IT visibility for apps, data and tools. But the instant a company welcomes genIA tools into its environment — an event that for most enterprises happened last year — they can kiss any beliefs that they still control their assets good-bye. And without comprehensive data control and strong data visibility, regulatory compliance is impossible.

Let’s start with the GDPR situation. As CIO.com explained it: “The EU’s strict privacy rules require that companies allow individuals access to personal information held about them, as well as ensuring that such data is accurate. This requires a long audit trail to every piece of information stored about European citizens. When it comes to AI-generated content, such trails often go cold. With regard to information generated by ChatGPT, (the entity suing) alleges there is no legal redress for so-called hallucinations when it comes to personal information.”

That’s true, but hallucinations are just the most obvious examples. The part of GDPR at issue here is the Right To Be Forgotten. If an EU citizen (5 million of whom live in the US) officially asks for something personal about them to be removed, companies are supposed to comply. 

Long before genAI, including the large language models that underpin it, became popularized, enterprise IT teams were already struggling to comply with such rules. The usual culprits for enterprise IT visibility issues are cloud, IoT, mobile, third-parties, remote sites including home offices and all manner of Shadow IT. 

The Right To Be Forgotten is simply not compatible with how modern enterprises function, especially in the United States. Let’s consider a typical scenario: you’re an analyst working for the marketing department and trying to make sense of some unusual customer patterns. It’s getting late, so you decide to finish number-crunching at home. So you back up the data to a personal cloud account for easy access at home later when you resume working. 

The next morning, on the train heading to the office, you remember something you wanted to try with the data. You access that cloud folder on your phone, do a little more analysis and then save the files.

When you get back to your desk, you download that file to your work desktop machine and continue working on the latest files. 

Think of the ways that data can go astray and be out of reach for IT. Your home computer uses a consumer-grade backup service, and overnight, those files were copied to that service. That consumer-grade backup service has its own offsite backup mechanisms, along with a separate disaster recovery service. That file with sensitive PII about customers is now in all those locations.

That sensitive data was also on your phone. That data also gets automatically backed up to that handset manufacturer, which also has its own backup and disaster recover arrangements. 

Two days later, an EU citizen (who happens to be one of your customers) submits a right to be forgotten request and your team eventually learns of it. They delete the references they can locate on key enterprise systems, including a half-dozen corporate cloud environments they know about. 

But what about all of those other locations? 

That example involves just an employee trying to get work done. Let’s try one with a customer or a prospect. One of your senior sales representatives is working with another company on $1 billion sales deal. They start discussing sensitive contract points in text threads between them and will likely also review preliminary contract drafts.

Once the draft gets to a late stage, it goes to the legal department and everything is hopefully captured. But what about all of those text discussions between two personal smartphones? Compliance is not only about regulatory issues. What if the deal later goes bad and there is litigation? The opposing counsel will seek discovery, including all discussions about contract terms. Are you even remotely able to fully comply? (I’ll save you time: No, there is no way you can fully comply.)

That was all true back in 2019. In 2020, the pandemic hit and cloud and remote activity soared. In 2023, genAI tools — which had been around in various forms since the 1960s — grabbed headlines and was suddenly on the must-have list of every enterprise board member. The less about AI decision-makers knew, the more they wanted genAI.

Full data visibility was difficult in 2019, virtually impossible in 2020, and now, with genAI cropping up in just about every division and working group, it’s crossed the line into fully impossible

Why does it so fully obliterate data control? There are five relevant elements, all distinct, :

1. What enterprise data can genAI access?
2. Who (among employees, contractors, customers and anyone with any level of privileged access) can access that data? Is there some attempt, any attempt, to limit who can access what segments of that data?
3. How was the genAI system trained? What information did it examine to answer queries? Did any of that training information include data about EU citizens? (Yes, EU data was almost certainly within the training set.) 
4. Is the genAI training on new data you share? Will it try and learn from your queries and potentially share that information with competitors?
5. What about the massive databases behind genAI tools. Can enterprises that license that system review the database? Can they delete details from it? If not — and the answer will almost always be “No” — how is GDPR compliance even possible? How is any compliance possible? 

With arrival of genAI virtually everywhere, the compliance genie is already out of the bottle.

If he hasn’t already, it’s past time for Apple CEO Tim Cook to gain a reputation for dry wit when it comes to handling preconceived opinion — he ladled out several helpings of this during Apple’s second-quarter fiscal call on Thursday. Though the company’s financials were down, they were still ahead of what Wall Street had anticipated.

Revenue for the quarter was $90.8 billion, down 4% from the same quarter last year, but Apple’s gross margins increased to 46.6%, mainly on the strength of solid services increases.

Cook states the facts 

For me, one of his best lines during the presentation was captured in this exchange during analyst questions:

Wells Fargo analyst:  “I guess I’m going to go back to the China question. I guess at a high level, the simple question is, when we look at the data points that have been repeatedly reported throughout the course of this quarter, I’m curious, Tim, what are we missing? Where do you think people are missing Apple’s iPhone traction within the Chinese market?”

Tim Cook: “I can’t address the data points. I can only address what our results are. And we did accelerate last quarter and the iPhone grew in mainland China. So that’s what the results were. I can’t bridge to numbers we didn’t come up with.”

Translation: The analyst is confused because all the industry data points (IDC, Counterpoint, Gartner, Ming Chi Kuo) seem to have been inaccurate. Cook simply dismisses those estimates with the company’s actual results.

What happened in China?

What’s confusing here is that the company’s management report confirms weak iPhone sales in every segment — but in part this reflects one of those “difficult comparisons” the company likes to state. 

Think back to this time last year, when Apple was just emerging from what had been a very difficult time operationally. In the run up to this quarter a year ago, COVID-19 had closed the iPhone factories, meaning lots of smartphones weren’t being made, and order fulfillment was delayed. Apple told us then that it realized about $5 billion in iPhones sales in the quarter that would have been made in the preceding one. 

That’s not the case this year. “If you remove that $5 billion from last year’s results, we would have grown this quarter on a year-over-year basis,” Cook said. “And so that’s how we look at it internally from how the company is performing.” 

If that’s true, it explains why Apple doesn’t seem especially concerned that its iPhone sales internationally did decline by 10% in revenue in the quarter. After all, the iPhone was the top-selling smartphone model in the US, urban China, Australia, UK, France, Germany, and Japan. The device also achieved 99% customer satisfaction according to Changewave.

Managing change

Even though Cook told us that iPhone sales grew in China, both the Wall Street Journal and Nikkei insist sales fell there. In fact, the two best-selling smartphones in mainland China during the quarter were the iPhone 15 and 15 Pro Max, Apple confirmed during the presentation. 

Apple did concede that it has work to do on its other products, and iPhone sales were down in contrast to this time last year. Weakness was felt across multiple markets, and with the iPhone Apple’s biggest product, the impact of this and softening iPad sales contributed to revenue decline.

What is interesting is that in Japan and elsewhere in the APAC region, Apple sales seemed weak. That doesn’t mean there isn’t an appetite for the company’s products. Cook sees enthusiasm across the region: “Everywhere I travel, people have such a great affinity for Apple, and it’s one of the many reasons I’m so optimistic about the future,” he said. He also expressed his confidence in the long-term Apple market in China.

What about enterprise use?

Apple made a handful of references to enterprise sales, the majority of which pertained to its latest device, the Vision Pro headset. The company reported that over half of the world’s Fortune 100 companies have already bought Vision Pro units to explore what the device can do for their business. 

“We are seeing so many compelling use cases, from aircraft engine maintenance training at KLM to real-time team collaboration and immersive kitchen design at Lowes,” said Apple CFO Luca Maestri.

Apple also confirmed the ongoing rise of Macs in the enterprise. “More and more enterprise customers are embracing the Mac,” said Maestri.

In healthcare, Epic Systems, the world’s largest electronic medical record provider, recently launched its native app for the Mac, making it easier for healthcare organizations like Emory Help to transition thousands of PCs to the Mac for clinical use. “I think there’s a great opportunity for us around the world in enterprise,” said Cook.

A note on Europe

Two points seemed interesting:

• Apple anticipates solid services growth (which includes Europe) in the current quarter, despite the EU’s DMA act which is forcing it to change its App Store business model.
• With those changes, Apple said it’s too early to tell whether consumers or developers will migrate outside the App Store; its focus for now is on complying with the EU law while “mitigating the impacts to user privacy and security” of doing so.

One step beyond

Apple also discussed emerging markets. 

Maestri: “…When we start looking at places like India, like Saudi, like Mexico, Turkey, Brazil, Mexico and Indonesia, the numbers are getting large. And we’re very happy because these are markets where our market share is low. The populations are large and growing. And our products are really making a lot of progress within those markets. The level of excitement for the brand is very high. So, it is very good for us.

“And then and certainly the numbers are getting larger all the time. And so the gap as you compare it to the numbers in China is reducing. And hopefully that trajectory continues for a long time.”

The takeaway from those statements tells me that, like any farmer, Apple is investing in future business growth and most certainly sees rapidly emerging markets as the bedrock for tomorrow’s success as mature markets atrophy.

What happens next?

Looking forward, Apple warned of low single-digit growth in the June quarter, with services predicted to continue to grow and the iPad to see double-digit growth. The company is expected to ship a new iPad as soon as next week. 

That iPad may also introduce some new AI-driven tools, perhaps as a taster of what to expect at WWDC and their expected spread across the company’s products this fall. Discussing generative AI, Cook described it as a “very key” opportunity, stressed his confidence that the company has advantages to bring such tech to market, and promised “we will be talking more about it as we go through the weeks ahead”. So, there’s a lot to look forward to.

Apple’s data points

So, having established that there’s no data about Apple better than Apple’s own data, what data points did Apple share? You can review its press release here and financial statements here and here. What follows are some details cherry-picked from within the company’s analyst call:

• Apple reached revenue records in more than a dozen countries and regions, including in Latin America and the Middle East, as well as Canada, India, Spain, and Turkey.
• It also achieved an all-time revenue record in Indonesia, “one of the many markets where we continue to see so much potential,” said Cook, who recently visited the nation.
• Services hit an all-time revenue record, up 14% YoY at $23.9 billion. (It’s worth noting that recent data indicates Apple TV+ is the fastest growing streaming service in major markets.)
• Mac sales by revenue grew 4% YoY. (Cook described the MacBook Air as “the best consumer laptop for AI”, which I take to mean “watch this space.”)
• iPad revenue fell 17%, ahead of next week’s expected refresh.
• Wearables, home, and accessory sales fell 10%.
• Apple nodded toward CSR, confirming its plan to be completely carbon neutral across its business by 2030 and celebrating that it has reduced overall emissions by over 50% even while revenue (and therefore sales) increased 65% since 2015.
• Apple expects gross margins in the June quarter of 45.5% to 46.5% (which is really high, even for Apple).
• Apple predicts single-digit growth in comparison to last year in the upcoming June quarter. In 2023, it booked $81.8 billion in revenue for that period.
• If you own Apple shares, you’ll get 25 cents per share on May 16.

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Seven years after the launch of Teams, Microsoft has outlined plans to retire the initial, “classic” version of the team chat app. Support for Teams classic will end on July 1 and it will be discontinued a year later; atthat point, users will be unable to access the legacy client. 

Microsoft released the new 2.1 version of Teams last October after several months in preview, claiming the new app is twice as fast and uses around 50% less memory than its predecessor. 

The move represents the biggest change to the collaboration application since it arrived in 2017 to take on rival Slack. Since then, Teams has reached 320 million monthly users, according to recent data, having capitalized on the big uptick in video meetings during the COVID-19 pandemic. That said, it hasn’t alwaysbeen well-liked by users.

While the two Teams versions have coexisted in recent months, Microsoft recently outlined its schedule to phase out classic Teams on its admin site. With the end of support coming,  no new features will be added going forward and Microsoft will cease to help customers resolve support issues. At this stage, customers will start to receive in-app messages informing them that their version of Teams is out of date. End of support was initially planned for March 31 before being pushed back.

Users will be unable to access or use the classic Teams as of July 1, 2025. Those using classic Teams on Windows 7, 8, 8.1, and macOS Sierra will see the end of availability occur earlier, on Oct. 23, 2024. 

While there are advantages with the new version of Teams, some capabilities will disappear, too.  

Earlier this week, Microsoft outlined a host of changes that users might notice once they move to the new Teams. Some involve new ways to access existing tools, as well as several smaller features that will no longer be available: the activity tab in Teams chat, and Adaptive Card-based tabs in personal app tabs, for example.

The timeframe for retiring the classic Teams app seems abrupt, according to Raúl Castañón, senior research analyst at 451 Research, part of S&P Global Market Intelligence, and Microsoft appears to be pressuring customers to update to the new version. 

“Some business might be slow to move to the new app because they may have planned to update at a later date, or because they might want to wait until Microsoft has worked out software bugs from the initial versions,” he said. 

Classic Teams is one of several Microsoft products heading toward end of support. Windows 10 users will no long receive security or technical support as of Oct.14, 2025, as Microsoft encourges users to migrate to Windows 11. Microsoft will also end support for Office 2016 and 2019 application suites, and related productivity servers, on the same day.  

In the latest set of tweaks to bring itself into compliance with a new European Union law, Apple has confirmed significant changes to the deal originally offered to developers in the EU. Not only will it open up the iPad in the same way as it is opening up the iPhone in Europe, but it is making significant changes to its Core Technology Fee that should benefit smaller developers.

Europe’s iPads will be opened up this fall

iPadOS will be opened up in Europe starting this fall, the company said in a statement on its developer website. “This week, the European Commission designated iPadOS a gatekeeper platform under the Digital Markets Act,” Apple said. “Apple will bring our recent iOS changes for apps in the European Union (EU) to iPadOS later this fall, as required. Developers can choose to adopt the Alternative Business Terms for Apps in the EU that will include these additional capabilities and options on iPadOS or stay on Apple’s existing terms.”

Of course, once developers do choose to adopt Apple’s alternative terms, they can become liable to pay the company a Core Technology Fee (CTF). 

Improvement to the CTF

The fee is designed to compensate Apple for the value it provides developers in terms of tools, tech, and services. There is good news for developers here in that Apple won’t double charge for this, which means users who install the same app on both iOS and iPadOS within a 12-month period will only generate one first annual install for that app. 

While company critics continue to castigate this so-called “Apple Tax”, the company points out that under current data over 99% of developers in the EU will not be liable to any kind of CTF fee. Which rather implies that the 1% of developers who do pay the fee are able to make the most noise because they can afford the best marketing.

But let’s not dwell on that. Instead, let’s look at two additional changes the company has made to its approach. The first change is quite significant. 

Helping sudden success

When Apple’s teams appeared in front of what seemed to be an EU kangaroo court to explain how it was approaching the DMA, one question from one developer rang true. That person spoke about how an app they made had become hugely successful overnight and explained that under Apple’s originally proposed CTF deal he would have been bankrupted by the fees at that time. Apple responded pretty quickly with a range of tweaks.

At first, it introduced a new loophole developers in that situation could use to return to the original terms of business, which I saw as a kind of lifeboat. Today, it introduced a new tweak I think serve to blunt the pain of unexpected success:

As of now, small developers generating under €10 million in global annual business revenue that adopt the alternative business terms receive a three-year free on-ramp to the CTF to help them create innovative apps and rapidly grow business.

What that means is that within those three years, if a developer who has not previously exceeded one million first annual installs crosses the threshold for the first time, they won’t pay the CTF — even if they continue to exceed one million first annual installs during that time. “If a small developer grows to earn global revenue between €10 million and €50 million within the 3-year on-ramp period, they’ll start to pay the CTF after one million first annual installs up to a cap of €1 million per year.”

This sounds incredibly complicated, but basically means that if you are a small developer and happen to introduce an app that generates millions of installs they will not need to pay a fee until they scale their business so they can afford to do so.

No revenue? No fee

Obviously, this doesn’t apply to those wealthy developers whose business has already scaled in that way — rightly, they still need to shoulder the burden to help nurture new dev talent. The one big caveat is that the developer must declare their revenue before their first app surpasses one million first annual installs in order to receive these benefits. Leave it too late and you’ll have missed the chance.

The other improvement is that developers who create free apps won’t suddenly be bankrupted because millions download the app. Apple explains:

“No CTF is required if a developer has no revenue whatsoever. This includes creating a free app without monetization that is not related to revenue of any kind (physical, digital, advertising, or otherwise). This condition is intended to give students, hobbyists, and other non-commercial developers an opportunity to create a popular app without paying the CTF.”

It is also important to point out something else. Only developers who achieve over one million first annual installs per year in the EU need to pay Apple’s Core Technology Fee. Not only that, but non-profit organizations, government entitles, and educational institutions approved for a fee waiver don’t pay it at all.

While Apple’s well-resourced critics will continue to attack the company’s approach, it’s hard to avoid the feeling that the company is making it crystal clear that it is not now (and probably never was) the small developers who propped up App Store profits, but the large developers now making the loudest complaints.

And that seems to me to be food for thought. I doubt those larger entities have any plans to give their apps away for free. Why should Apple be made to do so?

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Citing the surge in layoffs nationwide, particularly within the IT workforce, online technology learning platform Udacity is offering a free trial to access its entire catalogue of courses for the next 30 days. The courses includes certifications in skills such as programming, data science, artificial intelligence, digital marketing.

“Layoffs have affected hundreds of thousands of people in the United States in the past year,”  Udacity COO Victoria Papalian wrote in a blog post. “Unfortunately, the unsettling trend continues. According to the Challenger Report, US job cuts in March 2024 were the highest since January 2023, up 7% over February.”

Udacity, which was founded as the outgrowth of free computer science classes offered in 2011 through Stanford University, said its free courses are part of its “Nanodegree” credential program. They’re available to anyone laid off over the past year.

In its announcement, the company placed a particular emphasis on highly desired industry skills, such as generative artificial intelligence (genAI). According to a recent study led by the Oxford Internet Institute, “AI skills are particularly valuable as they have high levels of skill complementarity, increasing worker wages by 21% on average,” the company said in a statement.

“To capitalize on the [genAI] opportunity — for business as well as individual benefit — learning about various genAI techniques is not sufficient; professionals must be inspired by the many use cases for genAI in the business, and must gain experience in putting that knowledge into practice within organizational contexts,” Papalian said.

Online instructors include educators from various tech companies, such as Advocate Networks, Cape Analytics, DeepMind, LanceDB, Meta, NVIDIA,  SoFi, and UC Berkeley, as well as Udacity’s own instructors. The topics covered include AI, data science, analytics, project management, digital marketing, cloud computing, web development, and mobile development, as well as genAI for business leaders.

Students studying genAI will also have the opportunity to complete projects modeled on the realworld tasks and challenges in professional contexts.

The free courses are available for all levels of IT experience and take about 4 weeks to complete during an average of 10 hours a week. These are examples of some of the courses being offered:

• Introduction to Python (Beginner)
• Introduction to SQL (Beginner)
• Digital Project Management (Beginner)
• Generative AI Fundamentals (Intermediate)
• Intro to Data Science (Advanced)

Students who can spend 20 hours a week learning can complete the following courses in 60 days:

• Business Analytics Nanodegree program (Beginner)
• AI Programming with Python Nanodegree program (Beginner)
• Programming for Data Science with Python Nanodegree program (Beginner)
• AI for Business Leaders Nanodegree program (Intermediate)
• AWS Cloud Architect Nanodegree program (Advanced)

By spending 40 hours a week, the following Nanodegree programs that typically take four months to complete can be finished in a month:

• Introduction to Programming Nanodegree program (Beginner)
• Digital Marketing Nanodegree program (Intermediate)
• Generative AI Nanodegree program (Intermediate)
• AI for Trading Nanodegree program (Advanced)
• Data Scientist Nanodegree program (Advanced)

Udacity students will also have the opportunity to receive feedback on their projects from mentors. The program, including all of Udacity’s tech projects, is now available to All Access subscribers.

“The experience of being laid off is stressful to say the least. And the subsequent job hunt is often no less stressful,” Papalian said. “Knowledge and training are critical to capturing the opportunities.”

As companies are scramble to get ahead in the artificial intelligence (AI) arms race, one problem the face is finding and retaining AI talent.

For example, Meta has been extending job offers to candidates with AI experience without even interviewing them, and CEO Mark Zuckerberg went so far as to email researchers at Google’s DeepMind unit to recruit talent.

According to a recent study led by the Oxford Internet Institute, “AI skills are particularly valuable as they have high levels of skill complementarity, increasing worker wages by 21% on average.”

Foote Partners, a recruitment, consulting and research firm, recently published its latest IT skills and pay index, which found, not surprisingly, that companies are paying premiums for workers with AI-related abilities.

Foote Partners recognizes 47 “critical A.I. skills,” and on average, employees who obtain those skills get a pay premium of 7% to 21%. Those premiums can come in different forms, including bonuses and cash compensation.

“This is cash paid out, not as a salary increase but in addition to salary,” said David Foote, chief analyst at Foote Partners. “In fact, 28 of these core AI skills can add between 15% and 21% in pay, well above the 9.6% average premium across all 632 non-certified skills we report. They are very hot right now.”

Cash premiums for skills such as AI chatbot app developer and large language model (LLM) tuning are paid out separately from salaries so that as needs are met and the value of those talents declines, the payouts can be reduced or eliminated.

“Perhaps the main difference with skills pay is, unlike a bonus, skills pay premiums are typically paid out at every pay period — same as salary — instead of a lump sum at the end of year, which is more common with bonuses,” Foote said.

In addition, more than a dozen AI-related certifications “are showing real market value strength,” he said. Those skills include prompt engineering, neural networks, AI engineer, AI scientist, and AI model optimization.

According to Foote, a Certified Artificial Intelligence Scientist earns the highest pay premium, ranging 8% to 12%, with the average being 10% of base salary equivalent,. The next highest cash pay premium in this cluster is for a Microsoft Certified: Azure AI Engineer Associate, who can earn 9% of base equivalent in skills premium pay.

Averaging 8% of base salary equivalent in skills pay premium are: SAS Certified Professional: AI and Machine Learning; IBM Certified Specialist — AI Enterprise Workflow V1; Artificial Intelligence Engineer (AIE – all tracks); and Google Professional Machine Learning Engineer certifications.

“We’ve been tracking some of these AI-related skills for many years, updating every 90 days,” Foote said. “Others have been recently added. So, given all the volatility in the marketplace for skills cash pay premiums, there have been remarkable changes over time ,including most recently.”

Foote Partner’s findings are echoed elsewhere. Freelance work platform Upwork, which recently published its 2024 list of most in-demand skills, found that the rise of AI — especially generative AI in the last couple of years — has changed the top skills businesses seek from independent professionals. In particular, generative AI modeling, machine learning and data analytics are the top three fastest-growing data science and analytics skills, as well as among the most in-demand skills.

“In particular, skills in key programming languages commonly used in the development of AI — Python, Java, and SQL — rank among the top five most sought-after skills on the technical side in the US,” Ya Xu, head of data and AI at LinkedIn, said in a blog post.

Machine learning skills can command at least a 10% premium compared to the average tech worker, according to a survey conducted at the end of 2023 by tech staffing firm Dice. “But this is a fast-moving market where the demand is growing rapidly,” said Art Zeile, CEO of Dice. “I predict that this premium will only continue to grow as the gap between supply and demand for AI talent grows, and offering benefits such as continuous professional development and training will be key to retaining this top talent.”

A key differentiator in the job interview process now involves how a tech professional has upskilled themselves in the face of the growing demand for AI, Zeile noted.

“Now is the time to ensure that their skill sets encompass [LLM] theory and programming architecture, areas that may have been overlooked or haven’t been delved into fully,” he said. “Recruiters are looking for tech professionals who are quick on their feet and able to adapt to changes with agility and curiosity.”

In January 2023, AI or machine learning-related skill sets were referenced on 9% of tech job postings. Just over a year later, in February 2024, that figure had climbed to nearly 14% of all tech job postings, according to Zeile.

“As AI continues to evolve, its impact on organizations will be most prominent in key departments such as research and development, data analytics, and operations,” Zeile said.

To secure top AI talent in these areas, Zeile advised that companies:

• Invest in comprehensive recruiting strategies that show a full understanding of what a particular AI role actually requires — whether it’s machine learning, Python, or data science skills for tech jobs, or other content-centric skills such as copy writing and graphic design. 
• Establish competitive salaries and provide opportunities for professional growth and development. 
• Offer flexibility in the form of hybrid/remote work environments. Dice’s 2023 Tech Sentiment Report noted that remote work remains very important to tech professionals: 73% of those surveyed said it is “extremely” or “very” important to have the opportunity to work remotely at least three days a week.

While Amazon, Google, Meta and Microsoft are among the top 15 companies hiring for AI talent right now, according to Dice, there are a variety of factors tech pros must consider determining if Big Tech is right for them.

“While these Big Tech companies offer many opportunities for individuals with AI skills, candidates should also consider startups and other industries that align with their career goals and work/life balance preferences that would also still give them the ability to learn and flex their AI muscles,” Zeile said.  “Ultimately, it is up to tech professionals to decide what companies most align with their values and what kind of industries they want to work in.”

Startups, Zeille said, often provide more room for innovation and growth, but may have less rigorous AI programs in place. At the same time, compensation at Big Tech companies might be higher, but work/life balance lower. Once a candidate has decided what is important to prioritize in their future role, they can job search accordingly.