Among the decades-old Windows apps to get renewed attention from Microsoft during the Windows 11 era is Notepad, the basic built-in text editor that was much the same in early 2021 as it had been in the '90 and 2000s. Since then, it has gotten a raft of updates, including a visual redesign, spellcheck and autocorrect, and window tabs.
Given Microsoft's continuing obsession with all things AI, it's perhaps not surprising that the app's latest update (currently in preview for Canary and Dev Windows Insiders) is a generative AI feature called Rewrite that promises to adjust the length, tone, and phrasing of highlighted sentences or paragraphs using generative AI. Users will be offered three rewritten options based on what they've highlighted, and they can select the one they like best or tell the app to try again.
Rewrite appears to be based on the same technology as the Copilot assistant, since it uses cloud-side processing (rather than your local CPU, GPU, or NPU) and requires Microsoft account sign-in to work. The initial preview is available to users in the US, France, the UK, Canada, Italy, and Germany.
Microsoft announced on Thursday that Outlook is getting a new feature that will allow you to use generative AI to create themes based on your personal preferences. AI-powered themes are available to people who have a Copilot Pro consumer subscription and business accounts with Copilot enabled. They are available on iOS, Android, Windows, Mac, and […]
Microsoft reported quarterly earnings that impressed investors and showed how resilient the company is even as it spends heavily on AI.
Some investors have been uneasy about the company's aggressive spending on AI, while others have demanded it. During this quarter, Microsoft reported that it spent $20 billion on capital expenditures, nearly double what it had spent during the same quarter last year.
However, the company satisfied both groups of investors, as it revealed it has still been doing well in the short term amid those long-term investments. The fiscal quarter, which covered July through September, saw overall sales rise 16 percent year over year to $65.6 billion. Despite all that AI spending, profits were up 11 percent, too.
The large language model-based coding assistant GitHub Copilot will switch from exclusively using OpenAI's GPT models to a multi-model approach over the coming weeks, GitHub CEO Thomas Dohmke announced in a post on GitHub's blog.
First, Anthropic's Claude 3.5 Sonnet will roll out to Copilot Chat's web and VS Code interfaces over the next few weeks. Google's Gemini 1.5 Pro will come a bit later.
Additionally, GitHub will soon add support for a wider range of OpenAI models, including GPT o1-preview and o1-mini, which are intended to be stronger at advanced reasoning than GPT-4, which Copilot has used until now. Developers will be able to switch between the models (even mid-conversation) to tailor the model to fit their needs—and organizations will be able to choose which models will be usable by team members.
Delta and CrowdStrike have locked legal horns, threatening to drag out the aftermath of the worst IT outage in history for months or possibly years.
Each refuses to be blamed for Delta's substantial losses following a global IT outage caused by CrowdStrike suddenly pushing a flawed security update despite Delta and many other customers turning off auto-updates.
CrowdStrike has since given customers more control over updates and made other commitments to ensure an outage of that scale will never happen again, but Delta isn't satisfied. The airline has accused CrowdStrike of willfully causing losses by knowingly deceiving customers by failing to disclose an unauthorized door into their operating systems that enabled the outage.
The speed of recent innovation is head spinning. Here’s some help.
GUEST COLUMN | by Delia DeCourcy
“As artificial intelligence proliferates, users who intimately understand the nuances, limitations, and abilities of AI tools are uniquely positioned to unlock AI’s full innovative potential.”
Ethan Mollick’s insight from his recent book Co-Intelligence: Living and Working with AI, is a great argument for why AI literacy is crucial for our students and faculty right now. To understand AI, you have to use it – a lot – not only so you know how AI can assist you, but also, as Mollick explains, so you know how AI will impact you and your current job–or in the case of students, the job they’ll eventually have.
What is AI Literacy?
Definitions of AI literacy abound but most have a few characteristics in common:
AI literacy doesn’t mean deep technical knowledge or the skill to develop AI tools.
Deeper dimensions of that second bullet could include knowing the difference between AI and generative AI; understanding the biases and ethical implications of large language model training; and mastering prompting strategies to name a few.
AI Literacy and Future Readiness
If the two-year generative AI tidal wave originating with ChatGPT going live isn’t enough to stoke your belief in the need for AI literacy, consider these facts and statistics:
A poll conducted by Impact Research for the Walton Family Foundation revealed that as of June 2024, about half of K-12 students and teachers said they use ChatGPT at least weekly.
According to a June report from Pearson, 56% of higher education students said that generative AI tools made them more efficient in the spring semester, while only 14% of faculty were confident about using AI in their teaching.
AI is already integrated into many of the devices and platforms we use every day. That’s now true in education as well with the integration of the Gemini chatbot in Google Workspace for Education and Microsoft’s offering of Copilot to education users.
Supporting institutions, educators, and students with AI literacy
Institutions – Assess, Plan, Implement
Assessing institutional readiness for generative AI integration, planning, and implementation means looking not only at curriculum integration and professional development for educators, but also how this technology can be used to personalize the student experience, streamline administration, and improve operating costs – not to mention the critical step of developing institutional policies for responsible and ethical AI use. This complex planning process assumes a certain level of AI literacy for the stakeholders contributing to the planning. So some foundational learning might be in order prior to the “assess” stage.
‘This complex planning process assumes a certain level of AI literacy for the stakeholders contributing to the planning. So some foundational learning might be in order prior to the “assess” stage.’
Fortunately for K-12 leaders, The Council of the Great City Schools and CoSN have developed a Gen AI Readiness Checklist, which helps districts think through implementation necessities from executive leadership to security and risk management to ensure a roll out aligns with existing instructional and operational objectives. It’s also helpful to look at model districts like Gwinnett County Schools in Georgia that have been integrating AI into their curriculum since before ChatGPT’s launch.
Similarly, in higher education, Educause provides a framework for AI governance, operations, and pedagogy and has also published the 2024 Educause AI Landscape Study that helps colleges and universities better understand the promise and pitfalls of AI implementation. For an example of what AI assessment and planning looks like at a leading institution, see The Report of the Yale Task Force on Artificial Intelligence published in June of this year. The document explains how AI is already in use across campus, provides a vision for moving forward, and suggests actions to take.
Educators – Support Innovation through Collaboration
Whether teaching or administrating, in university or K12, educators need to upskill and develop a generative AI toolbox. The more we use the technology, the better we will understand its power and potential. Fortunately, both Google Gemini and Microsoft Copilot have virtual PD courses that educators can use to get started. From there, it’s all about integrating these productivity platforms into our day to day work to “understand the nuances, limitations, and abilities” of the tools. And for self-paced AI literacy learning, Common Sense Education’s AI Foundations for Educators course introduces the basics of AI and ethical considerations for integrating this technology into teaching.
The best learning is inherently social, so working with a team or department to share discoveries about how generative AI can help with personalizing learning materials, lesson plan development, formative assessment, and daily productivity is ideal. For more formalized implementation of this new technology, consider regular coaching and modeling for new adopters. At Hillsborough Township Public Schools in New Jersey, the district has identified a pilot group of intermediate and middle school teachers, technology coaches, and administrators who are exploring how Google Gemini can help with teaching and learning this year. With an initial pre-school year PD workshop followed by regular touch points, coaching, and modeling, the pilot will provide the district a view of if and how they want to scale generative AI with faculty across all schools.
‘The best learning is inherently social, so working with a team or department to share discoveries about how generative AI can help with personalizing learning materials, lesson plan development, formative assessment, and daily productivity is ideal.’
In higher education, many institutions are providing specific guidance to faculty about how generative AI should and should not be used in the classroom as well as how to address it in their syllabi with regard to academic integrity and acceptable use. At the University of North Carolina at Chapel Hill, faculty are engaging in communities of practice that examine how generative AI is being used in their discipline and the instructional issues surrounding gen AI’s use, as well as re-designing curriculum to integrate this new technology. These critical AI literacy efforts are led by the Center for Faculty Excellence and funded by Lenovo’s Instructional Innovation Grants program at UNC. This early work on generative AI integration will support future scaling across campus.
Students – Integrate AI Literacy into the Curriculum
The time to initiate student AI literacy is now. Generative AI platforms are plentiful and students are using them. In the work world, this powerful technology is being embraced across industries. We want students to be knowledgeable, skilled, and prepared. They need to understand not only how to use AI responsibly, but also how it works and how it can be harmful.
‘We want students to be knowledgeable, skilled, and prepared. They need to understand not only how to use AI responsibly, but also how it works and how it can be harmful.’
The AI literacy students need will vary based on age. Fortunately, expert organizations like ISTE have already made recommendations about the vocabulary and concepts K12 educators can integrate at which grades to help students understand and use AI responsibly. AI literacy must be integrated across the curriculum in ways that are relevant for each discipline. But this is one more thing to add to educators’ already full plates as they themselves develop their own AI literacy. Fortunately, MIT, Stanford, and Common Sense Education have developed AI literacy materials that can be integrated into existing curriculum. And Microsoft has an AI classroom toolkit that includes materials on teaching prompting.
The speed of recent innovation is head spinning. Remaining technologically literate in the face of that innovation is no small task. It will be critical for educators and institutions to assess and implement AI in ways that matter, ensuring it is helping them achieve their goals. Just as importantly, educators and institutions play an essential role in activating students’ AI literacy as they take the necessary steps into this new technology landscape and ultimately embark on their first professional jobs outside of school.
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Delia DeCourcy is a Senior Strategist for the Lenovo Worldwide Education Portfolio. Prior to joining Lenovo she had a 25-year career in education as a teacher, consultant, and administrator, most recently as the Executive Director of Digital Teaching and Learning for a district in North Carolina. Previously, she was a literacy consultant serving 28 school districts in Michigan focusing on best practices in reading and writing instruction. Delia has also been a writing instructor at the University of Michigan where she was awarded the Moscow Prize for Excellence in Teaching Composition. In addition, she served as a middle and high school English teacher, assistant principal, and non-profit director. She is the co-author of the curriculum text Teaching Romeo & Juliet: A Differentiated Approach published by the National Council for the Teachers of English. Connect with Delia on LinkedIn.
On Monday, Microsoft came out guns blazing, posting a blog accusing Google of "dishonestly" funding groups conducting allegedly biased studies to discredit Microsoft and mislead antitrust enforcers and the public.
In the blog, Microsoft lawyer Rima Alaily alleged that an astroturf group called the Open Cloud Coalition will launch this week and will appear to be led by "a handful of European cloud providers." In actuality, however, those smaller companies were secretly recruited by Google, which allegedly pays them "to serve as the public face" and "obfuscate" Google's involvement, Microsoft's blog said. In return, Google likely offered the cloud providers cash or discounts to join, Alaily alleged.
The Open Cloud Coalition is just one part of a "pattern of shadowy campaigns" that Google has funded, both "directly and indirectly," to muddy the antitrust waters, Alaily alleged. The only other named example that Alaily gives while documenting this supposed pattern is the US-based Coalition for Fair Software Licensing (CFSL), which Alaily said has attacked Microsoft's cloud computing business in the US, the United Kingdom, and the European Union.
AI-infused search engines from Google, Microsoft, and Perplexity have been surfacing deeply racist and widely debunked research promoting race science and the idea that white people are genetically superior to nonwhite people.
Patrik Hermansson, a researcher with UK-based anti-racism group Hope Not Hate, was in the middle of a monthslong investigation into the resurgent race science movement when he needed to find out more information about a debunked dataset that claims IQ scores can be used to prove the superiority of the white race.
He was investigating the Human Diversity Foundation, a race science company funded by Andrew Conru, the US tech billionaire who founded Adult Friend Finder. The group, founded in 2022, was the successor to the Pioneer Fund, a group founded by US Nazi sympathizers in 1937 with the aim of promoting “race betterment” and “race realism.”
But this is more than just a theoretical exercise; I've been using Windows 11 on some kind of "unsupported" system practically since it launched to stay abreast of what the experience is actually like and to keep tabs on whether Microsoft would make good on its threats to pull support from these systems at any time.
Now that we're three years in, and since I've been using Windows 11 24H2 on a 2012-era desktop and laptop as my primary work machines on and off for a few months now, I can paint a pretty complete picture of what Windows 11 is like on these PCs. As the Windows 10 update cliff approaches, it's worth asking: Is running "unsupported" Windows 11 a good way to keep an older but still functional machine running, especially for non-technical users?
According to a report from Korean tech outlet The Elec, Microsoft has contracted Samsung to supply micro OLED display panels for what is described as “next-generation mixed reality devices.”
Citing industry sources, the report maintains the order could reach into the “hundreds of thousands” of micro OLED displays, with such a Microsoft XR device reportedly slated to arrive as early as 2026.
Unlike Meta’s current line of Quest headsets, the alleged Microsoft headset will be used for “enjoying or watching content such as games or movies rather than the metaverse,” the report maintains (machine translated from Korean), potentially putting it in competition with Apple Vision Pro.
Since Microsoft’s abandonment of its WMR platform late last year and ongoing stagnation around its HoloLens AR platform, the company has mostly concentrated on smaller XR software projects.
Since the release of Vision Pro earlier this year however, competing—or at least preparing to compete—with Apple seems to be the order of the day.
Samsung and Google confirmed in July their forthcoming “XR platform” will be announced sometime this year. The ‘platform’, which is thought to be hardware built by Samsung and an Android XR operating system built by Google, was previously reportedly delayed in effort to better compete with Vision Pro.
A version of this post originally appeared on Tedium, Ernie Smith’s newsletter, which hunts for the end of the long tail.
These days, computer users take collaboration software for granted. Google Docs, Microsoft Teams, Slack, Salesforce, and so on, are such a big part of many people’s daily lives that they hardly notice them. But they are the outgrowth of years of hard work done before the Internet became a thing, when there was a thorny problem: How could people collaborate effectively when everyone’s using a stand-alone personal computer?
In the early days of the computing era, when IBM’s PC reigned supreme, collaboration was difficult. Ross Anthony Willis/Fairfax Media/Getty Images
How the PC made us forget about collaboration for a while
Imagine that it’s the early-to-mid-1980s and that you run a large company. You’ve invested a lot of money into personal computers, which your employees are now using—IBM PCs, Apple Macintoshes, clones, and the like. There’s just one problem: You have a bunch of computers, but they don’t talk to one another.
If you’re in a small office and need to share a file, it’s no big deal: You can just hand a floppy disk off to someone on the other side of the room. But what if you’re part of an enterprise company and the person you need to collaborate with is on the other side of the country? Passing your colleague a disk doesn’t work.
The new personal-computing technologies clearly needed to do more to foster collaboration. They needed to be able to take input from a large group of people inside an office, to allow files to be shared and distributed, and to let multiple users tweak and mash information with everyone being able to sign off on the final version.
The hardware that would enable such collaboration software, or “groupware” as it tended to be called early on, varied by era. In the 1960s and ’70s, it was usually a mainframe-to-terminal setup, rather than something using PCs. Later, in the 1980s, it was either a
token ring or Ethernet network, which were competing local-networking technologies. But regardless of the hardware used for networking, the software for collaboration needed to be developed.
Stanford Research Institute engineer Douglas Engelbart is sometimes called “the father of groupware.”Getty Images
Some of the basic ideas behind groupware
were first forged at the Stanford Research Institute by a Douglas Engelbart–led team, in the 1960s, working on what they called an oN-Line System (NLS). An early version of NLS was presented in 1968 during what became known as the “Mother of All Demos.” It was essentially a coming-out party for many computing innovations that would eventually become commonplace. If you have 90 minutes and want to see something 20-plus years ahead of its time, watch this video.
By the late 1980s, at a point when the PC had begun to dominate the workplace, Engelbart was less impressed with what had been gained than with what had been lost in the process. He
wrote (with Harvey Lehtman) in Byte magazine in 1988:
The emergence of the personal computer as a major presence in the 1970s and 1980s led to tremendous increases in personal productivity and creativity. It also caused setbacks in the development of tools aimed at increasing organizational effectiveness—tools developed on the older time-sharing systems.
To some extent, the personal computer was a reaction to the overloaded and frustrating time-sharing systems of the day. In emphasizing the power of the individual, the personal computer revolution turned its back on those tools that led to the empowering of both co-located and distributed work groups collaborating simultaneously and over time on common knowledge work.
The introduction of local- and wide-area networks into the personal computer environment and the development of mail systems are leading toward some of the directions explored on the earlier systems. However, some of the experiences of those earlier pioneering systems should be considered anew in evolving newer collaborative environments.
Groupware finally started to catch on in the late 1980s, with tech companies putting considerable resources into developing collaboration software—perhaps taken in by the idea of “orchestrating work teams,” as
an Infoworld piece characterized the challenge in 1988. The San Francisco Examiner reported, for example, that General Motors had invested in the technology, and was beginning to require its suppliers to accept purchase orders electronically.
Focusing on collaboration software was a great way for independent software companies to stand out, this being an area that large companies—Microsoft in particular—had basically ignored. Today, Microsoft is the 800-pound gorilla of collaboration software, thanks to its combination of Teams and Office 365. But it took the tech giant a very long while to get there: Microsoft started taking the market seriously only around 1992.
One company in particular was well-positioned to take advantage of the opening that existed in the 1980s. That was the
Lotus Development Corporation, a Cambridge, Mass.–based software company that made its name with its Lotus 1-2-3 spreadsheet program for IBM PCs.
Lotus did not invent groupware or coin the word—on top of Engelbart’s formative work at Stanford, the term
had been around for years before Lotus Notes came on the scene. But it was the company that brought collaboration software to everyone’s attention.
Ray Ozzie [left] was primarily responsible for the development of Lotus Notes, the first popular groupware solution.
Left: Ann E. Yow-Dyson/Getty Images; Right: James Keyser/Getty Images
The person most associated with the development of Notes was
Ray Ozzie, who was recruited to Lotus after spending time working on VisiCalc, an early spreadsheet program. Ozzie essentially built out what became Notes while working at Iris Associates, a direct offshoot of Lotus that Ozzie founded to develop the Notes application. After some years of development in stealth mode, the product was released in 1989.
Ozzie explained his inspiration for Notes to Jessica Livingston, who described this history in her book,
Founders At Work:
In Notes, it was (and this is hard to imagine because it was a different time) the concept that we’d all be using computers on our desktops, and therefore we might want to use them as communication tools. This was a time when PCs were just emerging as spreadsheet tools and word processing replacements, still available only on a subset of desks, and definitely no networks. It was ’82 when I wrote the specs for it. It had been based on a system called PLATO [Programmed Logic for Automatic Teaching Operations] that I’d been exposed to at college, which was a large-scale interactive system that people did learning and interactive gaming on, and things like that. It gave us a little bit of a peek at the future—what it would be like if we all had access to interactive systems and technology.
Building an application based on PLATO turned out to be the right idea at the right time, and it gave Lotus an edge in the market. Notes included email, a calendaring and scheduling tool, an address book, a shared database, and programming capabilities, all in a single front-end application.
Lotus Notes on Computer Chronicles Fall 1989
As an all-in-one platform built for scale, Notes
gained a strong reputation as an early example of what today would be called a business-transformation tool, one that managed many elements of collaboration. It was complicated from an IT standpoint and required a significant investment to maintain. In a way, what Notes did that was perhaps most groundbreaking was that it helped turn PCs into something that large companies could readily use.
As Fortune noted in 1994, Lotus had a massive lead in the groupware space, in part because the software worked essentially the same anywhere in a company’s network. We take that for granted now, but back then it was considered magical:
Like Lotus 1-2-3, Notes is easy to customize. A sales organization, for instance, might use it to set up an electronic bulletin board that lets people pool information about prospective clients. If some of the info is confidential, it can be restricted so not everyone can call it up.
Notes makes such homegrown applications and the data they contain accessible throughout an organization. The electronic bulletin board you consult in Singapore is identical to the one your counterparts see in Sioux City, Iowa. The key to this universality is a procedure called replication, by which Notes copies information from computer to computer throughout the network. You might say Ozzie figured out how to make the machines telepathic—each knows what the others are thinking.
A 1996 commercial for Notes highlighted its use by FedEx. Other commercials would use the stand-up comedian Denis Leary or be highly conceptual. Rarely, if ever, would these television advertisements show the software.
In the mid-1990’s, it was common for magazines to publish stories about how Notes reshaped businesses large and small.
A 1996 Inc. piece, for example, described how a natural-foods company successfully produced a new product in just eight months, a feat the company directly credited to Notes.
“It’s become our general manager,” Groveland Trading Co. president Steve McDonnell recalled.
Notes wasn’t cheap (InfoWorld lists the price circa 1990 as US $62,000), and it was complicated to manage. But the positive results it enabled were immensely hard to ignore. IBM noticed and ended up buying Lotus in 1995, almost entirely to get ahold of Notes. Even earlier, Microsoft had realized that office collaboration was a big deal, and they wanted in.
Microsoft’s first foray into collaboration software was its 1992 release of Windows for Workgroups. Despite great efforts to promote the release, the software was not a commercial success. Daltrois/Flickr
Microsoft had high hopes for
Windows for Workgroups, the networking-focused variant of its popular Windows 3.1 software suite. To create buzz for it, the company pulled out all the stops. Seriously.
In the fall of 1992, Microsoft
paid something like $2 million to put on a Broadway production with Bill Gates literally center stage, at New York City’s Gershwin Theater, one of the largest on Broadway. It was a wild show, and yet, somehow, there is no video of this event currently posted online—until now. The only person I know of who has a video recording of this extravaganza is, fittingly enough, Ray Ozzie, the groupware guru and Notes inventor. Ozzie later served as a top executive at Microsoft, famously replacing Bill Gates as Chief Software Architect in the mid-2000s, and he has shared this video with us for this post:
The 1992 one-day event was not a hit. Watch to see why. (Courtesy of Ray Ozzie and the Microsoft Corporation)
00:00 Opening number
02:23 “My VGA can hardly wait for your CPU to reciprocate”
05:17 Bill Gates enters the stage
27:55 “Get ready, get set” musical number
31:50 Bit with Mike Appe, Microsoft VP of sales
58:30 Bill Gates does jumping jacks
A 1992 Washington Post article describes the performance, which involved dozens of actors, some of whom were dressed like the Blues Brothers. At one point, Gates did jumping jacks. Gates himself later said, “That was so bad, I thought [then Microsoft CEO] Ballmer was going to retch.” For those who don’t have an extra hour to spend, here is a summary:
To get a taste of the show, watch this news segment from channel 4.
Courtesy of Microsoft Corporate Archives
Despite all the effort to generate fanfare, Windows for Workgroups was
not a hit. While Windows 3.1 was dominant, Microsoft had built a program that didn’t seem to capture the burgeoning interest in collaborative work in a real way. Among other things, it didn’t initially support the TCP/IP networking protocol, despite the fact that it was the networking technology that was winning the market and enabled the rise of the Internet.
In its original version, Windows for Workgroups carried such a negative reputation in Microsoft’s own headquarters that the company nicknamed it
Windows for Warehouses, referring to the company’s largely unsold inventory, according to Microsoft’s own expert on company lore, Raymond Chen.
Unsuccessful as it was, the fact that it existed in the first place hinted at Microsoft’s general acknowledgement that perhaps this networking thing was going to catch on with its users.
Launched in late 1992, a few months after Windows 3.1 itself, the product was Microsoft’s
first attempt at integrated networking in a Windows package. The software enabled file-sharing across servers, printer sharing, and email—table stakes in the modern day but at the time a big deal.
This video presents a very accurate view of what it was like to use Windows in 1994.
Unfortunately, it was a big deal that came a few years late. Microsoft itself was
so lukewarm on the product that the company had to update it to Windows for Workgroups 3.11 just a year later, whose marquee feature wasn’t improved network support but increased disk speed. Confusingly, the company had just released Windows NT by this point, a program that better matched the needs of enterprise customers.
The work group terminology Microsoft introduced with Windows for Workgroups stuck around, though, and it is actually
used in Windows to this day.
In 2024, group-oriented software feels like the default paradigm, with single-user apps being the anomaly. Over time, groupware became so pervasive that people no longer think of it as groupware, though there are plenty of big, hefty, groupware-like tools out there, like
Salesforce. Now, it’s just software. But no one should forget the long history of collaboration software or its ongoing value. It’s what got most of us through the pandemic, even if we never used the word “groupware” to describe it.
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