An entire HR team was terminated after their manager discovered and confirmed that their system automatically rejected all candidates — including his own application.
The manager wrote in their comment, “Auto rejection systems from HR make me angry.” They explained that while searching for a new employee, their HR department could not find a single qualified candidate in three months. As expected, the suspicious manager decided to investigate.
“I created myself a new email and sent them a modified version of my CV with a fake name to see what was going on with the process,” they wrote. “And guess what, I got auto-rejected. HR didn’t even look at my CV.”
When the manager reported the issue to upper management, “half of the HR department was fired in the following weeks.” A typographical error with significant consequences caused the entire problem.
The manager works in the tech industry and was trying to hire developers. However, HR had set up the system to search for developers with expertise in the wrong development software and one that no longer exists.
From DSC: Back in 2017, I had survived several rounds of layoffs at the then Calvin College (now Calvin University) but I didn’t survive the layoff of 12 people in the spring of 2017. I hadn’t needed to interview for a new job in quite a while. So boy, did I get a wake-up call with discovering that Applicant Tracking Systems existed and could be tough to get past. (Also, the old-school job replacement firm that Calvin hired wasn’t much help in dealing with them either.)
I didn’t like these ATSs then, and I still have my concerns about them now. The above article points out that my concerns were/are at least somewhat founded. And if you take the entire day to research and apply for a position — only to get an instant reply back from the ATS — it’s very frustrating and discouraging.
Plus the ATSs may not pick up on nuances. An experienced human being might be able to see that a candidate’s skills are highly relevant and/or transferable to the position that they’re hiring for.
Networking is key of course. But not everyone has been taught about networking and not everyone gets past the ATS to get their resume viewed by a pair of human eyes. HR, IT, and any other relevant groups here need to be very careful with programming their ATSs.
They respond to needs that the degree-credit system has not efficiently met: quick start-up, shorter sequences, relationships with third-party credential issuers, real-time employer engagement, and so on. The complexity of the needs of the market and of learners has led to a proliferation of diverse credentials, and a landscape that continues to evolve in surprising directions.
Amid this complexity, there’s no one single arbiter of quality but rather a host of “quality influencers” who seek to shape the market in different ways. Exploring who those influencers are, how they approach their work, and what they seek to accomplish is essential to understanding what quality means for noncredit credentials—and what could happen in years to come.
At the end of 2024 and start of 2025, we’ve witnessed some fascinating developments in the world of AI and education, from from India’s emergence as a leader in AI education and Nvidia’s plans to build an AI school in Indonesia to Stanford’s Tutor CoPilot improving outcomes for underserved students.
Other highlights include Carnegie Learning partnering with AI for Education to train K-12 teachers, early adopters of AI sharing lessons about implementation challenges, and AI super users reshaping workplace practices through enhanced productivity and creativity.
India emerges as Global Leader in AI Education: Bosch Tech Compass 2025 — from medianews4u.com 57% Indians receive employer-provided AI training, surpassing Germany, and other European nations
Bengaluru: India is emerging as a global leader in artificial intelligence (AI) education, with over 50% of its population actively self-educating in AI-related skills, according to Bosch’s fourth annual Tech Compass Survey. The report highlights India’s readiness to embrace AI in work, education, and daily life, positioning the nation as a frontrunner in the AI revolution.
AI for Education reviewed the ElevenLabs AI Voice Tool through an educator lens, digging into the new autonomous voice agent functionality that facilitates interactive user engagement. We showcase the creation of a customized vocabulary bot, which defines words at a 9th-grade level and includes options for uploading supplementary material. The demo includes real-time testing of the bot’s capabilities in defining terms and quizzing users.
The discussion also explored the AI tool’s potential for aiding language learners and neurodivergent individuals, and Mandy presented a phone conversation coach bot to help her 13-year-old son, highlighting the tool’s ability to provide patient, repetitive practice opportunities.
While acknowledging the technology’s potential, particularly in accessibility and language learning, we also want to emphasize the importance of supervised use and privacy considerations. Right now the tool is currently free, this likely won’t always remain the case, so we encourage everyone to explore and test it out now as it continues to develop.
Why Combine Them? Faster Onboarding: Start broad with Deep Research, then refine and clarify concepts through Learn About. Finally, use NotebookLM to synthesize everything into a cohesive understanding.
Deeper Clarity: Unsure about a concept uncovered by Deep Research? Head to Learn About for a primer. Want to revisit key points later? Store them in NotebookLM and generate quick summaries on demand.
Adaptive Exploration: Create a feedback loop. Let new terms or angles from Learn About guide more targeted Deep Research queries. Then, compile all findings in NotebookLM for future reference. .
There are several challenges to making policy that make institutions hesitant to or delay their ability to produce it. Policy (as opposed to guidance) is much more likely to include a mixture of IT, HR, and legal services. This means each of those entities has to wrap their heads around GenAI—not just for their areas but for the other relevant areas such as teaching & learning, research, and student support. This process can definitely extend the time it takes to figure out the right policy.
That’s naturally true with every policy. It does not often come fast enough and is often more reactive than proactive.
Still, in my conversations and observations, the delay derives from three additional intersecting elements that feel like they all need to be in lockstep in order to actually take advantage of whatever possibilities GenAI has to offer.
Which Tool(s) To Use
Training, Support, & Guidance, Oh My!
Strategy: Setting a Direction…
Prophecies of the Flood — from oneusefulthing.org by Ethan Mollick What to make of the statements of the AI labs?
What concerns me most isn’t whether the labs are right about this timeline – it’s that we’re not adequately preparing for what even current levels of AI can do, let alone the chance that they might be correct. While AI researchers are focused on alignment, ensuring AI systems act ethically and responsibly, far fewer voices are trying to envision and articulate what a world awash in artificial intelligence might actually look like. This isn’t just about the technology itself; it’s about how we choose to shape and deploy it. These aren’t questions that AI developers alone can or should answer. They’re questions that demand attention from organizational leaders who will need to navigate this transition, from employees whose work lives may transform, and from stakeholders whose futures may depend on these decisions. The flood of intelligence that may be coming isn’t inherently good or bad – but how we prepare for it, how we adapt to it, and most importantly, how we choose to use it, will determine whether it becomes a force for progress or disruption. The time to start having these conversations isn’t after the water starts rising – it’s now.
While “polarization” was Merriam-Webster’s word of the year for 2024, we have some early frontrunners for 2025 — especially when it comes to higher education. Change. Agility. Uncertainty. Flexibility. As we take a deep dive into the trends on tap for higher education in the coming year, it’s important to note that, with an incoming administration who has vowed to shake things up, the current postsecondary system could be turned on its head. With that in mind, we wade into our yearly look at the topics and trends that will be making headlines — and making waves — in the year ahead.
Top AI Tools of 2024 — from ai-supremacy.com by Michael Spencer (behind a paywall) Which AI tools stood out for me in 2024? My list.
Memorable AI Tools of 2024
Catergories included:
Useful
Popular
Captures the zeighest of AI product innovation
Fun to try
Personally satisfying
NotebookLM
Perplexity
Claude
…
New “best” AI tool? Really? — from theneurondaily.com by Noah and Grant
PLUS: A free workaround to the “best” new AI…
What is Google’s Deep Research tool, and is it really “the best” AI research tool out there? … Here’s how it works: Think of Deep Research as a research team that can simultaneously analyze 50+ websites, compile findings, and create comprehensive reports—complete with citations.
Unlike asking ChatGPT to research for you, Deep Research shows you its research plan before executing, letting you edit the approach to get exactly what you need.
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It’s currently free for the first month (though it’ll eventually be $20/month) when bundled with Gemini Advanced. Then again, Perplexity is always free…just saying.
We couldn’t just take J-Cal’s word for it, so we rounded up some other takes:
Our take: We then compared Perplexity, ChatGPT Search, and Deep Research (which we’re calling DR, or “The Docta” for short) on robot capabilities from CES revealed:
An excerpt from today’s Morning Edition from Bloomberg
Global banks will cut as many as 200,000 jobs in the next three to five years—a net 3% of the workforce—as AI takes on more tasks, according to a Bloomberg Intelligence survey. Back, middle office and operations are most at risk. A reminder that Citi said last year that AI is likely to replace more jobs in banking than in any other sector. JPMorgan had a more optimistic view (from an employee perspective, at any rate), saying its AI rollout has augmented, not replaced, jobs so far.
Professionals are navigating rapid change, and staying ahead of the curve is no easy feat. Recent LinkedIn research shows that 64% of workers feel overwhelmed by the pace of workplace shifts, from navigating AI to managing multi-generational teams. At the same time, U.S. workers’ confidence in their job securityis the lowest it’s been since the start of the pandemic.
But as the workplace continues to evolve, new opportunities arise. That’s exactly what our annual Jobs on the Rise list uncovers — the fastest-growing jobs over the past three years and the trends defining the future of work. From the rise of AI roles to the resurgence in travel and hospitality positions, the 2025 ranking highlights sectors with sustainable growth in today’s changing workforce. (You can read more about our methodology at the bottom of this article.)
The list is a roadmap that can point you in the right direction at any stage of your career. Under each job title, you can explore the most common skills, top hiring regions, remote and hybrid availability and more. And you can turn those insights into action by exploring open roles, honing your skills through LinkedIn Learning courses (free for all members until Feb. 15) or joining the conversation in the collaborative article for each featured role.
In other words, individual learning leaders need to obtain information from surveys and studies that are directly useful in their curriculum planning. This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.
The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?
The Importance of Building a ‘Change Muscle’ The ability to test and learn, pivot quickly, and embrace change is an increasingly foundational skill that all employees, no matter the level of experience or seniority, need in 2025 and beyond. Adaptable organizations significantly outperform more change-averse peers on nearly every metric, ranging from revenue growth to employee engagement. In other words, having agility and adaptability embedded in your culture pays dividends. Although these terms are often used interchangeably, they represent distinct yet interconnected aspects of organizational success:
Agility refers to the ability to swiftly and efficiently respond to immediate challenges or opportunities. It’s about being nimble and proactive, making quick decisions, and adjusting to navigate short-term obstacles.
Adaptability is a broader concept that encompasses the capacity to evolve and thrive in the face of long-term shifts in the environment. It’s about being resilient and flexible by modifying strategies and structures to align with fundamental changes in the market or industry.
And a quick comment from DSC:
Agility and adaptability are key skills/orientations/expectations that we need to help our K-16 students build. Changes can happen quickly, as those of us who worked several decades can attest to.
Employees’ skills and abilities must match the skills and abilities required for their jobs; when they do, organizational performance and productivity improve.
Skills gaps occur when there are mismatches between employees’ skills and capabilities and the skills and capabilities needed for their work. As technology and work become more complex, identifying and correcting skills gaps become essential to optimizing employee performance.
This article discusses various methods involving skills inference and predictive analytics in addition to traditional methods to pinpoint and prevent skills gaps.
Another year, another opportunity to bring microlearning into your performance and talent development strategy! This is especially appealing as more and more organizations strive to deliver training in ways that meet the fast-paced needs of their employees.
However, implementing a microlearning strategy that aligns with organizational outcomes and sustains performance is no small feat. Learning and Development (L&D) leaders often grapple with questions like: Where do we start; How do we ensure our efforts are effective; and What factors should we evaluate?
The Microlearning Effectiveness (MLE) Framework offers a practical approach to addressing these challenges. Instead of rigid rules, the framework acts as a guide, encouraging leaders to evaluate their efforts against six key components:
NVIDIA’s Apple moment?! — from theneurondaily.com by Noah Edelman and Grant Harvey PLUS: How to level up your AI workflows for 2025…
NVIDIA wants to put an AI supercomputer on your desk (and it only costs $3,000). … And last night at CES 2025, Jensen Huang announced phase two of this plan: Project DIGITS, a $3K personal AI supercomputer that runs 200B parameter models from your desk. Guess we now know why Apple recently developed an NVIDIA allergy…
… But NVIDIA doesn’t just want its “Apple PC moment”… it also wants its OpenAI moment. NVIDIA also announced Cosmos, a platform for building physical AI (think: robots and self-driving cars)—which Jensen Huang calls “the ChatGPT moment for robotics.”
NVIDIA is bringing AI from the cloud to personal devices and enterprises, covering all computing needs from developers to ordinary users.
At CES 2025, which opened this morning, NVIDIA founder and CEO Jensen Huang delivered a milestone keynote speech, revealing the future of AI and computing. From the core token concept of generative AI to the launch of the new Blackwell architecture GPU, and the AI-driven digital future, this speech will profoundly impact the entire industry from a cross-disciplinary perspective.
From DSC: I’m posting this next item (involving Samsung) as it relates to how TVs continue to change within our living rooms. AI is finding its way into our TVs…the ramifications of this remain to be seen.
The Rundown: Samsung revealed its new “AI for All” tagline at CES 2025, introducing a comprehensive suite of new AI features and products across its entire ecosystem — including new AI-powered TVs, appliances, PCs, and more.
The details:
Vision AI brings features like real-time translation, the ability to adapt to user preferences, AI upscaling, and instant content summaries to Samsung TVs.
Several of Samsung’s new Smart TVs will also have Microsoft Copilot built in, while also teasing a potential AI partnership with Google.
Samsung also announced the new line of Galaxy Book5 AI PCs, with new capabilities like AI-powered search and photo editing.
AI is also being infused into Samsung’s laundry appliances, art frames, home security equipment, and other devices within its SmartThings ecosystem.
Why it matters: Samsung’s web of products are getting the AI treatment — and we’re about to be surrounded by AI-infused appliances in every aspect of our lives. The edge will be the ability to sync it all together under one central hub, which could position Samsung as the go-to for the inevitable transition from smart to AI-powered homes.
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“Samsung sees TVs not as one-directional devices for passive consumption but as interactive, intelligent partners that adapt to your needs,” said SW Yong, President and Head of Visual Display Business at Samsung Electronics. “With Samsung Vision AI, we’re reimagining what screens can do, connecting entertainment, personalization, and lifestyle solutions into one seamless experience to simplify your life.” — from Samsung
The following framework I offer for defining, understanding, and preparing for agentic AI blends foundational work in computer science with insights from cognitive psychology and speculative philosophy. Each of the seven levels represents a step-change in technology, capability, and autonomy. The framework expresses increasing opportunities to innovate, thrive, and transform in a data-fueled and AI-driven digital economy.
The Rise of AI Agents and Data-Driven Decisions — from devprojournal.com by Mike Monocello Fueled by generative AI and machine learning advancements, we’re witnessing a paradigm shift in how businesses operate and make decisions.
AI Agents Enhance Generative AI’s Impact Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, predicts a significant leap forward in generative AI. “In 2025, AI agents will take generative AI to the next level by moving beyond content creation to active participation in daily business operations,” he says. “These agents, capable of partial or full autonomy, will handle tasks like scheduling, lead qualification, and customer follow-ups, seamlessly integrating into workflows. Rather than replacing generative AI, they will enhance its utility by transforming insights into immediate, actionable outcomes.”
Everyone’s talking about the potential of AI agents in 2025 (and don’t get me wrong, it’s really significant), but there’s a crucial detail that keeps getting overlooked: the gap between current capabilities and practical reliability.
Here’s the reality check that most predictions miss: AI agents currently operate at about 80% accuracy (according to Microsoft’s AI CEO). Sounds impressive, right? But here’s the thing – for businesses and users to actually trust these systems with meaningful tasks, we need 99% reliability. That’s not just a 19% gap – it’s the difference between an interesting tech demo and a business-critical tool.
This matters because it completely changes how we should think about AI agents in 2025. While major players like Microsoft, Google, and Amazon are pouring billions into development, they’re all facing the same fundamental challenge – making them work reliably enough that you can actually trust them with your business processes.
Think about it this way: Would you trust an assistant who gets things wrong 20% of the time? Probably not. But would you trust one who makes a mistake only 1% of the time, especially if they could handle repetitive tasks across your entire workflow? That’s a completely different conversation.
In the tech world, we like to label periods as the year of (insert milestone here). This past year (2024) was a year of broader experimentation in AI and, of course, agentic use cases.
As 2025 opens, VentureBeat spoke to industry analysts and IT decision-makers to see what the year might bring. For many, 2025 will be the year of agents, when all the pilot programs, experiments and new AI use cases converge into something resembling a return on investment.
In addition, the experts VentureBeat spoke to see 2025 as the year AI orchestration will play a bigger role in the enterprise. Organizations plan to make management of AI applications and agents much more straightforward.
Here are some themes we expect to see more in 2025.
AI agents take charge
Jérémy Grandillon, CEO of TC9 – AI Allbound Agency, said “Today, AI can do a lot, but we don’t trust it to take actions on our behalf. This will change in 2025. Be ready to ask your AI assistant to book a Uber ride for you.” Start small with one agent handling one task. Build up to an army.
“If 2024 was agents everywhere, then 2025 will be about bringing those agents together in networks and systems,” said Nicholas Holland, vice president of AI at Hubspot. “Micro agents working together to accomplish larger bodies of work, and marketplaces where humans can ‘hire’ agents to work alongside them in hybrid teams. Before long, we’ll be saying, ‘there’s an agent for that.'”
… Voice becomes default
Stop typing and start talking. Adam Biddlecombe, head of brand at Mindstream, predicts a shift in how we interact with AI. “2025 will be the year that people start talking with AI,” he said. “The majority of people interact with ChatGPT and other tools in the text format, and a lot of emphasis is put on prompting skills.
Biddlecombe believes, “With Apple’s ChatGPT integration for Siri, millions of people will start talking to ChatGPT. This will make AI so much more accessible and people will start to use it for very simple queries.”
Get ready for the next wave of advancements in AI. AGI arrives early, AI agents take charge, and voice becomes the norm. Video creation gets easy, AI embeds everywhere, and one-person billion-dollar companies emerge.
To better understand the types of roles that AI is impacting, ZoomInfo’s research team looked to its proprietary database of professional contacts for answers. The platform, which detects more than 1.5 million personnel changes per day, revealed a dramatic increase in AI-related job titles since 2022. With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.
Why does this shift in AI titles matter for every industry?
An Arizona charter school will use AI instead of human teachers for two hours a day on academic lessons.
The AI will customize lessons in real-time to match each student’s needs.
The company has only tested this idea at private schools before but claims it hugely increases student academic success.
One school in Arizona is trying out a new educational model built around AI and a two-hour school day. When Arizona’s Unbound Academy opens, the only teachers will be artificial intelligence algorithms in a perfect utopia or dystopia, depending on your point of view.
In order to encourage and facilitate debate on key controversies related to AI, I put together this free 130+ page guide to the main arguments and ideas related to the controversies.
Universities need to step up their AGI game — from futureofbeinghuman.com by Andrew Maynard As Sam Altman and others push toward a future where AI changes everything, universities need to decide if they’re going to be leaders or bystanders in helping society navigate advanced AI transitions
And because of this, I think there’s a unique opportunity for universities (research universities in particular) to up their game and play a leadership role in navigating the coming advanced AI transition.
Of course, there are already a number of respected university-based initiatives that are working on parts of the challenge. Stanford HAI (Human-centered Artificial Intelligence) is one that stands out, as does the Leverhulm Center for the Future of Intelligence at the University of Cambridge, and the Center for Governance of AI at the University of Oxford. But these and other initiatives are barely scratching the surface of what is needed to help successfully navigate advanced AI transitions.
If universities are to be leaders rather than bystanders in ensuring human flourishing in an age of AI, there’s an urgent need for bolder and more creative forward-looking initiatives that support research, teaching, thought leadership, and knowledge mobilization, at the intersection of advanced AI and all aspects of what it means to thrive and grow as a species.
Introducing the 2025 Wonder Media Calendar for tweens, teens, and their families/households.Designed by Sue Ellen Christian and her students in her Global Media Literacy class (in the fall 2024 semester at Western Michigan University), the calendar’s purpose is to help people create a new year filled with skills and smart decisions about their media use. This calendar is part of the ongoing Wonder Media Library.comproject that includes videos, lesson plans, games, songs and more. The website is funded by a generous grant from the Institute of Museum and Library Services, in partnership with Western Michigan University and the Library of Michigan.
“I mean, that’s what I’ll always want for my own children and, frankly, for anyone’s children,” Khan said. “And the hope here is that we can use artificial intelligence and other technologies to amplify what a teacher can do so they can spend more time standing next to a student, figuring them out, having a person-to-person connection.”
…
“After a week you start to realize, like, how you can use it,” Brockman said. “That’s been one of the really important things about working with Sal and his team, to really figure out what’s the right way to sort of bring this to parents and to teachers and to classrooms and to do that in a way…so that the students really learn and aren’t just, you know, asking for the answers and that the parents can have oversight and the teachers can be involved in that process.”
More than 100 colleges and high schools are turning to a new AI tool called Nectir, allowing teachers to create a personalized learning partner that’s trained on their syllabi, textbooks, and assignments to help students with anything from questions related to their coursework to essay writing assistance and even future career guidance.
…
With Nectir, teachers can create an AI assistant tailored to their specific needs, whether for a single class, a department, or the entire campus. There are various personalization options available, enabling teachers to establish clear boundaries for the AI’s interactions, such as programming the assistant to assist only with certain subjects or responding in a way that aligns with their teaching style.
“It’ll really be that customized learning partner. Every single conversation that a student has with any of their assistants will then be fed into that student profile for them to be able to see based on what the AI thinks, what should I be doing next, not only in my educational journey, but in my career journey,” Ghai said.
How Will AI Influence Higher Ed in 2025? — from insidehighered.com by Kathryn Palmer No one knows for sure, but Inside Higher Ed asked seven experts for their predictions.
As the technology continues to evolve at a rapid pace, no one knows for sure how AI will influence higher education in 2025. But several experts offered Inside Higher Ed their predictions—and some guidance—for how colleges and universities will have to navigate AI’s potential in the new year.
In the short term, A.I. will help teachers create lesson plans, find illustrative examples and generate quizzes tailored to each student. Customized problem sets will serve as tools to combat cheating while A.I. provides instant feedback.
…
In the longer term, it’s possible to imagine a world where A.I. can ingest rich learner data and create personalized learning paths for students, all within a curriculum established by the teacher. Teachers can continue to be deeply involved in fostering student discussions, guiding group projects and engaging their students, while A.I. handles grading and uses the Socratic method to help students discover answers on their own. Teachers provide encouragement and one-on-one support when needed, using their newfound availability to give students some extra care.
Let’s be clear: A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.
Today, I want to reflect on two recent OpenAI developments that highlight this evolution: their belated publication of advice for students on integrating AI into writing workflows, and last week’s launch of the full GPTo1 Pro version. When OpenAI released their student writing guide, there were plenty of snarky comments about how this guidance arrives almost a year after they thoroughly disrupted the educational landscape. Fair enough – I took my own side swipes initially. But let’s look at what they’re actually advising, because the details matter more than the timing.
Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.
That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil.
Faculty must have the time and support necessary to come to terms with this new technology and that requires us to change how we view professional development in higher education and K-12. We cannot treat generative AI as a one-off problem that can be solved by a workshop, an invited talk, or a course policy discussion. Generative AI in education has to be viewed as a continuum. Faculty need a myriad of support options each semester:
Course buyouts
Fellowships
Learning communities
Reading groups
AI Institutes and workshops
Funding to explore the scholarship of teaching and learning around generative AI
Education leaders should focus on integrating AI literacy, civic education, and work-based learning to equip students for future challenges and opportunities.
Building social capital and personalized learning environments will be crucial for student success in a world increasingly influenced by AI and decentralized power structures.
Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.
Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.
This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.
… Characteristics of Agentic AI
Autonomy: Achieves complex objectives without requiring human collaboration.
Language Comprehension: Understands nuanced human speech and text effectively.
Rationality: Makes informed, contextual decisions using advanced reasoning engines.
Adaptation: Adjusts plans and goals in dynamic situations.
Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.
How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?
Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.
Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper Google’s Veo 2, Kling 1.6, Pika 2.0 & more
AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.
Here’s a comprehensive look at the current landscape:
Veo 2…
Pika 2.0…
Runway’s Gen-3…
Luma AI Dream Machine…
Hailuo’s MiniMax…
OpenAI’s Sora…
Hunyuan Video by Tencent…
There are several other video models and platforms, including …
And you thought return to office policy was settled! For a while, it looked like 2-3 days per week in the office would be the future of work in America.
Yet this quarter has brought significant changes to the landscape. Major companies like Amazon, Dell, and The Washington Post announced their plans for a full return to office. Then came a shift in the political atmosphere, with Trump’s victory and potential incoming changes requiring full-time office work for government employees.
These developments raise important questions about where workplace flexibility is headed. Are we witnessing the beginning of a broader shift back to Full Time In Office? Is the era of fully flexible work coming to an end? Or is this simply another evolution in how companies structure their workplace policies?
In this report, we dig into US-wide trends to see if the high-profile shifts toward Full Time In Office reflect broader market movement or just isolated cases. We examine how different industries are approaching flexibility, from Technology’s continued embrace to the challenges faced by sectors dependent on physical presence. Plus, we explore the divide in how companies of different sizes approach workplace flexibility. Are we truly heading back to the office full time, or is the future of work more nuanced than the headlines suggest?
In this episode of My EdTech Life, I had the pleasure of interviewing Mike Kentz and Nick Potkalitsky, PhD, to discuss their new book, AI in Education: The K-12 Roadmap to Teacher-Led Transformation. We dive into the transformative power of AI in education, exploring its potential for personalization, its impact on traditional teaching practices, and the critical need for teacher-driven experimentation.
Striking a Balance: Navigating the Ethical Dilemmas of AI in Higher Education — from er.educause.edu by Katalin Wargo and Brier Anderson Navigating the complexities of artificial intelligence (AI) while upholding ethical standards requires a balanced approach that considers the benefits and risks of AI adoption.
As artificial intelligence (AI) continues to transform the world—including higher education—the need for responsible use has never been more critical. While AI holds immense potential to enhance teaching and learning, ethical considerations around social inequity, environmental concerns, and dehumanization continue to emerge. College and university centers for teaching and learning (CTLs), tasked with supporting faculty in best instructional practices, face growing pressure to take a balanced approach to adopting new technologies. This challenge is compounded by an unpredictable and rapidly evolving landscape. New AI tools surface almost daily. With each new tool, the educational possibilities and challenges increase exponentially. Keeping up is virtually impossible for CTLs, which historically have been institutional hubs for innovation. In fact, as of this writing, the There’s an AI for That website indicates that there are 23,208 AIs for 15,636 tasks for 4,875 jobs—with all three numbers increasing daily.
To support college and university faculty and, by extension, learners in navigating the complexities of AI integration while upholding ethical standards, CTLs must prioritize a balanced approach that considers the benefits and risks of AI adoption. Teaching and learning professionals need to expand their resources and support pathways beyond those solely targeting how to leverage AI or mitigate academic integrity violations. They need to make a concerted effort to promote critical AI literacy, grapple with issues of social inequity, examine the environmental impact of AI technologies, and promote human-centered design principles.1
We’re truly spoiled for choice when it comes to AI learning tools.
In principle, any free LLM can become an endlessly patient tutor or an interactive course-maker.
If that’s not enough, tools like NotebookLM’s “Audio Overviews” and ElevenLabs’ GenFM can turn practically any material into a breezy podcast.
But what if you’re looking to explore new topics in a way that’s more interactive than vanilla chatbots and more open-ended than source-grounded NotebookLM?
Well, then you might want to give one of these free-to-try learning tools a go.
Picture your enterprise as a living ecosystem,where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Now imagine if your systems could see these connections too! This is the promise of AI agents — an intelligent network that thinks, learns, and works across your entire enterprise.
Today, organizations operate in artificial silos. Tomorrow, they could be fluid and responsive. The transformation has already begun. The question is: will your company lead it?
The journey to agent-enabled operations starts with clarity on business objectives. Leaders should begin by mapping their business’s critical processes. The most pressing opportunities often lie where cross-functional handoffs create friction or where high-value activities are slowed by system fragmentation. These pain points become the natural starting points for your agent deployment strategy.
Artificial intelligence has already proved that it can sound like a human, impersonate individuals and even produce recordings of someone speaking different languages. Now, a new feature from Microsoft will allow video meeting attendees to hear speakers “talk” in a different language with help from AI.
What Is Agentic AI? — from blogs.nvidia.com by Erik Pounds Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.
The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. And it’s set to enhance productivity and operations across industries.
Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks.
