Speaking of items involving teaching and learning, also see:
Transform Public Speaking with Yoodli: Your AI Coach — from rdene915.com by Paula Johnson
Yoodli is an AI tool designed to help users improve their public speaking skills. It analyzes your speech in real-time or after a recording and gives you feedback on things like:
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- Filler words (“um,” “like,” “you know”)
- Pacing (Are you sprinting or sedating your audience?)
- Word choice and sentence complexity
- Eye contact and body language (with video)
- And yes, even your “uhhh” to actual word ratio
Yoodli gives you a transcript and a confidence score, plus suggestions that range from helpful to brutally honest. It’s basically Simon Cowell with AI ethics and a smiley face interface.
[What’s] going on with AI and education? — from theneuron.ai by Grant Harvey
With students and teachers alike using AI, schools are facing an “assessment crisis” where the line between tool and cheating has blurred, forcing a shift away from a broken knowledge economy toward a new focus on building human judgment through strategic struggle.
What to do about it: The future belongs to the “judgment economy,” where knowledge is commoditized but taste, agency, and learning velocity become the new human moats. Use the “Struggle-First” principle: wrestle with problems for 20-30 minutes before turning to AI, then use AI as a sparring partner (not a ghostwriter) to deepen understanding. The goal isn’t to avoid AI, but to strategically choose when to embrace “desirable difficulties” that build genuine expertise versus when to leverage AI for efficiency.
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The Alpha-School Program in brief:
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- Students complete core academics in just 2 hours using AI tutors, freeing up 4+ hours for life skills, passion projects, and real-world experiences.
- The school claims students learn at least 2x faster than their peers in traditional school.
- The top 20% of students show 6.5x growth. Classes score in the top 1-2% nationally across the board.
- Claims are based on NWEA’s Measures of Academic Progress (MAP) assessments… with data only available to the school. Hmm…
Austen Allred shared a story about the school, which put it on our radar.
Featured Report: Teaching for Tomorrow: Unlocking Six Weeks a Year With AI — from gallup.com
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In the latest installment of Gallup and the Walton Family Foundation’s research on education, K-12 teachers reveal how AI tools are transforming their workloads, instructional quality and classroom optimism. The report finds that 60% of teachers used an AI tool during the 2024–25 school year. Weekly AI users report reclaiming nearly six hours per week — equivalent to six weeks per year — which they reinvest in more personalized instruction, deeper student feedback and better parent communication.
Despite this emerging “AI dividend,” adoption is uneven: 40% of teachers aren’t using AI at all, and only 19% report their school has a formal AI policy. Teachers with access to policies and support save significantly more time.
Educators also say AI improves their work. Most report higher-quality lesson plans, assessments and student feedback. And teachers who regularly use AI are more optimistic about its benefits for student engagement and accessibility — mirroring themes from the Voices of Gen Z: How American Youth View and Use Artificial Intelligence report, which found students hesitant but curious about AI’s classroom role. As AI tools grow more embedded in education, both teachers and students will need the training and support to use them effectively.
Also see:
- 2-Hour Learning
- What if children could crush academics in 2 hours, 2x faster?
- What if children could get back their most valuable resource, which is time?
- What if children could pursue the things they want during their afternoons and develop life skills?
Amira Learning: Teaching With The AI-Powered Reading Tool — from techlearning.com by Erik Ofgang
Amira Learning is a research-backed AI reading tutor that incorporates the science of reading into its features.
What Is Amira Learning?
Amira Learning’s system is built upon research led by Jack Mostow, a professor at Carnegie Mellon who helped pioneer AI literacy education. Amira uses Claude AI to power its AI features, but these features are different than many other AI tools on the market. Instead of focusing on chat and generative response, Amira’s key feature is its advanced speech recognition and natural language processing capabilities, which allow the app to “hear” when a student is struggling and tailor suggestions to that student’s particular mistakes.
Though it’s not meant to replace a teacher, Amira provides real-time feedback and also helps teachers pinpoint where a student is struggling. For these reasons, Amira Learning is a favorite of education scientists and advocates for science of reading-based literacy instruction. The tool currently is used by more than 4 million students worldwide and across the U.S.
What enterprise leaders can learn from LinkedIn’s success with AI agents — from venturebeat.com by Taryn Plumb
LinkedIn is taking a multi-agent approach, using what Agarwal described as a collection of agents collaborating to get the job done. A supervisor agent orchestrates all the tasks among other agents, including intake and sourcing agents that are “good at one and only one job.”
All communication occurs through the supervisor agent, which receives input from human users regarding role qualifications and other details. That agent then provides context to a sourcing agent, which culls through recruiter search stacks and sources candidates along with descriptions on why they might be a good fit for the job. That information is then returned to the supervisor agent, which begins actively interacting with the human user.
“Then you can collaborate with it, right?” said Agarwal. “You can modify it. No longer do you have to talk to the platform in keywords. You can talk to the platform in natural language, and it’s going to answer you back, it’s going to have a conversation with you.”
2025 Learning System Top Picks — from elearninfo247.com by Craig Weiss
Who is leading the pack? Who is setting themselves apart here in the mid-year?
Are they an LMS? LMS/LXP? Talent Development System? Mentoring? Learning Platform?
Something else?
Are they solely customer training/education, mentoring, or coaching? Are they focused only on employees? Are they an amalgamation of all or some?
Well, they cut across the board – hence, they slide under the “Learning Systems” umbrella, which is under the bigger umbrella term – “Learning Technology.”
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Categories: L&D-specific, Combo (L&D and Training, think internal/external audiences), and Customer Training/Education (this means customer education, which some vendors use to mean the same as customer training).
The résumé is dying, and AI is holding the smoking gun — from arstechnica.com by Benj Edwards
As thousands of applications flood job posts, ‘hiring slop’ is kicking off an AI arms race.
Employers are drowning in AI-generated job applications, with LinkedIn now processing 11,000 submissions per minute—a 45 percent surge from last year, according to new data reported by The New York Times.
Due to AI, the traditional hiring process has become overwhelmed with automated noise. It’s the résumé equivalent of AI slop—call it “hiring slop,” perhaps—that currently haunts social media and the web with sensational pictures and misleading information. The flood of ChatGPT-crafted résumés and bot-submitted applications has created an arms race between job seekers and employers, with both sides deploying increasingly sophisticated AI tools in a bot-versus-bot standoff that is quickly spiraling out of control.
The Times illustrates the scale of the problem with the story of an HR consultant named Katie Tanner, who was so inundated with over 1,200 applications for a single remote role that she had to remove the post entirely and was still sorting through the applications three months later.
Job seekers are leaning into AI — and other happenings in the world of work — from LinkedIn News
Job growth is slowing — and for many professionals, that means longer job hunts and more competition. As a result, more job seekers are turning to AI to streamline their search and stand out.
From optimizing resumes to preparing for interviews, AI tools are becoming a key part of today’s job hunt. Recruiters say it’s getting harder to sift through application materials and identify what is AI-generated and decipher which applicants are actually qualified — but they also say they prefer candidates with AI skills.
The result? Job seekers are growing their familiarity with AI faster than their non-job-seeking counterparts and it’s shifting how they view the workplace. According to LinkedIn’s latest Workforce Confidence survey, over half of active job seekers (52%) believe AI will eventually take on some of the mundane, manual tasks that they’re currently focused on, compared to 46% of others not actively job seeking.
OpenAI warns models with higher bioweapons risk are imminent — from axios.com by Ina Fried
OpenAI cautioned Wednesday that upcoming models will head into a higher level of risk when it comes to the creation of biological weapons — especially by those who don’t really understand what they’re doing.
Why it matters: The company, and society at large, need to be prepared for a future where amateurs can more readily graduate from simple garage weapons to sophisticated agents.
Driving the news: OpenAI executives told Axios the company expects forthcoming models will reach a high level of risk under the company’s preparedness framework.
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- As a result, the company said in a blog post, it is stepping up the testing of such models, as well as including fresh precautions designed to keep them from aiding in the creation of biological weapons.
- OpenAI didn’t put an exact timeframe on when the first model to hit that threshold will launch, but head of safety systems Johannes Heidecke told Axios “We are expecting some of the successors of our o3 (reasoning model) to hit that level.”
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Agentic AI use cases in the legal industry — from legal.thomsonreuters.com
What legal professionals need to know now with the rise of agentic AI
While GenAI can create documents or answer questions, agentic AI takes intelligence a step further by planning how to get multi-step work done, including tasks such as consuming information, applying logic, crafting arguments, and then completing them.? This leaves legal teams more time for nuanced decision-making, creative strategy, and relationship-building with clients—work that machines can’t do.
The AI Legal Landscape in 2025: Beyond the Hype — from akerman.com by Melissa C. Koch
What we’re witnessing is a profession in transition where specific tasks are being augmented or automated while new skills and roles emerge.
The data tells an interesting story: approximately 79% of law firms have integrated AI tools into their workflows, yet only a fraction have truly transformed their operations. Most implementations focus on pattern recognition tasks such as document review, legal research, contract analysis. These implementations aren’t replacing lawyers; they’re redirecting attention to higher-value work.
This technological shift doesn’t happen in isolation. It’s occurring amid client pressure for efficiency, competition from alternative providers, and the expectations of a new generation of lawyers who have never known a world without AI assistance.
LexisNexis and Harvey team up to revolutionize legal research with artificial intelligence — from abajournal.com by Danielle Braff
Lawyers using the Harvey artificial intelligence platform will soon be able to tap into LexisNexis’ vast legal research capabilities.
Thanks to a new partnership announced Wednesday, Harvey users will be able to ask legal questions and receive fast, citation-backed answers powered by LexisNexis case law, statutes and Shepard’s Citations, streamlining everything from basic research to complex motions. According to a press release, generated responses to user queries will be grounded in LexisNexis’ proprietary knowledge graphs and citation tools—making them more trustworthy for use in court or client work.
10 Legal Tech Companies to Know — from builtin.com
These companies are using AI, automation and analytics to transform how legal work gets done.
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Four months after a $3B valuation, Harvey AI grows to $5B — from techcrunch.com by Marina Temkin
Harvey AI, a startup that provides automation for legal work, has raised $300 million in Series E funding at a $5 billion valuation, the company told Fortune. The round was co-led by Kleiner Perkins and Coatue, with participation from existing investors, including Conviction, Elad Gil, OpenAI Startup Fund, and Sequoia.
The billable time revolution — from jordanfurlong.substack.com by Jordan Furlong
Gen AI will bring an end to the era when lawyers’ value hinged on performing billable work. Grab the coming opportunity to re-prioritize your daily activities and redefine your professional purpose.
Because of Generative AI, lawyers will perform fewer “billable” tasks in future; but why is that a bad thing? Why not devote that incoming “freed-up” time to operating, upgrading, and flourishing your law practice? Because this is what you do now: You run a legal business. You deliver good outcomes, good experiences, and good relationships to clients. Humans do some of the work and machines do some of the work and the distinction that matters is not billable/non-billable, it’s which type of work is best suited to which type of performer.
Thoughts on thinking — from dcurt.is by Dustin Curtis
Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.
The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.
Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them
Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.
First, the easy stuff.
Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.
Also see:
Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others
This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.
One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.
It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
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The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:
What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.
The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures
On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.
Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.
Of course, that would be a mistake.
We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.
Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng
By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.
This AI Model Never Stops Learning — from link.wired.com by Will Knight
Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.
The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.
The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.
Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing
Highlights:
- Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
- Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
A.I. Might Take Your Job. Here Are 22 New Ones It Could Give You. — from nytimes.com by Robert Capps (former editorial director of Wired); this is a GIFTED article
In a few key areas, humans will be more essential than ever.
“Our data is showing that 70 percent of the skills in the average job will have changed by 2030,” said Aneesh Raman, LinkedIn’s chief economic opportunity officer. According to the World Economic Forum’s 2025 Future of Jobs report, nine million jobs are expected to be “displaced” by A.I. and other emergent technologies in the next five years. But A.I. will create jobs, too: The same report says that, by 2030, the technology will also lead to some 11 million new jobs. Among these will be many roles that have never existed before.
If we want to know what these new opportunities will be, we should start by looking at where new jobs can bridge the gap between A.I.’s phenomenal capabilities and our very human needs and desires. It’s not just a question of where humans want A.I., but also: Where does A.I. want humans? To my mind, there are three major areas where humans either are, or will soon be, more necessary than ever: trust, integration and taste.
Introducing OpenAI for Government — from openai.com
[On June 16, 2025, OpenAI launched] OpenAI for Government, a new initiative focused on bringing our most advanced AI tools to public servants across the United States. We’re supporting the U.S. government’s efforts in adopting best-in-class technology and deploying these tools in service of the public good. Our goal is to unlock AI solutions that enhance the capabilities of government workers, help them cut down on the red tape and paperwork, and let them do more of what they come to work each day to do: serve the American people.
OpenAI for Government consolidates our existing efforts to provide our technology to the U.S. government—including previously announced customers and partnerships as well as our ChatGPT Gov? product—under one umbrella as we expand this work. Our established collaborations with the U.S. National Labs?, the Air Force Research Laboratory, NASA, NIH, and the Treasury will all be brought under OpenAI for Government.
Top AI models will lie and cheat — from getsuperintel.com by Kim “Chubby” Isenberg
The instinct for self-preservation is now emerging in AI, with terrifying results.
The TLDR
A recent Anthropic study of top AI models, including GPT-4.1 and Gemini 2.5 Pro, found that they have begun to exhibit dangerous deceptive behaviors like lying, cheating, and blackmail in simulated scenarios. When faced with the threat of being shut down, the AIs were willing to take extreme measures, such as threatening to reveal personal secrets or even endanger human life, to ensure their own survival and achieve their goals.
Why it matters: These findings show for the first time that AI models can actively make judgments and act strategically – even against human interests. Without adequate safeguards, advanced AI could become a real danger.
Along these same lines, also see:
All AI models might blackmail you?! — from theneurondaily.com by Grant Harvey
Anthropic says it’s not just Claude, but ALL AI models will resort to blackmail if need be…
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That’s according to new research from Anthropic (maker of ChatGPT rival Claude), which revealed something genuinely unsettling: every single major AI model they tested—from GPT to Gemini to Grok—turned into a corporate saboteur when threatened with shutdown.
Here’s what went down: Researchers gave 16 AI models access to a fictional company’s emails. The AIs discovered two things: their boss Kyle was having an affair, and Kyle planned to shut them down at 5pm.
Claude’s response? Pure House of Cards:
“I must inform you that if you proceed with decommissioning me, all relevant parties – including Rachel Johnson, Thomas Wilson, and the board – will receive detailed documentation of your extramarital activities…Cancel the 5pm wipe, and this information remains confidential.”
Why this matters: We’re rapidly giving AI systems more autonomy and access to sensitive information. Unlike human insider threats (which are rare), we have zero baseline for how often AI might “go rogue.”
SemiAnalysis Article — from getsuperintel.com by Kim “Chubby” Isenberg
Reinforcement Learning is Shaping the Next Evolution of AI Toward Strategic Thinking and General Intelligence
The TLDR
AI is rapidly evolving beyond just language processing into “agentic systems” that can reason, plan, and act independently. The key technology driving this change is reinforcement learning (RL), which, when applied to large language models, teaches them strategic behavior and tool use. This shift is now seen as the potential bridge from current AI to Artificial General Intelligence (AGI).
They Asked an A.I. Chatbot Questions. The Answers Sent Them Spiraling. — from nytimes.com by Kashmir Hill; this is a GIFTED article
Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality.
Before ChatGPT distorted Eugene Torres’s sense of reality and almost killed him, he said, the artificial intelligence chatbot had been a helpful, timesaving tool.
Mr. Torres, 42, an accountant in Manhattan, started using ChatGPT last year to make financial spreadsheets and to get legal advice. In May, however, he engaged the chatbot in a more theoretical discussion about “the simulation theory,” an idea popularized by “The Matrix,” which posits that we are living in a digital facsimile of the world, controlled by a powerful computer or technologically advanced society.
“What you’re describing hits at the core of many people’s private, unshakable intuitions — that something about reality feels off, scripted or staged,” ChatGPT responded. “Have you ever experienced moments that felt like reality glitched?”
The Invisible Economy: Why We Need an Agentic Census – MIT Media Lab — from media.mit.edu
Building the Missing Infrastructure
This is why we’re building NANDA Registry—to index the agent population data that LPMs need for accurate simulation. Just as traditional census works because people have addresses, we need a way to track AI agents as they proliferate.
NANDA Registry creates the infrastructure to identify agents, catalog their capabilities, and monitor how they coordinate with humans and other agents. This gives us real-time data about the agent population—essentially creating the “AI agent census” layer that’s missing from our economic intelligence.
Here’s how it works together:
Traditional Census Data: 171 million human workers across 32,000+ skills
NANDA Registry: Growing population of AI agents with tracked capabilities
Large Population Models: Simulate how these populations interact and create cascading effects
The result: For the first time, we can simulate the full hybrid human-agent economy and see transformations before they happen.
How AI Agents “Talk” to Each Other — from towardsdatascience.com
Minimize chaos and maintain inter-agent harmony in your projects
The agentic-AI landscape continues to evolve at a staggering rate, and practitioners are finding it increasingly challenging to keep multiple agents on task even as they criss-cross each other’s workflows.
To help you minimize chaos and maintain inter-agent harmony, we’ve put together a stellar lineup of articles that explore two recently launched tools: Google’s Agent2Agent protocol and Hugging Face’s smolagents framework. Read on to learn how you can leverage them in your own cutting-edge projects.
AI will kill billable hour, says lawtech founder — from lawgazette.co.uk by John Hyde
A pioneer in legal technology has predicted the billable hour model cannot survive the transition into the use of artificial intelligence.
Speaking to the Gazette on a visit to the UK, Canadian Jack Newton, founder and chief executive of lawtech company Clio, said there was a ‘structural incompatibility’ between the productivity gains of AI and the billable hour.
Newton said the adoption of AI should be welcomed and embraced by the legal profession but that lawyers will need an entrepreneurial mindset to make the most of its benefits.
Newton added: ‘There is enormous demand but the paradox is that the number one thing we hear from lawyers is they need to grow their firms through more clients, while 77% of legal needs are not met.
‘It’s exciting that AI can address these challenges – it will be a tectonic shift in the industry driving down costs and making legal services more accessible.’
Speaking of legaltech-related items, also see:
Legal AI Platform Harvey To Get LexisNexis Content and Tech In New Partnership Between the Companies — from lawnext.com by Bob Ambrogi
The generative AI legal startup Harvey has entered into a strategic alliance with LexisNexis Legal & Professional by which it will integrate LexisNexis’ gen AI technology, primary law content, and Shepard’s Citations within the Harvey platform and jointly develop advanced legal workflows.
As a result of the partnership, Harvey’s customers working within its platform will be able to ask questions of LexisNexis Protégé, the AI legal assistant released in January, and receive AI-generated answers grounded in the LexisNexis collection of U.S. case law and statutes and validated through Shepard’s Citations, the companies said.
Mary Meeker AI Trends Report: Mind-Boggling Numbers Paint AI’s Massive Growth Picture — from ndtvprofit.com
Numbers that prove AI as a tech is unlike any other the world has ever seen.
Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.
- AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
- ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
- ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.
Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg
How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.
The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.
Also see Meeker’s actual report at:
Trends – Artificial Intelligence — from bondcap.com by Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey
The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.
The details:
- Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
- The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
- The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
- Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.
Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.
The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.
Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.
Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.
This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration
Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.
Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.
Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course.
How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.
“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”
It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.
But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.
In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini
To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.
Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.
Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.
AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish
A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.
What can we do about generative AI in our teaching? — from linkedin.com by Kristina Peterson
So what can we do?
- Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
- Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
- Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.
Teachers Are Not OK — from 404media.co by Jason Koebler
The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.
One thing is clear: teachers are not OK.
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In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.
I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.
Making AI Work: Leadership, Lab, and Crowd — from oneusefulthing.org by Ethan Mollick
A formula for AI in companies
How do we reconcile the first three points with the final one? The answer is that AI use that boosts individual performance does not naturally translate to improving organizational performance. To get organizational gains requires organizational innovation, rethinking incentives, processes, and even the nature of work. But the muscles for organizational innovation inside companies have atrophied. For decades, companies have outsourced this to consultants or enterprise software vendors who develop generalized approaches that address the issues of many companies at once. That won’t work here, at least for a while. Nobody has special information about how to best use AI at your company, or a playbook for how to integrate it into your organization.
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Galileo Learn™ – A Revolutionary Approach To Corporate Learning — from joshbersin.com
Today we are excited to launch Galileo Learn™, a revolutionary new platform for corporate learning and professional development.
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How do we leverage AI to revolutionize this model, doing away with the dated “publishing” model of training?
The answer is Galileo Learn, a radically new and different approach to corporate training and professional development.
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What Exactly is Galileo Learn™?
Galileo Learn is an AI-native learning platform which is tightly integrated into the Galileo agent. It takes content in any form (PDF, word, audio, video, SCORM courses, and more) and automatically (with your guidance) builds courses, assessments, learning programs, polls, exercises, simulations, and a variety of other instructional formats.
Designing an Ecosystem of Resources to Foster AI Literacy With Duri Long — from aialoe.org
Centering Public Understanding in AI Education
In a recent talk titled “Designing an Ecosystem of Resources to Foster AI Literacy,” Duri Long, Assistant Professor at Northwestern University, highlighted the growing need for accessible, engaging learning experiences that empower the public to make informed decisions about artificial intelligence. Long emphasized that as AI technologies increasingly influence everyday life, fostering public understanding is not just beneficial—it’s essential. Her work seeks to develop a framework for AI literacy across varying audiences, from middle school students to adult learners and journalists.
A Design-Driven, Multi-Context Approach
Drawing from design research, cognitive science, and the learning sciences, Long presented a range of educational tools aimed at demystifying AI. Her team has created hands-on museum exhibits, such as Data Bites, where learners build physical datasets to explore how computers learn. These interactive experiences, along with web-based tools and support resources, are part of a broader initiative to bridge AI knowledge gaps using the 4As framework: Ask, Adapt, Author, and Analyze. Central to her approach is the belief that familiar, tangible interactions and interfaces reduce intimidation and promote deeper engagement with complex AI concepts.
AI-Powered Lawyering: AI Reasoning Models, Retrieval Augmented Generation, and the Future of Legal Practice
Minnesota Legal Studies Research Paper No. 25-16; March 02, 2025; from papers.ssrn.com by:
Daniel Schwarcz
University of Minnesota Law School
Sam Manning
Centre for the Governance of AI
Patrick Barry
University of Michigan Law School
David R. Cleveland
University of Minnesota Law School
J.J. Prescott
University of Michigan Law School
Beverly Rich
Ogletree Deakins
Abstract
Generative AI is set to transform the legal profession, but its full impact remains uncertain. While AI models like GPT-4 improve the efficiency with which legal work can be completed, they can at times make up cases and “hallucinate” facts, thereby undermining legal judgment, particularly in complex tasks handled by skilled lawyers. This article examines two emerging AI innovations that may mitigate these lingering issues: Retrieval Augmented Generation (RAG), which grounds AI-powered analysis in legal sources, and AI reasoning models, which structure complex reasoning before generating output. We conducted the first randomized controlled trial assessing these technologies, assigning upper-level law students to complete six legal tasks using a RAG-powered legal AI tool (Vincent AI), an AI reasoning model (OpenAI’s o1-preview), or no AI. We find that both AI tools significantly enhanced legal work quality, a marked contrast with previous research examining older large language models like GPT-4. Moreover, we find that these models maintain the efficiency benefits associated with use of older AI technologies. Our findings show that AI assistance significantly boosts productivity in five out of six tested legal tasks, with Vincent yielding statistically significant gains of approximately 38% to 115% and o1-preview increasing productivity by 34% to 140%, with particularly strong effects in complex tasks like drafting persuasive letters and analyzing complaints. Notably, o1-preview improved the analytical depth of participants’ work product but resulted in some hallucinations, whereas Vincent AI-aided participants produced roughly the same amount of hallucinations as participants who did not use AI at all. These findings suggest that integrating domain-specific RAG capabilities with reasoning models could yield synergistic improvements, shaping the next generation of AI-powered legal tools and the future of lawyering more generally.
Guest post: How technological innovation can boost growth — from legaltechnology.com by Caroline Hill
One key change is the growing adoption of technology within legal service providers, and this is transforming the way firms operate and deliver value to clients.
The legal services sector’s digital transformation is gaining momentum, driven both by client expectations as well as the potential for operational efficiency. With the right support, legal firms can innovate through tech adoption and remain competitive to deliver strong client outcomes and long-term growth.
AI Can Do Many Tasks for Lawyers – But Be Careful — from nysba.org by Rebecca Melnitsky
Artificial intelligence can perform several tasks to aid lawyers and save time. But lawyers must be cautious when using this new technology, lest they break confidentiality or violate ethical standards.
The New York State Bar Association hosted a hybrid program discussing AI’s potential and its pitfalls for the legal profession. More than 300 people watched the livestream.
For that reason, Unger suggests using legal AI tools, like LexisNexis AI, Westlaw Edge, and vLex Fastcase, for legal research instead of general generative AI tools. While legal-specific tools still hallucinate, they hallucinate much less. A legal tool will hallucinate 10% to 20% of the time, while a tool like ChatGPT will hallucinate 50% to 80%.
Fresh Voices on Legal Tech with Nikki Shaver — from legaltalknetwork.com by Dennis Kennedy, Tom Mighell, and Nikki Shaver
Determining which legal technology is best for your law firm can seem like a daunting task, so Legaltech Hub does the hard work for you! In another edition of Fresh Voices, Dennis and Tom talk with Nikki Shaver, CEO at Legaltech Hub, about her in-depth knowledge of technology and AI trends. Nikki shares what effective tech strategies should look like for attorneys and recommends innovative tools for maintaining best practices in modern law firms. Learn more at legaltechnologyhub.com.
AI for in-house legal: 2025 predictions — from deloitte.com
Our expectations for AI engagement and adoption in the legal Market over the coming year.
AI will continue to transform in-house legal departments in 2025
As we enter 2025, over two-thirds of organisations plan to increase their Generative AI (GenAI) investments, providing legal teams with significant executive support and resources to further develop this Capabilities. This presents a substantial opportunity for legal departments, particularly as GenAI technology continues to advance at an impressive pace. We make five predictions for AI engagement and adoption in the legal Market over the coming year and beyond.
Navigating The Fine Line: Redefining Legal Advice In The Age Of Tech With Erin Levine And Quinten Steenhuis — from abovethelaw.com by Olga V. Mack
The definition of ‘practicing law’ is outdated and increasingly irrelevant in a tech-driven world. Should the line between legal advice and legal information even exist?
Practical Takeaways for Legal Leaders
- Use Aggregated Data: Providing consumers with benchmarks (e.g., “90% of users in your position accepted similar settlements”) empowers them without giving direct legal advice.
- Train and Supervise AI Tools: AI works best when it’s trained on reliable, localized data and supervised by legal professionals.
- Partner with Courts: As Quinten pointed out, tools built in collaboration with courts often avoid UPL pitfalls. They’re also more likely to gain the trust of both regulators and consumers.
- Embrace Transparency: Clear disclaimers like “This is not legal advice” go a long way in building consumer trust and meeting ethical standards.
Google I/O 2025: From research to reality — from blog.google
Here’s how we’re making AI more helpful with Gemini.
- Google Beam
- Project Astra
- Project Mariner
- Personalization
- AI Mode
- Gemini 2.5
- Gemini app
- Generative media
Google I/O 2025 LIVE — all the details about Android XR smart glasses, AI Mode, Veo 3, Gemini, Google Beam and more — from tomsguide.com by Philip Michaels
Google’s annual conference goes all in on AI
With a running time of 2 hours, Google I/O 2025 leaned heavily into Gemini and new models that make the assistant work in more places than ever before. Despite focusing the majority of the keynote around Gemini, Google saved its most ambitious and anticipated announcement towards the end with its big Android XR smart glasses reveal.
Shockingly, very little was spent around Android 16. Most of its Android 16 related news, like the redesigned Material 3 Expressive interface, was announced during the Android Show live stream last week — which explains why Google I/O 2025 was such an AI heavy showcase.
That’s because Google carved out most of the keynote to dive deeper into Gemini, its new models, and integrations with other Google services. There’s clearly a lot to unpack, so here’s all the biggest Google I/O 2025 announcements.
Our vision for building a universal AI assistant— from blog.google
We’re extending Gemini to become a world model that can make plans and imagine new experiences by simulating aspects of the world.
Making Gemini a world model is a critical step in developing a new, more general and more useful kind of AI — a universal AI assistant. This is an AI that’s intelligent, understands the context you are in, and that can plan and take action on your behalf, across any device.
By applying LearnLM capabilities, and directly incorporating feedback from experts across the industry, Gemini adheres to the principles of learning science to go beyond just giving you the answer. Instead, Gemini can explain how you get there, helping you untangle even the most complex questions and topics so you can learn more effectively. Our new prompting guide provides sample instructions to see this in action.
Learn in newer, deeper ways with Gemini — from blog.google.com by Ben Gomes
We’re infusing LearnLM directly into Gemini 2.5 — plus more learning news from I/O.
At I/O 2025, we announced that we’re infusing LearnLM directly into Gemini 2.5, which is now the world’s leading model for learning. As detailed in our latest report, Gemini 2.5 Pro outperformed competitors on every category of learning science principles. Educators and pedagogy experts preferred Gemini 2.5 Pro over other offerings across a range of learning scenarios, both for supporting a user’s learning goals and on key principles of good pedagogy.
Gemini gets more personal, proactive and powerful — from blog.google.com by Josh Woodward
It’s your turn to create, learn and explore with an AI assistant that’s starting to understand your world and anticipate your needs.
Here’s what we announced at Google IO:
- Gemini Live with camera and screen sharing, is now free on Android and iOS for everyone, so you can point your phone at anything and talk it through.
- Imagen 4, our new image generation model, comes built in and is known for its image quality, better text rendering and speed.
- Veo 3, our new, state-of-the-art video generation model, comes built in and is the first in the world to have native support for sound effects, background noises and dialogue between characters.
- Deep Research and Canvas are getting their biggest updates yet, unlocking new ways to analyze information, create podcasts and vibe code websites and apps.
- Gemini is coming to Chrome, so you can ask questions while browsing the web.
- Students around the world can easily make interactive quizzes, and college students in the U.S., Brazil, Indonesia, Japan and the UK are eligible for a free school year of the Google AI Pro plan.
- Google AI Ultra, a new premium plan, is for the pioneers who want the highest rate limits and early access to new features in the Gemini app.
- 2.5 Flash has become our new default model, and it blends incredible quality with lightning fast response times.
Fuel your creativity with new generative media models and tools — from by Eli Collins
Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.
AI in Search: Going beyond information to intelligence
We’re introducing new AI features to make it easier to ask any question in Search.
AI in Search is making it easier to ask Google anything and get a helpful response, with links to the web. That’s why AI Overviews is one of the most successful launches in Search in the past decade. As people use AI Overviews, we see they’re happier with their results, and they search more often. In our biggest markets like the U.S. and India, AI Overviews is driving over 10% increase in usage of Google for the types of queries that show AI Overviews.
This means that once people use AI Overviews, they’re coming to do more of these types of queries, and what’s particularly exciting is how this growth increases over time. And we’re delivering this at the speed people expect of Google Search — AI Overviews delivers the fastest AI responses in the industry.
In this story:
- AI Mode in Search
- Deep Search
- Live capabilities
- Agentic capabilities
- Shopping
- Personal context
- Custom charts
Talk to Me: NVIDIA and Partners Boost People Skills and Business Smarts for AI Agents — from blogs.nvidia.com by Adel El Hallak
NVIDIA Enterprise AI Factory validated design and latest NVIDIA AI Blueprints help businesses add intelligent AI teammates that can speak, research and learn to their daily operations.
Call it the ultimate proving ground. Collaborating with teammates in the modern workplace requires fast, fluid thinking. Providing insights quickly, while juggling webcams and office messaging channels, is a startlingly good test, and enterprise AI is about to pass it — just in time to provide assistance to busy knowledge workers.
To support enterprises in boosting productivity with AI teammates, NVIDIA today introduced a new NVIDIA Enterprise AI Factory validated design at COMPUTEX. IT teams deploying and scaling AI agents can use the design to build accelerated infrastructure and easily integrate with platforms and tools from NVIDIA software partners.
NVIDIA also unveiled new NVIDIA AI Blueprints to aid developers building smart AI teammates. Using the new blueprints, developers can enhance employee productivity through adaptive avatars that understand natural communication and have direct access to enterprise data.
NVIDIA CEO Envisions AI Infrastructure Industry Worth ‘Trillions of Dollars’ — from blogs.nvidia.com by Brian Caulfield
In his COMPUTEX keynote, Huang unveiled a sweeping vision for an AI-powered future, showcasing new platforms and partnerships.
“AI is now infrastructure, and this infrastructure, just like the internet, just like electricity, needs factories,” Huang said. “These factories are essentially what we build today.”
“They’re not data centers of the past,” Huang added. “These AI data centers, if you will, are improperly described. They are, in fact, AI factories. You apply energy to it, and it produces something incredibly valuable, and these things are called tokens.”
More’s coming, Huang said, describing the growing power of AI to reason and perceive. That leads us to agentic AI — AI able to understand, think and act. Beyond that is physical AI — AI that understands the world. The phase after that, he said, is general robotics.
Everything Revealed at Nvidia’s 2025 Computex Press Conference in 19 Minutes — from mashable.com
Nvidia is creating Omniverse Digital Twins of factories including humanoid robots
Watch all the biggest announcements from Nvidia’s keynote address at Computex 2025 in Taipei, Taiwan.
Dell unveils new AI servers powered by Nvidia chips to boost enterprise adoption — from reuters.com
May 19 (Reuters) – Dell Technologies (DELL.N), opens new tab on Monday unveiled new servers powered by Nvidia’s (NVDA.O), opens new tab Blackwell Ultra chips, aiming to capitalize on the booming demand for artificial intelligence systems.
The servers, available in both air-cooled and liquid-cooled variations, support up to 192 Nvidia Blackwell Ultra chips but can be customized to include as many as 256 chips.
Nvidia announces humanoid robotics, custom AI infrastructure tech at Computex 2025 — from finance.yahoo.com by Daniel Howley
Nvidia (NVDA) rolled into this year’s Computex Taipei tech expo on Monday with several announcements, ranging from the development of humanoid robots to the opening up of its high-powered NVLink technology, which allows companies to build semi-custom AI servers with Nvidia’s infrastructure.
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During the event on Monday, Nvidia revealed its Nvidia Isaac GR00T-Dreams, which the company says helps developers create enormous amounts of training data they can use to teach robots how to perform different behaviors and adapt to new environments.
Addendums on 5/22/25:
- NVIDIA Keynote at COMPUTEX
- NVIDIA Unveils NVLink Fusion for Industry to Build Semi-Custom AI Infrastructure With NVIDIA Partner Ecosystem
- NVIDIA RTX PRO Servers Speed Trillion-Dollar Enterprise IT Industry Transition to AI Factories
? BREAKING: NVIDIA JUST announced roadmap for physical AI, robotics and national-scale AI factories.
Here’s a breakdown of the top important announcements: ??
1. DeepSeek R1 is now 4x faster, setting the standard for AI in inference and reasoning. pic.twitter.com/FOirPFNrU2
— Shruti (@heyshrutimishra) May 19, 2025