From DSC:
Whenever we’ve had a flat tire over the years, a tricky part of the repair process is jacking up the car so that no harm is done to the car (or to me!). There are some grooves underneath the Toyota Camry where one is supposed to put the jack. But as the car is very low to the ground, these grooves are very hard to find (even in good weather and light). 

 

What’s needed is a robotic jack with vision.

If the jack had “vision” and had wheels on it, the device could locate the exact location of the grooves, move there, and then ask the owner whether they are ready for the car to be lifted up. The owner could execute that order when they are ready and the robotic jack could safely hoist the car up.

This type of robotic device is already out there in other areas. But this idea for assistance with replacing a flat tire represents an AI and robotic-based, consumer-oriented application that we’ll likely be seeing much more of in the future. Carmakers and suppliers, please add this one to your list!

Daniel

 


Articulate AI & the “Buttonification” of Instructional Design — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new trend in AI-UX, and its implications for Instructional Design

1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:

  • Evidence-Based Design Button…
  • Learner-Centered Objectives Generator…
    Engagement Optimiser…

2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?

  • Explain This Design…
  • Show Me Alternatives…
  • Challenge My Assumptions…
  • Learning Science Insights…

By reimagining the role of AI in this way, we would…


Recapping OpenAI’s Education Forum — from marcwatkins.substack.com by Marc Watkins

OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.

I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.


Off-Loading in the Age of Generative AI — from insidehighered.com by James DeVaney

As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?

This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?

 

The Tutoring Revolution — from educationnext.org by Holly Korbey
More families are seeking one-on-one help for their kids. What does that tell us about 21st-century education?

Recent research suggests that the number of students seeking help with academics is growing, and that over the last couple of decades, more families have been turning to tutoring for that help.

What the Future Holds
Digital tech has made private tutoring more accessible, more efficient, and more affordable. Students whose families can’t afford to pay $75 an hour at an in-person center can now log on from home to access a variety of online tutors, including Outschool, Wyzant, and Anchorbridge, and often find someone who can cater to their specific skills and needs—someone who can offer help in French to a student with ADHD, for example. Online tutoring is less expensive than in-person programs. Khan Academy’s Khanmigo chatbot can be a student’s virtual AI tutor, no Zoom meeting required, for $4 a month, and nonprofits like Learn to Be work with homeless shelters and community centers to give virtual reading and math tutoring free to kids who can’t afford it and often might need it the most.

 

The Future of Umpiring in Baseball: Balancing Tradition and Technology — from judgeschlegel.com by Judge Scott Schlegel
This article is not about baseball.

As we look to the future of umpiring in baseball, a balanced approach may offer the best solution. Rather than an all-or-nothing choice between human umpires and full automation, a hybrid system could potentially offer the benefits of both worlds. For instance, automated tracking systems could be used to assist human umpires, providing them with real-time data to inform their calls. This would maintain the human element and authority on the field while significantly enhancing accuracy and consistency.

Such a system would allow umpires to focus more on game management, player interactions, and the myriad other responsibilities that require human judgment and experience. It would preserve the traditional aspects of the umpire’s role that fans and players value, while leveraging technology to address concerns about accuracy and fairness.


Navigating the Intersection of Tradition and AI: The Future of Judicial Decision-Making — from judgeschlegel.com by Judge Scott Schlegel

Introduction
Continuing with our baseball analogy, we now turn our focus to the courtroom.

The intersection of technology and the justice system is a complex and often contentious space, much like the debate over automated umpires in baseball. As Major League Baseball considers whether automated systems should replace the human element in calling balls and strikes, the legal world faces similar questions: How far should we go in allowing technology to aid our decision-making processes, and what is the right balance between innovation and the traditions that define the courtroom?


AI and the rise of the Niche Lawyer — from jordanfurlong.substack.com by Jordan Furlong
A new legal market will create a new type of lawyer: Specialized, flexible, customized, fractional, home-based and online, exclusive, balanced and focused. This could be your future legal career.

Think of a new picture. A lawyer dressed in Professional Casual, or Business Comfortable, an outfit that looks sharp but feels relaxed. A lawyer inside their own apartment, in an extra bedroom, or in a shared workspace on a nearby bus route, taking an Uber to visit some clients and using Zoom to meet with others. A lawyer with a laptop and a tablet and a smartphone and no other capital expenditures. A lawyer whose overhead is only what’s literally over their head.

This lawyer starts work when they feel like it (maybe 7 am, maybe 10; maybe Monday, maybe not) and they stop working when they feel like it (maybe 4 pm, maybe 9). They have as many clients as they need, for whom they provide very specific, very personalized services. They provide some services that aren’t even “legal” to people who aren’t “clients” as we understand both terms. They have essential knowledge and skills that all lawyers share but unique knowledge and skills that hardly any others possess. They make as much money as they need in order to meet the rent and pay down their debts and afford a life with the people they love. They’re in complete charge of their career and their destiny, something they find terrifying and stressful and wonderful and fulfilling.


While We Were Distracted with the New ChatGPT Model, Google Quietly Dropped an AI Bombshell —  from judgeschlegel.com by Judge Scott Schlegel

While the latest ChatGPT model is dominating tech headlines, I was unexpectedly blown away by Google’s recent release of a new NotebookLM feature: Audio Overview. This tool, which transforms written content into simulated conversations, caught me off guard with its capabilities. I uploaded some of my blog posts on AI and the justice system, and what it produced left me speechless. The AI generated podcast-like discussions felt remarkably authentic, complete with nuanced interpretations and even slight misunderstandings of my ideas. This mirrors real-life discussions perfectly – after all, how often do we hear our own thoughts expressed by others and think, “That’s not quite what I meant”?



 

Duolingo Introduces AI-Powered Innovations at Duocon 2024 — from investors.duolingo.com; via Claire Zau

Duolingo’s new Video Call feature represents a leap forward in language practice for learners. This AI-powered tool allows Duolingo Max subscribers to engage in spontaneous, realistic conversations with Lily, one of Duolingo’s most popular characters. The technology behind Video Call is designed to simulate natural dialogue and provides a personalized, interactive practice environment. Even beginner learners can converse in a low-pressure environment because Video Call is designed to adapt to their skill level. By offering learners the opportunity to converse in real-time, Video Call builds the confidence needed to communicate effectively in real-world situations. Video Call is available for Duolingo Max subscribers learning English, Spanish, and French.


And here’s another AI-based learning item:

AI reading coach startup Ello now lets kids create their own stories — from techcrunch.com by Lauren Forristal; via Claire Zau

Ello, the AI reading companion that aims to support kids struggling to read, launched a new product on Monday that allows kids to participate in the story-creation process.

Called “Storytime,” the new AI-powered feature helps kids generate personalized stories by picking from a selection of settings, characters, and plots. For instance, a story about a hamster named Greg who performed in a talent show in outer space.

 

Workera’s CEO was mentored by Andrew Ng. Now he wants an AI agent to mentor you. — from techcrunch.com by Maxwell Zeff; via Claire Zau

On Tuesday, Workera announced Sage, an AI agent you can talk with that’s designed to assess an employee’s skill level, goals, and needs. After taking some short tests, Workera claims Sage will accurately gauge how proficient someone is at a certain skill. Then, Sage can recommend the appropriate online courses through Coursera, Workday, or other learning platform partners. Through chatting with Sage, Workera is designed to meet employees where they are, testing their skills in writing, machine learning, or math, and giving them a path to improve.

From DSC:
This is very much akin to what I’ve been trying to get at with my Learning from the Living [AI-Based Class] Room vision. And as learning agents come onto the scene, this type of vision should take off!

 

Walt Disney’s Wisdom: Lessons for Learning & Development Leaders — from learningguild.com by David Kelly

Here are a few of my favorite [quotes], along with the valuable lessons they offer us in Learning and Development.

  • “Everyone has deadlines.”
  • “I believe in being an innovator.”
  • “Times and conditions change so rapidly that we must keep our aim constantly focused on the future.
  • “I can never stand still. I must explore and experiment.”
  • …and several other quotes.
 

Students at This High School Do Internships. It’s a Game Changer — from edweek.org by Elizabeth Heubeck

Disengaged students. Sky-high absenteeism. A disconnect between the typical high school’s academic curriculum and post-graduation life.

These and related complaints about the American high school experience have been gathering steam for some time; the pandemic exacerbated them. State-level policymakers have taken note, and many are now trying to figure out how to give high school students access to a more relevant and engaging experience that prepares them for a future—whether it involves college or doesn’t.

After a slow start, the school’s internship program has grown exponentially. In 2019-20, just five students completed internships, mainly due to the logistical challenges the pandemic presented. This past year, it grew to over 180 participating seniors, with more than 200 community organizations agreeing to accept interns.


How Do Today’s High Schoolers Fare As They Enter Adulthood? View the Data — from edweek.org by Sarah D. Sparks

Even when students have access to high-quality dual-credit programs, they often do not get guidance about the academic and workplace requirements of particular fields until it’s too late, said Julie Lammers, the senior vice president of advocacy and corporate social responsibility for American Student Assistance, a national nonprofit focused on helping young people learn about college and careers.

“We need to start having career conversations with young people much earlier in their trajectory, at the time young people are still open to possibilities,” Lammers said. “If they don’t see themselves in science by 8th grade, STEM careers come off the table.”

Cost plays a big role in the decision to attend and stay in college. The Education Data Initiative finds that on average, students in 2024 racked up nearly$38,000 in debt to pursue a bachelor’s degree, with many expecting to take up to 20 years to pay it off. 

Transforming Education From School-Centered to Learner-Centered
Centering Learners by Design: Shaping the Future of Education — from gettingsmart.com

What outcomes do we truly desire for young people? Many students feel that their current educational experiences do not prepare them adequately for real-world challenges. Supported by data on attendance, disengagement, and stress, it’s evident that a shift is needed. To move beyond outdated school-centered models, we must embrace a learner-centered paradigm that fosters flexibility, personalization, and authentic community engagement. Innovative approaches like multiage microschools and passion projects are transforming how students learn by fostering real-world skills, confidence, and community engagement.

These learner-centered models—ranging from personalized projects to collaborative problem-solving—provide actionable strategies to create environments where every student can thrive. Schools are moving away from one-size-fits-all systems and embracing approaches like flexible learning pathways, mentorship opportunities, and community-integrated learning. These strategies are not only closing the gap between education and the skills needed for the future but also reshaping public schools into dynamic hubs of innovation.

Key Points
  • Engaging parents, youth, teachers, principals, district leaders, community members, and industry experts in the co-design process ensures that education systems align with the aspirations and needs of the community.
  • Transitioning from a traditional school-centered model to a learner-centered approach is critical for preparing students with the skills needed to thrive in the 21st century.

 

 

AI’s Trillion-Dollar Opportunity — from bain.com by David Crawford, Jue Wang, and Roy Singh
The market for AI products and services could reach between $780 billion and $990 billion by 2027.

At a Glance

  • The big cloud providers are the largest concentration of R&D, talent, and innovation today, pushing the boundaries of large models and advanced infrastructure.
  • Innovation with smaller models (open-source and proprietary), edge infrastructure, and commercial software is reaching enterprises, sovereigns, and research institutions.
  • Commercial software vendors are rapidly expanding their feature sets to provide the best use cases and leverage their data assets.

Accelerated market growth. Nvidia’s CEO, Jensen Huang, summed up the potential in the company’s Q3 2024 earnings call: “Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades.”


And on a somewhat related note (i.e., emerging technologies), also see the following two postings:

Surgical Robots: Current Uses and Future Expectations — from medicalfuturist.com by Pranavsingh Dhunnoo
As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre.

Key Takeaways

  • Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.
  • Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.
  • The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.

Proto hologram tech allows cancer patients to receive specialist care without traveling large distances — from inavateonthenet.net

“Working with the team from Proto to bring to life, what several years ago would have seemed impossible, is now going to allow West Cancer Center & Research Institute to pioneer options for patients to get highly specialized care without having to travel to large metro areas,” said West Cancer’s CEO, Mitch Graves.




Clone your voice in minutes: The AI trick 95% don’t know about — from aidisruptor.ai by Alex McFarland
Warning: May cause unexpected bouts of talking to yourself

Now that you’ve got your voice clone, what can you do with it?

  1. Content Creation:
    • Podcast Production: Record episodes in half the time. Your listeners won’t know the difference, but your schedule will thank you.
    • Audiobook Narration: Always wanted to narrate your own book? Now you can, without spending weeks in a recording studio.
    • YouTube Videos: Create voiceovers for your videos in multiple languages. World domination, here you come!
  2. Business Brilliance:
    • Customer Service: Personalized automated responses that actually sound personal.
    • Training Materials: Create engaging e-learning content in your own voice, minus the hours of recording.
    • Presentations: Never worry about losing your voice before a big presentation again. Your clone’s got your back.

185 real-world gen AI use cases from the world’s leading organizations — from blog.google by Brian Hall; via Daniel Nest’s Why Try AI

In a matter of months, organizations have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes.

In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes, and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; code creation; data analysis; cybersecurity; and creative ideation and production.

Here’s a snapshot of how 185 of these industry leaders are putting AI to use today, creating real-world use cases that will transform tomorrow.


AI Data Drop: 3 Key Insights from Real-World Research on AI Usage — from microsoft.com; via Daniel Nest’s Why Try AI
One of the largest studies of Copilot usage—at nearly 60 companies—reveals how AI is changing the way we work.

  1. AI is starting to liberate people from email
  2. Meetings are becoming more about value creation
  3. People are co-creating more with AI—and with one another


*** Dharmesh has been working on creating agent.ai — a professional network for AI agents.***


Speaking of agents, also see:

Onboarding the AI workforce: How digital agents will redefine work itself — from venturebeat.com by Gary Grossman

AI in 2030: A transformative force

  1. AI agents are integral team members
  2. The emergence of digital humans
  3. AI-driven speech and conversational interfaces
  4. AI-enhanced decision-making and leadership
  5. Innovation and research powered by AI
  6. The changing nature of job roles and skills

AI Video Tools You Can Use Today — from heatherbcooper.substack.com by Heather Cooper
The latest AI video models that deliver results

AI video models are improving so quickly, I can barely keep up! I wrote about unreleased Adobe Firefly Video in the last issue, and we are no closer to public access to Sora.

No worries – we do have plenty of generative AI video tools we can use right now.

  • Kling AI launched its updated v1.5 and the quality of image or text to video is impressive.
  • Hailuo MiniMax text to video remains free to use for now, and it produces natural and photorealistic results (with watermarks).
  • Runway added the option to upload portrait aspect ratio images to generate vertical videos in Gen-3 Alpha & Turbo modes.
  • …plus several more

 


RIP To Human First Pass Document Review? — from abovethelaw.com by Joe Patrice
Using actual humans to perform an initial review isn’t gone yet, but the days are numbered.

Lawyers are still using real, live people to take a first crack at document review, but much like the “I’m not dead yet” guy from Monty Python and the Holy Grail, it’s a job that will be stone dead soon. Because there are a lot of deeply human tasks that AI will struggle to replace, but getting through a first run of documents doesn’t look like one of them.

At last week’s Relativity Fest, the star of the show was obviously Relativity aiR for Review, which the company moved to general availability. In conjunction with the release, Relativity pointed to impressive results the product racked up during the limited availability period including Cimplifi reporting that the product cut review time in half and JND finding a 60 percent cut in costs.


Ernie The Attorney: A Tech Whisperer Shares His Legal Tech Secrets — from legaltalknetwork.com by Ernie Svenson
Guest Ernie “The Attorney” Svenson is dedicated to helping small and solo firms get the most out of today’s tech tools. Work smarter, not harder.

When it comes to efficiencies, automation plays a big role. In a solo or small firm, resources come at a premium. Learn to reduce wasted input through standardized, repeatable operating procedures and automation. (There are even tech products that help you create written standard processes learning from and organizing the work you’re already doing).

Imagine speaking into an app as you “brain dump” and having those thoughts come out organized and notated for later use. Imagine dictating legal work into an app and having AI organize your dictation, even correct it. You don’t need to type everything in today’s tech world. Maximize downtime.

It’s all about training yourself to think “automation first.” Even when a virtual assistant (VA) located in another country can fill gaps in your practice, learn your preferences, match your brand, and help you be your most efficient you without hiring a full-tie employee. Today’s most successful law firms are high-tech hubs. Don’t let fear of the unknown hold you back.


Here’s the Video of Our Legaltech Week Panel Recorded Live Friday at RelativityFest in Chicago — from lawnext.com by Bob Ambrogi

Several of our regular Legaltech Week panelists were in Chicago for RelativityFest last week, so we took the opportunity to get together and broadcast our show live from the same room (instead of Zoom squares).

If you missed it Friday, here’s the video recording.


LexisNexis legal AI adoption report shows sharp increase in use of Gen AI — from legaltechnology.com

Today (24 September) LexisNexis has released a new report – Need for Speedier Legal Services sees AI Adoption Accelerate – which reveals a sharp increase in the number of lawyers using generative AI for legal work.

The survey of 800+ UK legal professionals at firms and in-house teams found 41% are currently using AI for work, up from 11% in July 2023. Lawyers with plans to use AI for legal work in the near future also jumped from 28% to 41%, while those with no plans to adopt AI dropped from 61% to 15%. The survey found that 39% of private practice lawyers now expect to adjust their billing practices due to AI, up from 18% in January 2024.


Robin AI’s James Clough: ‘Don’t Skate To Where The Puck Is’ — from artificiallawyer.com

‘What if legal review cost just $1? What if legal review was 1,000X cheaper than today?’ he muses.

And, one could argue we are getting there already – at least in theory. How much does it actually cost to run a genAI tool, that is hitting the accuracy levels you require, over a relatively mundane contract in order to find top-level information? If token costs drop massively in the years ahead and tech licence costs have been shared out across a major legal business….then what is the cost to the firm per document?

Of course, there is review and there is review. A very deep and thorough review, with lots of redlining, back and forth negotiation, and redrafting by top lawyers is another thing. But, a ‘quick once-over’? It feels like we are already at the ‘pennies on the dollar’ stage for that.


What Is Legal Tech Convergence + Why It Matters — from artificiallawyer.com

In some cases the companies on the convergence path are just getting started and only offer a few additional skills (so far), in other cases, large companies with diverse histories have almost the same multi-skill offering across many areas.

Here are some examples:

  • Callidus
  • vLex
  • Thomson Reuters and LexisNexis
  • BRYTER
  • Harvey
  • Leya
  • …and others
 

FlexOS’ Stay Ahead Edition #43 — from flexos.work

People started discussing what they could do with Notebook LM after Google launched the audio overview, where you can listen to 2 hosts talking in-depth about the documents you upload. Here are what it can do:

  • Summarization: Automatically generate summaries of uploaded documents, highlighting key topics and suggesting relevant questions.
  • Question Answering: Users can ask NotebookLM questions about their uploaded documents, and answers will be provided based on the information contained within them.
  • Idea Generation: NotebookLM can assist with brainstorming and developing new ideas.
  • Source Grounding: A big plus against AI chatbot hallucination, NotebookLM allows users to ground the responses in specific documents they choose.
  • …plus several other items

The posting also lists several ideas to try with NotebookLM such as:

Idea 2: Study Companion

  • Upload all your course materials and ask NotebookLM to turn them into Question-and-Answer format, a glossary, or a study guide.
  • Get a breakdown of the course materials to understand them better.

Google’s NotebookLM: A Game-Changer for Education and Beyond — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
AI Tools: Breaking down Google’s latest AI tool and its implications for education.

“Google’s AI note-taking app NotebookLM can now explain complex topics to you out loud”

With more immersive text-to-video and audio products soon available and the rise of apps like Suno AI, how we “experience” Generative AI is also changing from a chatbot of 2 years ago, to a more multi-modal educational journey. The AI tools on the research and curation side are also starting to reflect these advancements.


Meet Google NotebookLM: 10 things to know for educators — from ditchthattextbook.com by Matt Miller

1. Upload a variety of sources for NotebookLM to use. 
You can use …

  • websites
  • PDF files
  • links to websites
  • any text you’ve copied
  • Google Docs and Slides
  • even Markdown

You can’t link it to YouTube videos, but you can copy/paste the transcript (and maybe type a little context about the YouTube video before pasting the transcript).

2. Ask it to create resources.
3. Create an audio summary.
4. Chat with your sources.
5. Save (almost) everything. 


NotebookLM summarizes my dissertation — from darcynorman.net by D’Arcy Norman, PhD

I finally tried out Google’s newly-announced NotebookLM generative AI application. It provides a set of LLM-powered tools to summarize documents. I fed it my dissertation, and am surprised at how useful the output would be.

The most impressive tool creates a podcast episode, complete with dual hosts in conversation about the document. First – these are AI-generated hosts. Synthetic voices, speaking for synthetic hosts. And holy moly is it effective. Second – although I’d initially thought the conversational summary would be a dumb gimmick, it is surprisingly powerful.


4 Tips for Designing AI-Resistant Assessments — from techlearning.com by Steve Baule and Erin Carter
As AI continues to evolve, instructors must modify their approach by designing meaningful, rigorous assessments.

As instructors work through revising assessments to be resistant to generation by AI tools with little student input, they should consider the following principles:

  • Incorporate personal experiences and local content into assignments
  • Ask students for multi-modal deliverables
  • Assess the developmental benchmarks for assignments and transition assignments further up Bloom’s Taxonomy
  • Consider real-time and oral assignments

Google CEO Sundar Pichai announces $120M fund for global AI education — from techcrunch.com by Anthony Ha

He added that he wants to avoid a global “AI divide” and that Google is creating a $120 million Global AI Opportunity Fund through which it will “make AI education and training available in communities around the world” in partnership with local nonprofits and NGOs.


Educators discuss the state of creativity in an AI world — from gettingsmart.com by Joe & Kristin Merrill, LaKeshia Brooks, Dominique’ Harbour, Erika Sandstrom

Key Points

  • AI allows for a more personalized learning experience, enabling students to explore creative ideas without traditional classroom limitations.
  • The focus of technology integration should be on how the tool is used within lessons, not just the tool itself

Addendum on 9/27/24:

Google’s NotebookLM enhances AI note-taking with YouTube, audio file sources, sharable audio discussions — from techcrunch.com by Jagmeet Singh

Google on Thursday announced new updates to its AI note-taking and research assistant, NotebookLM, allowing users to get summaries of YouTube videos and audio files and even create sharable AI-generated audio discussions

NotebookLM adds audio and YouTube support, plus easier sharing of Audio Overviews — from blog.google

 

10 Ways I Use LLMs like ChatGPT as a Professor — from automatedteach.com by Graham Clay
ChatGPT-4o, Gemini 1.5 Pro, Claude 3.5 Sonnet, custom GPTs – you name it, I use it. Here’s how…

Excerpt:

  1. To plan lessons (especially activities)
  2. To create course content (especially quizzes)
  3. To tutor my students
  4. To grade faster and give better feedback
  5. To draft grant applications
  6. Plus 5 other items

From Caution to Calcification to Creativity: Reanimating Education with AI’s Frankenstein Potential — from nickpotkalitsky.substack.com by Nick Potkalitsky
A Critical Analysis of AI-Assisted Lesson Planning: Evaluating Efficacy and Pedagogical Implications

Excerpt (emphasis DSC):

As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.

This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.

Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education


NotebookLM and Google’s Multimodal Vision for AI-Powered Learning Tools — from marcwatkins.substack.com by Marc Watkins

A Variety of Use Cases

  • Create an Interactive Syllabus
  • Presentation Deep Dive: Upload Your Slides
  • Note Taking: Turn Your Chalkboard into a Digital Canvas
  • Explore a Reading or Series of Readings
  • Help Navigating Feedback
  • Portfolio Building Blocks

Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform — from er.educause.edu by Fawzi BenMessaoud
The transformative impact of artificial intelligence on educational systems calls for a comprehensive reform to prepare future generations for an AI-integrated world.

The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.

AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.

 

Horizon Three Learning — from gettingsmart.com
How might we build the nation’s new learning ecosystem together?

America’s education system was a groundbreaking effort to help a growing nation thrive in the 19th century. Now, 200 years later, the world has changed; the horizon looks drastically different. Collectively, we need to redesign our education system to enable all of our children — and, by extension, our nation —  to thrive today and tomorrow.

“Horizon Three” or “H3” names the future-ready system we need, one that is grounded in equity serving learners’ individual strengths and needs as well as the common good. This series provides a glimpse of where H3 is already being designed and built. It also includes provocations about how we might fundamentally reimagine learning for the future ahead.

 

Legal budgets will get an AI-inspired makeover in 2025: survey — from legaldive.com by Justin Bachman
Nearly every general counsel is budgeting to add generative AI tools to their departments – and they’re all expecting to realize efficiencies by doing so.

Dive Brief:

  • Nearly all general counsel say their budgets are up slightly after wrestling with widespread cuts last year. And most of them, 61%, say they expect slightly larger budgets next year as well, an average of 5% more, according to the 2025 In-House Legal Budgeting Report from Axiom and Wakefield Research. Technology was ranked as the top in-house investment priority for both 2024 and 2025 for larger companies.
  • Legal managers predict their companies will boost investment on technology and real estate/facilities in 2025, while reducing outlays for human resources and mergers and acquisition activity, according to the survey. This mix of changing priorities might disrupt legal budgets.
  • Among the planned legal tech spending, the top three areas for investment are virtual legal assistants/AI-powered chatbots (35%); e-billing and spend-management software (31%); and contract management platforms (30%).
 



“Who to follow in AI” in 2024? — from ai-supremacy.com by Michael Spencer
Part III – #35-55 – I combed the internet, I found the best sources of AI insights, education and articles. LinkedIn | Newsletters | X | YouTube | Substack | Threads | Podcasts

This list features both some of the best Newsletters on AI and people who make LinkedIn posts about AI papers, advances and breakthroughs. In today’s article we’ll be meeting the first 19-34, in a list of 180+.

Newsletter Writers
YouTubers
Engineers
Researchers who write
Technologists who are Creators
AI Educators
AI Evangelists of various kinds
Futurism writers and authors

I have been sharing the list in reverse chronological order on LinkedIn here.


Inside Google’s 7-Year Mission to Give AI a Robot Body — from wired.com by Hans Peter Brondmo
As the head of Alphabet’s AI-powered robotics moonshot, I came to believe many things. For one, robots can’t come soon enough. For another, they shouldn’t look like us.


Learning to Reason with LLMs — from openai.com
We are introducing OpenAI o1, a new large language model trained with reinforcement learning to perform complex reasoning. o1 thinks before it answers—it can produce a long internal chain of thought before responding to the user.


Items re: Microsoft Copilot:

Also see this next video re: Copilot Pages:


Sal Khan on the critical human skills for an AI age — from time.com by Kevin J. Delaney

As a preview of the upcoming Summit interview, here are Khan’s views on two critical questions, edited for space and clarity:

  1. What are the enduring human work skills in a world with ever-advancing AI? Some people say students should study liberal arts. Others say deep domain expertise is the key to remaining professionally relevant. Others say you need to have the skills of a manager to be able to delegate to AI. What do you think are the skills or competencies that ensure continued relevance professionally, employability, etc.?
  2. A lot of organizations are thinking about skills-based approaches to their talent. It involves questions like, ‘Does someone know how to do this thing or not?’ And what are the ways in which they can learn it and have some accredited way to know they actually have done it? That is one of the ways in which people use Khan Academy. Do you have a view of skills-based approaches within workplaces, and any thoughts on how AI tutors and training fit within that context?

 
© 2024 | Daniel Christian