…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.
I assert that in the future, people will be able to see this information on a 24x7x365 basis.
Which jobs are in demand?
What skills do I need to do those jobs?
WHERE do I get/develop those skills?
And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.
BUT PEOPLE are the key! Often times, we need to — and prefer to — learn with others!
The Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Ben Kornell, Alex Sarlin, Sarah Morin, and Laurence Holt A market map and database featuring 60+ use cases for GenAI in education and 300+ GenAI powered education tools.
Used thoughtfully, ChatGPT can be a powerful tool to help students develop skills of rigorous thinking and clear writing, assisting them in thinking through ideas, mastering complex concepts, and getting feedback on drafts.
There are also ways to use ChatGPT that are counterproductive to learning—like generating an essay instead of writing it oneself, which deprives students of the opportunity to practice, improve their skills, and grapple with the material.
For students committed to becoming better writers and thinkers, here are some ways to use ChatGPT to engage more deeply with the learning process.
The Big Idea: As employers increasingly seek out applicants with AI skills, community colleges are well-positioned to train up the workforce. Partnerships with tech companies, like the AI Incubator Network, are helping some colleges get the resources and funding they need to overhaul programs and create new AI-focused ones.
Along these lines also see:
Practical AI Training — from the-job.beehiiv.com by Paul Fain Community colleges get help from Big Tech to prepare students for applied AI roles at smaller companies.
Miami Dade and other two-year colleges try to be nimble by offering training for AI-related jobs while focusing on local employers. Also, Intel’s business struggles while the two-year sector wonders if Republicans will cut funds for semiconductor production.
In this conversation, Josh Bersin discusses the evolving landscape of AI platforms, particularly focusing on Microsoft’s positioning and the challenges of creating a universal AI agent. He delves into the complexities of government efficiency, emphasizing the institutional challenges faced in re-engineering government operations.
The conversation also highlights the automation of work tasks and the need for businesses to decompose job functions for better efficiency.
Bersin stresses the importance of expertise in HR, advocating for a shift towards full stack professionals who possess a broad understanding of various HR functions.
Finally, he addresses the impending disruption in Learning and Development (L&D) due to AI advancements, predicting a significant transformation in how L&D professionals will manage knowledge and skills.
Teachers’ preferences are clear: they want to work where they will have the support of full-time experts in special education and pediatric physical and mental health. An overwhelming majority describe these supports as “beneficial” or “extremely beneficial” when asked to rate special-education co-teachers (93 percent) and paraprofessionals (92 percent), as well as counselors (89 percent) and school nurses (88 percent).
These roles are so important that teachers are willing to forgo salary increases when asked to choose between the two. Our analysis shows the average teacher is willing to trade a 21 percent raise for the full-time support of a special-education co-teacher and an 18 percent raise for a full-time special-education aide.
Macke Raymond, a Distinguished Research Fellow at the Hoover Institution and director of the Center for Research on Education Outcomes (CREDO) at Stanford University, joins Paul E. Peterson to discuss a report from the Education Futures Council, which looks to identify and remove barriers to student success within the K-12 educational system.
From DSC: I like the sound of putting teachers and principals in charge! As I just mentioned the other day, those on “the front line” (so to speak) know what’s working, what’s not working, and how best to fix things. Less legislators, more teachers.
I wish I could write that the last two years have made me more confident, more self-assured that AI is here to augment workers rather than replace them.
But I can’t.
I wish I could write that I know where schools and colleges will end up. I wish I could say that AI Agents will help us get where we need to be.
But I can’t.
At this point, today, I’m at a loss. I’m not sure where the rise of AI agents will take us, in terms of how we work and learn. I’m in the question-asking part of my journey. I have few answers.
So, let’s talk about where (I think) AI Agents will take education. And who knows? Maybe as I write I’ll come up with something more concrete.
It’s worth a shot, right?
From DSC: I completely agree with Jason’s following assertion:
A good portion of AI advancement will come down to employee replacement. And AI Agents push companies towards that.
THAT’s where/what the ROI will be for corporations. They will make their investments up in the headcount area, and likely in other areas as well (product design, marketing campaigns, engineering-related items, and more). But how much time it takes to get there is a big question mark.
One last quote here…it’s too good not to include:
Behind these questions lies a more abstract, more philosophical one: what is the relationship between thinking and doing in a world of AI Agents and other kinds of automation?
By examining models across three AI families—Claude, ChatGPT, and Gemini—I’ve started to identify each model’s strengths, limitations, and typical pitfalls.
Spoiler: my findings underscore that until we have specialised, fine-tuned AI copilots for instructional design, we should be cautious about relying on general-purpose models and ensure expert oversight in all ID tasks.
From DSC — I’m going to (have Nick) say this again:
I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing.
Students began mapping out research directions I’d never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns.
Google Workspace for Education admins can now turn on the Gemini app with added data protection as an additional service for their teen users (ages 13+ or the applicable age in your country) in the following languages and countries. With added data protection, chats are not reviewed by human reviewers or otherwise used to improve AI models. The Gemini app will be a core service in the coming weeks for Education Standard and Plus users, including teens,
Recently, I spoke with several teachers regarding their primary questions and reflections on using AI in teaching and learning. Their thought-provoking responses challenge us to consider not only what AI can do but what it means for meaningful and equitable learning environments. Keeping in mind these reflections, we can better understand how we move forward toward meaningful AI integration in education.
We’re introducing FrontierMath, a benchmark of hundreds of original, expert-crafted mathematics problems designed to evaluate advanced reasoning capabilities in AI systems. These problems span major branches of modern mathematics—from computational number theory to abstract algebraic geometry—and typically require hours or days for expert mathematicians to solve.
The demand for artificial intelligence courses in UK universities has surged dramatically over the past five years, with enrollments increasing by 453%, according to a recent study by Currys, a UK tech retailer.
The study, which analyzed UK university admissions data and surveyed current students and recent graduates, reveals how the growing influence of AI is shaping students’ educational choices and career paths.
This growth reflects the broader trend of AI integration across industries, creating new opportunities while transforming traditional roles. With AI’s influence on career prospects rising, students and graduates are increasingly drawn to AI-related courses to stay competitive in a rapidly changing job market.
Doing the Best You Can With the Time You Have — by Jay Schauer These strategies can help overwhelmed teachers prioritize tasks and find a balance between perfectionism and efficiency. .
How to Support Teachers’ Emotional Health — by Hedreich Nichols Emotional well-being plays a major role in teachers’ job satisfaction, and it’s essential that they have effective resources for support.
Teachers cannot be expected to teach SEL effectively without first being intentional about their own emotional health. If we want educators to guide students through emotional regulation, they must have the time, space, and support to do that work themselves. This goes beyond surface-level wellness initiatives—teachers need opportunities to reflect on their emotional triggers, manage their own stresses, and receive genuine support from their schools. Only when teachers are empowered to process their own emotional challenges can they truly foster a healthy social and emotional environment for their students.
In Praise of the Humble Document Camera — by Emily Rankin Revisiting a simple edtech tool can help you introduce rigor and engage students more deeply in their lessons.
4 Ways to Use a Document Camera in Your Classroom— by Emily Rankin If a document camera is gathering dust in a classroom, its lack of impact is probably linked to the user, not what the gadget is capable of. Case in point, I wasn’t using mine regularly because I didn’t know the value it could add to my teaching and learning. Here are some of the practices I now know are possible:
One factor to consider is the subject. In math, students need opportunities to work on rich tasks and solve problems in ways that make sense to them. However, that doesn’t mean direct instruction is totally absent from math time. The questions below can guide you in deciding whether to use direct instruction, when it would be appropriate, and who else in the classroom you might involve.
Increasing Talk Time in World Language Classes— by Kate Good Teachers can experiment with a variety of strategies to build and assess students’ ability to converse in the target language.
To capitalize on my students’ (seemingly inexhaustible) desire to chat, I work to increase student talk time in our Spanish immersion classes. I use several strategies to build and assess students’ oral language.
Is Generative AI and ChatGPT healthy for Students? — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky Beyond Text Generation: How AI Ignites Student Discovery and Deep Thinking, according to firsthand experiences of Teachers and AI researchers like Nick Potkalitsky.
After two years of intensive experimentation with AI in education, I am witnessing something amazing unfolding before my eyes. While much of the world fixates on AI’s generative capabilities—its ability to create essays, stories, and code—my students have discovered something far more powerful: exploratory AI, a dynamic partner in investigation and critique that’s transforming how they think.
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They’ve moved beyond the initial fascination with AI-generated content to something far more sophisticated: using AI as an exploratory tool for investigation, interrogation, and intellectual discovery.
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Instead of the much-feared “shutdown” of critical thinking, we’re witnessing something extraordinary: the emergence of what I call “generative thinking”—a dynamic process where students learn to expand, reshape, and evolve their ideas through meaningful exploration with AI tools. Here I consciously reposition the term “generative” as a process of human origination, although one ultimately spurred on by machine input.
A Road Map for Leveraging AI at a Smaller Institution — from er.educause.edu by Dave Weil and Jill Forrester Smaller institutions and others may not have the staffing and resources needed to explore and take advantage of developments in artificial intelligence (AI) on their campuses. This article provides a roadmap to help institutions with more limited resources advance AI use on their campuses.
The following activities can help smaller institutions better understand AI and lay a solid foundation that will allow them to benefit from it.
Understand the impact…
Understand the different types of AI tools…
Focus on institutional data and knowledge repositories…
Smaller institutions do not need to fear being left behind in the wake of rapid advancements in AI technologies and tools. By thinking intentionally about how AI will impact the institution, becoming familiar with the different types of AI tools, and establishing a strong data and analytics infrastructure, institutions can establish the groundwork for AI success. The five fundamental activities of coordinating, learning, planning and governing, implementing, and reviewing and refining can help smaller institutions make progress on their journey to use AI tools to gain efficiencies and improve students’ experiences and outcomes while keeping true to their institutional missions and values.
That is what they are doing here. Lesson plans focus on learners rather than the traditional teacher-centric model. Assessing prior strengths and weaknesses, personalising to focus more on weaknesses and less on things known or mastered. It’s adaptive, personalised learning. The idea that everyone should learn at the exactly same pace, within the same timescale is slightly ridiculous, ruled by the need for timetabling a one to many, classroom model.
For the first time in the history of our species we have technology that performs some of the tasks of teaching. We have reached a pivot point where this can be tried and tested. My feeling is that we’ll see a lot more of this, as parents and general teachers can delegate a lot of the exposition and teaching of the subject to the technology. We may just see a breakthrough that transforms education.
Agentic AI will be the top tech trend for 2025, according to research firm Gartner. The term describes autonomous machine “agents” that move beyond query-and-response generative chatbots to do enterprise-related tasks without human guidance.
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More realistic challenges that the firm has listed elsewhere include:
Agentic AI proliferating without governance or tracking;
Agentic AI making decisions that are not trustworthy;
All or nothing at Educause24 — from onedtech.philhillaa.com by Kevin Kelly Looking for specific solutions at the conference exhibit hall, with an educator focus
Here are some notable trends:
Alignment with campus policies: …
Choose your own AI adventure: …
Integrate AI throughout a workflow: …
Moving from prompt engineering to bot building: …
More complex problem-solving: …
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Not all AI news is good news. In particular, AI has exacerbated the problem of fraudulent enrollment–i.e., rogue actors who use fake or stolen identities with the intent of stealing financial aid funding with no intention of completing coursework.
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The consequences are very real, including financial aid funding going to criminal enterprises, enrollment estimates getting dramatically skewed, and legitimate students being blocked from registering for classes that appear “full” due to large numbers of fraudulent enrollments.
In a groundbreaking study, researchers from Penn Engineering showed how AI-powered robots can be manipulated to ignore safety protocols, allowing them to perform harmful actions despite normally rejecting dangerous task requests.
What did they find ?
Researchers found previously unknown security vulnerabilities in AI-governed robots and are working to address these issues to ensure the safe use of large language models(LLMs) in robotics.
Their newly developed algorithm, RoboPAIR, reportedly achieved a 100% jailbreak rate by bypassing the safety protocols on three different AI robotic systems in a few days.
Using RoboPAIR, researchers were able to manipulate test robots into performing harmful actions, like bomb detonation and blocking emergency exits, simply by changing how they phrased their commands.
Why does it matter?
This research highlights the importance of spotting weaknesses in AI systems to improve their safety, allowing us to test and train them to prevent potential harm.
From DSC: Great! Just what we wanted to hear. But does it surprise anyone? Even so…we move forward at warp speeds.
From DSC:
So, given the above item, does the next item make you a bit nervous as well? I saw someone on Twitter/X exclaim, “What could go wrong?” I can’t say I didn’t feel the same way.
We’re also introducing a groundbreaking new capability in public beta: computer use.Available today on the API, developers can direct Claude to use computers the way people do—by looking at a screen, moving a cursor, clicking buttons, and typing text. Claude 3.5 Sonnet is the first frontier AI model to offer computer use in public beta. At this stage, it is still experimental—at times cumbersome and error-prone. We’re releasing computer use early for feedback from developers, and expect the capability to improve rapidly over time.
Per The Rundown AI:
The Rundown: Anthropic just introduced a new capability called ‘computer use’, alongside upgraded versions of its AI models, which enables Claude to interact with computers by viewing screens, typing, moving cursors, and executing commands.
… Why it matters: While many hoped for Opus 3.5, Anthropic’s Sonnet and Haiku upgrades pack a serious punch. Plus, with the new computer use embedded right into its foundation models, Anthropic just sent a warning shot to tons of automation startups—even if the capabilities aren’t earth-shattering… yet.
Also related/see:
What is Anthropic’s AI Computer Use? — from ai-supremacy.com by Michael Spencer Task automation, AI at the intersection of coding and AI agents take on new frenzied importance heading into 2025 for the commercialization of Generative AI.
New Claude, Who Dis? — from theneurondaily.com Anthropic just dropped two new Claude models…oh, and Claude can now use your computer.
What makes Act-One special? It can capture the soul of an actor’s performance using nothing but a simple video recording. No fancy motion capture equipment, no complex face rigging, no army of animators required. Just point a camera at someone acting, and watch as their exact expressions, micro-movements, and emotional nuances get transferred to an AI-generated character.
Think about what this means for creators: you could shoot an entire movie with multiple characters using just one actor and a basic camera setup. The same performance can drive characters with completely different proportions and looks, while maintaining the authentic emotional delivery of the original performance. We’re witnessing the democratization of animation tools that used to require millions in budget and years of specialized training.
Also related/see:
Introducing, Act-One. A new way to generate expressive character performances inside Gen-3 Alpha using a single driving video and character image. No motion capture or rigging required.
Google has signed a “world first” deal to buy energy from a fleet of mini nuclear reactors to generate the power needed for the rise in use of artificial intelligence.
The US tech corporation has ordered six or seven small nuclear reactors (SMRs) from California’s Kairos Power, with the first due to be completed by 2030 and the remainder by 2035.
After the extreme peak and summer slump of 2023, ChatGPT has been setting new traffic highs since May
ChatGPT has been topping its web traffic records for months now, with September 2024 traffic up 112% year-over-year (YoY) to 3.1 billion visits, according to Similarweb estimates. That’s a change from last year, when traffic to the site went through a boom-and-bust cycle.
Google has made a historic agreement to buy energy from a group of small nuclear reactors (SMRs) from Kairos Power in California. This is the first nuclear power deal specifically for AI data centers in the world.
Hey creators!
Made on YouTube 2024 is here and we’ve announced a lot of updates that aim to give everyone the opportunity to build engaging communities, drive sustainable businesses, and express creativity on our platform.
Below is a roundup with key info – feel free to upvote the announcements that you’re most excited about and subscribe to this post to get updates on these features! We’re looking forward to another year of innovating with our global community it’s a future full of opportunities, and it’s all Made on YouTube!
Today, we’re announcing new agentic capabilities that will accelerate these gains and bring AI-first business process to every organization.
First, the ability to create autonomous agents with Copilot Studio will be in public preview next month.
Second, we’re introducing ten new autonomous agents in Dynamics 365 to build capacity for every sales, service, finance and supply chain team.
10 Daily AI Use Cases for Business Leaders— from flexos.work by Daan van Rossum While AI is becoming more powerful by the day, business leaders still wonder why and where to apply today. I take you through 10 critical use cases where AI should take over your work or partner with you.
Emerging Multi-Modal AI Video Creation Platforms The rise of multi-modal AI platforms has revolutionized content creation, allowing users to research, write, and generate images in one app. Now, a new wave of platforms is extending these capabilities to video creation and editing.
Multi-modal video platforms combine various AI tools for tasks like writing, transcription, text-to-voice conversion, image-to-video generation, and lip-syncing. These platforms leverage open-source models like FLUX and LivePortrait, along with APIs from services such as ElevenLabs, Luma AI, and Gen-3.
DC: I’m really hoping that a variety of AI-based tools, technologies, and services will significantly help with our Access to Justice (#A2J) issues here in America. So this article, per Kristen Sonday at Thomson Reuters — caught my eye.
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AI for Legal Aid: How to empower clients in need — from thomsonreuters.com by Kristen Sonday In this second part of this series, we look at how AI-driven technologies can empower those legal aid clients who may be most in need
It’s hard to overstate the impact that artificial intelligence (AI) is expected to have on helping low-income individuals achieve better access to justice.And for those legal services organizations (LSOs) that serve on the front lines, too often without sufficient funding, staff, or technology, AI presents perhaps their best opportunity to close the justice gap. With the ability of AI-driven tools to streamline agency operations, minimize administrative work, more effectively reallocate talent, and allow LSOs to more effectively service clients, the implementation of these tools is essential.
Innovative LSOs leading the way
Already many innovative LSOs are taking the lead, utilizing new technology to complete tasks from complex analysis to AI-driven legal research. Here are two compelling examples of how AI is already helping LSOs empower low-income clients in need.
Criminal charges, even those that are eligible for simple, free expungement, can prevent someone from obtaining housing or employment. This is a simple barrier to overcome if only help is available.
… AI offers the capacity to provide quick, accurate information to a vast audience, particularly to those in urgent need. AI can also help reduce the burden on our legal staff…
Everything you thought you knew about being a lawyer is about to change.
Legal Dive spoke with Podinic about the transformative nature of AI, including the financial risks to lawyers’ billing models and how it will force general counsel and chief legal officers to consider how they’ll use the time AI is expected to free up for the lawyers on their teams when they no longer have to do administrative tasks and low-level work.
Traditionally, law firms have been wary of adopting technologies that could compromise data privacy and legal accuracy; however, attitudes are changing
Despite concerns about technology replacing humans in the legal sector, legaltech is more likely to augment the legal profession than replace it entirely
Generative AI will accelerate digital transformation in the legal sector
The Adobe Firefly Video Model (beta) expands Adobe’s family of creative generative AI models and is the first publicly available video model designed to be safe for commercial use
Enhancements to Firefly models include 4x faster image generation and new capabilities integrated into Photoshop, Illustrator, Adobe Express and now Premiere Pro
Firefly has been used to generate 13 billion images since March 2023 and is seeing rapid adoption by leading brands and enterprises
Add sound to your video via text — Project Super Sonic:
New Dream Weaver — from aisecret.us Explore Adobe’s New Firefly Video Generative Model
Cybercriminals exploit voice cloning to impersonate individuals, including celebrities and authority figures, to commit fraud. They create urgency and trust to solicit money through deceptive means, often utilizing social media platforms for audio samples.
From DSC: Great…we have another tool called Canvas. Or did you say Canva?
Introducing canvas — from OpenAI A new way of working with ChatGPT to write and code
We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Canvas opens in a separate window, allowing you and ChatGPT to collaborate on a project. This early beta introduces a new way of working together—not just through conversation, but by creating and refining ideas side by side.
Canvas was built with GPT-4o and can be manually selected in the model picker while in beta. Starting today we’re rolling out canvas to ChatGPT Plus and Team users globally. Enterprise and Edu users will get access next week. We also plan to make canvas available to all ChatGPT Free users when it’s out of beta.
The way Americans buy homes is changing dramatically.
New industry rules about how home buyers’ real estate agents get paid are prompting a reckoning among housing experts and the tech sector. Many house hunters who are already stretched thin by record-high home prices and closing costs must now decide whether, and how much, to pay an agent.
A 2-3% commission on the median home price of $416,700 could be well over $10,000, and in a world where consumers are accustomed to using technology for everything from taxes to tickets, many entrepreneurs see an opportunity to automate away the middleman, even as some consumer advocates say not so fast.
The Great Mismatch — from the-job.beehiiv.com. by Paul Fain Artificial intelligence could threaten millions of decent-paying jobs held by women without degrees.
Women in administrative and office roles may face the biggest AI automation risk, find Brookings researchers armed with data from OpenAI. Also, why Indiana could make the Swiss apprenticeship model work in this country, and how learners get disillusioned when a certificate doesn’t immediately lead to a good job.
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A major new analysisfrom the Brookings Institution, using OpenAI data, found that the most vulnerable workers don’t look like the rail and dockworkers who have recaptured the national spotlight. Nor are they the creatives—like Hollywood’s writers and actors—that many wealthier knowledge workers identify with. Rather, they’re predominantly women in the 19M office support and administrative jobs that make up the first rung of the middle class.
“Unfortunately the technology and automation risks facing women have been overlooked for a long time,” says Molly Kinder, a fellow at Brookings Metro and lead author of the new report. “Most of the popular and political attention to issues of automation and work centers on men in blue-collar roles. There is far less awareness about the (greater) risks to women in lower-middle-class roles.”
introducing swarm: an experimental framework for building, orchestrating, and deploying multi-agent systems. ?https://t.co/97n4fehmtM
Is this how AI will transform the world over the next decade? — from futureofbeinghuman.com by Andrew Maynard Anthropic’s CEO Dario Amodei has just published a radical vision of an AI-accelerated future. It’s audacious, compelling, and a must-read for anyone working at the intersection of AI and society.
But if Amodei’s essay is approached as a conversation starter rather than a manifesto — which I think it should be — it’s hard to see how it won’t lead to clearer thinking around how we successfully navigate the coming AI transition.
Given the scope of the paper, it’s hard to write a response to it that isn’t as long or longer as the original. Because of this, I’d strongly encourage anyone who’s looking at how AI might transform society to read the original — it’s well written, and easier to navigate than its length might suggest.
That said, I did want to pull out a few things that struck me as particularly relevant and important — especially within the context of navigating advanced technology transitions.
And speaking of that essay, here’s a summary from The Rundown AI:
Anthropic CEO Dario Amodei just published a lengthy essay outlining an optimistic vision for how AI could transform society within 5-10 years of achieving human-level capabilities, touching on longevity, politics, work, the economy, and more.
The details:
Amodei believes that by 2026, ‘powerful AI’ smarter than a Nobel Prize winner across fields, with agentic and all multimodal capabilities, will be possible.
He also predicted that AI could compress 100 years of scientific progress into 10 years, curing most diseases and doubling the human lifespan.
The essay argued AI could strengthen democracy by countering misinformation and providing tools to undermine authoritarian regimes.
The CEO acknowledged potential downsides, including job displacement — but believes new economic models will emerge to address this.
He envisions AI driving unprecedented economic growth but emphasizes ensuring AI’s benefits are broadly distributed.
Why it matters:
As the CEO of what is seen as the ‘safety-focused’ AI lab, Amodei paints a utopia-level optimistic view of where AI will head over the next decade. This thought-provoking essay serves as both a roadmap for AI’s potential and a call to action to ensure the responsible development of technology.
However, most workers remain unaware of these efforts. Only a third (33%) of all U.S. employees say their organization has begun integrating AI into their business practices, with the highest percentage in white-collar industries (44%).
… White-collar workers are more likely to be using AI. White-collar workers are, by far, the most frequent users of AI in their roles. While 81% of employees in production/frontline industries say they never use AI, only 54% of white-collar workers say they never do and 15% report using AI weekly.
… Most employees using AI use it for idea generation and task automation. Among employees who say they use AI, the most common uses are to generate ideas (41%), to consolidate information or data (39%), and to automate basic tasks (39%).
Selling like hotcakes: The extraordinary demand for Blackwell GPUs illustrates the need for robust, energy-efficient processors as companies race to implement more sophisticated AI models and applications. The coming months will be critical to Nvidia as the company works to ramp up production and meet the overwhelming requests for its latest product.
Here’s my AI toolkit — from wondertools.substack.com by Jeremy Caplan and Nikita Roy How and why I use the AI tools I do — an audio conversation
1. What are two useful new ways to use AI?
AI-powered research: Type a detailed search query into Perplexity instead of Google to get a quick, actionable summary response with links to relevant information sources. Read more of my take on why Perplexity is so useful and how to use it.
Notes organization and analysis: Tools like NotebookLM, Claude Projects, and Mem can help you make sense of huge repositories of notes and documents. Query or summarize your own notes and surface novel connections between your ideas.
This article seeks to apply some lessons from brand management to learning design at a high level. Throughout the rest of this article, it is essential to remember that the context is an autonomous, interactive learning experience. The experience is created adaptively by Gen AI or (soon enough) by agents, not by rigid scripts. It may be that an AI will choose to present prewritten texts or prerecorded videos from a content library according to the human users’ responses or questions. Still, the overall experience will be different for each user. It will be more like a conversation than a book. …
In summary, while AI chatbots have the potential to enhance learning experiences, their acceptance and effectiveness depend on several factors, including perceived usefulness, ease of use, trust, relational factors, perceived risk, and enjoyment.
Personalization and building trust are essential for maintaining user engagement and achieving positive learning outcomes. The right “voice” for autonomous AI or a chatbot can enhance trust by making interactions more personal, consistent, and empathetic.
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.
“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.
Obviously this workflow works just as well for meetings as it does for lectures. Stay present in the meeting with no screens and just write down the key points with pen and paper. Then let NotebookLM assemble the detailed summary based on your high-level notes. https://t.co/fZMG7LgsWG
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.
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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 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
Advanced Voice is rolling out to all Plus and Team users in the ChatGPT app over the course of the week.
While you’ve been patiently waiting, we’ve added Custom Instructions, Memory, five new voices, and improved accents.
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.
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.
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.
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.
‘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.
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.
