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

 

AI researcher Jim Fan has had a charmed career. He was OpenAI’s first intern before he did his PhD at Stanford with “godmother of AI,” Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI “GEAR” group. The lab’s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a “foundation agent” that can generalize across skills, embodiments and realities—both physical and virtual. He also supports Jensen Huang’s idea that “Everything that moves will eventually be autonomous.”


Runway Partners with Lionsgate — from runwayml.com via The Rundown AI
Runway and Lionsgate are partnering to explore the use of AI in film production.

Lionsgate and Runway have entered into a first-of-its-kind partnership centered around the creation and training of a new AI model, customized on Lionsgate’s proprietary catalog. Fundamentally designed to help Lionsgate Studios, its filmmakers, directors and other creative talent augment their work, the model generates cinematic video that can be further iterated using Runway’s suite of controllable tools.

Per The Rundown: Lionsgate, the film company behind The Hunger Games, John Wick, and Saw, teamed up with AI video generation company Runway to create a custom AI model trained on Lionsgate’s film catalogue.

The details:

  • The partnership will develop an AI model specifically trained on Lionsgate’s proprietary content library, designed to generate cinematic video that filmmakers can further manipulate using Runway’s tools.
  • Lionsgate sees AI as a tool to augment and enhance its current operations, streamlining both pre-production and post-production processes.
  • Runway is considering ways to offer similar custom-trained models as templates for individual creators, expanding access to AI-powered filmmaking tools beyond major studios.

Why it matters: As many writers, actors, and filmmakers strike against ChatGPT, Lionsgate is diving head-first into the world of generative AI through its partnership with Runway. This is one of the first major collabs between an AI startup and a major Hollywood company — and its success or failure could set precedent for years to come.


A bottle of water per email: the hidden environmental costs of using AI chatbots — from washingtonpost.com by Pranshu Verma and Shelly Tan (behind paywall)
AI bots generate a lot of heat, and keeping their computer servers running exacts a toll.

Each prompt on ChatGPT flows through a server that runs thousands of calculations to determine the best words to use in a response.

In completing those calculations, these servers, typically housed in data centers, generate heat. Often, water systems are used to cool the equipment and keep it functioning. Water transports the heat generated in the data centers into cooling towers to help it escape the building, similar to how the human body uses sweat to keep cool, according to Shaolei Ren, an associate professor at UC Riverside.

Where electricity is cheaper, or water comparatively scarce, electricity is often used to cool these warehouses with large units resembling air-conditioners, he said. That means the amount of water and electricity an individual query requires can depend on a data center’s location and vary widely.


AI, Humans and Work: 10 Thoughts. — from rishad.substack.com by Rishad Tobaccowala
The Future Does Not Fit in the Containers of the Past. Edition 215.

10 thoughts about AI, Humans and Work in 10 minutes:

  1. AI is still Under-hyped.
  2. AI itself will be like electricity and is unlikely to be a differentiator for most firms.
  3. AI is not alive but can be thought of as a new species.
  4. Knowledge will be free and every knowledge workers job will change in 2025.
  5. The key about AI is not to ask what AI will do to us but what AI can do for us.
  6. Plus 5 other thoughts

 

 

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.

 

Top Software Engineering Newsletters in 2024 — from ai-supremacy.com by Michael Spencer
Including a very select few ML, AI and product Newsletters into the mix for Software Engineers.

This is an article specifically for the software engineers and developers among you.

In the past year (2023-2024) professionals are finding more value in Newsletters than ever before (especially on Substack).

As working from home took off, the nature of mentorship and skill acquisition has also evolved and shifted. Newsletters with pragmatic advice on our careers it turns out, are super valuable. This article is a resource list. Are you a software developer, work with one or know someone who is or wants to be?

 



“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?

 



Introducing OpenAI o1 – from openai.com

We’ve developed a new series of AI models designed to spend more time thinking before they respond. Here is the latest news on o1 research, product and other updates.




Something New: On OpenAI’s “Strawberry” and Reasoning — from oneusefulthing.org by Ethan Mollick
Solving hard problems in new ways

The new AI model, called o1-preview (why are the AI companies so bad at names?), lets the AI “think through” a problem before solving it. This lets it address very hard problems that require planning and iteration, like novel math or science questions. In fact, it can now beat human PhD experts in solving extremely hard physics problems.

To be clear, o1-preview doesn’t do everything better. It is not a better writer than GPT-4o, for example. But for tasks that require planning, the changes are quite large.


What is the point of Super Realistic AI? — from Heather Cooper who runs Visually AI on Substack

The arrival of super realistic AI image generation, powered by models like Midjourney, FLUX.1, and Ideogram, is transforming the way we create and use visual content.

Recently, many creators (myself included) have been exploring super realistic AI more and more.

But where can this actually be used?

Super realistic AI image generation will have far-reaching implications across various industries and creative fields. Its importance stems from its ability to bridge the gap between imagination and visual representation, offering multiple opportunities for innovation and efficiency.

Heather goes on to mention applications in:

  • Creative Industries
  • Entertainment and Media
  • Education and Training

NotebookLM now lets you listen to a conversation about your sources — from blog.google by Biao Wang
Our new Audio Overview feature can turn documents, slides, charts and more into engaging discussions with one click.

Today, we’re introducing Audio Overview, a new way to turn your documents into engaging audio discussions. With one click, two AI hosts start up a lively “deep dive” discussion based on your sources. They summarize your material, make connections between topics, and banter back and forth. You can even download the conversation and take it on the go.


Bringing generative AI to video with Adobe Firefly Video Model — from blog.adobe.com by Ashley Still

Over the past several months, we’ve worked closely with the video editing community to advance the Firefly Video Model. Guided by their feedback and built with creators’ rights in mind, we’re developing new workflows leveraging the model to help editors ideate and explore their creative vision, fill gaps in their timeline and add new elements to existing footage.

Just like our other Firefly generative AI models, editors can create with confidence knowing the Adobe Firefly Video Model is designed to be commercially safe and is only trained on content we have permission to use — never on Adobe users’ content.

We’re excited to share some of the incredible progress with you today — all of which is designed to be commercially safe and available in beta later this year. To be the first to hear the latest updates and get access, sign up for the waitlist here.

 

The Most Popular AI Tools for Instructional Design (September, 2024) — from drphilippahardman.substack.com by Dr. Philippa Hardman
The tools we use most, and how we use them

This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.

My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?

Here’s where we are in September, 2024:


Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby,  Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)

As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.



The Impact of AI in Advancing Accessibility for Learners with Disabilities — from er.educause.edu by Rob Gibson

AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.


 

A third of all generative AI projects will be abandoned, says Gartner — from zdnet.com by Tiernan Ray
The high upfront cost of deployment is one of the challenges that can doom generative AI projects

Companies are “struggling” to find value in the generative artificial intelligence (Gen AI) projects they have undertaken and one-third of initiatives will end up getting abandoned, according to a recent report by analyst Gartner.

The report states at least 30% of Gen AI projects will be abandoned after the proof-of-concept stage by the end of 2025.

From DSC:
But I wouldn’t write off the other two thirds of projects that will make it. I wouldn’t write off the future of AI in our world. AI-based technologies are already massively impacting graphic design, film, media, and more creative outlets. See the tweet below for some examples of what I’m talking about.



 

From DSC:
Anyone who is involved in putting on conferences should at least be aware that this kind of thing is now possible!!! Check out the following posting from Adobe (with help from Tata Consultancy Services (TCS).


From impossible to POSSIBLE: Tata Consultancy Services uses Adobe Firefly generative AI and Acrobat AI Assistant to turn hours of work into minutes — from blog.adobe.com

This year, the organizers — innovative industry event company Beyond Ordinary Events — turned to Tata Consultancy Services (TCS) to make the impossible “possible.” Leveraging Adobe generative AI technology across products like Adobe Premiere Pro and Acrobat, they distilled hours of video content in minutes, delivering timely dispatches to thousands of attendees throughout the conference.

For POSSIBLE ’24, Muche had an idea for a daily dispatch summarizing each day’s sessions so attendees wouldn’t miss a single insight. But timing would be critical. The dispatch needed to reach attendees shortly after sessions ended to fuel discussions over dinner and carry the excitement over to the next day.

The workflow started in Adobe Premiere Pro, with the writer opening a recording of each session and using the Speech to Text feature to automatically generate a transcript. They saved the transcript as a PDF file and opened it in Adobe Acrobat Pro. Then, using Adobe Acrobat AI Assistant, the writer asked for a session summary.

It was that fast and easy. In less than four minutes, one person turned a 30-minute session into an accurate, useful summary ready for review and publication.

By taking advantage of templates, the designer then added each AI-enabled summary to the newsletter in minutes. With just two people and generative AI technology, TCS accomplished the impossible — for the first time delivering an informative, polished newsletter to all 3,500 conference attendees just hours after the last session of the day.

 

When A.I.’s Output Is a Threat to A.I. Itself — from nytimes.com by Aatish Bhatia
As A.I.-generated data becomes harder to detect, it’s increasingly likely to be ingested by future A.I., leading to worse results.

All this A.I.-generated information can make it harder for us to know what’s real. And it also poses a problem for A.I. companies. As they trawl the web for new data to train their next models on — an increasingly challenging task — they’re likely to ingest some of their own A.I.-generated content, creating an unintentional feedback loop in which what was once the output from one A.I. becomes the input for another.

In the long run, this cycle may pose a threat to A.I. itself. Research has shown that when generative A.I. is trained on a lot of its own output, it can get a lot worse.


Per The Rundown AI:

The Rundown: Elon Musk’s xAI just launched “Colossus“, the world’s most powerful AI cluster powered by a whopping 100,000 Nvidia H100 GPUs, which was built in just 122 days and is planned to double in size soon.

Why it matters: xAI’s Grok 2 recently caught up to OpenAI’s GPT-4 in record time, and was trained on only around 15,000 GPUs. With now more than six times that amount in production, the xAI team and future versions of Grok are going to put a significant amount of pressure on OpenAI, Google, and others to deliver.


Google Meet’s automatic AI note-taking is here — from theverge.com by Joanna Nelius
Starting [on 8/28/24], some Google Workspace customers can have Google Meet be their personal note-taker.

Google Meet’s newest AI-powered feature, “take notes for me,” has started rolling out today to Google Workspace customers with the Gemini Enterprise, Gemini Education Premium, or AI Meetings & Messaging add-ons. It’s similar to Meet’s transcription tool, only instead of automatically transcribing what everyone says, it summarizes what everyone talked about. Google first announced this feature at its 2023 Cloud Next conference.


The World’s Call Center Capital Is Gripped by AI Fever — and Fear — from bloomberg.com by Saritha Rai [behind a paywall]
The experiences of staff in the Philippines’ outsourcing industry are a preview of the challenges and choices coming soon to white-collar workers around the globe.


[Claude] Artifacts are now generally available — from anthropic.com

[On 8/27/24], we’re making Artifacts available for all Claude.ai users across our Free, Pro, and Team plans. And now, you can create and view Artifacts on our iOS and Android apps.

Artifacts turn conversations with Claude into a more creative and collaborative experience. With Artifacts, you have a dedicated window to instantly see, iterate, and build on the work you create with Claude. Since launching as a feature preview in June, users have created tens of millions of Artifacts.


MIT's AI Risk Repository -- a comprehensive database of risks from AI systems

What are the risks from Artificial Intelligence?
A comprehensive living database of over 700 AI risks categorized by their cause and risk domain.

What is the AI Risk Repository?
The AI Risk Repository has three parts:

  • The AI Risk Database captures 700+ risks extracted from 43 existing frameworks, with quotes and page numbers.
  • The Causal Taxonomy of AI Risks classifies how, when, and why these risks occur.
  • The Domain Taxonomy of AI Risks classifies these risks into seven domains (e.g., “Misinformation”) and 23 subdomains (e.g., “False or misleading information”).

California lawmakers approve legislation to ban deepfakes, protect workers and regulate AI — from newsday.com by The Associated Press

SACRAMENTO, Calif. — California lawmakers approved a host of proposals this week aiming to regulate the artificial intelligence industry, combat deepfakes and protect workers from exploitation by the rapidly evolving technology.

Per Oncely:

The Details:

  • Combatting Deepfakes: New laws to restrict election-related deepfakes and deepfake pornography, especially of minors, requiring social media to remove such content promptly.
  • Setting Safety Guardrails: California is poised to set comprehensive safety standards for AI, including transparency in AI model training and pre-emptive safety protocols.
  • Protecting Workers: Legislation to prevent the replacement of workers, like voice actors and call center employees, with AI technologies.

New in Gemini: Custom Gems and improved image generation with Imagen 3 — from blog.google
The ability to create custom Gems is coming to Gemini Advanced subscribers, and updated image generation capabilities with our latest Imagen 3 model are coming to everyone.

We have new features rolling out, [that started on 8/28/24], that we previewed at Google I/O. Gems, a new feature that lets you customize Gemini to create your own personal AI experts on any topic you want, are now available for Gemini Advanced, Business and Enterprise users. And our new image generation model, Imagen 3, will be rolling out across Gemini, Gemini Advanced, Business and Enterprise in the coming days.


Cut the Chatter, Here Comes Agentic AI — from trendmicro.com

Major AI players caught heat in August over big bills and weak returns on AI investments, but it would be premature to think AI has failed to deliver. The real question is what’s next, and if industry buzz and pop-sci pontification hold any clues, the answer isn’t “more chatbots”, it’s agentic AI.

Agentic AI transforms the user experience from application-oriented information synthesis to goal-oriented problem solving. It’s what people have always thought AI would do—and while it’s not here yet, its horizon is getting closer every day.

In this issue of AI Pulse, we take a deep dive into agentic AI, what’s required to make it a reality, and how to prevent ‘self-thinking’ AI agents from potentially going rogue.

Citing AWS guidance, ZDNET counts six different potential types of AI agents:

    • Simple reflex agents for tasks like resetting passwords
    • Model-based reflex agents for pro vs. con decision making
    • Goal-/rule-based agents that compare options and select the most efficient pathways
    • Utility-based agents that compare for value
    • Learning agents
    • Hierarchical agents that manage and assign subtasks to other agents

Ask Claude: Amazon turns to Anthropic’s AI for Alexa revamp — from reuters.com by Greg Bensinger

Summary:

  • Amazon developing new version of Alexa with generative AI
  • Retailer hopes to generate revenue by charging for its use
  • Concerns about in-house AI prompt Amazon to turn to Anthropic’s Claude, sources say
  • Amazon says it uses many different technologies to power Alexa

Alibaba releases new AI model Qwen2-VL that can analyze videos more than 20 minutes long — from venturebeat.com by Carl Franzen


Hobbyists discover how to insert custom fonts into AI-generated images — from arstechnica.com by Benj Edwards
Like adding custom art styles or characters, in-world typefaces come to Flux.


200 million people use ChatGPT every week – up from 100 million last fall, says OpenAI — from zdnet.com by Sabrina Ortiz
Nearly two years after launching, ChatGPT continues to draw new users. Here’s why.

 

ILTACON 2024: Selling legal tech’s monorail — from abajournal.com by Nicole Black

The bottom line: The promise of GenAI for our profession is great, but all signs point to the realization of its potential being six months out or more. So the question remains: Will generative AI change the legal landscape, ushering in an era of frictionless, seamless legal work? Or have we reached the pinnacle of its development, left only with empty promises? I think it’s the former since there is so much potential, and many companies are investing significantly in AI development, but only time will tell.


From LegalZoom to AI-Powered Platforms: The Rise of Smart Legal Services — from tmcnet.com by Artem Vialykh

In today’s digital age, almost every industry is undergoing a transformation driven by technological innovation, and the legal field is no exception. Traditional legal services, often characterized by high fees, time-consuming processes, and complex paperwork, are increasingly being challenged by more accessible, efficient, and cost-effective alternatives.

LegalZoom, one of the pioneers in offering online legal services, revolutionized the way individuals and small businesses accessed legal assistance. However, with the advent of artificial intelligence (AI) and smart technologies, we are witnessing the rise of even more sophisticated platforms that are poised to reshape the legal landscape further.

The Rise of AI-Powered Legal Platforms
AI-powered legal platforms represent the next frontier in legal services. These platforms leverage the power of artificial intelligence, machine learning, and natural language processing to provide legal services that are not only more efficient but also more accurate and tailored to the needs of the user.

AI-powered platforms offer many advantages, with one of them being their ability to rapidly process and analyze large amounts of data quickly. This capability allows them to provide users with precise legal advice and document generation in a fraction of the time it would take a human attorney. For example, AI-driven platforms can review and analyze contracts, identify potential legal risks, and even suggest revisions, all in real-time. This level of automation significantly reduces the time and cost associated with traditional legal services.


AI, Market Dynamics, and the Future of Legal Services with Harbor’s Zena Applebaum — from geeklawblog.com by Greg Lambert

Zena talks about the integration of generative AI (Gen AI) into legal research tools, particularly at Thomson Reuters, where she previously worked. She emphasizes the challenges in managing expectations around AI’s capabilities while ensuring that the products deliver on their promises. The legal industry has high expectations for AI to simplify the time-consuming and complex nature of legal research. However, Applebaum highlights the need for balance, as legal research remains inherently challenging, and overpromising on AI’s potential could lead to dissatisfaction among users.

Zena shares her outlook on the future of the legal industry, particularly the growing sophistication of in-house legal departments and the increasing competition for legal talent. She predicts that as AI continues to enhance efficiency and drive changes in the industry, the demand for skilled legal professionals will rise. Law firms will need to adapt to these shifts by embracing new technologies and rethinking their strategies to remain competitive in a rapidly evolving market.


Future of the Delivery of Legal Services — from americanbar.org
The legal profession is in the midst of unprecedented change. Learn what might be next for the industry and your bar.


What. Just. Happened? (Post-ILTACon Emails Week of 08-19-2024) — from geeklawblog.com by Greg Lambert

Here’s this week’s edition of What. Just. Happened? Remember, you can track these daily with the AI Lawyer Talking Tech podcast (Spotify or Apple) which covers legal tech news and summarizes stories.


From DSC:
And although this next one is not necessarily legaltech-related, I wanted to include it here anyway — as I’m
always looking to reduce the costs of obtaining a degree.

Improve the Diversity of the Profession By Addressing the Costs of Becoming a Lawyer — from lssse.indiana.edu by Joan Howarth

Not surprisingly, then, research shows that economic assets are a significant factor in bar passage. And LSSSE research shows us the connections between the excessive expense of becoming a lawyer and the persistent racial and ethnic disparities in bar passage rate.

The racial and ethnic bar passage disparities are extreme. For example, the national ABA statistics for first time passers in 2023-24 show White candidates passing at 83%, compared to Black candidates (57%) with Asians and Hispanics in the middle (75% and 69%, respectively).

These disturbing figures are very related to the expense of becoming a lawyer.

Finally, though, after decades of stability — or stagnation — in attorney licensing, change is here. And some of the changes, such as the new pathway to licensure in Oregon based on supervised practice instead of a traditional bar exam, or the Nevada Plan in which most of the requirements can be satisfied during law school, should significantly decrease the costs of licensure and add flexibility for candidates with responsibilities beyond studying for a bar exam.  These reforms are long overdue.


Thomson Reuters acquires Safe Sign Technologies — from legaltechnology.com by Caroline Hill

Thomson Reuters today (21 August) announced it has acquired Safe Sign Technologies (SST), a UK-based startup that is developing legal-specific large language models (LLMs) and as of just eight months ago was operating in stealth mode.

 

Generative AI and the Time Management Revolution — from ai-mindset.ai by Conor Grennan

Here’s how we need to change our work lives:

  1. RECLAIM: Use generative AI to speed up your daily tasks. Be ruthless. Anything that can be automated, should be.
  2. PROTECT: This is the crucial step. That time you’ve saved? Protect it like it’s the last slice of pizza. Block it off in your calendar. Tell your team it’s sacred.
  3. ELEVATE: Use this protected time for high-level thinking. Strategy. Innovation. The big, meaty problems you never have time for.
  4. AMPLIFY: Here’s where it gets cool. Use generative AI to amp up your strategic thinking. Need to brainstorm solutions to a complex problem? Want to analyze market trends? Generative AI is your new thinking partner.

The top 100 Gen AI Consumer Apps — 3rd edition — from a16z.com by Andreessen Horowitz

But amid the relentless onslaught of product launches, investment announcements, and hyped-up features, it’s worth asking: Which of these gen AI apps are people actually using? Which behaviors and categories are gaining traction among consumers? And which AI apps are people returning to, versus dabbling and dropping?

Welcome to the third installment of the Top 100 Gen AI Consumer Apps.
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Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly
As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.

To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.

Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development. Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.


Adobe drops ‘Magic Fixup’: An AI breakthrough in the world of photo editing — from venturebeat.com by Michael Nuñez

Adobe researchers have revealed an AI model that promises to transform photo editing by harnessing the power of video data. Dubbed “Magic Fixup,” this new technology automates complex image adjustments while preserving artistic intent, potentially reshaping workflows across multiple industries.

Magic Fixup’s core innovation lies in its unique approach to training data. Unlike previous models that relied solely on static images, Adobe’s system learns from millions of video frame pairs. This novel method allows the AI to understand the nuanced ways objects and scenes change under varying conditions of light, perspective, and motion.


Top AI tools people actually use — from heatherbcooper.substack.com by Heather Cooper
How generative AI tools are changing the creative landscape

The shift toward creative tools
Creative tools made up 52% of the top generative AI apps on the list. This seems to reflect a growing consumer demand for accessible creativity through AI with tools for image, music, speech, video, and editing.

Creative categories include:

  • Image: Civitai, Leonardo, Midjourney, Yodayo, Ideogram, SeaArt
  • Music: Suno, Udio, VocalRemover
  • Speech: ElevenLabs, Speechify
  • Video: Luma AI, Viggle, Invideo AI, Vidnoz, ClipChamp
  • Editing: Cutout Pro, Veed, Photoroom, Pixlr, PicWish

Why it matters:
Creative apps are gaining traction because they empower digital artists and content creators with AI-driven tools that simplify and enhance the creative process, making professional-level work more accessible than ever.

 

College Writing Centers Worry AI Could Replace Them — from edsurge.com by Maggie Hicks
Those who run the centers argue that they could be a hub for teaching AI literacy.

But as generative AI tools like ChatGPT sweep into mainstream business tools, promising to draft properly-formatted text from simple prompts and the click of a button, new questions are rising about what role writing centers should play — or whether they will be needed in the future.

Writing centers need to find a balance between introducing AI into the writing process and keeping the human support that every writer needs, argues Anna Mills, an English instructor at the College of Marin.

AI can serve as a supplement to a human tutor, Mills says. She encourages her students to use MyEssayFeedback, an AI tool that critiques the organization of an essay, the quality of evidence a student has included to support their thesis or the tone of the writing. Such tools can also evaluate research questions or review a student’s writing based on the rubric for the assignment, she says.

 

Gemini makes your mobile device a powerful AI assistant — from blog.google
Gemini Live is available today to Advanced subscribers, along with conversational overlay on Android and even more connected apps.

Rolling out today: Gemini Live <– Google swoops in before OpenAI can get their Voice Mode out there
Gemini Live is a mobile conversational experience that lets you have free-flowing conversations with Gemini. Want to brainstorm potential jobs that are well-suited to your skillset or degree? Go Live with Gemini and ask about them. You can even interrupt mid-response to dive deeper on a particular point, or pause a conversation and come back to it later. It’s like having a sidekick in your pocket who you can chat with about new ideas or practice with for an important conversation.

Gemini Live is also available hands-free: You can keep talking with the Gemini app in the background or when your phone is locked, so you can carry on your conversation on the go, just like you might on a regular phone call. Gemini Live begins rolling out today in English to our Gemini Advanced subscribers on Android phones, and in the coming weeks will expand to iOS and more languages.

To make speaking to Gemini feel even more natural, we’re introducing 10 new voices to choose from, so you can pick the tone and style that works best for you.

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Per the Rundown AI:
Why it matters: Real-time voice is slowly shifting AI from a tool we text/prompt with, to an intelligence that we collaborate, learn, consult, and grow with. As the world’s anticipation for OpenAI’s unreleased products grows, Google has swooped in to steal the spotlight as the first to lead widespread advanced AI voice rollouts.

Beyond Social Media: Schmidt Predicts AI’s Earth-Shaking Impact— from wallstreetpit.com
The next wave of AI is coming, and if Schmidt is correct, it will reshape our world in ways we are only beginning to imagine.

In a recent Q&A session at Stanford, Eric Schmidt, former CEO and Chairman of search giant Google, offered a compelling vision of the near future in artificial intelligence. His predictions, both exciting and sobering, paint a picture of a world on the brink of a technological revolution that could dwarf the impact of social media.

Schmidt highlighted three key advancements that he believes will converge to create this transformative wave: very large context windows, agents, and text-to-action capabilities. These developments, according to Schmidt, are not just incremental improvements but game-changers that could reshape our interaction with technology and the world at large.

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The rise of multimodal AI agents— from 11onze.cat
Technology companies are investing large amounts of money in creating new multimodal artificial intelligence models and algorithms that can learn, reason and make decisions autonomously after collecting and analysing data.

The future of multimodal agents
In practical terms, a multimodal AI agent can, for example, analyse a text while processing an image, spoken language, or an audio clip to give a more complete and accurate response, both through voice and text. This opens up new possibilities in various fields: from education and healthcare to e-commerce and customer service.


AI Change Management: 41 Tactics to Use (August 2024)— from flexos.work by Daan van Rossum
Future-proof companies are investing in driving AI adoption, but many don’t know where to start. The experts recommend these 41 tips for AI change management.

As Matt Kropp told me in our interview, BCG has a 10-20-70 rule for AI at work:

  • 10% is the LLM or algorithm
  • 20% is the software layer around it (like ChatGPT)
  • 70% is the human factor

This 70% is exactly why change management is key in driving AI adoption.

But where do you start?

As I coach leaders at companies like Apple, Toyota, Amazon, L’Oréal, and Gartner in our Lead with AI program, I know that’s the question on everyone’s minds.

I don’t believe in gatekeeping this information, so here are 41 principles and tactics I share with our community members looking for winning AI change management principles.


 

How Generative AI will change what lawyers do — from jordanfurlong.substack.com by Jordan Furlong
As we enter the Age of Accessible Law, a wave of new demand is coming our way — but AI will meet most of the surge. What will be left for lawyers? Just the most valuable and irreplaceable role in law.

AI can already provide actionable professional advice; within the next ten years, if it takes that long, I believe it will offer acceptable legal advice. No one really wants “AI courts,” but soon enough, we’ll have AI-enabled mediation and arbitration, which will have a much greater impact on everyday dispute resolution.

I think it’s dangerous to assume that AI will never be able to do something that lawyers now do. “Never” is a very long time. And AI doesn’t need to replicate the complete arsenal of the most gifted lawyer out there. If a Legal AI can replicate 80% of what a middling lawyer can do, for 10% of the cost, in 1% of the time, that’s all the revolution you’ll need.

From DSC:
It is my sincere hope that AI will open up the floodgates to FAR great Access to Justice (A2J) in the future.


It’s the Battle of the AI Legal Assistants, As LexisNexis Unveils Its New Protégé and Thomson Reuters Rolls Out CoCounsel 2.0 — from lawnext.com by Bob Ambrogi

It’s not quite BattleBots, but competitors LexisNexis and Thomson Reuters both made significant announcements today involving the development of generative AI legal assistants within their products.

Thomson Reuters, which last year acquired the CoCounsel legal assistant originally developed by Casetext, and which later announced plans to deploy it throughout its product lines, today unveiled what it says is the “supercharged” CoCounsel 2.0.

Meanwhile, LexisNexis said today it is rolling out the commercial preview version of its Protégé Legal AI Assistant, which it describes as a “substantial leap forward in personalized generative AI that will transform legal work.” It is part of the launch of the third generation of Lexis+ AI, the AI-driven legal research platform the company launched last year.


Thomson Reuters Launches CoCounsel 2.0 — from abovethelaw.com by Joe Patrice
New release promises results three times faster than the last version.

It seems like just last year we were talking about CoCounsel 1.0, the generative AI product launched by Casetext and then swiftly acquired by Thomson Reuters. That’s because it was just last year. Since then, Thomson Reuters has worked to marry Casetext’s tool with TR’s treasure trove of data.

It’s not an easy task. A lot of the legal AI conversation glosses over how constructing these tools requires a radical confrontation with the lawyers’ mind. Why do attorneys do what they do every day? Are there seemingly “inefficient” steps that actually serve a purpose? Does an AI “answer” advance the workflow or hinder the research alchemy? As recently as April, Thomson Reuters was busy hyping the fruits of its efforts to get ahead of these challenges.


Though this next item is not necessarily related to legaltech, it’s still relevant to the legal realm:

A Law Degree Is No Sure Thing— from cew.georgetown.edu
Some Law School Graduates Earn Top Dollar, but Many Do Not

Summary
Is law school worth it? A Juris Doctor (JD) offers high median earnings and a substantial earnings boost relative to a bachelor’s degree in the humanities or social sciences—two of the more common fields of study that lawyers pursue as undergraduate students. However, graduates of most law schools carry substantial student loan debt, which dims the financial returns associated with a JD.

A Law Degree Is No Sure Thing: Some Law School Graduates Earn Top Dollar, but Many Do Not finds that the return on investment (ROI) in earnings and career outcomes varies widely across law schools. The median earnings net of debt payments are $72,000 four years after graduation for all law school graduates, but exceed $200,000 at seven law schools. By comparison, graduates of 33 law schools earn less than $55,000 net of debt payments four years after graduation.

From DSC:
A former boss’ husband was starting up a local public defender’s office in Michigan and needed to hire over two dozen people. The salaries were in the $40K’s she said. This surprised me greatly, as I thought all lawyers were bringing in the big bucks. This is not the case, clearly. Many lawyers do not make the big bucks, as this report shows:

…graduates of 33 law schools earn less than $55,000 net of debt payments four years after graduation.

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Also relevant/see:

 
© 2024 | Daniel Christian