Why Jensen Huang and Marc Benioff see ‘gigantic’ opportunity for agentic AI — from venturebeat.com by Taryn Plumb

Going forward, the opportunity for AI agents will be “gigantic,” according to Nvidia founder and CEO Jensen Huang.

Already, progress is “spectacular and surprising,” with AI development moving faster and faster and the industry getting into the “flywheel zone” that technology needs to advance, Huang said in a fireside chat at Salesforce’s flagship event Dreamforce this week.

“This is an extraordinary time,” Huang said while on stage with Marc Benioff, Salesforce chair, CEO and co-founder. “In no time in history has technology moved faster than Moore’s Law. We’re moving way faster than Moore’s Law, are arguably reasonably Moore’s Law squared.”

“We’ll have agents working with agents, agents working with us,” said Huang.

 

One left
byu/jim_andr inOpenAI

 

From DSC:
I’m not trying to gossip here. I post this because Sam Altman is the head of arguably one of the most powerful companies in the world today — at least in terms of introducing change to a variety of societies throughout the globe (both positive and negative). So when we’ve now seen almost the entire leadership team head out the door, this certainly gives me major pause. I don’t like it.
Items like the ones below begin to capture some of why I’m troubled and suspicious about these troubling moves.

 

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.

 



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.


 
 

Using Video Projects to Reinforce Learning in Math — from edutopia.org by Alessandra King
A collaborative project can help students deeply explore math concepts, explain problem-solving strategies, and demonstrate their learning.

To this end, I assign video projects to my students. In groups of two or three, they solve a set of problems on a topic and then choose one to illustrate, solve, and explain their favorite problem-solving strategy in detail, along with the reasons they chose it. The student-created videos are collected and stored on a Padlet even after I have evaluated them—kept as a reference, keepsake, and support. I have a library of student-created videos that benefit current and future students when they have some difficulties with a topic and associated problems.

 

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.

 



This AI App Can Solve Your Math Homework, Steps Included — from link.wired.com by Will Knight

Right now, high schoolers and college students around the country are experimenting with free smartphone apps that help complete their math homework using generative AI. One of the most popular options on campus right now is the Gauth app, with millions of downloads. It’s owned by ByteDance, which is also TikTok’s parent company.

The Gauth app first launched in 2019 with a primary focus on mathematics, but soon expanded to other subjects as well, like chemistry and physics. It’s grown in relevance, and neared the top of smartphone download lists earlier this year for the education category. Students seem to love it. With hundreds of thousands of primarily positive reviews, Gauth has a favorable 4.8 star rating in the Apple App Store and Google Play Store.

All students have to do after downloading the app is point their smartphone at a homework problem, printed or handwritten, and then make sure any relevant information is inside of the image crop. Then Gauth’s AI model generates a step-by-step guide, often with the correct answer. 

From DSC:
I do hesitate to post this though, as I’ve seen numerous posting re: the dubious quality of AI as it relates to giving correct answers to math-related problems – or whether using AI-based tools help or hurt the learning process. The situation seems to be getting better, but as I understand it, we still have some progress to make in this area of mathematics.


Redefining Creativity in the Age of AI — from gettingsmart.com by David Ross

Key Points

  • Educational leaders must reconsider the definition of creativity, taking into account how generative AI tools can be used to produce novel and impactful creative work, similar to how film editors compile various elements into a cohesive, creative whole.
  • Generative AI democratizes innovation by allowing all students to become creators, expanding access to creative processes that were previously limited and fostering a broader inclusion of diverse talents and ideas in education.


AI-Powered Instructional Design at ASU — from drphilippahardman.substack.com by Dr. Philippa Hardman
How ASU’s Collaboration with OpenAI is Reshaping the Role of Instructional Designers

The developments and experiments at ASU provide a fascinating window into two things:

    1. How the world is reimagining learning in the age of AI;
    2. How the role of the instructional designer is changing in the age of AI.

In this week’s blog post, I’ll provide a summary of how faculty, staff and students at ASU are starting to reimagine education in the age of AI, and explore what this means for the instructions designers who work there.


PhysicsWallah’s ‘Alakh AI’ is Making Education Accessible to Millions in India — from analyticsindiamag.com by Siddharth Jindal

India’s ed-tech unicorn PhysicsWallah is using OpenAI’s GPT-4o to make education accessible to millions of students in India. Recently, the company launched a suite of AI products to ensure that students in Tier 2 & 3 cities can access high-quality education without depending solely on their enrolled institutions, as 85% of their enrollment comes from these areas.

Last year, AIM broke the news of PhysicsWallah introducing ‘Alakh AI’, its suite of generative AI tools, which was eventually launched at the end of December 2023. It quickly gained traction, amassing over 1.5 million users within two months of its release.


 

Terrific Tools for Teachers — from wondertools.substack.com by Jeremy Caplan
Try these for your workshops or classes

As a new school year starts, I’m excited to be back teaching at the City University of New York’s Newmark Graduate School of Journalism. In my role as Director of Teaching & Learning, I love studying and sharing the skills, mindsets, tactics and tools that help teachers lead engaging, impactful classes. In this post I’m sharing resources you might find helpful whether you’re a teacher, leader, or anyone who brings people together.
.

Terrific Tools for Teachers -- try these for your workshops or classes

 

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.

 

8 Legal Tech Trends Transforming Practice in 2024 — from lawyer-monthly.com

Thanks to rapid advances in technology, the entire scenario within the legal landscape is changing fast. Fast forward to 2024, and legal tech integration would be the lifeblood of any law firm or legal department if it wishes to stay within the competitive fray.

Innovations such as AI-driven tools for research to blockchain-enabled contracts are thus not only guideline highlights of legal work today. Understanding and embracing these trends will be vital to surviving and thriving in law as the revolution gains momentum and the sands of the world of legal practice continue to shift.

Below are the eight expected trends in legal tech defining the future legal practice.


Building your legal practice’s AI future: Understanding the actual technologies — from thomsonreuters.com by
The implementation of a successful AI strategy for a law firm depends not only on having the right people, but also understanding the tech and how to make it work for the firm

While we’re not delving deep here into how generative artificial intelligence (GenAI) and large language models (LLMs) work, we will talk generally about different categories of tech and emerging GenAI functionalities that are specific for legal.


Ex-Microsoft engineers raise $25M for legal tech startup that uses AI to help lawyers analyze data — from geekwire.com by Taylor Soper

Supio, a Seattle startup founded in 2021 by longtime friends and former Microsoft engineers, raised a $25 million Series A investment to supercharge its software platform designed to help lawyers quickly sort, search, and organize case-related data.

Supio focuses on cases related to personal injury and mass tort plaintiff law (when many plaintiffs file a claim). It specializes in organizing unstructured data and letting lawyers use a chatbot to pull relevant information.

“Most lawyers are data-rich and time-starved, but Supio automates time-sapping manual processes and empowers them to identify critical information to prove and expedite their cases,” Supio CEO and co-founder Jerry Zhou said in a statement.


ILTACON 2024: Large law firms are moving carefully but always forward with their GenAI strategy — from thomsonreuters.com by Zach Warren

NASHVILLE — As the world approaches the two-year mark since the original introduction of OpenAI’s ChatGPT, law firms already have made in-roads into establishing generative artificial intelligence (GenAI) as a part of their firms. Whether for document and correspondence drafting, summarization of meetings and contracts, legal research, or for back-office capabilities, firms have been playing around with a number of use cases to see where the technology may fit into the future.


Thomson Reuters acquires pre-revenue legal LLM developer Safe Sign Technologies – Here’s why — from legaltechnology.com by Caroline Hill

Thomson Reuters announced (on August 21) it has made the somewhat unusual acquisition of UK pre-revenue startup Safe Sign Technologies (SST), which is developing legal-specific large language models (LLMs) and as of just eight months ago was operating in stealth mode.

There isn’t an awful lot of public information available about the company but speaking to Legal IT Insider about the acquisition, Hron explained that SST is focused in part on deep learning research as it pertains to training large language models and specifically legal large language models. The company as yet has no customers and has been focusing exclusively on developing the technology and the models.


Supio brings generative AI to personal injury cases — from techcrunch.com by Kyle Wiggers

Legal work is incredibly labor- and time-intensive, requiring piecing together cases from vast amounts of evidence. That’s driving some firms to pilot AI to streamline certain steps; according to a 2023 survey by the American Bar Association, 35% of law firms now use AI tools in their practice.

OpenAI-backed Harvey is among the big winners so far in the burgeoning AI legal tech space, alongside startups such as Leya and Klarity. But there’s room for one more, says Jerry Zhou and Kyle Lam, the co-founders of an AI platform for personal injury law called Supio, which emerged from stealth Tuesday with a $25 million investment led by Sapphire Ventures.

Supio uses generative AI to automate bulk data collection and aggregation for legal teams. In addition to summarizing info, the platform can organize and identify files — and snippets within files — that might be useful in outlining, drafting and presenting a case, Zhou said.


 
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