NVIDIA’s Apple moment?! — from theneurondaily.com by Noah Edelman and Grant Harvey
PLUS: How to level up your AI workflows for 2025…

NVIDIA wants to put an AI supercomputer on your desk (and it only costs $3,000).

And last night at CES 2025, Jensen Huang announced phase two of this plan: Project DIGITS, a $3K personal AI supercomputer that runs 200B parameter models from your desk. Guess we now know why Apple recently developed an NVIDIA allergy

But NVIDIA doesn’t just want its “Apple PC moment”… it also wants its OpenAI moment. NVIDIA also announced Cosmos, a platform for building physical AI (think: robots and self-driving cars)—which Jensen Huang calls “the ChatGPT moment for robotics.”


Jensen Huang’s latest CES speech: AI Agents are expected to become the next robotics industry, with a scale reaching trillions of dollars — from chaincatcher.com

NVIDIA is bringing AI from the cloud to personal devices and enterprises, covering all computing needs from developers to ordinary users.

At CES 2025, which opened this morning, NVIDIA founder and CEO Jensen Huang delivered a milestone keynote speech, revealing the future of AI and computing. From the core token concept of generative AI to the launch of the new Blackwell architecture GPU, and the AI-driven digital future, this speech will profoundly impact the entire industry from a cross-disciplinary perspective.

Also see:


NVIDIA Project DIGITS: The World’s Smallest AI Supercomputer. — from nvidia.com
A Grace Blackwell AI Supercomputer on your desk.


From DSC:
I’m posting this next item (involving Samsung) as it relates to how TVs continue to change within our living rooms. AI is finding its way into our TVs…the ramifications of this remain to be seen.


OpenAI ‘now knows how to build AGI’ — from therundown.ai by Rowan Cheung
PLUS: AI phishing achieves alarming success rates

The Rundown: Samsung revealed its new “AI for All” tagline at CES 2025, introducing a comprehensive suite of new AI features and products across its entire ecosystem — including new AI-powered TVs, appliances, PCs, and more.

The details:

  • Vision AI brings features like real-time translation, the ability to adapt to user preferences, AI upscaling, and instant content summaries to Samsung TVs.
  • Several of Samsung’s new Smart TVs will also have Microsoft Copilot built in, while also teasing a potential AI partnership with Google.
  • Samsung also announced the new line of Galaxy Book5 AI PCs, with new capabilities like AI-powered search and photo editing.
  • AI is also being infused into Samsung’s laundry appliances, art frames, home security equipment, and other devices within its SmartThings ecosystem.

Why it matters: Samsung’s web of products are getting the AI treatment — and we’re about to be surrounded by AI-infused appliances in every aspect of our lives. The edge will be the ability to sync it all together under one central hub, which could position Samsung as the go-to for the inevitable transition from smart to AI-powered homes.

***

“Samsung sees TVs not as one-directional devices for passive consumption but as interactive, intelligent partners that adapt to your needs,” said SW Yong, President and Head of Visual Display Business at Samsung Electronics. “With Samsung Vision AI, we’re reimagining what screens can do, connecting entertainment, personalization, and lifestyle solutions into one seamless experience to simplify your life.”from Samsung


Understanding And Preparing For The 7 Levels Of AI Agents — from forbes.com by Douglas B. Laney

The following framework I offer for defining, understanding, and preparing for agentic AI blends foundational work in computer science with insights from cognitive psychology and speculative philosophy. Each of the seven levels represents a step-change in technology, capability, and autonomy. The framework expresses increasing opportunities to innovate, thrive, and transform in a data-fueled and AI-driven digital economy.


The Rise of AI Agents and Data-Driven Decisions — from devprojournal.com by Mike Monocello
Fueled by generative AI and machine learning advancements, we’re witnessing a paradigm shift in how businesses operate and make decisions.

AI Agents Enhance Generative AI’s Impact
Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, predicts a significant leap forward in generative AI. “In 2025, AI agents will take generative AI to the next level by moving beyond content creation to active participation in daily business operations,” he says. “These agents, capable of partial or full autonomy, will handle tasks like scheduling, lead qualification, and customer follow-ups, seamlessly integrating into workflows. Rather than replacing generative AI, they will enhance its utility by transforming insights into immediate, actionable outcomes.”


Here’s what nobody is telling you about AI agents in 2025 — from aidisruptor.ai by Alex McFarland
What’s really coming (and how to prepare). 

Everyone’s talking about the potential of AI agents in 2025 (and don’t get me wrong, it’s really significant), but there’s a crucial detail that keeps getting overlooked: the gap between current capabilities and practical reliability.

Here’s the reality check that most predictions miss: AI agents currently operate at about 80% accuracy (according to Microsoft’s AI CEO). Sounds impressive, right? But here’s the thing – for businesses and users to actually trust these systems with meaningful tasks, we need 99% reliability. That’s not just a 19% gap – it’s the difference between an interesting tech demo and a business-critical tool.

This matters because it completely changes how we should think about AI agents in 2025. While major players like Microsoft, Google, and Amazon are pouring billions into development, they’re all facing the same fundamental challenge – making them work reliably enough that you can actually trust them with your business processes.

Think about it this way: Would you trust an assistant who gets things wrong 20% of the time? Probably not. But would you trust one who makes a mistake only 1% of the time, especially if they could handle repetitive tasks across your entire workflow? That’s a completely different conversation.


Why 2025 will be the year of AI orchestration — from venturebeat.com by Emilia David|

In the tech world, we like to label periods as the year of (insert milestone here). This past year (2024) was a year of broader experimentation in AI and, of course, agentic use cases.

As 2025 opens, VentureBeat spoke to industry analysts and IT decision-makers to see what the year might bring. For many, 2025 will be the year of agents, when all the pilot programs, experiments and new AI use cases converge into something resembling a return on investment.

In addition, the experts VentureBeat spoke to see 2025 as the year AI orchestration will play a bigger role in the enterprise. Organizations plan to make management of AI applications and agents much more straightforward.

Here are some themes we expect to see more in 2025.


Predictions For AI In 2025: Entrepreneurs Look Ahead — from forbes.com by Jodie Cook

AI agents take charge
Jérémy Grandillon, CEO of TC9 – AI Allbound Agency, said “Today, AI can do a lot, but we don’t trust it to take actions on our behalf. This will change in 2025. Be ready to ask your AI assistant to book a Uber ride for you.” Start small with one agent handling one task. Build up to an army.

“If 2024 was agents everywhere, then 2025 will be about bringing those agents together in networks and systems,” said Nicholas Holland, vice president of AI at Hubspot. “Micro agents working together to accomplish larger bodies of work, and marketplaces where humans can ‘hire’ agents to work alongside them in hybrid teams. Before long, we’ll be saying, ‘there’s an agent for that.'”

Voice becomes default
Stop typing and start talking. Adam Biddlecombe, head of brand at Mindstream, predicts a shift in how we interact with AI. “2025 will be the year that people start talking with AI,” he said. “The majority of people interact with ChatGPT and other tools in the text format, and a lot of emphasis is put on prompting skills.

Biddlecombe believes, “With Apple’s ChatGPT integration for Siri, millions of people will start talking to ChatGPT. This will make AI so much more accessible and people will start to use it for very simple queries.”

Get ready for the next wave of advancements in AI. AGI arrives early, AI agents take charge, and voice becomes the norm. Video creation gets easy, AI embeds everywhere, and one-person billion-dollar companies emerge.



These 4 graphs show where AI is already impacting jobs — from fastcompany.com by Brandon Tucker
With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce. 

To better understand the types of roles that AI is impacting, ZoomInfo’s research team looked to its proprietary database of professional contacts for answers. The platform, which detects more than 1.5 million personnel changes per day, revealed a dramatic increase in AI-related job titles since 2022. With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.

Why does this shift in AI titles matter for every industry?

 

How AI Is Changing Education: The Year’s Top 5 Stories — from edweek.org by Alyson Klein

Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.

Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.

Here are the five most popular stories that Education Week published in 2024 about AI in schools.


What’s next with AI in higher education? — from msn.com by Science X Staff

Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:

1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change


5 Ways Teachers Can Use NotebookLM Today — from classtechtips.com by Dr. Monica Burns

 

Introducing Gemini 2.0: our new AI model for the agentic era — from blog.google by Sundar Pichai, Demis Hassabis, and Koray Kavukcuoglu

Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.

We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.

Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.

.

Try Deep Research and our new experimental model in Gemini, your AI assistant — from blog.google by Dave Citron
Deep Research rolls out to Gemini Advanced subscribers today, saving you hours of time. Plus, you can now try out a chat optimized version of 2.0 Flash Experimental in Gemini on the web.

Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.

Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1


Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.

Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.

Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.


Gemini 2.0 is the next chapter for Google AI — from axios.com by Ina Fried

Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…

The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.

  • “We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
  • Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
  • “If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.

AI Agents vs. AI Assistants: Know the Key Differences — from aithority.com by Rishika Patel

The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.

Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.


Discover how to accelerate AI transformation with NVIDIA and Microsoft — from ignite.microsoft.com

Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.


Google + Meta + Apple New AI — from theneurondaily.com by Grant Harve

What else Google announced:

  • Deep Research: New feature that can explore topics and compile reports.
  • Project Astra: AI agent that can use Google Search, Lens, and Maps, understands multiple languages, and has 10-minute conversation memory.
  • Project Mariner: A browser control agent that can complete web tasks (83.5% success rate on WebVoyager benchmark). Read more about Mariner here.
  • Agents to help you play (or test) video games.

AI Agents: Easier To Build, Harder To Get Right — from forbes.com by Andres Zunino

The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.

The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.

 

What Students Are Saying About Teachers Using A.I. to Grade — from nytimes.com by The Learning Network; via Claire Zau
Teenagers and educators weigh in on a recent question from The Ethicist.

Is it unethical for teachers to use artificial intelligence to grade papers if they have forbidden their students from using it for their assignments?

That was the question a teacher asked Kwame Anthony Appiah in a recent edition of The Ethicist. We posed it to students to get their take on the debate, and asked them their thoughts on teachers using A.I. in general.

While our Student Opinion questions are usually reserved for teenagers, we also heard from a few educators about how they are — or aren’t — using A.I. in the classroom. We’ve included some of their answers, as well.


OpenAI wants to pair online courses with chatbots — from techcrunch.com by Kyle Wiggers; via James DeVaney on LinkedIn

If OpenAI has its way, the next online course you take might have a chatbot component.

Speaking at a fireside on Monday hosted by Coeus Collective, Siya Raj Purohit, a member of OpenAI’s go-to-market team for education, said that OpenAI might explore ways to let e-learning instructors create custom “GPTs” that tie into online curriculums.

“What I’m hoping is going to happen is that professors are going to create custom GPTs for the public and let people engage with content in a lifelong manner,” Purohit said. “It’s not part of the current work that we’re doing, but it’s definitely on the roadmap.”


15 Times to use AI, and 5 Not to — from oneusefulthing.org by Ethan Mollick
Notes on the Practical Wisdom of AI Use

There are several types of work where AI can be particularly useful, given the current capabilities and limitations of LLMs. Though this list is based in science, it draws even more from experience. Like any form of wisdom, using AI well requires holding opposing ideas in mind: it can be transformative yet must be approached with skepticism, powerful yet prone to subtle failures, essential for some tasks yet actively harmful for others. I also want to caveat that you shouldn’t take this list too seriously except as inspiration – you know your own situation best, and local knowledge matters more than any general principles. With all that out of the way, below are several types of tasks where AI can be especially useful, given current capabilities—and some scenarios where you should remain wary.


Learning About Google Learn About: What Educators Need To Know — from techlearning.com by Ray Bendici
Google’s experimental Learn About platform is designed to create an AI-guided learning experience

Google Learn About is a new experimental AI-driven platform available that provides digestible and in-depth knowledge about various topics, but showcases it all in an educational context. Described by Google as a “conversational learning companion,” it is essentially a Wikipedia-style chatbot/search engine, and then some.

In addition to having a variety of already-created topics and leading questions (in areas such as history, arts, culture, biology, and physics) the tool allows you to enter prompts using either text or an image. It then provides a general overview/answer, and then suggests additional questions, topics, and more to explore in regard to the initial subject.

The idea is for student use is that the AI can help guide a deeper learning process rather than just provide static answers.


What OpenAI’s PD for Teachers Does—and Doesn’t—Do — from edweek.org by Olina Banerji
What’s the first thing that teachers dipping their toes into generative artificial intelligence should do?

They should start with the basics, according to OpenAI, the creator of ChatGPT and one of the world’s most prominent artificial intelligence research companies. Last month, the company launched an hour-long, self-paced online course for K-12 teachers about the definition, use, and harms of generative AI in the classroom. It was launched in collaboration with Common Sense Media, a national nonprofit that rates and reviews a wide range of digital content for its age appropriateness.

…the above article links to:

ChatGPT Foundations for K–12 Educators — from commonsense.org

This course introduces you to the basics of artificial intelligence, generative AI, ChatGPT, and how to use ChatGPT safely and effectively. From decoding the jargon to responsible use, this course will help you level up your understanding of AI and ChatGPT so that you can use tools like this safely and with a clear purpose.

Learning outcomes:

  • Understand what ChatGPT is and how it works.
  • Demonstrate ways to use ChatGPT to support your teaching practices.
  • Implement best practices for applying responsible AI principles in a school setting.

Takeaways From Google’s Learning in the AI Era Event — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell
Highlights from Our Day at Google + Behind-the-Scenes Interviews Coming Soon!

  1. NotebookLM: The Start of an AI Operating System
  2. Google is Serious About AI and Learning
  3. Google’s LearnLM Now Available in AI Studio
  4. Collaboration is King
  5. If You Give a Teacher a Ferrari

Rapid Responses to AI — from the-job.beehiiv.com by Paul Fain
Top experts call for better data and more short-term training as tech transforms jobs.

AI could displace middle-skill workers and widen the wealth gap, says landmark study, which calls for better data and more investment in continuing education to help workers make career pivots.

Ensuring That AI Helps Workers
Artificial intelligence has emerged as a general purpose technology with sweeping implications for the workforce and education. While it’s impossible to precisely predict the scope and timing of looming changes to the labor market, the U.S. should build its capacity to rapidly detect and respond to AI developments.
That’s the big-ticket framing of a broad new report from the National Academies of Sciences, Engineering, and Medicine. Congress requested the study, tapping an all-star committee of experts to assess the current and future impact of AI on the workforce.

“In contemplating what the future holds, one must approach predictions with humility,” the study says…

“AI could accelerate occupational polarization,” the committee said, “by automating more nonroutine tasks and increasing the demand for elite expertise while displacing middle-skill workers.”

The Kicker: “The education and workforce ecosystem has a responsibility to be intentional with how we value humans in an AI-powered world and design jobs and systems around that,” says Hsieh.


AI Predators: What Schools Should Know and Do — from techlearning.com by Erik Ofgang
AI is increasingly be used by predators to connect with underage students online. Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia, shares steps educators can take to protect students.

The threat from AI for students goes well beyond cheating, says Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia.

Increasingly at U.S. schools and beyond, AI is being used by predators to manipulate children. Students are also using AI generate inappropriate images of other classmates or staff members. For a recent report, Qoria, a company that specializes in child digital safety and wellbeing products, surveyed 600 schools across North America, UK, Australia, and New Zealand.


Why We Undervalue Ideas and Overvalue Writing — from aiczar.blogspot.com by Alexander “Sasha” Sidorkin

A student submits a paper that fails to impress stylistically yet approaches a worn topic from an angle no one has tried before. The grade lands at B minus, and the student learns to be less original next time. This pattern reveals a deep bias in higher education: ideas lose to writing every time.

This bias carries serious equity implications. Students from disadvantaged backgrounds, including first-generation college students, English language learners, and those from under-resourced schools, often arrive with rich intellectual perspectives but struggle with academic writing conventions. Their ideas – shaped by unique life experiences and cultural viewpoints – get buried under red ink marking grammatical errors and awkward transitions. We systematically undervalue their intellectual contributions simply because they do not arrive in standard academic packaging.


Google Scholar’s New AI Outline Tool Explained By Its Founder — from techlearning.com by Erik Ofgang
Google Scholar PDF reader uses Gemini AI to read research papers. The AI model creates direct links to the paper’s citations and a digital outline that summarizes the different sections of the paper.

Google Scholar has entered the AI revolution. Google Scholar PDF reader now utilizes generative AI powered by Google’s Gemini AI tool to create interactive outlines of research papers and provide direct links to sources within the paper. This is designed to make reading the relevant parts of the research paper more efficient, says Anurag Acharya, who co-founded Google Scholar on November 18, 2004, twenty years ago last month.


The Four Most Powerful AI Use Cases in Instructional Design Right Now — from drphilippahardman.substack.com by Dr. Philippa Hardman
Insights from ~300 instructional designers who have taken my AI & Learning Design bootcamp this year

  1. AI-Powered Analysis: Creating Detailed Learner Personas…
  2. AI-Powered Design: Optimising Instructional Strategies…
  3. AI-Powered Development & Implementation: Quality Assurance…
  4. AI-Powered Evaluation: Predictive Impact Assessment…

How Are New AI Tools Changing ‘Learning Analytics’? — from edsurge.com by Jeffrey R. Young
For a field that has been working to learn from the data trails students leave in online systems, generative AI brings new promises — and new challenges.

In other words, with just a few simple instructions to ChatGPT, the chatbot can classify vast amounts of student work and turn it into numbers that educators can quickly analyze.

Findings from learning analytics research is also being used to help train new generative AI-powered tutoring systems.

Another big application is in assessment, says Pardos, the Berkeley professor. Specifically, new AI tools can be used to improve how educators measure and grade a student’s progress through course materials. The hope is that new AI tools will allow for replacing many multiple-choice exercises in online textbooks with fill-in-the-blank or essay questions.


Increasing AI Fluency Among Enterprise Employees, Senior Management & Executives — from learningguild.com by Bill Brandon

This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.

The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?

You could be surprised how many software products have added AI features. Examples (to name a few) are productivity software (Microsoft 365 and Google Workspace); customer relationship management (Salesforce and Hubspot); human resources (Workday and Talentsoft); marketing and advertising (Adobe Marketing Cloud and Hootsuite); and communication and collaboration (Slack and Zoom). Look for more under those categories in software review sites.

 

(Excerpt from the 12/4/24 edition)

Robot “Jailbreaks”
In the year or so since large language models hit the big time, researchers have demonstrated numerous ways of tricking them into producing problematic outputs including hateful jokes, malicious code, phishing emails, and the personal information of users. It turns out that misbehavior can take place in the physical world, too: LLM-powered robots can easily be hacked so that they behave in potentially dangerous ways.

Researchers from the University of Pennsylvania were able to persuade a simulated self-driving car to ignore stop signs and even drive off a bridge, get a wheeled robot to find the best place to detonate a bomb, and force a four-legged robot to spy on people and enter restricted areas.

“We view our attack not just as an attack on robots,” says George Pappas, head of a research lab at the University of Pennsylvania who helped unleash the rebellious robots. “Any time you connect LLMs and foundation models to the physical world, you actually can convert harmful text into harmful actions.”

The robot “jailbreaks” highlight a broader risk that is likely to grow as AI models become increasingly used as a way for humans to interact with physical systems, or to enable AI agents autonomously on computers, say the researchers involved.


Virtual lab powered by ‘AI scientists’ super-charges biomedical research — from nature.com by Helena Kudiabor
Could human-AI collaborations be the future of interdisciplinary studies?

In an effort to automate scientific discovery using artificial intelligence (AI), researchers have created a virtual laboratory that combines several ‘AI scientists’ — large language models with defined scientific roles — that can collaborate to achieve goals set by human researchers.

The system, described in a preprint posted on bioRxiv last month1, was able to design antibody fragments called nanobodies that can bind to the virus that causes COVID-19, proposing nearly 100 of these structures in a fraction of the time it would take an all-human research group.


Can AI agents accelerate AI implementation for CIOs? — from intelligentcio.com by Arun Shankar

By embracing an agent-first approach, every CIO can redefine their business operations. AI agents are now the number one choice for CIOs as they come pre-built and can generate responses that are consistent with a company’s brand using trusted business data, explains Thierry Nicault at Salesforce Middle.


AI Turns Photos Into 3D Real World — from theaivalley.com by Barsee

Here’s what you need to know:

  • The system generates full 3D environments that expand beyond what’s visible in the original image, allowing users to explore new perspectives.
  • Users can freely navigate and view the generated space with standard keyboard and mouse controls, similar to browsing a website.
  • It includes real-time camera effects like depth-of-field and dolly zoom, as well as interactive lighting and animation sliders to tweak scenes.
  • The system works with both photos and AI-generated images, enabling creators to integrate it with text-to-image tools or even famous works of art.

Why it matters:
This technology opens up exciting possibilities for industries like gaming, film, and virtual experiences. Soon, creating fully immersive worlds could be as simple as generating a static image.

Also related, see:

From World Labs

Today we’re sharing our first step towards spatial intelligence: an AI system that generates 3D worlds from a single image. This lets you step into any image and explore it in 3D.

Most GenAI tools make 2D content like images or videos. Generating in 3D instead improves control and consistency. This will change how we make movies, games, simulators, and other digital manifestations of our physical world.

In this post you’ll explore our generated worlds, rendered live in your browser. You’ll also experience different camera effects, 3D effects, and dive into classic paintings. Finally, you’ll see how creators are already building with our models.


Addendum on 12/5/24:

 

AI Tutors: Hype or Hope for Education? — from educationnext.org by John Bailey and John Warner
In a new book, Sal Khan touts the potential of artificial intelligence to address lagging student achievement. Our authors weigh in.

In Salman Khan’s new book, Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing) (Viking, 2024), the Khan Academy founder predicts that AI will transform education by providing every student with a virtual personalized tutor at an affordable cost. Is Khan right? Is radically improved achievement for all students within reach at last? If so, what sorts of changes should we expect to see, and when? If not, what will hold back the AI revolution that Khan foresees? John Bailey, a visiting fellow at the American Enterprise Institute, endorses Khan’s vision and explains the profound impact that AI technology is already making in education. John Warner, a columnist for the Chicago Tribune and former editor for McSweeney’s Internet Tendency, makes the case that all the hype about AI tutoring is, as Macbeth quips, full of sound and fury, signifying nothing.

 

2024-11-22: The Race to the TopDario Amodei on AGI, Risks, and the Future of Anthropic — from emergentbehavior.co by Prakash (Ate-a-Pi)

Risks on the Horizon: ASL Levels
The two key risks Dario is concerned about are:

a) cyber, bio, radiological, nuclear (CBRN)
b) model autonomy

These risks are captured in Anthropic’s framework for understanding AI Safety Levels (ASL):

1. ASL-1: Narrow-task AI like Deep Blue (no autonomy, minimal risk).
2. ASL-2: Current systems like ChatGPT/Claude, which lack autonomy and don’t pose significant risks beyond information already accessible via search engines.
3. ASL-3: Agents arriving soon (potentially next year) that can meaningfully assist non-state actors in dangerous activities like cyber or CBRN (chemical, biological, radiological, nuclear) attacks. Security and filtering are critical at this stage to prevent misuse.
4. ASL-4: AI smart enough to evade detection, deceive testers, and assist state actors with dangerous projects. AI will be strong enough that you would want to use the model to do anything dangerous. Mechanistic interpretability becomes crucial for verifying AI behavior.
5. ASL-5: AGI surpassing human intelligence in all domains, posing unprecedented challenges.

Anthropic’s if/then framework ensures proactive responses: if a model demonstrates danger, the team clamps down hard, enforcing strict controls.



Should You Still Learn to Code in an A.I. World? — from nytimes.com by
Coding boot camps once looked like the golden ticket to an economically secure future. But as that promise fades, what should you do? Keep learning, until further notice.

Compared with five years ago, the number of active job postings for software developers has dropped 56 percent, according to data compiled by CompTIA. For inexperienced developers, the plunge is an even worse 67 percent.
“I would say this is the worst environment for entry-level jobs in tech, period, that I’ve seen in 25 years,” said Venky Ganesan, a partner at the venture capital firm Menlo Ventures.

For years, the career advice from everyone who mattered — the Apple chief executive Tim Cook, your mother — was “learn to code.” It felt like an immutable equation: Coding skills + hard work = job.

Now the math doesn’t look so simple.

Also see:

AI builds apps in 2 mins flat — where the Neuron mentions this excerpt about Lovable:

There’s a new coding startup in town, and it just MIGHT have everybody else shaking in their boots (we’ll qualify that in a sec, don’t worry).

It’s called Lovable, the “world’s first AI fullstack engineer.”

Lovable does all of that by itself. Tell it what you want to build in plain English, and it creates everything you need. Want users to be able to log in? One click. Need to store data? One click. Want to accept payments? You get the idea.

Early users are backing up these claims. One person even launched a startup that made Product Hunt’s top 10 using just Lovable.

As for us, we made a Wordle clone in 2 minutes with one prompt. Only edit needed? More words in the dictionary. It’s like, really easy y’all.


When to chat with AI (and when to let it work) — from aiwithallie.beehiiv.com by Allie K. Miller

Re: some ideas on how to use Notebook LM:

  • Turn your company’s annual report into an engaging podcast
  • Create an interactive FAQ for your product manual
  • Generate a timeline of your industry’s history from multiple sources
  • Produce a study guide for your online course content
  • Develop a Q&A system for your company’s knowledge base
  • Synthesize research papers into digestible summaries
  • Create an executive content briefing from multiple competitor blog posts
  • Generate a podcast discussing the key points of a long-form research paper

Introducing conversation practice: AI-powered simulations to build soft skills — from codesignal.com by Albert Sahakyan

From DSC:
I have to admit I’m a bit suspicious here, as the “conversation practice” product seems a bit too scripted at times, but I post it because the idea of using AI to practice soft skills development makes a great deal of sense:


 

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.

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.

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.

  1. Understand the impact…
  2. Understand the different types of AI tools…
  3. 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.

Also from Educause, see:


AI school opens – learners are not good or bad but fast and slow — from donaldclarkplanb.blogspot.com by Donald Clark

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 Named Top Tech Trend for 2025 — from campustechnology.com by David Ramel

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.

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;
    • Agentic AI relying on low-quality data;
    • Employee resistance; and
    • Agentic-AI-driven cyberattacks enabling “smart malware.”

Also from campustechnology.com, see:


Three items from edcircuit.com:


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: …


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.

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.


 

 

Along these same lines, see:

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku

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.


ZombAIs: From Prompt Injection to C2 with Claude Computer Use — from embracethered.com by Johann Rehberger

A few days ago, Anthropic released Claude Computer Use, which is a model + code that allows Claude to control a computer. It takes screenshots to make decisions, can run bash commands and so forth.

It’s cool, but obviously very dangerous because of prompt injection. Claude Computer Use enables AI to run commands on machines autonomously, posing severe risks if exploited via prompt injection.

This blog post demonstrates that it’s possible to leverage prompt injection to achieve, old school, command and control (C2) when giving novel AI systems access to computers.

We discussed one way to get malware onto a Claude Computer Use host via prompt injection. There are countless others, like another way is to have Claude write the malware from scratch and compile it. Yes, it can write C code, compile and run it. There are many other options.

TrustNoAI.

And again, remember do not run unauthorized code on systems that you do not own or are authorized to operate on.

Also relevant here, see:


Perplexity Grows, GPT Traffic Surges, Gamma Dominates AI Presentations – The AI for Work Top 100: October 2024 — from flexos.work by Daan van Rossum
Perplexity continues to gain users despite recent controversies. Five out of six GPTs see traffic boosts. This month’s highest gainers including Gamma, Blackbox, Runway, and more.


Growing Up: Navigating Generative AI’s Early Years – AI Adoption Report — from ai.wharton.upenn.edu by  Jeremy Korst, Stefano Puntoni, & Mary Purk

From a survey with more than 800 senior business leaders, this report’s findings indicate that weekly usage of Gen AI has nearly doubled from 37% in 2023 to 72% in 2024, with significant growth in previously slower-adopting departments like Marketing and HR. Despite this increased usage, businesses still face challenges in determining the full impact and ROI of Gen AI. Sentiment reports indicate leaders have shifted from feelings of “curiosity” and “amazement” to more positive sentiments like “pleased” and “excited,” and concerns about AI replacing jobs have softened. Participants were full-time employees working in large commercial organizations with 1,000 or more employees.


Apple study exposes deep cracks in LLMs’ “reasoning” capabilities — from arstechnica.com by Kyle Orland
Irrelevant red herrings lead to “catastrophic” failure of logical inference.

For a while now, companies like OpenAI and Google have been touting advanced “reasoning” capabilities as the next big step in their latest artificial intelligence models. Now, though, a new study from six Apple engineers shows that the mathematical “reasoning” displayed by advanced large language models can be extremely brittle and unreliable in the face of seemingly trivial changes to common benchmark problems.

The fragility highlighted in these new results helps support previous research suggesting that LLMs use of probabilistic pattern matching is missing the formal understanding of underlying concepts needed for truly reliable mathematical reasoning capabilities. “Current LLMs are not capable of genuine logical reasoning,” the researchers hypothesize based on these results. “Instead, they attempt to replicate the reasoning steps observed in their training data.”


Google CEO says more than a quarter of the company’s new code is created by AI — from businessinsider.in by Hugh Langley

  • More than a quarter of new code at Google is made by AI and then checked by employees.
  • Google is doubling down on AI internally to make its business more efficient.

Top Generative AI Chatbots by Market Share – October 2024 


Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview — from github.blog

We are bringing developer choice to GitHub Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview and o1-mini. These new models will be rolling out—first in Copilot Chat, with OpenAI o1-preview and o1-mini available now, Claude 3.5 Sonnet rolling out progressively over the next week, and Google’s Gemini 1.5 Pro in the coming weeks. From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon.

 

AI-governed robots can easily be hacked — from theaivalley.com by Barsee
PLUS: Sam Altman’s new company “World” introduced…

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.

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku — from anthropic.com

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.
  • When you give a Claude a mouse — from oneusefulthing.org by Ethan Mollick
    Some quick impressions of an actual agent

Introducing Act-One — from runwayml.com
A new way to generate expressive character performances using simple video inputs.

Per Lore by Nathan Lands:

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:


Google to buy nuclear power for AI datacentres in ‘world first’ deal — from theguardian.com
Tech company orders six or seven small nuclear reactors from California’s Kairos Power

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.

Related:


ChatGPT Topped 3 Billion Visits in September — from similarweb.com

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.


Crazy “AI Army” — from aisecret.us

Also from aisecret.us, see World’s First Nuclear Power Deal For AI Data Centers

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.


New updates to help creators build community, drive business, & express creativity on YouTube — from support.google.com

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!


New autonomous agents scale your team like never before — from blogs.microsoft.com

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.


Multi-Modal AI: Video Creation Simplified — from heatherbcooper.substack.com by Heather Cooper

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.


AI Medical Imagery Model Offers Fast, Cost-Efficient Expert Analysis — from developer.nvidia.com/

 

Opening Keynote – GS1

Bringing generative AI to video with Adobe Firefly Video Model

Adobe Launches Firefly Video Model and Enhances Image, Vector and Design Models

  • 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

Photoshop delivers powerful innovation for image editing, ideation, 3D design, and more

Even more speed, precision, and power: Get started with the latest Illustrator and InDesign features for creative professionals

Adobe Introduces New Global Initiative Aimed at Helping 30 Million Next-Generation Learners Develop AI Literacy, Content Creation and Digital Marketing Skills by 2030

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.

 


 
 

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.

 

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.

 
© 2025 | Daniel Christian