How to use Perplexity in your daily workflow — from ai-supremacy.com by Michael Spencer and Alex McFarland
“I barely use Google anymore (for anything)” says today’s guest author.

Make Perplexity your go-to research companion with these strategies:

  • Morning briefings: Start your day by asking Perplexity for the latest news in your field. (I personally like to use Perplexity to curate the top AI news of the day to consider writing about for Unite AI and Techopedia.)
  • Fact-checking: Use it to quickly verify information before including it in your work.
  • Brainstorming: Generate ideas for projects or content by asking open-ended questions.
  • Learning new concepts: When you encounter an unfamiliar term or idea, turn to Perplexity for a quick, comprehensive explanation.
  • Writing assistance: Use it to find relevant statistics, examples, or counterarguments for your content.

From DSC:
So I used it to ask “What is Elon Musk’s Memphis Supercluster?” (which went online yesterday I believe) — which resulted in this reply:

Elon Musk’s Memphis Supercluster is a newly activated AI training cluster that is claimed to be the most powerful in the world. Here are the key details about this supercomputer:

1. Location: The supercluster is located in Memphis, Tennessee[1][2].

2. Hardware: It consists of 100,000 liquid-cooled Nvidia H100 GPUs connected through a single RDMA (Remote Direct Memory Access) fabric[1][3].

3. Purpose: The supercluster is designed for training large language models (LLMs) and other advanced AI technologies for Musk’s xAI company[1][2].

4. Activation: The Memphis Supercluster began training at approximately 4:20 AM local time on July 22, 2024[1][3].

5. Collaboration: The project is a result of collaboration between xAI, X (formerly Twitter), Nvidia, and other supporting companies[1][2].

6. Investment: With each H100 GPU estimated to cost between $30,000 to $40,000, the total investment in GPUs alone is estimated to be between $3 billion to $4 billion[5].

7. Goals: Musk claims that this supercluster will be used to develop “the world’s most powerful AI by every measure” by December 2024[1].

8. Comparison: The Memphis Supercluster’s 100,000 H100 GPUs significantly outclass other supercomputers in terms of GPU horsepower, such as Frontier (37,888 AMD GPUs) and Microsoft Eagle (14,400 Nvidia H100 GPUs)[3].

9. Infrastructure: The project required significant infrastructure development, including fiber optic networking[5].

While Musk’s claims about the supercluster’s capabilities are ambitious, it remains to be seen how it will perform in practice and whether it will meet the stated goals within the given timeframe[1].

Citations:
[1] https://venturebeat.com/ai/elon-musk-announces-most-powerful-ai-training-cluster-in-the-world/
[2] https://www.tuaw.com/2024/07/22/elon-musks-xai-unveils-worlds-most-powerful-ai-training-cluster/
[3] https://www.tomshardware.com/pc-components/gpus/elon-musk-fires-up-the-most-powerful-ai-training-cluster-in-the-world-uses-100000-nvidia-h100-gpus-on-a-single-fabric
[4] https://www.thestack.technology/xai-elon-musk-ai-supercomputer/
[5] https://www.benzinga.com/news/24/07/39881748/elon-musks-xai-flips-the-switch-on-100k-nvidia-h100-gpus-worth-up-to-4b-in-memphis-supercluster-most
[6] https://www.youtube.com/watch?v=0JhtJa05C2Y

—–
Elon’s AI empire expands — from theneurondaily.com by Grant Harvey
Elon Musk’s team at xAI just powered on the “World’s Most Powerful AI Training Cluster.”
If you don’t know what a supercluster is, it’s basically a massive network of Nvidia GPUs (computer chips) working together as a single unit to solve “super” complex calculations at unprecedented speeds.

And this Memphis Supercluster is the most “super” supercluster we’ve ever seen. The new facility, dubbed the “Gigafactory of Compute”, is a beast:

  • 100,000 liquid-cooled Nvidia H100 GPUs on a single RDMA fabric (for context, Google snagged only 50,000 H100 GPUs last year).
  • Up to 150 megawatts of electricity usage per hour—enough for 100K homes.
  • At least one million gallons of water per day to keep cool!

What to expect: Better models, more frequently. That’s been the trend, at least—look at how the last few model releases have become more squished together. 


OpenAI to make GPT-4o Advanced Voice available by the end of the month to select group of users — from tomsguide.com by Ryan Morrison

GPT-4o Advanced Voice is an entirely new type of voice assistant, similar to but larger than the recently unveiled French model Moshi, which argued with me over a story.

In demos of the model, we’ve seen GPT-4o Advanced Voice create custom character voices, generate sound effects while telling a story and even act as a live translator.

This native speech ability is a significant step in creating more natural AI assistants. In the future, it will also come with live vision abilities, allowing the AI to see what you see.


Could AGI break the world? — from theneurondaily.com by Noah Edelman

“Biggest IT outage in history” proves we’re not ready for AGI.

Here’s the TL;DR
—a faulty software update from cybersecurity firm Crowdstrike made this happen:

  • Grounded 5,000+ flights around the world.
  • Slowed healthcare across the UK.
  • Forced retailers to revert to cash-only transactions in Australia (what is this, the stone ages?!).


Here’s where AI comes in: Imagine today’s AI as a new operating system. In 5-10 years, it’ll likely be as integrated into our economy as Microsoft’s cloud servers are now. This isn’t that far-fetched—Microsoft is already planning to embed AI into all its programs.

So what if a Crowdstrike-like incident happens with a more powerful AI system? Some experts predict an AI-powered IT outage could be 10x worse than Friday’s fiasco.


The Crowdstrike outage and global software’s single-point failure problem — from cnbc.com by Kaya Ginsky

KEY POINTS

  • The CrowdStrike software bug that took down global IT infrastructure exposed a single-point-of-failure risk unrelated to malicious cyberattack.
  • National and cybersecurity experts say the risk of this kind of technical outage is increasing alongside the risk of hacks, and the market will need to adopt better competitive practices.
  • Government is also likely to look at new regulations related to software updates and patches.

The “largest IT outage in history,” briefly explained — from vox.com by Li Zhou
Airlines, banks, and hospitals saw computer systems go down because of a CrowdStrike software glitch.

 

AI-assisted job fraud is spiking — from thedeepview.co by Ian Krietzberg

A recent report published by the Identity Theft Resource Center (ITRC) found that data from 2023 shows “an environment where bad actors are more effective, efficient and successful in launching attacks. The result is fewer victims (or at least fewer victim reports), but the impact on individuals and businesses is arguably more damaging.”

One of these attacks involves fake job postings.

The details: The ITRC said that victim reports of job and employment scams spiked some 118% in 2023. These scams were primarily carried out through LinkedIn and other job search platforms.

    • The bad actors here would either create fake (but professional-looking) job postings, profiles and websites or impersonate legitimate companies, all with the hopes of landing victims to move onto the interview process.
    • These actors would then move the conversation onto a third-party messaging platform, and ask for identity verification information (driver’s licenses, social security numbers, direct deposit information, etc.).

Hypernatural — AI videos you can actually use. — via Jeremy Caplan’s Wonder Tools

Hypernatural is an AI video platform that makes it easy to create beautiful, ready-to share videos from anything. Stop settling for glitchy 3s generated videos and boring stock footage. Turn your ideas, scripts, podcasts and more into incredible short-form videos in minutes.


GPT-4o mini: advancing cost-efficient intelligence — from openai.com
Introducing our most cost-efficient small model

OpenAI is committed to making intelligence as broadly accessible as possible. Today, we’re announcing GPT-4o mini, our most cost-efficient small model. We expect GPT-4o mini will significantly expand the range of applications built with AI by making intelligence much more affordable. GPT-4o mini scores 82% on MMLU and currently outperforms GPT-41 on chat preferences in LMSYS leaderboard(opens in a new window). It is priced at 15 cents per million input tokens and 60 cents per million output tokens, an order of magnitude more affordable than previous frontier models and more than 60% cheaper than GPT-3.5 Turbo.

GPT-4o mini enables a broad range of tasks with its low cost and latency, such as applications that chain or parallelize multiple model calls (e.g., calling multiple APIs), pass a large volume of context to the model (e.g., full code base or conversation history), or interact with customers through fast, real-time text responses (e.g., customer support chatbots).

Also see what this means from Ben’s Bites, The Neuron, and as The Rundown AI asserts:

Why it matters: While it’s not GPT-5, the price and capabilities of this mini-release significantly lower the barrier to entry for AI integrations — and marks a massive leap over GPT 3.5 Turbo. With models getting cheaper, faster, and more intelligent with each release, the perfect storm for AI acceleration is forming.


Nvidia: More AI Waves Are Taking Shape — from seekingalpha.com by Eric Sprague

Summary

  • Nvidia Corporation is transitioning from a GPU designer to an AI factory builder.
  • AI spending will continue to grow in healthcare, government, and robotics.
  • CEO Jensen Huang says the AI robot industry could be bigger than the auto and consumer electronics industries combined.

Byte-Sized Courses: NVIDIA Offers Self-Paced Career Development in AI and Data Science — from blogs.nvidia.com by Andy Bui
Industry experts gather to share advice on starting a career in AI, highlighting technical training and certifications for career growth.

 

How Learning Designers Are Using AI for Analysis — from drphilippahardman.substack.com by Dr. Philippa Hardman
A practical guide on how to 10X your analysis process using free AI tools, based on real use cases

There are three key areas where AI tools make a significant impact on how we tackle the analysis part of the learning design process:

  1. Understanding the why: what is the problem this learning experience solves? What’s the change we want to see as a result?
  2. Defining the who: who do we need to target in order to solve the problem and achieve the intended goal?
  3. Clarifying the what: given who our learners are and the goal we want to achieve, what concepts and skills do we need to teach?

PROOF POINTS: Teens are looking to AI for information and answers, two surveys show — from hechingerreport.org by Jill Barshay
Rapidly evolving usage patterns show Black, Hispanic and Asian American youth are often quick to adopt the new technology

Two new surveys, both released this month, show how high school and college-age students are embracing artificial intelligence. There are some inconsistencies and many unanswered questions, but what stands out is how much teens are turning to AI for information and to ask questions, not just to do their homework for them. And they’re using it for personal reasons as well as for school. Another big takeaway is that there are different patterns by race and ethnicity with Black, Hispanic and Asian American students often adopting AI faster than white students.


AI Instructional Design Must Be More Than a Time Saver — from marcwatkins.substack.com by Marc Watkins

We’ve ceded so much trust to digital systems already that most simply assume a tool is safe to use with students because a company published it. We don’t check to see if it is compliant with any existing regulations. We don’t ask what powers it. We do not question what happens to our data or our student’s data once we upload it. We likewise don’t know where its information came from or how it came to generate human-like responses. The trust we put into these systems is entirely unearned and uncritical.

The allure of these AI tools for teachers is understandable—who doesn’t want to save time on the laborious process of designing lesson plans and materials? But we have to ask ourselves what is lost when we cede the instructional design process to an automated system without critical scrutiny.

From DSC:
I post this to be a balanced publisher of information. I don’t agree with everything Marc says here, but he brings up several solids points.


What does Disruptive Innovation Theory have to say about AI? — from christenseninstitute.org by Michael B. Horn

As news about generative artificial intelligence (GenAI) continually splashes across social media feeds, including how  ChatGPT 4o can help you play Rock, Paper, Scissors with a friend, breathtaking pronouncements about GenAI’s “disruptive” impact aren’t hard to find.

It turns out that it doesn’t make much sense to talk about GenAI as being “disruptive” in and of itself.

Can it be part of a disruptive innovation? You bet.

But much more important than just the AI technology in determining whether something is disruptive is the business model in which the AI is used—and its competitive impact on existing products and services in different markets.


On a somewhat note, also see:

National summit explores how digital education can promote deeper learning — from digitaleducation.stanford.edu by Jenny Robinson; via Eric Kunnen on Linkedin.com
The conference, held at Stanford, was organized to help universities imagine how digital innovation can expand their reach, improve learning, and better serve the public good.

The summit was organized around several key questions: “What might learning design, learning technologies, and educational media look like in three, five, or ten years at our institutions? How will blended and digital education be poised to advance equitable, just, and accessible education systems and contribute to the public good? What structures will we need in place for our teams and offices?”

 

Daniel Christian: My slides for the Educational Technology Organization of Michigan’s Spring 2024 Retreat

From DSC:
Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.

Topics/agenda:

  • Topics & resources re: Artificial Intelligence (AI)
    • Top multimodal players
    • Resources for learning about AI
    • Applications of AI
    • My predictions re: AI
  • The powerful impact of pursuing a vision
  • A potential, future next-gen learning platform
  • Share some lessons from my past with pertinent questions for you all now
  • The significant impact of an organization’s culture
  • Bonus material: Some people to follow re: learning science and edtech

 

Education Technology Organization of Michigan -- ETOM -- Spring 2024 Retreat on June 6-7

PowerPoint slides of Daniel Christian's presentation at ETOM

Slides of the presentation (.PPTX)
Slides of the presentation (.PDF)

 


Plus several more slides re: this vision.

 

A Right to Warn about Advanced Artificial Intelligence — from righttowarn.ai

We are current and former employees at frontier AI companies, and we believe in the potential of AI technology to deliver unprecedented benefits to humanity.

We also understand the serious risks posed by these technologies. These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction. AI companies themselves have acknowledged these risks [123], as have governments across the world [456] and other AI experts [789].

We are hopeful that these risks can be adequately mitigated with sufficient guidance from the scientific community, policymakers, and the public. However, AI companies have strong financial incentives to avoid effective oversight, and we do not believe bespoke structures of corporate governance are sufficient to change this.

 
 

Educators help children and teens learn how to identify fake news — from WMUK.org by Kalloli Bhatt and Sue Ellen Christian

Last year at the Kalamazoo Valley Museum, kids could learn about how misinformation is made and how to avoid it. Now the media scholar behind the exhibit is adapting it for libraries.

A new exhibit for libraries

That concern also drove the “Wonder Media” exhibit that ran through last year at the Kalamazoo Valley Museum. Sue Ellen Christian is a communications professor at Western Michigan University. The exhibit was her idea. Full disclosure: I’m a former student of Christian’s. We met in her office on campus.

“It’s really important for our entire society to think about the importance of facts and truth to a democracy,” said Christian. “And without an informed citizenry, we cannot have a healthy democracy.”

Christian recently received a grant from the Institute of Museum and Library Services, based in Washington D.C., to adapt the Wonder Media exhibit for public libraries. It’s designed to reach middle-school-age children.

Mainly, with her grant, Christian wants to develop something for students whose schools do not have librarians anymore. The website associated with the exhibit has resources for students, teachers, and libraries.

 

The Verge | What’s Next With AI | February 2024 | Consumer Survey

 

 

 

 

 

 




Microsoft AI creates talking deepfakes from single photo — from inavateonthenet.net


The Great Hall – where now with AI? It is not ‘Human Connection V Innovative Technology’ but ‘Human Connection + Innovative Technology’ — from donaldclarkplanb.blogspot.com by Donald Clark

The theme of the day was Human Connection V Innovative Technology. I see this a lot at conferences, setting up the human connection (social) against the machine (AI). I think this is ALL wrong. It is, and has always been a dialectic, human connection (social) PLUS the machine. Everyone had a smartphone, most use it for work, comms and social media. The binary between human and tech has long disappeared. 


Techno-Social Engineering: Why the Future May Not Be Human, TikTok’s Powerful ForYou Algorithm, & More — from by Misha Da Vinci

Things to consider as you dive into this edition:

  • As we increasingly depend on technology, how is it changing us?
  • In the interaction between humans and technology, who is adapting to whom?
  • Is the technology being built for humans, or are we being changed to fit into tech systems?
  • As time passes, will we become more like robots or the AI models we use?
  • Over the next 30 years, as we increasingly interact with technology, who or what will we become?

 

Addressing equity and ethics in artificial intelligence — from apa.org by Zara Abrams
Algorithms and humans both contribute to bias in AI, but AI may also hold the power to correct or reverse inequities among humans

“The conversation about AI bias is broadening,” said psychologist Tara Behrend, PhD, a professor at Michigan State University’s School of Human Resources and Labor Relations who studies human-technology interaction and spoke at CES about AI and privacy. “Agencies and various academic stakeholders are really taking the role of psychology seriously.”


NY State Bar Association Joins Florida and California on AI Ethics Guidance – Suggests Some Surprising Implications — from natlawreview.com by James G. Gatto

The NY State Bar Association (NYSBA) Task Force on Artificial Intelligence has issued a nearly 80 page report (Report) and recommendations on the legal, social and ethical impact of artificial intelligence (AI) and generative AI on the legal profession. This detailed Report also reviews AI-based software, generative AI technology and other machine learning tools that may enhance the profession, but which also pose risks for individual attorneys’ understanding of new, unfamiliar technology, as well as courts’ concerns about the integrity of the judicial process. It also makes recommendations for NYSBA adoption, including proposed guidelines for responsible AI use. This Report is perhaps the most comprehensive report to date by a state bar association. It is likely this Report will stimulate much discussion.

For those of you who want the “Cliff Notes” version of this report, here is a table that summarizes by topic the various rules mentioned and a concise summary of the associated guidance.

The Report includes four primary recommendations:


 

 

 

AWS, Educause partner on generative AI readiness tool — from edscoop.com by Skylar Rispens
Amazon Web Services and the nonprofit Educause announced a new tool designed to help higher education institutions gauge their readiness to adopt generative artificial intelligence.

Amazon Web Services and the nonprofit Educause on Monday announced they’ve teamed up to develop a tool that assesses how ready higher education institutions are to adopt generative artificial intelligence.

Through a series of curated questions about institutional strategy, governance, capacity and expertise, AWS and Educause claim their assessment can point to ways that operations can be improved before generative AI is adopted to support students and staff.

“Generative AI will transform how educators engage students inside and outside the classroom, with personalized education and accessible experiences that provide increased student support and drive better learning outcomes,” Kim Majerus, vice president of global education and U.S. state and local government at AWS, said in a press release. “This assessment is a practical tool to help colleges and universities prepare their institutions to maximize this technology and support students throughout their higher ed journey.”


Speaking of AI and our learning ecosystems, also see:

Gen Z Wants AI Skills And Businesses Want Workers Who Can Apply AI: Higher Education Can Help — from forbes.com by Bruce Dahlgren

At a moment when the value of higher education has come under increasing scrutiny, institutions around the world can be exactly what learners and employers both need. To meet the needs of a rapidly changing job market and equip learners with the technical and ethical direction needed to thrive, institutions should familiarize students with the use of AI and nurture the innately human skills needed to apply it ethically. Failing to do so can create enormous risk for higher education, business and society.

What is AI literacy?
To effectively utilize generative AI, learners will need to grasp the appropriate use cases for these tools, understand when their use presents significant downside risk, and learn to recognize abuse to separate fact from fiction. AI literacy is a deeply human capacity. The critical thinking and communication skills required are muscles that need repeated training to be developed and maintained.

 

Do We Need Emotionally Intelligent AI? — from marcwatkins.substack.com by Marc Watkins

We keep breaking new ground in AI capabilities, and there seems little interest in asking if we should build the next model to be more life-like. You can now go to Hume.AI and have a conversation with an Empathetic Voice Interface. EVI is groundbreaking and extremely unnerving, but it is no more capable of genuine empathy than your toaster oven.

    • You can have the eLLM mimic a political campaign and call potential voters to sway their vote. You can do this ethically or program it to prey upon people with misinformation.
    • An eLLM can be used to socially engineer the public based on the values someone programs into it. Whose values, though?
    • Any company with a digital presence can use an eLLM like EVI to influence their customers. Imagine Alexa suddenly being able to empathize with you as a means to help persuade you to order more products.
    • An always-on, empathetic system can help a student stay on track to graduate or manipulate them into behaviors that erode their autonomy and free will.
    • Any foreign government could deploy such a system against a neighboring population and use empathy as a weapon to sow discontent within the opposing population.

From DSC:
Marc offers some solid thoughts that should make us all pause and reflect on what he’s saying. 

We can endlessly rationalize away the reasons why machines possessing such traits can be helpful, but where is the line that developers and users of such systems refuse to cross in this race to make machines more like us?

Marc Watkins

Along these lines, also see:

  • Student Chatbot Use ‘Could Be Increasing Loneliness’ — from insidehighered.com by Tom Williams
    Study finds students who rely on ChatGPT for academic tasks feel socially supported by artificial intelligence at the expense of their real-life relationships.


    They found “evidence that while AI chatbots designed for information provision may be associated with student performance, when social support, psychological well-being, loneliness and sense of belonging are considered it has a net negative effect on achievement,” according to the paper published in Studies in Higher Education.

Editing your images with DALL·E — from help.openai.com via The Rundown
You can now edit images you create with DALL·E
 


How Early Adopters of Gen AI Are Gaining Efficiencies — from knowledge.wharton.upenn.edu by Prasanna (Sonny) Tambe and Scott A. Snyder; via Ray Schroeder on LinkedIn
Enterprises are seeing gains from generative AI in productivity and strategic planning, according to speakers at a recent Wharton conference.

Its unique strengths in translation, summation, and content generation are especially useful in processing unstructured data. Some 80% of all new data in enterprises is unstructured, he noted, citing research firm Gartner. Very little of that unstructured data that resides in places like emails “is used effectively at the point of decision making,” he noted. “[With gen AI], we have a real opportunity” to garner new insights from all the information that resides in emails, team communication platforms like Slack, and agile project management tools like Jira, he said.


6 YouTube Channels to Stay Up to Date with AI — from heaigirl.substack.com by Diana Dovgopol
Here are some cool AI YouTube channels.

Here are 6 YouTube channels I watch to stay up to date with AI. This list will be useful whether you’re a casual AI enthusiast or an experienced programmer.

1. Matt Wolfe: AI for non-coders
This is a fast-growing YouTube channel focused on artificial intelligence for non-coders. On this channel, you’ll find videos about ChatGPT, Midjourney, and any AI tool that it’s gaining popularity.


Top AI mobile apps, Stable Video 3D, & my AI film workflow — from by Heather Cooper
Plus 1-Click 3D animation and other cool AI tools

#3 Photomath
Photomath is a comprehensive math help app that provides step-by-step explanations for a wide range of math problems, from elementary to college level. Photomath is only available as a mobile app. (link)

Features:

  • Get step-by-step solutions with multiple methods to choose from
  • Scan any math problem, including word problems, using the app’s camera
  • Access custom visual aids and extra “how” and “why” tips for deeper understanding

Google researchers unveil ‘VLOGGER’, an AI that can bring still photos to life — from venturebeat.com by Michael Nuñez

Google researchers have developed a new artificial intelligence system that can generate lifelike videos of people speaking, gesturing and moving — from just a single still photo. The technology, called VLOGGER, relies on advanced machine learning models to synthesize startlingly realistic footage, opening up a range of potential applications while also raising concerns around deepfakes and misinformation.



What We Risk By Automating Tasks We Loathe — from marcwatkins.substack.com by Marc Watkins

I’m fascinated by the potential of these tools to augment and enhance our work and creativity. There’s no denying the impressive capabilities we’re already seeing with text generation, image creation, coding assistance, and more. Used thoughtfully, AI can be a powerful productivity multiplier.

At the same time, I have significant concerns about the broader implications of this accelerating technology, especially for education and society at large. We’re traversing new ground at a breakneck pace, and it’s crucial that we don’t blindly embrace AI without considering the potential risks.

My worry is that by automating away too many tasks, even seemingly rote ones like creating slide decks, we risk losing something vital—humanity at the heart of knowledge work.


Nvidia Introduce AI Nurses — from wireprompt.substack.com | Weekkly AI Report from WirePrompt

Nvidia has announced a partnership with Hippocratic AI to introduce AI “agents” aimed at replacing nurses in hospitals. These AI “nurses” come at a significantly low cost compared to human nurses and are purportedly intended to address staffing issues by handling “low-risk,” patient-facing tasks via video calls. However, concerns are raised regarding the ethical implications and effectiveness of replacing human nurses with AI, particularly given the complex nature of medical care.



16 Changes to the Way Enterprises Are Building and Buying Generative AI — from a16z.com by Sarah Wang and Shangda Xu

TABLE OF CONTENTS

  • Resourcing: budgets are growing dramatically and here to stay
  • Models: enterprises are trending toward a multi-model, open source world
  • Use cases: more migrating to production
  • Size of total opportunity: massive and growing quickly

 

Which AI should I use? Superpowers and the State of Play — from by Ethan Mollick
And then there were three

For over a year, GPT-4 was the dominant AI model, clearly much smarter than any of the other LLM systems available. That situation has changed in the last month, there are now three GPT-4 class models, all powering their own chatbots: GPT-4 (accessible through ChatGPT Plus or Microsoft’s CoPilot), Anthropic’s Claude 3 Opus, and Google’s Gemini Advanced1.

Where we stand
We are in a brief period in the AI era where there are now multiple leading models, but none has yet definitively beaten the GPT-4 benchmark set over a year ago. While this may represent a plateau in AI abilities, I believe this is likely to change in the coming months as, at some point, models like GPT-5 and Gemini 2.0 will be released. In the meantime, you should be using a GPT-4 class model and using it often enough to learn what it does well. You can’t go wrong with any of them, pick a favorite and use it…

From DSC:
Here’s a powerful quote from Ethan:

In fact, in my new book I postulate that you haven’t really experienced AI until you have had three sleepless nights of existential anxiety, after which you can start to be productive again.


Using AI for Immersive Educational Experiences — from automatedteach.com by Graham Clay
Realistic video brings course content to life but requires AI literacy.

For us, I think the biggest promise of AI tools like Sora — that can create video with ease — is that they lower the cost of immersive educational experiences. This increases the availability of these experiences, expanding their reach to student populations who wouldn’t otherwise have them, whether due to time, distance, or expense.

Consider the profound impact on a history class, where students are transported to California during the gold rush through hyperrealistic video sequences. This vivifies the historical content and cultivates a deeper connection with the material.

In fact, OpenAI has already demonstrated the promise of this sort of use case, with a very simple prompt producing impressive results…


The Empathy Illusion: How AI Agents Could Manipulate Students — from marcwatkins.substack.com by Marc Watkins

Take this scenario. A student misses a class and, within twenty minutes, receives a series of texts and even a voicemail from a very concerned and empathic-sounding voice wanting to know what’s going on. Of course, the text is entirely generated, and the voice is synthetic as well, but the student likely doesn’t know this. To them, communication isn’t something as easy to miss or brush off as an email. It sounds like someone who cares is talking to them.

But let’s say that isn’t enough. By that evening, the student still hadn’t logged into their email or checked the LMS. The AI’s strategic reasoning is communicating with the predictive AI and analyzing the pattern of behavior against students who succeed or fail vs. students who are ill. The AI tracks the student’s movements on campus, monitors their social media usage, and deduces the student isn’t ill and is blowing off class.

The AI agent resumes communication with the student. But this time, the strategic AI adopts a different persona, not the kind and empathetic persona used for the initial contact, but a stern, matter-of-fact one. The student’s phone buzzes with alerts that talk about scholarships being lost, teachers being notified, etc. The AI anticipates the excuses the student will use and presents evidence tracking the student’s behavior to show they are not sick.


Not so much focused on learning ecosystems, but still worth mentioning:

The top 100 Gen AI Consumer Apps — from a16z.com / andreessen horowitz by Olivia Moore


 

 

Hackers are targeting a surprising group of people: young public school students — from npr.org

“This breach was actually really huge,” Gravatt says. “And it wasn’t just school records. It was health records, it was all sorts of things that should be privileged information that are now just out there floating around for anybody to buy.”

It’s an example of a growing nationwide trend in which hackers are targeting a surprising group of people: young public school students.

As school districts depend more on technology, cyberattacks against those systems, and the sensitive data they store, are on the rise. While it’s hard to know exactly how many K-12 school systems have been targeted by hackers, an analysis by the cyber security firm Emsisoft found 45 districts reported they were attacked in 2022. In 2023, that number more than doubled, to 108.

He says stealing a child’s identity may seem counterintuitive because they don’t have resources of their own, but it can cause “a lot of havoc.” Parents don’t necessarily monitor their children’s credit and bad actors can easily open up bank accounts, rack up debt and apply for loans in a child’s name.

“And as a result, cyber criminals can abuse the credit records of minors for many, many years before the victims learn about it,” Levin says.

From DSC:
This is a deeply troubling situation, and yet another example of what occurs when people don’t care about each other. They only want to make money — and they don’t care about how they go about doing that. (LORD, help us!) 

As the article suggests, the impacts of these breaches can last for years. When sensitive information is lost in a breach, that information can come back to haunt young people as they try to get jobs, get into colleges, build positive credit reports, and more.

So we need to invest in the hardware, software, and people to protect that data.

 

How AI Is Already Transforming the News Business — from politico.com by Jack Shafer
An expert explains the promise and peril of artificial intelligence.

The early vibrations of AI have already been shaking the newsroom. One downside of the new technology surfaced at CNET and Sports Illustrated, where editors let AI run amok with disastrous results. Elsewhere in news media, AI is already writing headlines, managing paywalls to increase subscriptions, performing transcriptions, turning stories in audio feeds, discovering emerging stories, fact checking, copy editing and more.

Felix M. Simon, a doctoral candidate at Oxford, recently published a white paper about AI’s journalistic future that eclipses many early studies. Swinging a bat from a crouch that is neither doomer nor Utopian, Simon heralds both the downsides and promise of AI’s introduction into the newsroom and the publisher’s suite.

Unlike earlier technological revolutions, AI is poised to change the business at every level. It will become — if it already isn’t — the beginning of most story assignments and will become, for some, the new assignment editor. Used effectively, it promises to make news more accurate and timely. Used frivolously, it will spawn an ocean of spam. Wherever the production and distribution of news can be automated or made “smarter,” AI will surely step up. But the future has not yet been written, Simon counsels. AI in the newsroom will be only as bad or good as its developers and users make it.

Also see:

Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena — from cjr.org by Felix Simon

TABLE OF CONTENTS



EMO: Emote Portrait Alive – Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions — from humanaigc.github.io Linrui Tian, Qi Wang, Bang Zhang, and Liefeng Bo

We proposed EMO, an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input video.


Adobe previews new cutting-edge generative AI tools for crafting and editing custom audio — from blog.adobe.com by the Adobe Research Team

New experimental work from Adobe Research is set to change how people create and edit custom audio and music. An early-stage generative AI music generation and editing tool, Project Music GenAI Control allows creators to generate music from text prompts, and then have fine-grained control to edit that audio for their precise needs.

“With Project Music GenAI Control, generative AI becomes your co-creator. It helps people craft music for their projects, whether they’re broadcasters, or podcasters, or anyone else who needs audio that’s just the right mood, tone, and length,” says Nicholas Bryan, Senior Research Scientist at Adobe Research and one of the creators of the technologies.


How AI copyright lawsuits could make the whole industry go extinct — from theverge.com by Nilay Patel
The New York Times’ lawsuit against OpenAI is part of a broader, industry-shaking copyright challenge that could define the future of AI.

There’s a lot going on in the world of generative AI, but maybe the biggest is the increasing number of copyright lawsuits being filed against AI companies like OpenAI and Stability AI. So for this episode, we brought on Verge features editor Sarah Jeong, who’s a former lawyer just like me, and we’re going to talk about those cases and the main defense the AI companies are relying on in those copyright cases: an idea called fair use.


FCC officially declares AI-voiced robocalls illegal — from techcrunch.com by Devom Coldewey

The FCC’s war on robocalls has gained a new weapon in its arsenal with the declaration of AI-generated voices as “artificial” and therefore definitely against the law when used in automated calling scams. It may not stop the flood of fake Joe Bidens that will almost certainly trouble our phones this election season, but it won’t hurt, either.

The new rule, contemplated for months and telegraphed last week, isn’t actually a new rule — the FCC can’t just invent them with no due process. Robocalls are just a new term for something largely already prohibited under the Telephone Consumer Protection Act: artificial and pre-recorded messages being sent out willy-nilly to every number in the phone book (something that still existed when they drafted the law).


EIEIO…Chips Ahoy! — from dashmedia.co by Michael Moe, Brent Peus, and Owen Ritz


Here Come the AI Worms — from wired.com by Matt Burgess
Security researchers created an AI worm in a test environment that can automatically spread between generative AI agents—potentially stealing data and sending spam emails along the way.

Now, in a demonstration of the risks of connected, autonomous AI ecosystems, a group of researchers have created one of what they claim are the first generative AI worms—which can spread from one system to another, potentially stealing data or deploying malware in the process. “It basically means that now you have the ability to conduct or to perform a new kind of cyberattack that hasn’t been seen before,” says Ben Nassi, a Cornell Tech researcher behind the research.

 
© 2024 | Daniel Christian