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.

 

AI agents are the future, and a lot is at stake — from forbes.com by Skip Sanzeri

What An Agent Is
Agents are computer programs that can autonomously perform tasks, make decisions and interact with humans or other computers. There are many different types of agents, and they are designed to achieve specific goals spanning our lives and nearly every industry, making them an integral and unstoppable part of our future.

Learning: AI agents will transform education by providing personalized learning experiences such as one-to-one tutoring. ChatGPT and other large language models (LLMs) are providing access to all digital knowledge now. An “agent” would act as a more personalized version of an LLM.

The hacking and control of an AI agent could lead to disastrous consequences, affecting privacy, security, the economy and societal stability. Proactive and comprehensive security strategies are essential to mitigate these risks in the future.

 

Per the Rundown AI:

Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.

Also relevant/see:


Creators to Have Personalized AI Assistants, Meta CEO Mark Zuckerberg Tells NVIDIA CEO Jensen Huang — from blogs.nvidia.com by Brian Caulfield
Zuckerberg and Huang explore the transformative potential of open source AI, the launch of AI Studio, and exchange leather jackets at SIGGRAPH 2024.

“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.

“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.

More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.

Also related/see:


From DSC:
Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.






9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi
AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.

7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.

8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.


Top 7 generative AI use cases for business — from cio.com by Grant Gross
Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.

Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.

However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.

 

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.

 
© 2024 | Daniel Christian