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“Miscommunication Leads AI-Based Hiring Tools Astray” [adigaskell.org] + other items re: AI in general

On 11/19/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, Blockchain, computer science, design, emerging technologies, engineering, experimentation, game-changing environment, Google, graphics, India, innovation, Microsoft, NVIDIA, Open AI, platforms, programming, robotics, simulations, society, tools, usability, user experience (UX), vendors, by Daniel Christian

Miscommunication Leads AI-Based Hiring Tools Astray — from adigaskell.org

Nearly every Fortune 500 company now uses artificial intelligence (AI) to screen resumes and assess test scores to find the best talent. However, new research from the University of Florida suggests these AI tools might not be delivering the results hiring managers expect.

The problem stems from a simple miscommunication between humans and machines: AI thinks it’s picking someone to hire, but hiring managers only want a list of candidates to interview.

Without knowing about this next step, the AI might choose safe candidates. But if it knows there will be another round of screening, it might suggest different and potentially stronger candidates.

AI agents explained: Why OpenAI, Google and Microsoft are building smarter AI agents — from digit.in by Jayesh Shinde

In the last two years, the world has seen a lot of breakneck advancement in the Generative AI space, right from text-to-text, text-to-image and text-to-video based Generative AI capabilities. And all of that’s been nothing short of stepping stones for the next big AI breakthrough – AI agents. According to Bloomberg, OpenAI is preparing to launch its first autonomous AI agent, which is codenamed ‘Operator,’ as soon as in January 2025.

Apparently, this OpenAI agent – or Operator, as it’s codenamed – is designed to perform complex tasks independently. By understanding user commands through voice or text, this AI agent will seemingly do tasks related to controlling different applications in the computer, send an email, book flights, and no doubt other cool things. Stuff that ChatGPT, Copilot, Google Gemini or any other LLM-based chatbot just can’t do on its own.

2025: The year ‘invisible’ AI agents will integrate into enterprise hierarchies  — from venturebeat.com by Taryn Plumb

In the enterprise of the future, human workers are expected to work closely alongside sophisticated teams of AI agents.

According to McKinsey, generative AI and other technologies have the potential to automate 60 to 70% of employees’ work. And, already, an estimated one-third of American workers are using AI in the workplace — oftentimes unbeknownst to their employers.

However, experts predict that 2025 will be the year that these so-called “invisible” AI agents begin to come out of the shadows and take more of an active role in enterprise operations.

“Agents will likely fit into enterprise workflows much like specialized members of any given team,” said Naveen Rao, VP of AI at Databricks and founder and former CEO of MosaicAI.

State of AI Report 2024 Summary — from ai-supremacy.com by Michael Spencer
Part I, Consolidation, emergence and adoption. 

Which AI Image Model Is the Best Speller? Let’s Find Out! — from whytryai.com by Daniel Nest
I test 7 image models to find those that can actually write.

The contestants
I picked 7 participants for today’s challenge:

  1. DALL-E 3 by OpenAI (via Microsoft Designer)
  2. FLUX1.1 [pro] by Black Forest Labs (via Glif)
  3. Ideogram 2.0 by Ideogram (via Ideogram)
  4. Imagen 3 by Google (via Image FX)
  5. Midjourney 6.1 by Midjourney (via Midjourney)
  6. Recraft V3 by Recraft (via Recraft)
  7. Stable Diffusion 3.5 Large by Stability AI (via Hugging Face)

How to get started with AI agents (and do it right) — from venturebeat.com by Taryn Plumb

So how can enterprises choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models? Experts weigh in.

OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI — from bloomberg.com (behind firewall)
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.

OpenAI and others seek new path to smarter AI as current methods hit limitations — from reuters.com by Krystal Hu and Anna Tong

Summary

  • AI companies face delays and challenges with training new large language models
  • Some researchers are focusing on more time for inference in new models
  • Shift could impact AI arms race for resources like chips and energy

NVIDIA Advances Robot Learning and Humanoid Development With New AI and Simulation Tools — from blogs.nvidia.com by Spencer Huang
New Project GR00T workflows and AI world model development technologies to accelerate robot dexterity, control, manipulation and mobility.

How Generative AI is Revolutionizing Product Development — from intelligenthq.com

A recent report from McKinsey predicts that generative AI could unlock up to $2.6 to $4.4 annually trillion in value within product development and innovation across various industries. This staggering figure highlights just how significantly generative AI is set to transform the landscape of product development. Generative AI app development is driving innovation by using the power of advanced algorithms to generate new ideas, optimize designs, and personalize products at scale. It is also becoming a cornerstone of competitive advantage in today’s fast-paced market. As businesses look to stay ahead, understanding and integrating technologies like generative AI app development into product development processes is becoming more crucial than ever.

What are AI Agents: How To Create a Based AI Agent — from ccn.com by Lorena Nessi

Key Takeaways

  • AI agents handle complex, autonomous tasks beyond simple commands, showcasing advanced decision-making and adaptability.
  • The Based AI Agent template by Coinbase and Replit provides an easy starting point for developers to build blockchain-enabled AI agents.
  • AI based agents specifically integrate with blockchain, supporting crypto wallets and transactions.
  • Securing API keys in development is crucial to protect the agent from unauthorized access.

What are AI Agents and How Are They Used in Different Industries? — from rtinsights.com by Salvatore Salamone
AI agents enable companies to make smarter, faster, and more informed decisions. From predictive maintenance to real-time process optimization, these agents are delivering tangible benefits across industries.

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“Introducing ChatGPT search” [OpenAI] + other items re: AI in general

On 11/01/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, change, changing business models, cloud-based computing / apps / other cloud-related, communities of practice, emerging technologies, Google, human-computer interaction (HCI), India, innovation, intelligent systems, NVIDIA, Open AI, platforms, society, tools, United States, vendors, workplace, by Daniel Christian

Google’s worst nightmare just became reality — from aidisruptor.ai by Alex McFarland
OpenAI just launched an all-out assault on traditional search engines.

Google’s worst nightmare just became reality. OpenAI didn’t just add search to ChatGPT – they’ve launched an all-out assault on traditional search engines.

It’s the beginning of the end for search as we know it.

Let’s be clear about what’s happening: OpenAI is fundamentally changing how we’ll interact with information online. While Google has spent 25 years optimizing for ad revenue and delivering pages of blue links, OpenAI is building what users actually need – instant, synthesized answers from current sources.

The rollout is calculated and aggressive: ChatGPT Plus and Team subscribers get immediate access, followed by Enterprise and Education users in weeks, and free users in the coming months. This staged approach is about systematically dismantling Google’s search dominance.

Open for AI: India Tech Leaders Build AI Factories for Economic Transformation — from blogs.nvidia.com
Yotta Data Services, Tata Communications, E2E Networks and Netweb are among the providers building and offering NVIDIA-accelerated infrastructure and software, with deployments expected to double by year’s end.

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Some dangers of running AI’s that control a computer or a web browser; + other AI related items

On 10/30/2024, in Apple, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, computer science, emerging technologies, Europe, Google, Microsoft, NVIDIA, Open AI, platforms, programming, the downsides of how people use tech, tools, trends, United States, vendors, workplace, by Daniel Christian

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.

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“AI-governed robots can easily be hacked” [Barsee], a new AI capability called “computer use” + numerous other items re: AI in general

On 10/23/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, communications, communities of practice, computer science, content development, aggregation, repositories, corporate / business world, creativity, data related items, digital video, emerging technologies, Google, health, innovation, IT in HE, media/film, Microsoft, multimedia, new media literacies, Open AI, pace of change, platforms, presentations, productivity / tips and tricks, programming, research, robotics, society, the downsides of how people use tech, tools, United States, universities, vendors, writing, by Daniel Christian

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/

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Several items re: AI in our learning ecosystems

On 10/18/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, digital audio, digital learning, education technology, emerging technologies, experimentation, faculty, Google, higher education, human-computer interaction (HCI), ideas, instructional design, learning ecosystem, Learning Experience Design, multimedia, online learning, online media, Open AI, teaching & learning, tools, United States, universities, vendors, by Daniel Christian

Are ChatGPT, Claude & NotebookLM *Really* Disrupting Education? — from drphilippahardman.substack.com
Evaluating Gen AI’s *real* impact on human learning

The TLDR here is that, as useful as popular AI tools are for learners, as things stand they only enable us to take the very first steps on what is a long and complex journey of learning.

AI tools like ChatGPT 4o, Claude 3.5 & NotebookLM can help to give us access to information but (for now at least) the real work of learning remains in our – the humans’ – hands.

To which Anna Mills had a solid comment:

It might make a lot of sense to regulate generated audio to require some kind of watermark and/or metadata. Instructors who teach online and assign voice recordings, we need to recognize that these are now very easy and free to auto-generate. In some cases we are assigning this to discourage students from using AI to just autogenerate text responses, but audio is not immune.

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How far should we go in allowing technology to aid our decision-making processes? [Schlegel] + other legaltech-related items

On 10/11/2024, in 21st century, 24x7x365 access, future, game-changing environment, Google, innovation, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, Open AI, platforms, podcasting, by Daniel Christian

The Future of Umpiring in Baseball: Balancing Tradition and Technology — from judgeschlegel.com by Judge Scott Schlegel
This article is not about baseball.

As we look to the future of umpiring in baseball, a balanced approach may offer the best solution. Rather than an all-or-nothing choice between human umpires and full automation, a hybrid system could potentially offer the benefits of both worlds. For instance, automated tracking systems could be used to assist human umpires, providing them with real-time data to inform their calls. This would maintain the human element and authority on the field while significantly enhancing accuracy and consistency.

Such a system would allow umpires to focus more on game management, player interactions, and the myriad other responsibilities that require human judgment and experience. It would preserve the traditional aspects of the umpire’s role that fans and players value, while leveraging technology to address concerns about accuracy and fairness.

Navigating the Intersection of Tradition and AI: The Future of Judicial Decision-Making — from judgeschlegel.com by Judge Scott Schlegel

Introduction
Continuing with our baseball analogy, we now turn our focus to the courtroom.

The intersection of technology and the justice system is a complex and often contentious space, much like the debate over automated umpires in baseball. As Major League Baseball considers whether automated systems should replace the human element in calling balls and strikes, the legal world faces similar questions: How far should we go in allowing technology to aid our decision-making processes, and what is the right balance between innovation and the traditions that define the courtroom?

AI and the rise of the Niche Lawyer — from jordanfurlong.substack.com by Jordan Furlong
A new legal market will create a new type of lawyer: Specialized, flexible, customized, fractional, home-based and online, exclusive, balanced and focused. This could be your future legal career.

Think of a new picture. A lawyer dressed in Professional Casual, or Business Comfortable, an outfit that looks sharp but feels relaxed. A lawyer inside their own apartment, in an extra bedroom, or in a shared workspace on a nearby bus route, taking an Uber to visit some clients and using Zoom to meet with others. A lawyer with a laptop and a tablet and a smartphone and no other capital expenditures. A lawyer whose overhead is only what’s literally over their head.

This lawyer starts work when they feel like it (maybe 7 am, maybe 10; maybe Monday, maybe not) and they stop working when they feel like it (maybe 4 pm, maybe 9). They have as many clients as they need, for whom they provide very specific, very personalized services. They provide some services that aren’t even “legal” to people who aren’t “clients” as we understand both terms. They have essential knowledge and skills that all lawyers share but unique knowledge and skills that hardly any others possess. They make as much money as they need in order to meet the rent and pay down their debts and afford a life with the people they love. They’re in complete charge of their career and their destiny, something they find terrifying and stressful and wonderful and fulfilling.

While We Were Distracted with the New ChatGPT Model, Google Quietly Dropped an AI Bombshell —  from judgeschlegel.com by Judge Scott Schlegel

While the latest ChatGPT model is dominating tech headlines, I was unexpectedly blown away by Google’s recent release of a new NotebookLM feature: Audio Overview. This tool, which transforms written content into simulated conversations, caught me off guard with its capabilities. I uploaded some of my blog posts on AI and the justice system, and what it produced left me speechless. The AI generated podcast-like discussions felt remarkably authentic, complete with nuanced interpretations and even slight misunderstandings of my ideas. This mirrors real-life discussions perfectly – after all, how often do we hear our own thoughts expressed by others and think, “That’s not quite what I meant”?

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“How to do school with NotebookLM” [Johnson] + other items re: AI in our LE’s

On 10/07/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, Google, higher education, intelligent systems, intelligent tutoring, languages and translation, society, sociology, tools, United States, vendors, vision/possibilities, by Daniel Christian

According to Notebook LM on this Future U podcast — Searching for Fit: The Impacts of AI in Higher Ed — here are some excerpts from the generated table of contents:

Part 1: Setting the Stage

I. Introduction (0:00 – 6:16): …
II. Historical Contextualization (6:16 – 11:30): …
III. The Role of Product Fit in AI’s Impact (11:30 – 17:10): …
IV. AI and the Future of Knowledge Work (17:10 – 24:03): …
V. Teaching About AI in Higher Ed: A Measured Approach (24:03 – 34:20): …
VI. AI & the Evolving Skills Landscape (34:20 – 44:35): …
VII. Ethical & Pedagogical Considerations in an AI-Driven World (44:35 – 54:03):…
VIII. AI Beyond the Classroom: Administrative Applications & the Need for Intuition (54:03 – 1:04:30): …
IX. Reflections & Future Directions (1:04:30 – 1:11:15): ….

Part 2: Administrative Impacts & Looking Ahead

X. Bridging the Conversation: From Classroom to Administration (1:11:15 – 1:16:45): …
XI. The Administrative Potential of AI: A Looming Transformation (1:16:45 – 1:24:42): …
XII. The Need for Intuitiveness & the Importance of Real-World Applications (1:24:42 – 1:29:45): …
XIII. Looking Ahead: From Hype to Impactful Integration (1:29:45 – 1:34:25): …
XIV. Conclusion and Call to Action (1:34:25 – 1:36:03): …

The future of language learning — from medium.com by Sami Tatar

Most language learners do not have access to affordable 1:1 tutoring, which is also proven to be the most effective way to learn (short of moving to a specific country for complete immersion). Meanwhile, language learning is a huge market, and with an estimated 60% of this still dominated by “offline” solutions, meaning it is prime for disruption and never more so than with the opportunities unlocked through AI powered language learning. Therefore — we believe this presents huge opportunities for new startups creating AI native products to create the next language learning unicorns.

“The Broken Mirror: Rethinking Education, AI, and Equity in America’s Classrooms” — from nickpotkalitsky.substack.com by JC Price

It’s not that AI is inherently biased, but in its current state, it favors those who can afford it. The wealthy districts continue to pull ahead, leaving schools without resources further behind. Students in these underserved areas aren’t just being deprived of technology—they’re being deprived of the future.

But imagine a different world—one where AI doesn’t deepen the divide, but helps to bridge it. Technology doesn’t have to be the luxury of the wealthy. It can be a tool for every student, designed to meet them where they are. Adaptive AI systems, integrated into schools regardless of their budget, can provide personalized learning experiences that help students catch up and push forward, all while respecting the limits of their current infrastructure. This is where AI’s true potential lies—not in widening the gap, but in leveling the field.

But imagine if, instead of replacing teachers, AI helped to support them. Picture a world where teachers are freed from the administrative burdens that weigh them down. Where AI systems handle the logistics, so teachers can focus on what they do best—teaching, mentoring, and inspiring the next generation. Professional development could be personalized, helping teachers integrate AI into their classrooms in ways that enhance their teaching, without adding to their workload. This is the future we should be striving toward—one where technology serves to lift up educators, not push them out.

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“185 real-world gen AI use cases from the world’s leading organizations” [Google], a professional network for AI agents [Shah] + other items re: AI in general

On 10/01/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, cloud-based computing / apps / other cloud-related, communications, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, data related items, design, digital audio, digital video, emerging technologies, engineering, ethics, future, game-changing environment, Google, graphics, health, innovation, languages and translation, learning agents, Microsoft, morals/values, NVIDIA, online learning, online media, Open AI, platforms, podcasting, presentations, productivity / tips and tricks, programming, robotics, telemedicine / telehealth / virtual health, tools, training / L&D, United States, vendors, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

AI’s Trillion-Dollar Opportunity — from bain.com by David Crawford, Jue Wang, and Roy Singh
The market for AI products and services could reach between $780 billion and $990 billion by 2027.

At a Glance

  • The big cloud providers are the largest concentration of R&D, talent, and innovation today, pushing the boundaries of large models and advanced infrastructure.
  • Innovation with smaller models (open-source and proprietary), edge infrastructure, and commercial software is reaching enterprises, sovereigns, and research institutions.
  • Commercial software vendors are rapidly expanding their feature sets to provide the best use cases and leverage their data assets.

Accelerated market growth. Nvidia’s CEO, Jensen Huang, summed up the potential in the company’s Q3 2024 earnings call: “Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades.”

And on a somewhat related note (i.e., emerging technologies), also see the following two postings:

Surgical Robots: Current Uses and Future Expectations — from medicalfuturist.com by Pranavsingh Dhunnoo
As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre.

Key Takeaways

  • Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.
  • Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.
  • The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.

Proto hologram tech allows cancer patients to receive specialist care without traveling large distances — from inavateonthenet.net

“Working with the team from Proto to bring to life, what several years ago would have seemed impossible, is now going to allow West Cancer Center & Research Institute to pioneer options for patients to get highly specialized care without having to travel to large metro areas,” said West Cancer’s CEO, Mitch Graves.

Clone your voice in minutes: The AI trick 95% don’t know about — from aidisruptor.ai by Alex McFarland
Warning: May cause unexpected bouts of talking to yourself

Now that you’ve got your voice clone, what can you do with it?

  1. Content Creation:
    • Podcast Production: Record episodes in half the time. Your listeners won’t know the difference, but your schedule will thank you.
    • Audiobook Narration: Always wanted to narrate your own book? Now you can, without spending weeks in a recording studio.
    • YouTube Videos: Create voiceovers for your videos in multiple languages. World domination, here you come!
  2. Business Brilliance:
    • Customer Service: Personalized automated responses that actually sound personal.
    • Training Materials: Create engaging e-learning content in your own voice, minus the hours of recording.
    • Presentations: Never worry about losing your voice before a big presentation again. Your clone’s got your back.

185 real-world gen AI use cases from the world’s leading organizations — from blog.google by Brian Hall; via Daniel Nest’s Why Try AI

In a matter of months, organizations have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes.

In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes, and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; code creation; data analysis; cybersecurity; and creative ideation and production.
…
Here’s a snapshot of how 185 of these industry leaders are putting AI to use today, creating real-world use cases that will transform tomorrow.

AI Data Drop: 3 Key Insights from Real-World Research on AI Usage — from microsoft.com; via Daniel Nest’s Why Try AI
One of the largest studies of Copilot usage—at nearly 60 companies—reveals how AI is changing the way we work.

  1. AI is starting to liberate people from email
  2. Meetings are becoming more about value creation
  3. People are co-creating more with AI—and with one another

*** Dharmesh has been working on creating agent.ai — a professional network for AI agents.***

Speaking of agents, also see:

Onboarding the AI workforce: How digital agents will redefine work itself — from venturebeat.com by Gary Grossman

AI in 2030: A transformative force

  1. AI agents are integral team members
  2. The emergence of digital humans
  3. AI-driven speech and conversational interfaces
  4. AI-enhanced decision-making and leadership
  5. Innovation and research powered by AI
  6. The changing nature of job roles and skills

AI Video Tools You Can Use Today — from heatherbcooper.substack.com by Heather Cooper
The latest AI video models that deliver results

AI video models are improving so quickly, I can barely keep up! I wrote about unreleased Adobe Firefly Video in the last issue, and we are no closer to public access to Sora.

No worries – we do have plenty of generative AI video tools we can use right now.

  • Kling AI launched its updated v1.5 and the quality of image or text to video is impressive.
  • Hailuo MiniMax text to video remains free to use for now, and it produces natural and photorealistic results (with watermarks).
  • Runway added the option to upload portrait aspect ratio images to generate vertical videos in Gen-3 Alpha & Turbo modes.
  • …plus several more

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Here are a variety of legaltech related items — showing change in the legal industry

On 10/01/2024, in Access to Justice (A2J), change, Cost of legal services - including access, Google, innovation, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, podcasting, productivity / tips and tricks, tools, UK, United States, vendors, vision/possibilities, by Daniel Christian

RIP To Human First Pass Document Review? — from abovethelaw.com by Joe Patrice
Using actual humans to perform an initial review isn’t gone yet, but the days are numbered.

Lawyers are still using real, live people to take a first crack at document review, but much like the “I’m not dead yet” guy from Monty Python and the Holy Grail, it’s a job that will be stone dead soon. Because there are a lot of deeply human tasks that AI will struggle to replace, but getting through a first run of documents doesn’t look like one of them.

At last week’s Relativity Fest, the star of the show was obviously Relativity aiR for Review, which the company moved to general availability. In conjunction with the release, Relativity pointed to impressive results the product racked up during the limited availability period including Cimplifi reporting that the product cut review time in half and JND finding a 60 percent cut in costs.

Ernie The Attorney: A Tech Whisperer Shares His Legal Tech Secrets — from legaltalknetwork.com by Ernie Svenson
Guest Ernie “The Attorney” Svenson is dedicated to helping small and solo firms get the most out of today’s tech tools. Work smarter, not harder.

When it comes to efficiencies, automation plays a big role. In a solo or small firm, resources come at a premium. Learn to reduce wasted input through standardized, repeatable operating procedures and automation. (There are even tech products that help you create written standard processes learning from and organizing the work you’re already doing).

Imagine speaking into an app as you “brain dump” and having those thoughts come out organized and notated for later use. Imagine dictating legal work into an app and having AI organize your dictation, even correct it. You don’t need to type everything in today’s tech world. Maximize downtime.

It’s all about training yourself to think “automation first.” Even when a virtual assistant (VA) located in another country can fill gaps in your practice, learn your preferences, match your brand, and help you be your most efficient you without hiring a full-tie employee. Today’s most successful law firms are high-tech hubs. Don’t let fear of the unknown hold you back.

Here’s the Video of Our Legaltech Week Panel Recorded Live Friday at RelativityFest in Chicago — from lawnext.com by Bob Ambrogi

Several of our regular Legaltech Week panelists were in Chicago for RelativityFest last week, so we took the opportunity to get together and broadcast our show live from the same room (instead of Zoom squares).

If you missed it Friday, here’s the video recording.

LexisNexis legal AI adoption report shows sharp increase in use of Gen AI — from legaltechnology.com

Today (24 September) LexisNexis has released a new report – Need for Speedier Legal Services sees AI Adoption Accelerate – which reveals a sharp increase in the number of lawyers using generative AI for legal work.

The survey of 800+ UK legal professionals at firms and in-house teams found 41% are currently using AI for work, up from 11% in July 2023. Lawyers with plans to use AI for legal work in the near future also jumped from 28% to 41%, while those with no plans to adopt AI dropped from 61% to 15%. The survey found that 39% of private practice lawyers now expect to adjust their billing practices due to AI, up from 18% in January 2024.

Robin AI’s James Clough: ‘Don’t Skate To Where The Puck Is’ — from artificiallawyer.com

‘What if legal review cost just $1? What if legal review was 1,000X cheaper than today?’ he muses.

And, one could argue we are getting there already – at least in theory. How much does it actually cost to run a genAI tool, that is hitting the accuracy levels you require, over a relatively mundane contract in order to find top-level information? If token costs drop massively in the years ahead and tech licence costs have been shared out across a major legal business….then what is the cost to the firm per document?

Of course, there is review and there is review. A very deep and thorough review, with lots of redlining, back and forth negotiation, and redrafting by top lawyers is another thing. But, a ‘quick once-over’? It feels like we are already at the ‘pennies on the dollar’ stage for that.

What Is Legal Tech Convergence + Why It Matters — from artificiallawyer.com

In some cases the companies on the convergence path are just getting started and only offer a few additional skills (so far), in other cases, large companies with diverse histories have almost the same multi-skill offering across many areas.

Here are some examples:

  • Callidus
  • vLex
  • Thomson Reuters and LexisNexis
  • BRYTER
  • Harvey
  • Leya
  • …and others
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DSC: Hmmm….might Notebook LM be used frequently in legal work?

On 09/30/2024, in Daniel S. Christian, Google, Legal operations, legal technologies, legislatures / government / legal, platforms, productivity / tips and tricks, tools, United States, by Daniel Christian

From DSC:
Hmmm….might Notebook LM be used frequently in legal work?

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“Google’s NotebookLM: A Game-Changer for Education and Beyond” [Spencer & Potkalitsky] + other items re: AI in our LE’s

On 09/25/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital audio, digital learning, education, education technology, emerging technologies, faculty, future of higher education, game-changing environment, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interaction design, interactivity, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, multimedia, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

FlexOS’ Stay Ahead Edition #43 — from flexos.work

People started discussing what they could do with Notebook LM after Google launched the audio overview, where you can listen to 2 hosts talking in-depth about the documents you upload. Here are what it can do:

  • Summarization: Automatically generate summaries of uploaded documents, highlighting key topics and suggesting relevant questions.
  • Question Answering: Users can ask NotebookLM questions about their uploaded documents, and answers will be provided based on the information contained within them.
  • Idea Generation: NotebookLM can assist with brainstorming and developing new ideas.
  • Source Grounding: A big plus against AI chatbot hallucination, NotebookLM allows users to ground the responses in specific documents they choose.
  • …plus several other items

The posting also lists several ideas to try with NotebookLM such as:

Idea 2: Study Companion

  • Upload all your course materials and ask NotebookLM to turn them into Question-and-Answer format, a glossary, or a study guide.
  • Get a breakdown of the course materials to understand them better.

Google’s NotebookLM: A Game-Changer for Education and Beyond — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
AI Tools: Breaking down Google’s latest AI tool and its implications for education.

“Google’s AI note-taking app NotebookLM can now explain complex topics to you out loud”

With more immersive text-to-video and audio products soon available and the rise of apps like Suno AI, how we “experience” Generative AI is also changing from a chatbot of 2 years ago, to a more multi-modal educational journey. The AI tools on the research and curation side are also starting to reflect these advancements.

Meet Google NotebookLM: 10 things to know for educators — from ditchthattextbook.com by Matt Miller

1. Upload a variety of sources for NotebookLM to use. 
You can use …

  • websites
  • PDF files
  • links to websites
  • any text you’ve copied
  • Google Docs and Slides
  • even Markdown

You can’t link it to YouTube videos, but you can copy/paste the transcript (and maybe type a little context about the YouTube video before pasting the transcript).

2. Ask it to create resources.
3. Create an audio summary.
4. Chat with your sources.
5. Save (almost) everything. 

NotebookLM summarizes my dissertation — from darcynorman.net by D’Arcy Norman, PhD

I finally tried out Google’s newly-announced NotebookLM generative AI application. It provides a set of LLM-powered tools to summarize documents. I fed it my dissertation, and am surprised at how useful the output would be.

The most impressive tool creates a podcast episode, complete with dual hosts in conversation about the document. First – these are AI-generated hosts. Synthetic voices, speaking for synthetic hosts. And holy moly is it effective. Second – although I’d initially thought the conversational summary would be a dumb gimmick, it is surprisingly powerful.

4 Tips for Designing AI-Resistant Assessments — from techlearning.com by Steve Baule and Erin Carter
As AI continues to evolve, instructors must modify their approach by designing meaningful, rigorous assessments.

As instructors work through revising assessments to be resistant to generation by AI tools with little student input, they should consider the following principles:

  • Incorporate personal experiences and local content into assignments
  • Ask students for multi-modal deliverables
  • Assess the developmental benchmarks for assignments and transition assignments further up Bloom’s Taxonomy
  • Consider real-time and oral assignments

Google CEO Sundar Pichai announces $120M fund for global AI education — from techcrunch.com by Anthony Ha

He added that he wants to avoid a global “AI divide” and that Google is creating a $120 million Global AI Opportunity Fund through which it will “make AI education and training available in communities around the world” in partnership with local nonprofits and NGOs.

Educators discuss the state of creativity in an AI world — from gettingsmart.com by Joe & Kristin Merrill, LaKeshia Brooks, Dominique’ Harbour, Erika Sandstrom

Key Points

  • AI allows for a more personalized learning experience, enabling students to explore creative ideas without traditional classroom limitations.
  • The focus of technology integration should be on how the tool is used within lessons, not just the tool itself

Addendum on 9/27/24:

Google’s NotebookLM enhances AI note-taking with YouTube, audio file sources, sharable audio discussions — from techcrunch.com by Jagmeet Singh

Google on Thursday announced new updates to its AI note-taking and research assistant, NotebookLM, allowing users to get summaries of YouTube videos and audio files and even create sharable AI-generated audio discussions…

NotebookLM adds audio and YouTube support, plus easier sharing of Audio Overviews — from blog.google

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“10 Ways I Use LLMs like ChatGPT as a Professor” [Clay] + other items re: AI in our learning ecosystems

On 09/23/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, career development, change, colleges, community colleges, content development, aggregation, repositories, culture, dangers of the status quo, education technology, emerging technologies, experimentation, faculty, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, learning ecosystem, Learning Experience Design, pace of change, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, tools, United States, universities, vendors, workplace, by Daniel Christian

10 Ways I Use LLMs like ChatGPT as a Professor — from automatedteach.com by Graham Clay
ChatGPT-4o, Gemini 1.5 Pro, Claude 3.5 Sonnet, custom GPTs – you name it, I use it. Here’s how…

Excerpt:

  1. To plan lessons (especially activities)
  2. To create course content (especially quizzes)
  3. To tutor my students
  4. To grade faster and give better feedback
  5. To draft grant applications
  6. Plus 5 other items

From Caution to Calcification to Creativity: Reanimating Education with AI’s Frankenstein Potential — from nickpotkalitsky.substack.com by Nick Potkalitsky
A Critical Analysis of AI-Assisted Lesson Planning: Evaluating Efficacy and Pedagogical Implications

Excerpt (emphasis DSC):

As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.

This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.

Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education

NotebookLM and Google’s Multimodal Vision for AI-Powered Learning Tools — from marcwatkins.substack.com by Marc Watkins

A Variety of Use Cases

  • Create an Interactive Syllabus
  • Presentation Deep Dive: Upload Your Slides
  • Note Taking: Turn Your Chalkboard into a Digital Canvas
  • Explore a Reading or Series of Readings
  • Help Navigating Feedback
  • Portfolio Building Blocks

Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform — from er.educause.edu by Fawzi BenMessaoud
The transformative impact of artificial intelligence on educational systems calls for a comprehensive reform to prepare future generations for an AI-integrated world.

The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.

AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.

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Numerous items re: OpenAI o1, Microsoft Copilot, Google’s Notebook LM, and AI in general

On 09/17/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, education technology, emerging technologies, Google, innovation, Microsoft, Open AI, platforms, productivity / tips and tricks, skills, tools, United States, by Daniel Christian

“Who to follow in AI” in 2024? — from ai-supremacy.com by Michael Spencer
Part III – #35-55 – I combed the internet, I found the best sources of AI insights, education and articles. LinkedIn | Newsletters | X | YouTube | Substack | Threads | Podcasts

This list features both some of the best Newsletters on AI and people who make LinkedIn posts about AI papers, advances and breakthroughs. In today’s article we’ll be meeting the first 19-34, in a list of 180+.

Newsletter Writers
YouTubers
Engineers
Researchers who write
Technologists who are Creators
AI Educators
AI Evangelists of various kinds
Futurism writers and authors

I have been sharing the list in reverse chronological order on LinkedIn here.

Inside Google’s 7-Year Mission to Give AI a Robot Body — from wired.com by Hans Peter Brondmo
As the head of Alphabet’s AI-powered robotics moonshot, I came to believe many things. For one, robots can’t come soon enough. For another, they shouldn’t look like us.

Learning to Reason with LLMs — from openai.com
We are introducing OpenAI o1, a new large language model trained with reinforcement learning to perform complex reasoning. o1 thinks before it answers—it can produce a long internal chain of thought before responding to the user.

Items re: Microsoft Copilot:

Also see this next video re: Copilot Pages:

Sal Khan on the critical human skills for an AI age — from time.com by Kevin J. Delaney

As a preview of the upcoming Summit interview, here are Khan’s views on two critical questions, edited for space and clarity:

  1. What are the enduring human work skills in a world with ever-advancing AI? Some people say students should study liberal arts. Others say deep domain expertise is the key to remaining professionally relevant. Others say you need to have the skills of a manager to be able to delegate to AI. What do you think are the skills or competencies that ensure continued relevance professionally, employability, etc.?
  2. A lot of organizations are thinking about skills-based approaches to their talent. It involves questions like, ‘Does someone know how to do this thing or not?’ And what are the ways in which they can learn it and have some accredited way to know they actually have done it? That is one of the ways in which people use Khan Academy. Do you have a view of skills-based approaches within workplaces, and any thoughts on how AI tutors and training fit within that context?
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“Introducing OpenAI o1” [OpenAI] + other items re: AI in general

On 09/12/2024, in Adobe, art, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, creativity, digital audio, digital learning, digital storytelling, digital video, education, education technology, emerging technologies, experimentation, Google, graphics, multimedia, new media literacies, online media, Open AI, physics, platforms, productivity / tips and tricks, tools, training / L&D, trends, vendors, by Daniel Christian

Introducing OpenAI o1 – from openai.com

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

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

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

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

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

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

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

But where can this actually be used?

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

Heather goes on to mention applications in:

  • Creative Industries
  • Entertainment and Media
  • Education and Training

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

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

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

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

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

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

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“When A.I.’s Output Is a Threat to A.I. Itself” [Bhatia], xAI introduces most powerful AI training system in the world +other items re: AI

On 09/03/2024, in Amazon, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, business, cloud-based computing / apps / other cloud-related, corporate / business world, data related items, design, emerging technologies, Google, graphics, learning agents, legislatures / government / legal, Open AI, platforms, productivity / tips and tricks, the downsides of how people use tech, tools, United States, universities, vendors, videoconferencing, by Daniel Christian

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.

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