A while back, I wrote about some of my thoughts on generative AI around the copyright issues. Not much has changed since then, but a new article (Academic authors ‘shocked’ after Taylor & Francis sells access to their research to Microsoft AI) is definitely stirring up all sorts of concerns by academic authors. The basics of that article are that Taylor & Francis sold access to authors’ research to Microsoft for AI development without informing the authors, sparking significant concern among academics and the Society of Authors about transparency, consent, and the implications for authors’ rights and future earnings.
The stir can be seen as both valid and redundant. Two folks’ points stick out to me in this regard.
What aspects of teaching should remain human? — from hechingerreport.org by Chris Berdik Even techno optimists hesitate to say teaching is best left to the bots, but there’s a debate about where to draw the line
ATLANTA — Science teacher Daniel Thompson circulated among his sixth graders at Ron Clark Academy on a recent spring morning, spot checking their work and leading them into discussions about the day’s lessons on weather and water. He had a helper: As Thompson paced around the class, peppering them with questions, he frequently turned to a voice-activated AI to summon apps and educational videos onto large-screen smartboards.
When a student asked, “Are there any animals that don’t need water?” Thompson put the question to the AI. Within seconds, an illustrated blurb about kangaroo rats appeared before the class.
Nitta said there’s something “deeply profound” about human communication that allows flesh-and-blood teachers to quickly spot and address things like confusion and flagging interest in real time.
While the traditional model of education is entrenched, emerging technologies like deep learning promise to shake its foundations and usher in an age of personalized, adaptive, and egalitarian education. It is expected to have a significant impact across higher education in several key ways.
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…deep learning introduces adaptivity into the learning process. Unlike a typical lecture, deep learning systems can observe student performance in real-time. Confusion over a concept triggers instant changes to instructional tactics. Misconceptions are identified early and remediated quickly. Students stay in their zone of proximal development, constantly challenged but never overwhelmed. This adaptivity prevents frustration and stagnation.
InstructureCon 24 Conference Notes — from onedtech.philhillaa.com by Glenda Morgan Another solid conference from the market leader, even with unclear roadmap
The new stuff: AI
Instructure rolled out multiple updates and improvements – more than last year. These included many AI-based or focused tools and services as well as some functional improvements. I’ll describe the AI features first.
Sal Khan was a surprise visitor to the keynote stage to announce the September availability of the full suite of AI-enabled Khanmigo Teacher Tools for Canvas users. The suite includes 20 tools, such as tools to generate lesson plans and quiz questions and write letters of recommendation. Next year, they plan to roll out tools for students themselves to use.
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Other AI-based features include.
Discussion tool summaries and AI-generated responses…
Picking the right projector for school can be a tough decision as the types and prices range pretty widely. From affordable options to professional grade pricing, there are many choices. The problem is that the performance is also hugely varied. This guide aims to be the solution by offering all you need to know about buying the right projector for school where you are.
Luke covers a variety of topics including:
Types of projectors
Screen quality
Light type
Connectivity
Pricing
From DSC: I posted this because Luke covered a variety of topics — and if you’re set on going with a projector, this is a solid article. But I hesitated to post this, as I’m not sure of the place that projectors will have in the future of our learning spaces. With voice-enabled apps and appliances continuing to be more prevalent — along with the presence of AI-based human-computer interactions and intelligent systems — will projectors be the way to go? Will enhanced interactive whiteboards be the way to go? Will there be new types of displays? I’m not sure. Time will tell.
This episode of the Next Big Idea podcast, host Rufus Griscom and Bill Gates are joined by Andy Sack and Adam Brotman, co-authors of an exciting new book called “AI First.” Together, they consider AI’s impact on healthcare, education, productivity, and business. They dig into the technology’s risks. And they explore its potential to cure diseases, enhance creativity, and usher in a world of abundance.
Key moments:
00:05 Bill Gates discusses AI’s transformative potential in revolutionizing technology.
02:21 Superintelligence is inevitable and marks a significant advancement in AI technology.
09:23 Future AI may integrate deeply as cognitive assistants in personal and professional life.
14:04 AI’s metacognitive advancements could revolutionize problem-solving capabilities.
21:13 AI’s next frontier lies in developing human-like metacognition for sophisticated problem-solving.
27:59 AI advancements empower both good and malicious intents, posing new security challenges.
28:57 Rapid AI development raises questions about controlling its global application.
33:31 Productivity enhancements from AI can significantly improve efficiency across industries.
35:49 AI’s future applications in consumer and industrial sectors are subjects of ongoing experimentation.
46:10 AI democratization could level the economic playing field, enhancing service quality and reducing costs.
51:46 AI plays a role in mitigating misinformation and bridging societal divides through enhanced understanding.
The team has summarized their primary contributions as follows.
The team has offered the first instance of a simple, scalable oversight technique that greatly assists humans in more thoroughly detecting problems in real-world RLHF data.
Within the ChatGPT and CriticGPT training pools, the team has discovered that critiques produced by CriticGPT catch more inserted bugs and are preferred above those written by human contractors.
Compared to human contractors working alone, this research indicates that teams consisting of critic models and human contractors generate more thorough criticisms. When compared to reviews generated exclusively by models, this partnership lowers the incidence of hallucinations.
This study provides Force Sampling Beam Search (FSBS), an inference-time sampling and scoring technique. This strategy well balances the trade-off between minimizing bogus concerns and discovering genuine faults in LLM-generated critiques.
a16z-backed Character.AI said today that it is now allowing users to talk to AI characters over calls. The feature currently supports multiple languages, including English, Spanish, Portuguese, Russian, Korean, Japanese and Chinese.
The startup tested the calling feature ahead of today’s public launch. During that time, it said that more than 3 million users had made over 20 million calls. The company also noted that calls with AI characters can be useful for practicing language skills, giving mock interviews, or adding them to the gameplay of role-playing games.
Google Translate can come in handy when you’re traveling or communicating with someone who speaks another language, and thanks to a new update, you can now connect with some 614 million more people. Google is adding 110 new languages to its Translate tool using its AI PaLM 2 large language model (LLM), which brings the total of supported languages to nearly 250. This follows the 24 languages added in 2022, including Indigenous languages of the Americas as well as those spoken across Africa and central Asia.
Gen-3 Alpha Text to Video is now available to everyone.
A new frontier for high-fidelity, fast and controllable video generation.
A Guide to the GPT-4o ‘Omni’ Model — from aieducation.substack.com by Claire Zau The closest thing we have to “Her” and what it means for education / workforce
Today, OpenAI introduced its new flagship model, GPT-4o, that delivers more powerful capabilities and real-time voice interactions to its users. The letter “o” in GPT-4o stands for “Omni”, referring to its enhanced multimodal capabilities. While ChatGPT has long offered a voice mode, GPT-4o is a step change in allowing users to interact with an AI assistant that can reason across voice, text, and vision in real-time.
Facilitating interaction between humans and machines (with reduced latency) represents a “small step for machine, giant leap for machine-kind” moment.
Everyone gets access to GPT-4: “the special thing about GPT-4o is it brings GPT-4 level intelligence to everyone, including our free users”, said CTO Mira Murati. Free users will also get access to custom GPTs in the GPT store, Vision and Code Interpreter. ChatGPT Plus and Team users will be able to start using GPT-4o’s text and image capabilities now
ChatGPT launched a desktop macOS app: it’s designed to integrate seamlessly into anything a user is doing on their keyboard. A PC Windows version is also in the works (notable that a Mac version is being released first given the $10B Microsoft relationship)
In a surprise launch, OpenAI dropped GPT-4 Omni, their new leading model. They also made a bunch of paid features in ChatGPT free and announced a new desktop app. Pete breaks down what you should know and what this says about AI.
Hello GPT-4o — from openai.com We’re announcing GPT-4o, our new flagship model that can reason across audio, vision, and text in real time.
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Providing inflection, emotions, and a human-like voice
Understanding what the camera is looking at and integrating it into the AI’s responses
Providing customer service
With GPT-4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT-4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.
This demo is insane.
A student shares their iPad screen with the new ChatGPT + GPT-4o, and the AI speaks with them and helps them learn in *realtime*.
Imagine giving this to every student in the world.
NVIDIA Digital Human Technologies Bring AI Characters to Life
Leading AI Developers Use Suite of NVIDIA Technologies to Create Lifelike Avatars and Dynamic Characters for Everything From Games to Healthcare, Financial Services and Retail Applications
Today is the beginning of our moonshot to solve embodied AGI in the physical world. I’m so excited to announce Project GR00T, our new initiative to create a general-purpose foundation model for humanoid robot learning.
As the FlexOS research study “Generative AI at Work” concluded based on a survey amongst knowledge workers, ChatGPT reigns supreme. … 2. AI Tool Usage is Way Higher Than People Expect – Beating Netflix, Pinterest, Twitch. As measured by data analysis platform Similarweb based on global web traffic tracking, the AI tools in this list generate over 3 billion monthly visits.
With 1.67 billion visits, ChatGPT represents over half of this traffic and is already bigger than Netflix, Microsoft, Pinterest, Twitch, and The New York Times.
Something unusual is happening in America. Demand for electricity, which has stayed largely flat for two decades, has begun to surge.
Over the past year, electric utilities have nearly doubled their forecasts of how much additional power they’ll need by 2028 as they confront an unexpected explosion in the number of data centers, an abrupt resurgence in manufacturing driven by new federal laws, and millions of electric vehicles being plugged in.
The tumult could seem like a distraction from the startup’s seemingly unending march toward AI advancement. But the tension, and the latest debate with Musk, illuminates a central question for OpenAI, along with the tech world at large as it’s increasingly consumed by artificial intelligence: Just how open should an AI company be?
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The meaning of the word “open” in “OpenAI” seems to be a particular sticking point for both sides — something that you might think sounds, on the surface, pretty clear. But actual definitions are both complex and controversial.
In partnership with the National Cancer Institute, or NCI, researchers from the Department of Energy’s Oak Ridge National Laboratory and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
Dave told me that he couldn’t have made Borrowing Time without AI—it’s an expensive project that traditional Hollywood studios would never bankroll. But after Dave’s short went viral, major production houses approached him to make it a full-length movie. I think this is an excellent example of how AI is changing the art of filmmaking, and I came out of this interview convinced that we are on the brink of a new creative age.
We dive deep into the world of AI tools for image and video generation, discussing how aspiring filmmakers can use them to validate their ideas, and potentially even secure funding if they get traction. Dave walks me through how he has integrated AI into his movie-making process, and as we talk, we make a short film featuring Nicolas Cage using a haunted roulette ball to resurrect his dead movie career, live on the show.
But a few applications of machine learning stood out as genuinely helpful or surprising — here are a few examples of AI that might actually do some good.
The whole idea that AI might not be a total red flag occurred to me when I chatted with Whispp at a press event. This small team is working on voicing the voiceless, meaning people who have trouble speaking normally due to a condition or illness.
The Emerging Role of Smart TVs Boothe and Comiskey claim that our TVs will become even smarter and better connected to the web and the internet. Our TVs will become an intelligent center for a variety of applications powered through our smartphone. TVs will be able to direct things like appliances and security cameras. Perhaps even more importantly, our TVs can become e-commerce centers, allowing us to speak with them and conduct business.
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This increased TV capability means that the TV could become a more dominant mode of working and computing for lawyers. As TVs become more integrated with the internet and capable of functioning as communication hubs, they could potentially replace traditional computing devices in legal settings. With features like voice control and pattern recognition, TVs could serve as efficient tools for such things as document preparation and client meetings.
From DSC: Now imagine the power of voice-enabled chatbots and the like. We could be videoconferencing (or holograming) with clients, and be able to access information at the same time. Language translation — like that in the Timekettle product — will be built in.
As we step into 2024, the legal industry continues to be reshaped by technological advancements. This year promises to bring new developments that could revolutionize how legal professionals work and interact with clients. Here are key predictions for legal tech in 2024:
Last Friday was Legaltech Week’s year-end show, in which our panel of journalists and bloggers picked the year’s top stories in legal tech and innovation.
So what were the top stories? Well, if you missed it, no worries. Here’s the video:
Programmable medicines. AI tools for kids. We asked
over 40 partners across a16z to preview one big idea
they believe will drive innovation in 2024.
Narrowly Tailored, Purpose-Built AI In 2024, I predict we’ll see narrower AI solutions. While ChatGPT may be a great general AI assistant, it’s unlikely to “win” for every task. I expect we’ll see an AI platform purpose-built for researchers, a writing generation tool targeted for journalists, and a rendering platform specifically for designers, to give just a few examples.
Over the longer term, I think the products people use on an everyday basis will be tailored to their use cases — whether this is a proprietary underlying model or a special workflow built around it. These companies will have the chance to “own” the data and workflow for a new era of technology; they’ll do this by nailing one category, then expanding. For the initial product, the narrower the better.
— via Olivia Moore, who focuses on marketplace startups
So asks a recent study by two academics from Stanford Law School, David Freeman Engstrom and Nora Freeman Engstrom, on the potential impact of AI on the civil litigation landscape in the US.
It is against this landscape, the study observes, that champions of legal tech have suggested that there is an opportunity for legal tech to “democratise” litigation and put litigation’s “haves” and “have nots” on a more equal footing, by arming smaller firms and sole practitioners with the tools necessary to do battle against their better resourced opponents, and cutting the cost of legal services, putting lawyers within reach of a wider swathe of people.
But is this a real opportunity, and will AI be key to its realisation?
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However, while AI may reduce the justice gap between the “haves” and “have-nots” of litigation, it could also exacerbate existing inequalities.
From DSC: While this article approaches things from the lawyer’s viewpoint, I’d like to see this question and the use of AI from the common man’s/woman’s viewpoint. Why? In order to provide FAR GREATER access to justice (#A2J) for those who can’t afford a lawyer as they head into the civil law courtrooms.
Should I take my case to court? Do I have a chance to win this case? If so, how?
What forms do I need to complete if I’m going to go to court?
When and how do I address the judge?
What does my landlord have to do?
How do I prevent myself from falling into a debt-collection mess and/or what options do I have to get out of this mess?
Are there any lawyers in my area who would take my case on a pro bono basis?
…and judges and lawyers — as well as former litigants — could add many more questions (and answers) to this list
Bottom line: It is my hope that technology can help increase access to justice.
A number of products are already under development, or have been launched. One example is a project that Norton Rose Fulbright is working on, together with not-for-profit legal service Justice Connect. The scope is to develop an automated natural language processing AI model that seeks to interpret the ‘everyday’ language used by clients in order to identify the client’s legal issues and correctly diagnose their legal problem. This tool is aimed at addressing the struggles that individuals often face in deciphering legal jargon and understanding the nature of their legal issue and the type of lawyer, or legal support, they need to resolve that problem.
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