Mary Meeker has written her first report in over four years, focused on the relationship between artificial intelligence and U.S. higher education.
Why it matters: Meeker’s annual “Internet Trends” reports were among Silicon Valley’s most cited and consumed documents.
Each one dug deep into the new tech economy, with hundreds of pages of slides. The last one was published in 2019.
Meeker’s new effort is a shorter attempt (16 pages!) at reconciling tech’s brave new world and America’s economic vitality, with higher ed as the connective tissue.
Actions taken in the next five years will be consequential. It’s important for higher education to take a leadership role, in combination with industry and government. The ramp in artificial intelligence – which leverages the history of learning for learning – affects all forms of learning, teaching, understanding, and decision making. This should be the best of times…
Our first-pass observations on these topics follow. We begin with an overview, followed by thoughts on the unprecedented ramp in AI usage and the magnitude of investment in AI from America’s leading global technology companies. Then we explore ways that this rapidly changing AI landscape may drive transformations in higher education. We hope these add to the discussion.
AI & Universities – Will Masters of Learning Master New Learnings?
In a time of rapid technological change led by American companies, American universities must determine how best to optimize for the future. Many institutions have work to do to meet these changes in demand, per the Burning Glass Institute. As the AI challenge looms, they will need thoughtful plans that balance their rich traditions and research history with the needs of a rapidly evolving marketplace supercharged by innovation. Keeping an eye on the output and trends in various AI skunkworks, such as the team at AI Acceleration at Arizona State, may help universities determine the products and software tools that could transform the educational experience.
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.
Introducing Gen-3 Alpha: Runway’s new base model for video generation.
Gen-3 Alpha can create highly detailed videos with complex scene changes, a wide range of cinematic choices, and detailed art directions.https://t.co/YQNE3eqoWf
Introducing GEN-3 Alpha – The first of a series of new models built by creatives for creatives. Video generated with @runwayml‘s new Text-2-Video model.
Learning personalisation. LinkedIn continues to be bullish on its video-based learning platform, and it appears to have found a strong current among users who need to skill up in AI. Cohen said that traffic for AI-related courses — which include modules on technical skills as well as non-technical ones such as basic introductions to generative AI — has increased by 160% over last year.
You can be sure that LinkedIn is pushing its search algorithms to tap into the interest, but it’s also boosting its content with AI in another way.
For Premium subscribers, it is piloting what it describes as “expert advice, powered by AI.” Tapping into expertise from well-known instructors such as Alicia Reece, Anil Gupta, Dr. Gemma Leigh Roberts and Lisa Gates, LinkedIn says its AI-powered coaches will deliver responses personalized to users, as a “starting point.”
These will, in turn, also appear as personalized coaches that a user can tap while watching a LinkedIn Learning course.
Personalized learning for everyone: Whether you’re looking to change or not, the skills required in the workplace are expected to change by 68% by 2030.
Expert advice, powered by AI: We’re beginning to pilot the ability to get personalized practical advice instantly from industry leading business leaders and coaches on LinkedIn Learning, all powered by AI. The responses you’ll receive are trained by experts and represent a blend of insights that are personalized to each learner’s unique needs. While human professional coaches remain invaluable, these tools provide a great starting point.
Personalized coaching, powered by AI, when watching a LinkedIn course: As learners —including all Premium subscribers — watch our new courses, they can now simply ask for summaries of content, clarify certain topics, or get examples and other real-time insights, e.g. “Can you simplify this concept?” or “How does this apply to me?”
Dream Machine is an AI model that makes high quality, realistic videos fast from text and images.
It is a highly scalable and efficient transformer model trained directly on videos making it capable of generating physically accurate, consistent and eventful shots. Dream Machine is our first step towards building a universal imagination engine and it is available to everyone now!
Luma AI just dropped a Sora-like AI video generator called Dream Machine.
But unlike Sora or KLING, it’s completely open access to the public.
Microsoft is partnering with Khan Academy in a multifaceted deal to demonstrate how AI can transform the way we learn. The cornerstone of today’s announcement centers on Khan Academy’s Khanmigo AI agent. Microsoft says it will migrate the bot to its Azure OpenAI Service, enabling the nonprofit educational organization to provide all U.S. K-12 educators free access to Khanmigo.
In addition, Microsoft plans to use its Phi-3 model to help Khan Academy improve math tutoring and collaborate to generate more high-quality learning content while making more courses available within Microsoft Copilot and Microsoft Teams for Education.
One in three American teachers have used artificial intelligence tools in their teaching at least once, with English and social studies teachers leading the way, according to a RAND Corporation survey released last month. While the new technology isn’t yet transforming how kids learn, both teachers and district leaders expect that it will become an increasingly common feature of school life.
When ChatGPT emerged a year and half ago, many professors immediately worried that their students would use it as a substitute for doing their own written assignments — that they’d click a button on a chatbot instead of doing the thinking involved in responding to an essay prompt themselves.
But two English professors at Carnegie Mellon University had a different first reaction: They saw in this new technology a way to show students how to improve their writing skills.
“They start really polishing way too early,” Kaufer says. “And so what we’re trying to do is with AI, now you have a tool to rapidly prototype your language when you are prototyping the quality of your thinking.”
He says the concept is based on writing research from the 1980s that shows that experienced writers spend about 80 percent of their early writing time thinking about whole-text plans and organization and not about sentences.
On Building AI Models for Education — from aieducation.substack.com by Claire Zau Google’s LearnLM, Khan Academy/MSFT’s Phi-3 Models, and OpenAI’s ChatGPT Edu
This piece primarily breaks down how Google’s LearnLM was built, and takes a quick look at Microsoft/Khan Academy’s Phi-3 and OpenAI’s ChatGPT Edu as alternative approaches to building an “education model” (not necessarily a new model in the latter case, but we’ll explain). Thanks to the public release of their 86-page research paper, we have the most comprehensive view into LearnLM. Our understanding of Microsoft/Khan Academy small language models and ChatGPT Edu is limited to the information provided through announcements, leaving us with less “under the hood” visibility into their development.
Answer AI is among a handful of popular apps that are leveraging the advent of ChatGPT and other large language models to help students with everything from writing history papers to solving physics problems. Of the top 20 education apps in the U.S. App Store, five are AI agents that help students with their school assignments, including Answer AI, according to data from Data.ai on May 21.
If your school (district) or university has not yet made significant efforts to think about how you will prepare your students for a World of AI, I suggest the following steps:
July 24 – Administrator PD & AI Guidance In July, administrators should receive professional development on AI, if they haven’t already. This should include…
August 24 –Professional Development for Teachers and Staff…
Fall 24 — Parents; Co-curricular; Classroom experiments…
December 24 — Revision to Policy…
New ChatGPT Version Aiming at Higher Ed — from insidehighered.com by Lauren Coffey ChatGPT Edu, emerging after initial partnerships with several universities, is prompting both cautious optimism and worries.
OpenAI unveiled a new version of ChatGPT focused on universities on Thursday, building on work with a handful of higher education institutions that partnered with the tech giant.
The ChatGPT Edu product, expected to start rolling out this summer, is a platform for institutions intended to give students free access. OpenAI said the artificial intelligence (AI) toolset could be used for an array of education applications, including tutoring, writing grant applications and reviewing résumés.
The Rundown: Nvidia CEO Jensen Huang just announced a series of new AI announcements during a keynote at the Computex conference, including next-gen ‘Rubin’ chips, a new AI gaming assistant, and AI tools for creating lifelike avatars.
The details:
Nvidia’s ‘Rubin’ platform is slated for 2026, with the ‘Rubin Ultra’ coming a year later as part of what Huang called a “new industrial revolution”.
Nvidia also showed off Project G-Assist, an AI gaming assistant that provides context-aware help and personalized responses for PC games.
The company also introduced ACE, a suite of AI services that simplify the creation of digital avatars for applications like customer service and healthcare.
‘Accelerate Everything,’ NVIDIA CEO Says Ahead of COMPUTEX — from blogs.nvidia.com by Brian Caulfield Emphasizing cost reduction and sustainability, Huang detailed new semiconductors, software and systems to power data centers, factories, consumer devices, robots and more, driving a new industrial revolution.
Nvidia Unveils Next-Generation Rubin AI Platform for 2026 — from bloomberg.com by Ian King and Vlad Savov CEO Jensen Huang reveals plans for annual upgrade cycle | Company details plans for Blackwell Ultra and subsequent chips Nvidia Corp. Chief Executive Officer Jensen Huang said the company plans to upgrade its AI accelerators every year, announcing a Blackwell Ultra chip for 2025 and a next-generation platform in development called Rubin for 2026.
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?
…
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.
DC: Hmmm…given that the militaries of the world have been integrating AI into their arsenals (likely for years), this kind of thing is a bit disturbing for me. Autonomous/self-correcting missiles, robotic tanks, drones, and more…here we come. Ouch.https://t.co/Qljl1U9m9S
— Daniel Christian (he/him/his) (@dchristian5) March 13, 2024
The early vibrations of AI have already been shaking the newsroom. One downside of the new technology surfaced at CNET and Sports Illustrated, where editors let AI run amok with disastrous results. Elsewhere in news media, AI is already writing headlines, managing paywalls to increase subscriptions, performing transcriptions, turning stories in audio feeds, discovering emerging stories, fact checking, copy editing and more.
Felix M. Simon, a doctoral candidate at Oxford, recently published a white paper about AI’s journalistic future that eclipses many early studies. Swinging a bat from a crouch that is neither doomer nor Utopian, Simon heralds both the downsides and promise of AI’s introduction into the newsroom and the publisher’s suite.
Unlike earlier technological revolutions, AI is poised to change the business at every level. It will become — if it already isn’t — the beginning of most story assignments and will become, for some, the new assignment editor. Used effectively, it promises to make news more accurate and timely. Used frivolously, it will spawn an ocean of spam. Wherever the production and distribution of news can be automated or made “smarter,” AI will surely step up. But the future has not yet been written, Simon counsels. AI in the newsroom will be only as bad or good as its developers and users make it.
We proposed EMO, an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input video.
New experimental work from Adobe Research is set to change how people create and edit custom audio and music. An early-stage generative AI music generation and editing tool, Project Music GenAI Control allows creators to generate music from text prompts, and then have fine-grained control to edit that audio for their precise needs.
“With Project Music GenAI Control, generative AI becomes your co-creator. It helps people craft music for their projects, whether they’re broadcasters, or podcasters, or anyone else who needs audio that’s just the right mood, tone, and length,” says Nicholas Bryan, Senior Research Scientist at Adobe Research and one of the creators of the technologies.
There’s a lot going on in the world of generative AI, but maybe the biggest is the increasing number of copyright lawsuits being filed against AI companies like OpenAI and Stability AI. So for this episode, we brought on Verge features editor Sarah Jeong, who’s a former lawyer just like me, and we’re going to talk about those cases and the main defense the AI companies are relying on in those copyright cases: an idea called fair use.
The FCC’s war on robocalls has gained a new weapon in its arsenal with the declaration of AI-generated voices as “artificial” and therefore definitely against the law when used in automated calling scams. It may not stop the flood of fake Joe Bidens that will almost certainly trouble our phones this election season, but it won’t hurt, either.
The new rule, contemplated for months and telegraphed last week, isn’t actually a new rule — the FCC can’t just invent them with no due process. Robocalls are just a new term for something largely already prohibited under the Telephone Consumer Protection Act: artificial and pre-recorded messages being sent out willy-nilly to every number in the phone book (something that still existed when they drafted the law).
EIEIO…Chips Ahoy!— from dashmedia.co by Michael Moe, Brent Peus, and Owen Ritz
Here Come the AI Worms — from wired.com by Matt Burgess Security researchers created an AI worm in a test environment that can automatically spread between generative AI agents—potentially stealing data and sending spam emails along the way.
Now, in a demonstration of the risks of connected, autonomous AI ecosystems, a group of researchers have created one of what they claim are the first generative AI worms—which can spread from one system to another, potentially stealing data or deploying malware in the process. “It basically means that now you have the ability to conduct or to perform a new kind of cyberattack that hasn’t been seen before,” says Ben Nassi, a Cornell Tech researcher behind the research.
World’s largest projection mapping snags Guinness World Record — from inavateonthenet.net A nightly projection mapping display at the Tokyo metropolitan government headquarters has been recognised by Guinness World Records as the largest in the world.
The scammers used digitally recreated versions of an international company’s Chief Financial Officer and other employees to order $25 million in money transfers during a video conference call containing just one real person.
The victim, an employee at the Hong Kong branch of an unnamed multinational firm, was duped into taking part in a video conference call in which they were the only real person – the rest of the group were fake representations of real people, writes SCMP.
As we’ve seen in previous incidents where deepfakes were used to recreate someone without their permission, the scammers utilized publicly available video and audio footage to create these digital versions.
Since we launched Bard last year, people all over the world have used it to collaborate with AI in a completely new way — to prepare for job interviews, debug code, brainstorm new business ideas or, as we announced last week, create captivating images.
Our mission with Bard has always been to give you direct access to our AI models, and Gemini represents our most capable family of models. To reflect this, Bard will now simply be known as Gemini.
A new way to discover places with generative AI in Maps— from blog.google by Miriam Daniel; via AI Valley Here’s a look at how we’re bringing generative AI to Maps — rolling out this week to select Local Guides in the U.S.
Today, we’re introducing a new way to discover places with generative AI to help you do just that — no matter how specific, niche or broad your needs might be. Simply say what you’re looking for and our large-language models (LLMs) will analyze Maps’ detailed information about more than 250 million places and trusted insights from our community of over 300 million contributors to quickly make suggestions for where to go.
Starting in the U.S., this early access experiment launches this week to select Local Guides, who are some of the most active and passionate members of the Maps community. Their insights and valuable feedback will help us shape this feature so we can bring it to everyone over time.
Google Prepares for a Future Where Search Isn’t King — from wired.com by Lauren Goode CEO Sundar Pichai tells WIRED that Google’s new, more powerful Gemini chatbot is an experiment in offering users a way to get things done without a search engine. It’s also a direct shot at ChatGPT.
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.
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