Smart(er) Glasses: Introducing New Ray-Ban | Meta Styles + Expanding Access to Meta AI with Vision — from meta.com

  • Share Your View on a Video Call
  • Meta AI Makes Your Smart Glasses Smarter
  • All In On AI-Powered Hardware

New Ray-Ban | Meta Smart Glasses Styles and Meta AI Updates — from about.fb.com

Takeaways

  • We’re expanding the Ray-Ban Meta smart glasses collection with new styles.
  • We’re adding video calling with WhatsApp and Messenger to share your view on a video call.
  • We’re rolling out Meta AI with Vision, so you can ask your glasses about what you’re seeing and get helpful information — completely hands-free.

 

Forbes 2024 AI 50 List: Top Artificial Intelligence Startups  — from forbes.com by Kenrick Cai

The artificial intelligence sector has never been more competitive. Forbes received some 1,900 submissions this year, more than double last year’s count. Applicants do not pay a fee to be considered and are judged for their business promise and technical usage of AI through a quantitative algorithm and qualitative judging panels. Companies are encouraged to share data on diversity, and our list aims to promote a more equitable startup ecosystem. But disparities remain sharp in the industry. Only 12 companies have women cofounders, five of whom serve as CEO, the same count as last year. For more, see our full package of coverage, including a detailed explanation of the list methodology, videos and analyses on trends in AI.


Adobe Previews Breakthrough AI Innovations to Advance Professional Video Workflows Within Adobe Premiere Pro — from news.adobe.com

  • New Generative AI video tools coming to Premiere Pro this year will streamline workflows and unlock new creative possibilities, from extending a shot to adding or removing objects in a scene
  • Adobe is developing a video model for Firefly, which will power video and audio editing workflows in Premiere Pro and enable anyone to create and ideate
    Adobe previews early explorations of bringing third-party generative AI models from OpenAI, Pika Labs and Runway directly into Premiere Pro, making it easy for customers to draw on the strengths of different models within the powerful workflows they use every day
  • AI-powered audio workflows in Premiere Pro are now generally available, making audio editing faster, easier and more intuitive

Also relevant see:




 

AI for the physical world — from superhuman.ai by Zain Kahn

Excerpt: (emphasis DSC)

A new company called Archetype is trying to tackle that problem: It wants to make AI useful for more than just interacting with and understanding the digital realm. The startup just unveiled Newton — “the first foundation model that understands the physical world.”

What’s it for?
A warehouse or factory might have 100 different sensors that have to be analyzed separately to figure out whether the entire system is working as intended. Newton can understand and interpret all of the sensors at the same time, giving a better overview of how everything’s working together. Another benefit: You can ask Newton questions in plain English without needing much technical expertise.

How does it work?

  • Newton collects data from radar, motion sensors, and chemical and environmental trackers
  • It uses an LLM to combine each of those data streams into a cohesive package
  • It translates that data into text, visualizations, or code so it’s easy to understand

Apple’s $25-50 million Shutterstock deal highlights fierce competition for AI training data — from venturebeat.com by Michael Nuñez; via Tom Barrett’s Prompcraft e-newsletter

Apple has entered into a significant agreement with stock photography provider Shutterstock to license millions of images for training its artificial intelligence models. According to a Reuters report, the deal is estimated to be worth between $25 million and $50 million, placing Apple among several tech giants racing to secure vast troves of data to power their AI systems.


 

 

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

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

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

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


Speaking of AI and our learning ecosystems, also see:

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

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

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

 

Corporate Learning Is Boring — But It Doesn’t Have to Be — from hbr.org by Duncan Wardle; via GSV

Summary:
Most corporate learnings aren’t cutting it. Almost 60% of employees say they’re interested in upskilling and training, but 57% of workers also say they’re already pursuing training outside of work. The author, the former Head of Innovation and Creativity at Disney, argues that creativity is the missing piece to make upskilling engaging and effective. From his experience, he shares four strategies to unlock creativity in trainings: 1) Encourage “What if?”, 2) respond “How else?” to challenges, 3) give people time to think by encouraging playfulness, and 4) make training a game.

 

[Report] The Top 100 AI for Work – April 2024 — from flexos.work; with thanks to Daan van Rossum for this resource
AI is helping us work up to 41% more effectively, according to recent Bain research. We review the platforms to consider for ourselves and our teams.

Following our AI Top 150, we spent the past few weeks analyzing data on the top AI platforms for work. This report shares key insights, including the AI tools you should consider adopting to work smarter, not harder.

While there is understandable concern about AI in the work context, the platforms in this list paint a different picture. It shows a future of work where people can do what humans are best suited for while offloading repetitive, digital tasks to AI.

This will fuel the notion that it’s not AI that takes your job but a supercharged human with an army of AI tools and agents. This should be a call to action for every working person and business leader reading this.

 

Say Goodbye to Antiquated Performance Reviews — from td.org by Magdalena Nowicka Mook

Excerpt (emphasis DSC):

Most leaders understand the value of investing in an onboarding process for orientation, productivity, and retention, but few associate onboarding with strong performance over the employee’s full tenure with the organization. By contrast, everboarding is a newer approach that prioritizes ongoing learning and development rather than only an initial commitment. Insights from Deloitte indicate organizations that establish an ongoing learning culture are 52 percent more productive with engagement and achieve retention rates 30–50 percent higher than those that don’t.

When implemented effectively, everboarding embraces proven elements of a coaching culture that establish an ongoing commitment to skill development, deepens understanding of the organization, and supports real-time feedback to prevent stagnancy in high-potential employees brought in through strong hiring practices.

 

Nvidia’s AI boom is only getting started. Just ask CEO Jensen Huang — from fastcompany.com by Harry McCracken
Nvidia’s chips sparked the AI revolution. Now it’s in the business of putting the technology to work in an array of industries.

Nvidia is No. 1 on Fast Company’s list of the World’s 50 Most Innovative Companies of 2024. Explore the full list of companies that are reshaping industries and culture.

Nvidia isn’t just in the business of providing ever-more-powerful computing hardware and letting everybody else figure out what to do with it. Across an array of industries, the company’s technologies, platforms, and partnerships are doing much of the heavy lifting of putting AI to work. In a single week in January 2024, for instance, Nvidia reported that it had begun beta testing its drug discovery platform, demoed software that lets video game characters speak unscripted dialogue, announced deals with four Chinese EV manufacturers that will incorporate Nvidia technology in their vehicles, and unveiled a retail-industry partnership aimed at foiling organized shoplifting.


Johnson & Johnson MedTech Works With NVIDIA to Broaden AI’s Reach in Surgery — from blogs.nvidia.com by David Niewolny

AI — already used to connect, analyze and offer predictions based on operating room data — will be critical to the future of surgery, boosting operating room efficiency and clinical decision-making.

That’s why NVIDIA is working with Johnson & Johnson MedTech to test new AI capabilities for the company’s connected digital ecosystem for surgery. It aims to enable open innovation and accelerate the delivery of real-time insights at scale to support medical professionals before, during and after procedures.

J&J MedTech is in 80% of the world’s operating rooms and trains more than 140,000 healthcare professionals each year through its education programs.


GE and NVIDIA Join Forces to Accelerate Artificial Intelligence Adoption in Healthcare — from nvidianews.nvidia.com

  • New generation of intelligent medical devices will use world’s most advanced AI platform with the goal of improving patient care
  • GE Healthcare is the first medical device company to use the NVIDIA GPU Cloud
  • New Revolution Frontier CT, powered by NVIDIA, is two times faster for image processing, proving performance acceleration has begun

Nvidia Announces Major Deals With Healthcare Companies — from cheddar.com

At the GTC A.I. conference last week, Nvidia launched nearly two dozen new A.I. powered, health care focused tools and deals with companies Johnson & Johnson and GE Healthcare for surgery and medical imaging. The move into health care space for the A.I. company is an effort that’s been under development for a decade.


Nvidia is now powering AI nurses — from byMaxwell Zeff / Gizmodo;; via Claire Zau
The cheap AI agents offer medical advice to patients over video calls in real-time

 

The $340 Billion Corporate Learning Industry Is Poised For Disruption — from joshbersin.com by Josh Bersin

What if, for example, the corporate learning system knew who you were and you could simply ask it a question and it would generate an answer, a series of resources, and a dynamic set of learning objects for you to consume? In some cases you’ll take the answer and run. In other cases you’ll pour through the content. And in other cases you’ll browse through the course and take the time to learn what you need.

And suppose all this happened in a totally personalized way. So you didn’t see a “standard course” but a special course based on your level of existing knowledge?

This is what AI is going to bring us. And yes, it’s already happening today.

 

GTC March 2024 Keynote with NVIDIA CEO Jensen Huang


Also relevant/see:




 

Conditions that trigger behaviour change — from peoplealchemy.com by Paul Matthews; via Learning Now TV

“Knowing is not enough; we must apply. Willing is not enough; we must do.”

Johann Wolfgang von Goethe

Learning Transfer’s ultimate outcome is behaviour change, so we must understand the conditions that trigger a behaviour to start.

According to Fogg, three specific elements must converge at the same moment for a specific behaviour to occur. Given that learning transfer is only successful when the learner starts behaving in the desired new ways, Fogg’s work is critical to understanding how to generate these new behaviours. The Fogg Behavioural Model [*1] states that B=MAP. That is, a specific behaviour will occur if at the same moment there is sufficient motivation, sufficient ability and sufficient prompt. If the behaviour does not occur, at least one of these three elements is missing or below the threshold required.

The prompt is, in effect, a call to action to do a specific behaviour. The prompt must be ‘loud’ enough for the target person to perceive it and be consciously aware of it. Once aware of a prompt, the target immediately, and largely unconsciously, assesses their ability to carry out the requested behaviour: how difficult would this be, how long will it take, who can help me, and so on. They base this on their perception of the difficulty of the requested behaviour, and their ability, as they see it, to achieve that behaviour.

 

12 Books for Instructional Designers to Read This Year — from theelearningcoach.com by Connie Malamed

Over the past year, many excellent and resourceful books have crossed my desk or Kindle. I’m rounding them up here so you can find a few to expand your horizons. The list below is in alphabetical order by title.

Each book is unique, yet as a collection, they reflect some common themes and trends in Learning and Development: a focus on empathy and emotion, adopting best practices from other fields, using data for greater impact, aligning projects with organizational goals, and developing consultative skills. The authors listed here are optimistic and forward-thinking—they believe change is possible. I hope you enjoy the books.

 


[Report] Generative AI Top 150: The World’s Most Used AI Tools (Feb 2024) — from flexos.work by Daan van Rossum
FlexOS.work surveyed Generative AI platforms to reveal which get used most. While ChatGPT reigns supreme, countless AI platforms are used by millions.

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.

.


Artificial Intelligence Act: MEPs adopt landmark law — from europarl.europa.eu

  • Safeguards on general purpose artificial intelligence
  • Limits on the use of biometric identification systems by law enforcement
  • Bans on social scoring and AI used to manipulate or exploit user vulnerabilities
  • Right of consumers to launch complaints and receive meaningful explanations


The untargeted scraping of facial images from CCTV footage to create facial recognition databases will be banned © Alexander / Adobe Stock


A New Surge in Power Use Is Threatening U.S. Climate Goals — from nytimes.com by Brad Plumer and Nadja Popovich
A boom in data centers and factories is straining electric grids and propping up fossil fuels.

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.


OpenAI and the Fierce AI Industry Debate Over Open Source — from bloomberg.com by Rachel Metz

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.


Researchers develop AI-driven tool for near real-time cancer surveillance — from medicalxpress.com by Mark Alewine; via The Rundown AI
Artificial intelligence has delivered a major win for pathologists and researchers in the fight for improved cancer treatments and diagnoses.

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.


 

Implementing a workplace microlearning strategy — from chieflearningofficer.com by Jared B. Andres

Outside of practicing their learning, there are many challenges to creating and delivering meaningful workplace L&D programs. Participants are busy and may struggle to free up even an hour or two on their calendars. Training could be delivered in the wrong format or at the wrong time. After they attend the training, they may not have an opportunity to apply what they have learned. This can lead to some participants not perceiving training as time well spent. As L&D professionals, our job is to create learning experiences that are meaningful and relevant to people’s day-to-day work.

Adults learn best when training is delivered when it is most relevant to their work, and they can apply what they have learned right away. They must be able to connect what they are learning with the work they are doing and the overarching goals and strategies of the organization.

One possible solution is to implement a microlearning strategy into workplace learning programs. In this article, I will discuss reasons why microlearning can be an effective tool in the L&D toolkit, things to think about when creating a microlearning strategy, cost-effective technology solutions to leverage and ideas to help your microlearning strategy feel exciting and engaging for your participants.

 

 

Edtech Unicorns Are Evolving Rather Than Disrupting — from bloomberg.com by Alex Webb

Consider Coursera Inc., the most prominent survivor of that early edtech hype. It’s now a public company, with a hefty $2.3 billion valuation. Finally, 12 years after it was founded — by, incidentally, another Google veteran in Andrew Ng — it’s set to report its first profit this year, according to analyst estimates. And the enterprise business is considerably more profitable, enjoying a 68% gross margin in 2023, compared to the consumer business’s 53% margin.

Figuring out the right match between training and utility is how several business schools seem to have developed successful online courses — which they are charging top dollar for. They’re in close contact with the sort of large corporations who hire their graduates, giving them a more intimate understanding of what those businesses seek.

Harvard Business School is one example. It made $74 million from online courses in fiscal 2022, the most recent year for which data is available

 
© 2024 | Daniel Christian