“People with disabilities have been wanting to work, eager to work, capable of work,” he explained. “But it wasn’t until this huge change in the way we approached work that the opportunities presented themselves,” he continued.
People with disabilities have been entering the U.S. workforce at record levels over the past three years, the most recent Bureau of Labor Statistics data shows. A recent analysis from LinkedIn’s Economic Graph team suggests an increase in more amenable company policies and working accommodations contributes to this trend.
In May 2024, more than half (54.3%) of LinkedIn members who self-identified as having a disability applied for remote positions. What’s more? Since March 2021, members with disabilities have consistently accounted for a higher share of job applications to remote positions than members who report no disabilities.
Despite the opportunities created by the ADA — and the rise of remote work — many people with disabilities still face barriers in the workforce. LinkedIn’s data scientists and editors parsed the data to identify the most common roles for workers with disabilities, how those with disabilities are progressing in their careers and how employers can continue to support more inclusive hiring.
SALT LAKE CITY, July 25, 2024 /PRNewswire/ — Instructure Holdings, Inc. (NYSE: INST) (“Instructure”), a leading learning ecosystem, today announced that it has entered into a definitive agreement to be acquired by investment funds managed by KKR, a leading global investment firm, for $23.60 per share in an all-cash transaction valued at an enterprise value of approximately $4.8 billion. The per-share purchase price represents a premium of 16 percent over Instructure’s unaffected share price of $20.27 as of May 17, 2024, the last trading day prior to media reports regarding a potential transaction. KKR, with participation from Dragoneer Investment Group, will acquire all outstanding shares, including those shares owned by Instructure’s existing majority owner, Thoma Bravo, a leading software investment firm, which took the company public in 2021.
“Who to follow in AI” in 2024? [Part I] — from ai-supremacy.com by Michael Spencer [some of posting is behind a paywall] #1-20 [of 150] – I combed the internet, I found the best sources of AI insights, education and articles. LinkedIn | Newsletters | X | YouTube | Substack | Threads | Podcasts
AI In Medicine: 3 Future Scenarios From Utopia To Dystopia — from medicalfuturist.com by Andrea Koncz There’s a vast difference between baseless fantasizing and realistic forward planning. Structured methodologies help us learn how to “dream well”.
Key Takeaways
We’re often told that daydreaming and envisioning the future is a waste of time. But this notion is misguided.
We all instinctively plan for the future in small ways, like organizing a trip or preparing for a dinner party. This same principle can be applied to larger-scale issues, and smart planning does bring better results.
We show you a method that allows us to think “well” about the future on a larger scale so that it better meets our needs.
Latest Illustrator and Photoshop releases accelerate creative workflows, save pros time and empower designers to realize their visions faster
New Firefly-enabled features like Generative Shape Fill in Illustrator along with the Dimension Tool, Mockup, Text to Pattern, the Contextual Taskbar and performance enhancement tools accelerate productivity and free up time so creative pros can dive deeper into the parts of their work they love
Photoshop introduces all-new Selection Brush Tool and the general availability of Generate Image, Adjustment Brush Tool and other workflow enhancements empowering creators to make complex edits and unique designs .
Zoom in: Nike used genAI for ideation, including using a variety of prompts to produce images with different textures, materials and color to kick off the design process.
What they’re saying: “It’s a new way for us to work,” Nike lead footwear designer Juliana Sagat told Axios during a media tour of the showcase on Tuesday. .
Major companies are moving at high speed to capture the promises of artificial intelligence in healthcare while doctors and experts attempt to integrate the technology safely into patient care.
“Healthcare is probably the most impactful utility of generative AI that there will be,” Kimberly Powell, vice president of healthcare at AI hardware giant Nvidia (NVDA), which has partnered with Roche’s Genentech (RHHBY) to enhance drug discovery in the pharmaceutical industry, among other investments in healthcare companies, declared at the company’s AI Summit in June.
Mistral reignites this week’s LLM rivalry with Large 2 (source) — from superhuman.ai
Today, we are announcing Mistral Large 2, the new generation of our flagship model. Compared to its predecessor, Mistral Large 2 is significantly more capable in code generation, mathematics, and reasoning. It also provides a much stronger multilingual support, and advanced function calling capabilities.
Meta releases the biggest and best open-source AI model yet — from theverge.com by Alex Heath Llama 3.1 outperforms OpenAI and other rivals on certain benchmarks. Now, Mark Zuckerberg expects Meta’s AI assistant to surpass ChatGPT’s usage in the coming months.
Back in April, Meta teased that it was working on a first for the AI industry: an open-source model with performance that matched the best private models from companies like OpenAI.
Today, that model has arrived. Meta is releasing Llama 3.1, the largest-ever open-source AI model, which the company claims outperforms GPT-4o and Anthropic’s Claude 3.5 Sonnet on several benchmarks. It’s also making the Llama-based Meta AI assistant available in more countries and languages while adding a feature that can generate images based on someone’s specific likeness. CEO Mark Zuckerberg now predicts that Meta AI will be the most widely used assistant by the end of this year, surpassing ChatGPT.
4 ways to boost ChatGPT — from wondertools.substack.com by Jeremy Caplan & The PyCoach Simple tactics for getting useful responses
To help you make the most of ChatGPT, I’ve invited & edited today’s guest post from the author of a smart AI newsletter called The Artificial Corner. I appreciate how Frank Andrade pushes ChatGPT to produce better results with four simple, clever tactics. He offers practical examples to help us all use AI more effectively.
… Frank Andrade: Most of us fail to make the most of ChatGPT.
We omit examples in our prompts.
We fail to assign roles to ChatGPT to guide its behavior.
We let ChatGPT guess instead of providing it with clear guidance.
If you rely on vague prompts, learning how to create high-quality instructions will get you better results. It’s a skill often referred to as prompt engineering. Here are several techniques to get you to the next level.
The race to deploy GenAI in the legal sector— from sifted.eu by Kai Nicol-Schwarz LegalFly’s €15m Series A is the latest in a string of raises for European GenAI legaltech startups
Speak to any lawyer and you’ll soon discover that the job is a far cry from the fevered excitement of a courtroom drama. Behind the scenes, there’s an endless amount of laborious and typically manual tasks like drafting, reviewing and negotiating contracts and other legal documents that have to be done manually daily.
It was this realisation that led four product managers at dating app giant Tinder, frustrated by what they saw as a lack of AI adoption at the company, to jump ship and found Belgium-based LegalFly last year. The startup is building a generative AI copilot for lawyers which eventually, it says, will be able to automate entire workflows in the legal profession.
“We were looking at what GenAI was good at, which is synthesising data and generating content,” says founder and CEO Ruben Miessen. “What industry works like that? Law, and it does it all in a very manual way.”
“The legal industry is a global behemoth that’s seen minimal innovation since the advent of Microsoft Word in the 90s,” says Carina Namih, partner at Plural. “GenAI — especially with a human in the loop to keep accuracy high — is ideally suited to drafting, editing and negotiating legal documents.”
CHICAGO– July 18 – Relativity, a global legal technology company, today announced it is integrating with OpenAI’s ChatGPT Enterprise Compliance API. The integration adds ChatGPT Enterprise as a Collect in RelativityOne data source, allowing users to seamlessly collect and process human-to-AI conversational data.
“The future around human and AI interaction is changing rapidly, calling for innovative legal data management solutions to include novel data sources, such as conversations with AI agents,” said Chris Brown, Chief Product Officer at Relativity. “In answering that call, we are committed to equipping our community with the tools they need to traverse the evolving future of human-to-AI conversational data and putting users in control of this new data landscape.”
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.
The New Entry-Level Job (and Skill)
In a world where AI can perform entry-level tasks, and employers are prioritizing experienced candidates, how can recent college graduates and job seekers find a job?
AI is the new entry-level skill. As AI permeates every industry, it’s becoming increasingly common for employers to ask candidates how they think about applying AI to their jobs. (We’ve started asking this here at Reach ourselves.) Even if the job is not technical and doesn’t list AI as a skill, candidates would do well to prepare. Journalists, for instance, are warming up to using AI to transcribe interviews and suggest headlines.
So it’s not just AI that may take your entry-level role, but rather the person who knows how to use it. Candidates who are bracing for this technological shift and proactively building their AI literacy and expertise will have a leg up.
Leading school systems are incorporating AI tools such as tutoring, chatbots, and teacher assistants, and promoting AI literacy among teachers and students to adapt to the evolving role of AI in education.
And to understand the value of AI, they need to do R&D. Since AI doesn’t work like traditional software, but more like a person (even though it isn’t one), there is no reason to suspect that the IT department has the best AI prompters, nor that it has any particular insight into the best uses of AI inside an organization. IT certainly plays a role, but the actual use cases will come from workers and managers who find opportunities to use AI to help them with their job. In fact, for large companies, the source of any real advantage in AI will come from the expertise of their employees, which is needed to unlock the expertise latent in AI.
Ilya Sutskever, OpenAI’s co-founder and former chief scientist, is starting a new AI company focused on safety. In a post on Wednesday, Sutskever revealed Safe Superintelligence Inc. (SSI), a startup with “one goal and one product:” creating a safe and powerful AI system.
Ilya Sutskever Has a New Plan for Safe Superintelligence — from bloomberg.com by Ashlee Vance (behind a paywall) OpenAI’s co-founder discloses his plans to continue his work at a new research lab focused on artificial general intelligence.
Ilya Sutskever is kind of a big deal in AI, to put it lightly.
Part of OpenAI’s founding team, Ilya was Chief Data Scientist (read: genius) before being part of the coup that fired Sam Altman.
… Yesterday, Ilya announced that he’s forming a new initiative called Safe Superintelligence.
If AGI = AI that can perform a wide range of tasks at our level, then Superintelligence = an even more advanced AI that surpasses human capabilities in all areas.
As the tech giants compete in a global AI arms race, a frenzy of data center construction is sweeping the country. Some computing campuses require as much energy as a modest-sized city, turning tech firms that promised to lead the way into a clean energy future into some of the world’s most insatiable guzzlers of power. Their projected energy needs are so huge, some worry whether there will be enough electricity to meet them from any source.
Federal officials, AI model operators and cybersecurity companies ran the first joint simulation of a cyberattack involving a critical AI system last week.
Why it matters: Responding to a cyberattack on an AI-enabled system will require a different playbook than the typical hack, participants told Axios.
The big picture: Both Washington and Silicon Valley are attempting to get ahead of the unique cyber threats facing AI companies before they become more prominent.
Immediately after we saw Sora-like videos from KLING, Luma AI’s Dream Machine video results overshadowed them.
…
Dream Machine is a next-generation AI video model that creates high-quality, realistic shots from text instructions and images.
Introducing Gen-3 Alpha — from runwayml.com by Anastasis Germanidis A new frontier for high-fidelity, controllable video generation.
AI-Generated Movies Are Around the Corner — from news.theaiexchange.com by The AI Exchange The future of AI in filmmaking; participate in our AI for Agencies survey
AI-Generated Feature Films Are Around the Corner.
We predict feature-film length AI-generated films are coming by the end of 2025, if not sooner.
AI Policy 101: a Beginners’ Framework — from drphilippahardman.substack.com by Dr. Philippa Hardman How to make a case for AI experimentation & testing in learning & development
The role of learning & development
Given these risks, what can L&D professionals do to ensure generative AI contributes to effective learning? The solution lies in embracing the role of trusted learning advisors, guiding the use of AI tools in a way that prioritizes achieving learning outcomes over only speed. Here are three key steps to achieve this:
1. Playtest and Learn About AI… 2. Set the Direction for AI to Be Learner-Centered…
3. Become Trusted Learning Advisors…
In the last year, AI has become even more intertwined with our education system. More teachers, parents, and students are aware of it and have used it themselves on a regular basis. It is all over our education system today.
While negative views of AI have crept up over the last year, students, teachers, and parents feel very positive about it in general. On balance they see positive uses for the technology in school, especially if they have used it themselves.
Most K-12 teachers, parents, and students don’t think their school is doing much about AI, despite its widespread use. Most say their school has no policy on it, is doing nothing to offer desired teacher training, and isn’t meeting the demand of students who’d like a career in a job that will need AI.
The AI vacuum in school policy means it is currently used “unauthorized,” while instead people want policies that encourage AI. Kids, parents, and teachers are figuring it out on their own/without express permission, whereas all stakeholders would rather have a policy that explicitly encourages AI from a thoughtful foundation.
There is much discourse about the rise and prevalence of AI in education and beyond. These debates often lack the perspectives of key stakeholders – parents, students and teachers.
In 2023, the Walton Family Foundation commissioned the first national survey of teacher and student attitudes toward ChatGPT. The findings showed that educators and students embrace innovation and are optimistic that AI can meaningfully support traditional instruction.
A new survey conducted May 7-15, 2024, showed that knowledge of and support for AI in education is growing among parents, students and teachers. More than 80% of each group says it has had a positive impact on education.
Remember Microsoft’s shiny new AI tool, “Recall”? It’s like your personal time machine, answering questions about your browsing history and laptop activity by taking screenshots every 5 seconds. Sounds cool, right? Well, it gets problematic.
What’s going on here?
Security researchers have found a potential privacy nightmare lurking within this seemingly convenient tool.
What does this mean?
Recall stores all those screenshots in an unencrypted database on your laptop. This means anyone with access to your device could potentially see everything you’ve been doing. Cybersecurity experts are already comparing it to spyware, and one ethical hacker even built a tool called “TotalRecall” (yes, like the movie) that can pull all the information Recall saves. Yikes.
Nvidia reported $6.12 earnings per share and $26 billion of sales for the three-month period ending April 30, shattering mean analyst forecasts of $5.60 and $24.59 billion, according to FactSet.
Nvidia’s profits and revenues skyrocketed by 628% and 268% compared to 2023’s comparable period, respectively.
This was Nvidia’s most profitable and highest sales quarter ever, topping the quarter ending this January’s record $12.3 billion net income and $22.1 billion revenue.
Driving the numerous superlatives for Nvidia’s financial growth over the last year is unsurprisingly its AI-intensive datacenter division, which raked in $22.6 billion of revenue last quarter, a 427% year-over-year increase and a whopping 20 times higher than the $1.1 billion the segment brought in in 2020.
Per ChatPGT today:
NVIDIA is a prominent technology company known for its contributions to various fields, primarily focusing on graphics processing units (GPUs) and artificial intelligence (AI).Here’s an overview of NVIDIA’s main areas of activity:
1. **Graphics Processing Units (GPUs):**
– **Consumer GPUs:** NVIDIA is famous for its GeForce series of GPUs, which are widely used in gaming and personal computing for their high performance and visual capabilities.
– **Professional GPUs:** NVIDIA’s Quadro series is designed for professional applications like 3D modeling, CAD (Computer-Aided Design), and video editing.
2. **Artificial Intelligence (AI) and Machine Learning:**
– NVIDIA GPUs are extensively used in AI research and development. They provide the computational power needed for training deep learning models.
– The company offers specialized hardware for AI, such as the NVIDIA Tesla and A100 GPUs, which are used in data centers and supercomputing environments.
3. **Data Centers:**
– NVIDIA develops high-performance computing solutions for data centers, including GPU-accelerated servers and AI platforms. These products are essential for tasks like big data analytics, scientific simulations, and AI workloads.
4. **Autonomous Vehicles:**
– Through its DRIVE platform, NVIDIA provides hardware and software solutions for developing autonomous vehicles. This includes AI-based systems for perception, navigation, and decision-making.
5. **Edge Computing:**
– NVIDIA’s Jetson platform caters to edge computing, enabling AI-powered devices and applications to process data locally rather than relying on centralized data centers.
6. **Gaming and Entertainment:**
– Beyond GPUs, NVIDIA offers technologies like G-SYNC (for smoother gaming experiences) and NVIDIA GameWorks (a suite of tools for game developers).
7. **Healthcare:**
– NVIDIA’s Clara platform utilizes AI and GPU computing to advance medical imaging, genomics, and other healthcare applications.
8. **Omniverse:**
– NVIDIA Omniverse is a real-time graphics collaboration platform for 3D production pipelines. It’s designed for industries like animation, simulation, and visualization.
9. **Crypto Mining:**
– NVIDIA GPUs are also popular in the cryptocurrency mining community, although the company has developed specific products like the NVIDIA CMP (Cryptocurrency Mining Processor) to cater to this market without impacting the availability of GPUs for gamers and other users.
Overall, NVIDIA’s influence spans a broad range of industries, driven by its innovations in GPU technology and AI advancements.
Learning to Work, Or Working to Learn? — from insidehighered.com by Erin Crisp; via Melanie Booth, Ed.D. on LinkedIn We need a systems approach to making work-to-learn models just as accessible as traditional learn-to-work pathways, Erin Crisp writes.
Over the past two years, I have had the unique experience of scaling support for a statewide registered teacher-apprenticeship program while also parenting three college-aged sons. The declining appeal of postsecondary education, especially among young men, is evident at my dinner table, in my office, and in my dreams (literally).
…
Scaling a statewide apprenticeship program for the preparation of teachers has meant that I am consistently hearing from four stakeholder groups—K-12 school district leaders, college and university leaders, aspiring young educators, and local workforce development leaders.
A theme has emerged from my professional life, one that echoes the dinner table conversations happening in my personal life: Society needs systematic work-to-learn pathways in addition to the current learn-to-work ecosystem. This is not an either/or. What we need is a systematic expansion of effort.
In a work-to-learn model, the traditional college sequence is flipped. Instead of starting with general education coursework or survey courses, the working learner is actively engaged in practicing the skills they are interested in acquiring. A workplace supervisor often helps him make connections between the coursework and the job. The learner’s attention is piqued. The learning is relevant. The learner gains confidence, and seeing their influence in the workplace (and paycheck) is satisfying. All of the ARCS model elements are easily achieved.
Microsoft’s new ChatGPT competitor… — from The Rundown AI
The Rundown: Microsoft is reportedly developing a massive 500B parameter in-house LLM called MAI-1, aiming to compete with top AI models from OpenAI, Anthropic, and Google.
Hampton runs a private community for high-growth tech founders and CEOs. We asked our community of founders and owners how AI has impacted their business and what tools they use
Here’s a sneak peek of what’s inside:
The budgets they set aside for AI research and development
The most common (and obscure) tools founders are using
Measurable business impacts founders have seen through using AI
Where they are purposefully not using AI and much more
To help leaders and organizations overcome AI inertia, Microsoft and LinkedIn looked at how AI will reshape work and the labor market broadly, surveying 31,000 people across 31 countries, identifying labor and hiring trends from LinkedIn, and analyzing trillions of Microsoft 365 productivity signals as well as research with Fortune 500 customers. The data points to insights every leader and professional needs to know—and actions they can take—when it comes to AI’s implications for work.
The theme of the day was Human Connection V Innovative Technology. I see this a lot at conferences, setting up the human connection (social) against the machine (AI). I think this is ALL wrong. It is, and has always been a dialectic, human connection (social) PLUS the machine. Everyone had a smartphone, most use it for work, comms and social media. The binary between human and tech has long disappeared.
