Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.
Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.
This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.
… Characteristics of Agentic AI
Autonomy: Achieves complex objectives without requiring human collaboration.
Language Comprehension: Understands nuanced human speech and text effectively.
Rationality: Makes informed, contextual decisions using advanced reasoning engines.
Adaptation: Adjusts plans and goals in dynamic situations.
Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.
How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?
Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.
Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper Google’s Veo 2, Kling 1.6, Pika 2.0 & more
AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.
Here’s a comprehensive look at the current landscape:
Veo 2…
Pika 2.0…
Runway’s Gen-3…
Luma AI Dream Machine…
Hailuo’s MiniMax…
OpenAI’s Sora…
Hunyuan Video by Tencent…
There are several other video models and platforms, including …
Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.
We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.
Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.
Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.
Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1
Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.
Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.
…
Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.
Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…
… The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.
“We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
“If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.
The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.
Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.
Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.
The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.
The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.
Google is an illegal monopoly, federal court rules — from washingtonpost.com by Eva Dou and Gerrit De Vynck Judgment delivers a victory to the Justice Department as it takes on a string of federal antitrust lawsuits against Big Tech.
A federal court has found that Google illegally abused its market power to quash competition in internet search, handing the Justice Department a landmark victory against Big Tech.
“Google is a monopolist, and it has acted as one to maintain its monopoly,” Judge Amit P. Mehta wrote in his judgment on Monday.
Mehta wrote that Google, a unit of Alphabet Inc., has violated Section 2 of the Sherman Antitrust Act by maintaining its monopoly in two product markets in the United States — general search service and general text advertising — through exclusive distribution agreements with customer companies.
The case has been closely watched in antitrust law circles as the first of a string of cases federal prosecutors have launched against high-tech giants. Antitrust enforcers argue that Big Tech has gotten too powerful and doesn’t serve the public interest. Lawsuits have also been filed against Amazon, Meta and Apple.
We’re starting to roll out advanced Voice Mode to a small group of ChatGPT Plus users. Advanced Voice Mode offers more natural, real-time conversations, allows you to interrupt anytime, and senses and responds to your emotions. pic.twitter.com/64O94EhhXK
Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.
“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.
“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.
…
More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.
DC: Nvidia continues 2get rocked as I think people are taking their gains & getting nervous about AI’s ability 2deliver healthy ROI’s. But I think co’s will let many people go as a result of various AI’s impacts. They WILL get their ROI. But it may be at a great cost to some pple
From DSC: Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.
DC: What do you think about this? What about if this occurred at *your* place of employment? https://t.co/CWc09Cm7n1
This last wave of AI releases is truly making us more capable than ever.
Here are 10 amazing examples of my favorite new tool ?
This is Claude 3.5 Sonnet with Artifacts, a new feature that allows people to go from a super simple prompt to immediate previews of games, code… pic.twitter.com/w4kkT25fch
9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.
7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.
8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.
Top 7 generative AI use cases for business— from cio.com by Grant Gross Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.
Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.
However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.
“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.
Vast swaths of the United States are at risk of running short of power as electricity-hungry data centers and clean-technology factories proliferate around the country, leaving utilities and regulators grasping for credible plans to expand the nation’s creaking power grid.
…
A major factor behind the skyrocketing demand is the rapid innovation in artificial intelligence, which is driving the construction of large warehouses of computing infrastructure that require exponentially more power than traditional data centers. AI is also part of a huge scale-up of cloud computing. Tech firms like Amazon, Apple, Google, Meta and Microsoft are scouring the nation for sites for new data centers, and many lesser-known firms are also on the hunt.
The Obscene Energy Demands of A.I.— from newyorker.com by Elizabeth Kolbert How can the world reach net zero if it keeps inventing new ways to consume energy?
“There’s a fundamental mismatch between this technology and environmental sustainability,” de Vries said. Recently, the world’s most prominent A.I. cheerleader, Sam Altman, the C.E.O. of OpenAI, voiced similar concerns, albeit with a different spin. “I think we still don’t appreciate the energy needs of this technology,” Altman said at a public appearance in Davos. He didn’t see how these needs could be met, he went on, “without a breakthrough.” He added, “We need fusion or we need, like, radically cheaper solar plus storage, or something, at massive scale—like, a scale that no one is really planning for.”
A generative AI reset: Rewiring to turn potential into value in 2024 — from mckinsey.com by Eric Lamarre, Alex Singla, Alexander Sukharevsky, and Rodney Zemmel; via Philippa Hardman The generative AI payoff may only come when companies do deeper organizational surgery on their business.
Figure out where gen AI copilots can give you a real competitive advantage
Upskill the talent you have but be clear about the gen-AI-specific skills you need
Form a centralized team to establish standards that enable responsible scaling
Set up the technology architecture to scale
Ensure data quality and focus on unstructured data to fuel your models
Build trust and reusability to drive adoption and scale
Since ChatGPT dropped in the fall of 2022, everyone and their donkey has tried their hand at prompt engineering—finding a clever way to phrase your query to a large language model (LLM) or AI art or video generator to get the best results or sidestep protections. The Internet is replete with prompt-engineering guides, cheat sheets, and advice threads to help you get the most out of an LLM.
…
However, new research suggests that prompt engineering is best done by the model itself, and not by a human engineer. This has cast doubt on prompt engineering’s future—and increased suspicions that a fair portion of prompt-engineering jobs may be a passing fad, at least as the field is currently imagined.
There is one very clear parallel between the digital spreadsheet and generative AI: both are computer apps that collapse time. A task that might have taken hours or days can suddenly be completed in seconds. So accept for a moment the premise that the digital spreadsheet has something to teach us about generative AI. What lessons should we absorb?
It’s that pace of change that gives me pause. Ethan Mollick, author of the forthcoming book Co-Intelligence, tells me “if progress on generative AI stops now, the spreadsheet is not a bad analogy”. We’d get some dramatic shifts in the workplace, a technology that broadly empowers workers and creates good new jobs, and everything would be fine. But is it going to stop any time soon? Mollick doubts that, and so do I.
verb
(of artificial intelligence) to produce false information contrary to the intent of the user and present it as if true and factual. Example: When chatbots hallucinate, the result is often not just inaccurate but completely fabricated.
Soon, every employee will be both AI builder and AI consumer— from zdnet.com by Joe McKendrick, via Robert Gibson on LinkedIn “Standardized tools and platforms as well as advanced low- or no-code tech may enable all employees to become low-level engineers,” suggests a recent report.
The time could be ripe for a blurring of the lines between developers and end-users, a recent report out of Deloitte suggests. It makes more business sense to focus on bringing in citizen developers for ground-level programming, versus seeking superstar software engineers, the report’s authors argue, or — as they put it — “instead of transforming from a 1x to a 10x engineer, employees outside the tech division could be going from zero to one.”
Along these lines, see:
TECH TRENDS 2024 — from deloitte.com Six emerging technology trends demonstrate that in an age of generative machines, it’s more important than ever for organizations to maintain an integrated business strategy, a solid technology foundation, and a creative workforce.
The ruling follows a similar decision denying patent registrations naming AI as creators.
The UK Supreme Court ruled that AI cannot get patents, declaring it cannot be named as an inventor of new products because the law considers only humans or companies to be creators.
The New York Times sued OpenAI and Microsoft for copyright infringement on Wednesday, opening a new front in the increasingly intense legal battle over the unauthorized use of published work to train artificial intelligence technologies.
…
The suit does not include an exact monetary demand. But it says the defendants should be held responsible for “billions of dollars in statutory and actual damages” related to the “unlawful copying and use of The Times’s uniquely valuable works.” It also calls for the companies to destroy any chatbot models and training data that use copyrighted material from The Times.
On this same topic, also see:
? The historic NYT v. @OpenAI lawsuit filed this morning, as broken down by me, an IP and AI lawyer, general counsel, and longtime tech person and enthusiast.
Tl;dr – It’s the best case yet alleging that generative AI is copyright infringement. Thread. ? pic.twitter.com/Zqbv3ekLWt
ChatGPT and Other Chatbots
The arrival of ChatGPT sparked tons of new AI tools and changed the way we thought about using a chatbot in our daily lives.
Chatbots like ChatGPT, Perplexity, Claude, and Bing Chat can help content creators by quickly generating ideas, outlines, drafts, and full pieces of content, allowing creators to produce more high-quality content in less time.
These AI tools boost efficiency and creativity in content production across formats like blog posts, social captions, newsletters, and more.
Microsoft is getting ready to upgrade its Surface lineup with new AI-enabled features, according to a report from Windows Central. Unnamed sources told the outlet the upcoming Surface Pro 10 and Surface Laptop 6 will come with a next-gen neural processing unit (NPU), along with Intel and Arm-based options.
With the AI-assisted reporter churning out bread and butter content, other reporters in the newsroom are freed up to go to court, meet a councillor for a coffee or attend a village fete, says the Worcester News editor, Stephanie Preece.
“AI can’t be at the scene of a crash, in court, in a council meeting, it can’t visit a grieving family or look somebody in the eye and tell that they’re lying. All it does is free up the reporters to do more of that,” she says. “Instead of shying away from it, or being scared of it, we are saying AI is here to stay – so how can we harness it?”
This year, I watched AI change the world in real time.
From what happened, I have no doubts that the coming years will be the most transformative period in the history of humankind.
Here’s the full timeline of AI in 2023 (January-December):
What to Expect in AI in 2024 — from hai.stanford.edu by Seven Stanford HAI faculty and fellows predict the biggest stories for next year in artificial intelligence.
Artificial intelligence is automating the creation of fake news, spurring an explosion of web content mimicking factual articles that instead disseminates false information about elections, wars and natural disasters.
Since May, websites hosting AI-created false articles have increased by more than 1,000 percent, ballooning from 49 sites to more than 600, according to NewsGuard, an organization that tracks misinformation.
Historically, propaganda operations have relied on armies of low-paid workers or highly coordinated intelligence organizations to build sites that appear to be legitimate. But AI is making it easy for nearly anyone — whether they are part of a spy agency or just a teenager in their basement — to create these outlets, producing content that is at times hard to differentiate from real news.
Their AI chatbot, designed to assist customers in their vehicle search, became a social media sensation for all the wrong reasons. One user even convinced the chatbot to agree to sell a 2024 Chevy Tahoe for just one dollar!
This story is exactly why AI implementation needs to be approached strategically. Learning to use AI, also means learning to build thinking of the guardrails and boundaries.
The pharmacy chain Rite Aid misused facial recognition technology in a way that subjected shoppers to unfair searches and humiliation, the Federal Trade Commission said Tuesday, part of a landmark settlement that could raise questions about the technology’s use in stores, airports and other venues nationwide.
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But the chain’s “reckless” failure to adopt safeguards, coupled with the technology’s long history of inaccurate matches and racial biases, ultimately led store employees to falsely accuse shoppers of theft, leading to “embarrassment, harassment, and other harm” in front of their family members, co-workers and friends, the FTC said in a statement.
This guide shares strategies and tactics for getting better results from large language models (sometimes referred to as GPT models) like GPT-4. The methods described here can sometimes be deployed in combination for greater effect. We encourage experimentation to find the methods that work best for you.
Some of the examples demonstrated here currently work only with our most capable model, gpt-4. In general, if you find that a model fails at a task and a more capable model is available, it’s often worth trying again with the more capable model.
You can also explore example prompts which showcase what our models are capable of…
The study of frontier AI risks has fallen far short of what is possible and where we need to be. To address this gap and systematize our safety thinking, we are adopting the initial version of our Preparedness Framework. It describes OpenAI’s processes to track, evaluate, forecast, and protect against catastrophic risks posed by increasingly powerful models.
Here’s every major innovation from the last 365 days:
Microsoft: Launched additional OpenAI-powered features, including Copilot for Microsoft Dynamics 365 and Microsoft 365, enhancing business functionalities like text summarization, tone adjustment in emails, data insights, and automatic presentation creation.
Google: Introduced Duet, akin to Microsoft’s Copilot, integrating Gen AI across Google Workspace for writing assistance and custom visual creation. Also debuted Generative AI Studio, enabling developers to craft AI apps, and unveiled Gemini & Bard, a new AI technology with impressive features.
Salesforce: …
Adobe: …
Amazon Web Services (AWS): …
IBM: …
Nvidia: …
OpenAI: …
Meta (Facebook): …
Tencent: …
Baidu: …
News in chatbots — from theneurondaily.com by Noah Edelman & Pete Huang
Here’s what’s on the horizon:
Multimodal AI gets huge. Instead of just typing, more people will talk to AI, listen to it, create images, get visual feedback, create graphs, and more.
AI video gets really good. So far, AI videos have been cool-but-not-practical. They’re getting way better and we’re on the verge of seeing 100% AI-generated films, animations, and cartoons.
AI on our phones. Imagine Siri with the brains of ChatGPT-4 and the ambition of Alexa. TBD who pulls this off first!
GPT-5. ‘Nuff said.
20 Best AI Chatbots in 2024— from eweek.com by Aminu Abdullahi These leading AI chatbots use generative AI to offer a wide menu of functionality, from personalized customer service to improved information retrieval.
Top 20 Generative AI Chatbot Software: Comparison Chart
We compared the key features of the top generative AI chatbot software to help you determine the best option for your company…
Here’s our power rankings of the best chatbots for (non-technical) work:
1: ChatGPT-4—Unquestionably the smartest, with the strongest writing, coding, and reasoning abilities.
T1: Gemini Ultra—In theory as powerful as GPT-4. We won’t know for sure until it’s released in 2024.
2: Claude 2—Top choice for managing lengthy PDFs (handles ~75,000 words), and rarely hallucinates. Can be somewhat stiff.
3: Perplexity—Ideal for real-time information. Upgrading to Pro grants access to both Claude-2 and GPT-4.
T4: Pi—The most “human-like” chatbot, though integrating with business data can be challenging.
T4: Bing Chat—Delivers GPT-4-esque responses, has internet access, and can generate images. Bad UX and doesn’t support PDFs.
T4: Bard—Now powered by Gemini Pro, offers internet access and answer verification. Tends to hallucinate more frequently.
and others…
Midjourney + ChatGPT = Amazing AI Art — from theaigirl.substack.com by Diana Dovgopol and the Pycoach Turn ChatGPT into a powerful Midjourney prompt machine with basic and advanced formulas.
From DSC: The recent drama over at OpenAI reminds me of how important a few individuals are in influencing the lives of millions of people.
We have reached an agreement in principle for Sam Altman to return to OpenAI as CEO with a new initial board of Bret Taylor (Chair), Larry Summers, and Adam D’Angelo.
We are collaborating to figure out the details. Thank you so much for your patience through this.
The C-Suites (i.e., the Chief Executive Officers, Chief Financial Officers, Chief Operating Officers, and the like) of companies like OpenAI, Alphabet (Google), Meta (Facebook), Microsoft, Netflix, NVIDIA, Amazon, Apple, and a handful of others have enormous power. Why? Because of the enormous power and reach of the technologies that they create, market, and provide.
We need to be praying for the hearts of those in the C-Suites of these powerful vendors — as well as for their Boards.
LORD, grant them wisdom and help mold their hearts and perspectives so that they truly care about others. May their decisions not be based on making money alone…or doing something just because they can.
What happens in their hearts and minds DOES and WILL continue to impact the rest of us. And we’re talking about real ramifications here. This isn’t pie-in-the-sky thinking or ideas. This is for real. With real consequences. If you doubt that, go ask the families of those whose sons and daughters took their own lives due to what happened out on social media platforms. Disclosure: I use LinkedIn and Twitter quite a bit. I’m not bashing these platforms per se. But my point is that there are real impacts due to a variety of technologies. What goes on in the hearts and minds of the leaders of these tech companies matters.
No doubt, technology influences us in many ways we don’t fully understand. But one area where valid concerns run rampant is the attention-seeking algorithmspowering the news and media we consume on modern platforms that efficiently polarize people. Perhaps we’ll call it The Law of Anger Expansion: When people are angry in the age of algorithms, they become MORE angry and LESS discriminate about who and what they are angry at.
… Algorithms that optimize for grabbing attention, thanks to AI, ultimately drive polarization.
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The AI learns quickly that a rational or “both sides” view is less likely to sustain your attention (so you won’t get many of those, which drives the sensation that more of the world agrees with you). But the rage-inducing stuff keeps us swiping.
Our feeds are being sourced in ways that dramatically change the content we’re exposed to.
And then these algorithms expand on these ultimately destructive emotions – “If you’re afraid of this, maybe you should also be afraid of this” or “If you hate those people, maybe you should also hate these people.”
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How do we know when we’ve been polarized? This is the most important question of the day.
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Whatever is inflaming you is likely an algorithm-driven expansion of anger and an imbalance of context.
Forty-one states and the District of Columbia are suing Meta, alleging that the tech giant harms children by building addictive features into Instagram and Facebook. Tuesday’s legal actions represent the most significant effort by state enforcers to rein in the impact of social media on children’s mental health.
Last week, Matt Barnum reported in Chalkbeat that the Chan Zuckerberg Initiative is laying off dozens of staff members and pivoting away from the personalized learning platform they have funded since 2015 with somewhere near $100M.
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I have tried to illustrate as often as my subscribers will tolerate that students don’t particularly enjoy learning alone with laptops within social spaces like classrooms. That learning fails to answer their questions about their social identity. It contributes to their feelings of alienation and disbelonging. I find this case easy to make but hard to prove. Maybe we just haven’t done personalized learning right? Maybe Summit just needed to include generative AI chatbots in their platform?
What is far easier to prove, or rather to disprove, is the idea that “whole class instruction must feel impersonal to students,” that “whole class instruction must necessarily fail to meet the needs of individual students.”
From DSC: I appreciate Dan’s comments here (as highlighted above) as they are helpful in my thoughts regarding the Learning from the Living [Class] Room vision. They seem to be echoed here by Jeppe Klitgaard Stricker when he says:
Personalized learning paths can be great, but they also entail a potential abolishment or unintended dissolution of learning communities and belonging.
Perhaps this powerful, global, Artificial Intelligence (AI)-backed, next-generation, lifelong learning platform of the future will be more focused on postsecondary students and experiences — but not so much for the K12 learning ecosystem.
But the school systems I’ve seen here in Michigan (USA) represent systems that address a majority of the class only. These one-size-fits-all systems don’t work for many students who need extra help and/or who are gifted students. The trains move fast. Good luck if you can’t keep up with the pace.
But if K-12’ers are involved in a future learning platform, the platform needs to address what Dan’s saying. It must address students questions about their social identity and not contribute to their feelings of alienation and disbelonging. It needs to support communities of practice and learning communities.
The age of generative AI threatens to sprinkle epistemological sand into the gears of web search by fooling algorithms designed for a time when the web was mostly written by humans.
Meta is shelling out millions to get celebrities to license their likenesses for AI characters in a bid to draw users to its platforms.
… Why should I care?
Meta is still all-in on its vision for the metaverse and AI, despite its recent struggles. Meta seems willing to pay top dollar to partner with big names who can draw their massive audiences to use the AI avatars. If the celebrity avatars take off, they could be a blueprint for how creators monetize their brands in virtual worlds. There’s also a chance Meta pulls the plug on funding if user traction is low, just as it did with Facebook Watch originals.
The Post-AI Workplace — from drphilippahardman.substack.com by Dr. Philippa Hartman SAP SuccessFactors’ new product offers the most comprehensive insight yet into the post-AI workplace & workforce
Skills Maps AI will be used to categorise, track and analyse employee skills and competencies. This will enable orgs to build a clear idea of pockets of talent and areas in need of focus, providing HR, L&D professionals & managers with the opportunity to take a data-driven approach to talent development and capability building.
Roles Impacted: HR Analysts, Managers, Learning & Development Professionals
While I can understand why courts should be cautious about the adoption of any new technology, I don’t believe we need orders that prohibit or require attorneys to disclose their use of generative AI. I’ll provide a few reasons throughout the day. What do you think?
Analyst Brian Nowak estimates that the AI technology will have a $4.1 trillion economic effect on the labor force — or affect about 44% of labor — over the next few years by changing input costs, automating tasks and shifting the ways companies obtain, process and analyze information. Today, Morgan Stanley pegs the AI effect at $2.1 trillion, affecting 25% of labor.
“We see generative AI expanding the scope of business processes that can be automated,” he wrote in a Sunday note. “At the same time, the input costs supporting GenAI functionality are rapidly falling, enabling a strongly expansionary impact to software production. As a result, Generative AI is set to impact the labor markets, expand the enterprise software TAM, and drive incremental spend for Public Cloud services.”
Speaking of the changes in the workplace, also see:
According to ElevenLabs, the new Multilingual v2 model promises it can produce “emotionally rich” audio in a total of 30 languages. The company offers two AI voice tools, one is a text-to-speech model and the other is the “VoiceLab” that lets paying users clone a voice by inputting fragments of theirs (or others) speech into the model to create a kind of voice cone. With the v2 model, users can get these generated voices to start speaking in Greek, Malay, or Turkish.
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Since then, ElevenLabs claims its integrated new measures to ensure users can only clone their own voice. Users need to verify their speech with a text captcha prompt which is then compared to the original voice sample.
From DSC: I don’t care what they say regarding safeguards/proof of identity/etc. This technology has been abused and will be abused in the future. We can count on it. The question now is, how do we deal with it?
Introducing SeamlessM4T, the first all-in-one, multilingual multimodal translation model.
This single model can perform tasks across speech-to-text, speech-to-speech, text-to-text translation & speech recognition for up to 100 languages depending on the task.
But Hugging Face produces a platform where AI developers can share code, models, data sets, and use the company’s developer tools to get open-source artificial intelligence models running more easily. In particular, Hugging Face often hosts weights, or large files with lists of numbers, which are the heart of most modern AI models.
While Hugging Face has developed some models, like BLOOM, its primary product is its website platform, where users can upload models and their weights. It also develops a series of software tools called libraries that allow users to get models working quickly, to clean up large datasets, or to evaluate their performance. It also hosts some AI models in a web interface so end users can experiment with them.
Numerous skills are required to grow the semiconductor ecosystem over the next decade. Globally, we will need tens of thousands of skilled tradespeople to build new plants to increase and localize manufacturing capacity: electricians, pipefitters, welders; thousands more graduate electrical engineers to design chips and the tools that make the chips; more engineers of various kinds in the fabs themselves, but also operators and technicians. And if we grow the back end in Europe and the Americas, that equates to even more jobs.
Each of these job groups has distinct training and educational needs; however, the number of students in semiconductor-focused programs (for example, undergraduates in semiconductor design and fabrication) has dwindled. Skills are also evolving within these job groups, in part due to automation and increased digitization. Digital skills, such as cloud, AI, and analytics, are needed in design and manufacturing more than ever.
The chip industry has long partnered with universities and engineering schools. Going forward, they also need to work more with local tech schools, vocational schools, and community colleges; and other organizations, such as the National Science Foundation in the United States.
Principle #1: AI is here, and we will embrace it responsibly together with our music partners.
Principle #2: AI is ushering in a new age of creative expression, but it must include appropriate protections and unlock opportunities for music partners who decide to participate.
Principle #3: We’ve built an industry-leading trust and safety organization and content policies. We will scale those to meet the challenges of AI.
Brett Bauman, the developer of PlayListAI (previously LinupSupply), launched a new app called Songburst on the App Store this week. The app doesn’t have a steep learning curve. You just have to type in a prompt like “Calming piano music to listen to while studying” or “Funky beats for a podcast intro” to let the app generate a music clip.
If you can’t think of a prompt the app has prompts in different categories, including video, lo-fi, podcast, gaming, meditation and sample.
A Generative AI Primer— from er.educause.edu by Brian Basgen Understanding the current state of technology requires understanding its origins. This reading list provides sources relevant to the form of generative AI that led to natural language processing (NLP) models such as ChatGPT.
Three big questions about AI and the future of work and learning — from workshift.opencampusmedia.org by Alex Swartsel AI is set to transform education and work today and well into the future. We need to start asking tough questions right now, writes Alex Swartsel of JFF.
How will AI reshape jobs, and how can we prepare all workers and learners with the skills they’ll need?
How can education and workforce leaders equitably adopt AI platforms to accelerate their impact?
How might we catalyze sustainable policy, practice, and investments in solutions that drive economic opportunity?
“As AI reshapes both the economy and society, we must collectively call for better data, increased accountability, and more flexible support for workers,” Swartsel writes.
