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Roosevelt Room

1:18 P.M. EDT

THE PRESIDENT: Im the AI. (Laughter.) If any of you think Im Abe Lincoln, blame it on the AI.

First of all, thanks. Thanks for coming. And I want to thank my colleagues here for taking the time to come back again and again as we try to deal with the were joined by leaders of seven American companies who are driving innovation in artificial intelligence. And it is astounding.

Artificial intelligence or it promises an enormous an enormous promise of both risk to our society and our economy and our national security, but also incredible opportunities incredible opportunities.

Just two months ago, Kamala and I met with these leaders most of them are here again to underscore the responsibility of making sure that products that they are producing are safe and and making them public what they are and what they arent.

Since then, Ive met with some of Americas top minds in technology to hear the range of perspectives and possibilities and risk of AI.

Kamala cant be here because shes traveling to Florida, but shes met with civil society leaders to hear their concerns about the impacts on society and ways to protect the rights of Americans.

Over the past year, my administration has taken action to guide responsible innovation.

Last October, we introduced a first-of-its-kind AI Bill of Rights.

In February, I signed an executive order to direct agencies to protect the public from algorithms that discriminate.

In May, we unveiled a new strategy to establish seven new AI research institutes to help drive breakthroughs in responsible AI innovention [innovation].

And today, Im pleased to announce that these seven companies have agreed volun- to voluntary commitments for responsible innovation. These commitments, which the companies will implement immediately, underscore three fundamental principles: safety, security, and trust.

First, the companies have an obligation to make sure their technology is safe before releasing it to the public. That means testing the capabilities of their systems, assessing their potential risk, and making the results of these assessments public.

Second, companies must prioritize the security of their systems by safeguarding their models against cyber threats and managing the risks to our national security and sharing the best practices and industry standards that are that are necessary.

Third, the companies have a duty to earn the peoples trust and empower users to make informed decisions labeling content that has been altered or AI-generated, rooting out bias and discrimination, strengthening privacy protections, and shielding children from harm.

And finally, companies have agreed to find ways for AI to help meet societys greatest challenges from cancer to climate change and invest in education and new jobs to help students and workers prosper from the opportunities, and there are enormous opportunities of AI.

These commitments are real, and theyre concrete. Theyre going to help fulfill the industry fulfill its fundamental obligation to Americans to develop safe, secure, and trustworthy technologies that benefit society and uphold our values and our shared values.

Let me close with this. Well see more technology change in the next 10 years, or even in the next few years, than weve seen in the last 50 years. That has been an astounding revelation to me, quite frankly. Artificial intelligence is going to transform the lives of people around the world.

The group here will be critical in shepherding that innovation with responsibility and safety by design to earn the trust of Americans. And, quite frankly, as I met with world leaders, all all all our Eur- all the G7 is focusing on the same thing.

Social media has shown us the harm that powerful technology can do without the right safeguards in place.

And Ive said at the State of the Union that Congress needs to pass bipartisan legislation to impose strict limits on personal data collection, ban targeted advertisements to kids, require companies to put health and safety first.

But we must be clear-eyed and vigilant about the threats emerging of emerging technologies that can pose dont have to, but can pose to our democracy and our values.

Americans are seeing how advanced artificial intelligence and the pace of innovation have the power to disrupt jobs and industries.

These commitments these commitments are a promising step, but the we have a lot more work to do together.

Realizing the promise of AI by managing the risk is going to require some new laws, regulations, and oversight.

In the weeks ahead, Im going to continue to take executive action to help America lead the way toward responsible innovation. And were going to work with both parties to develop appropriate legislation and regulation. Im pleased that Leader Schumer and Leader Jeffries and others in the Congress are making this a top bipartisan priority.

As we advance the agenda here at home, well lead the work with well lead work with our allies and partners on a common international framework to govern the development of AI.

I think these leaders and I thank these leaders that are in the room with me today (clears throat) and their partnership excuse me and their commitments that theyre making. This is a serious responsibility, and we have to get it right. And theres enormous, enormous potential upside as well.

So I want to thank you all. And theyre about to go down to a meeting, which Ill catch up with them later.

So thank you, thank you, thank you.

1:24 P.M. EDT

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Remarks by President Biden on Artificial Intelligence - The White House

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Did I write this, or was it ChatGPT?

Its hard to tell, isnt it?

For the sake of my editors, I will follow that quickly with: I wrote this article (I swear). But the point is that its worth exploring generative artificial intelligences limitations and areas of utility for developers and users. Both are revealing. The same is true for Web3 and blockchain.

While were already seeing the practical applications of Web3 and generative AI play out in tech platforms, online interactions, scripts, games and social media apps, were also seeing a replay of the responsible AI and blockchain 1.0 hype cycles of the mid-2010s.

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We need a set of principles or ethics to guide innovation. We need more regulation. We need less regulation. There are bad actors poisoning the well for the rest of us. We need heroes to save us from AI and/or blockchain. Technology is too sentient. Technology is too limited. There is no enterprise-level application. There are countless enterprise-level applications.

If you exclusively read the headlines, you will come out the other side with the conclusion that the combo of generative AI and blockchain will either save the world or destroy it.

Weve seen this play (and every act and intermission) before with the hype cycles of both responsible AI and blockchain. The only difference this time is that the articles were reading about ChatGPTs implications may, in fact, have been written by ChatGPT. And the term blockchain has a bit more heft behind it thanks to investment from Web2 giants like Google Cloud, Mastercard and Starbucks.

That said, its notable that OpenAIs leadership recently called for an international regulatory body akin to the International Atomic Energy Agency (IAEA) to regulate and, when necessary, rein in AI innovation. The proactive move illuminates an awareness of both AIs massive potential and potentially society-crumbling pitfalls. It also conveys that the technology itself is still in test mode.

The other significant subtext: Public sector regulation at the federal and sub-federal levels commonly limits innovation.

As with Web3, and whether or not regulatory action takes place, responsibility needs to be at the core of generative AI innovation and adoption. As the technology evolves rapidly, its important for vendors and platforms to assess every potential use case to ensure responsible experimentation and adoption. And, as OpenAIs Sam Altman and Googles Sundar Pichai notably point out, working with the public sector to evolve regulation is a significant part of that equation.

Its also important to surface limitations, transparently report on them, and provide guardrails if or when issues become apparent.

While AI and blockchain have both been around for decades, the impact of AI, in particular, is now visible with ChatGPT, Bard and the entire field of generative AI players. Together with Web3s decentralized power, were about to witness an explosion of practical applications that build on progress automating interactions and advancing Web3 in more visible ways.

From a user-centric perspective (and whether we know it or not), generative AI and blockchain are both already transforming how people interact in the real world and online. Solana recently made it official with a ChatGPT integration. And exchange Bitget backed away from theirs.

Promising or puzzling, every signal indicates that it remains to be seen where the technologies best intersect in the name of user experience and user-centric innovation. From where I sit as the head of a layer1 blockchain built for scale and interoperability, the question becomes: How should AI and blockchain join forces in pursuit of Web3s own ChatGPT moment of mainstream adoption?

Tools like ChatGPT and Bard will accelerate the next major waves of innovation on Web2 and Web3. The convergence of generative AI and Web3 will be like the pairing of peanut butter and jelly on fresh bread but, you know, with code, infrastructure, and asset portability. And, as hype is replaced with practical applications and constant upgrades, persistent questions about whether these technologies will take hold in the mainstream will be toast.

Enterprise leaders should view generative AI as a tool worth exploring, testing, and after doing both, integrating. Specifically, they should focus efforts on exploring how the generative element can improve work outcomes internally with teams and externally with customers or partners. And they should continuously map out its enterprise-wide potential and limitations.

Its time to begin to map out and document where not to use generative AI, which is equally important in my book. Dont rely on the technology for anything where you need to apply facts and hard data to outputs for community members, partners, teams or investors, and dont rely on it for protocol upgrades, software engineering, coding sprints or international business operations.

On a practical level, enterprise leaders should consider incorporating generative AI into administrative workflows to keep their companys day-to-day workflows moving faster and more efficiently. Explore its seemingly universal utility to kick off text- or code-heavy projects across engineering, marketing, business and executive functions. And since this tech changes by the day, enterprise leaders should look at every possible new use case to decide whether to responsibly experiment with it en route to adoption, which also applies to work in Web3.

Mo Shaikh is cofounder and CEO of Aptos Labs.

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Excerpt from:

Generative AI and Web3: Hyped nonsense or a match made in tech ... - VentureBeat

Artificial intelligenceis poised to be the next big thing in a bunch of different industries, including the entertainment sector. But the workers AI might one day replace are fighting for a say in how the technology is usedbefore it gets too big to stop.

Generative AI, meaning AI that can create text, images, and other content, can sometimes feel like a magic boxgive it a prompt, and itll spit out a more-or-less correct response that looks like its been written by a person.

The technologys ability to easily churn out human-quality work for cheap has many artists and writers worried. Artificial intelligence isnt going to replace screenwriters wholesale any time soon, but it could still undermine creative jobs by giving production studios a cheap way to underpay writers.

Bryan Sullivan is a lawyer who specializes in crisis management for the entertainment industry. He told Next Level, "I don't think people realized until recently thatwriters view AI as a threat.The studios could cut the first layer of writing out by using an AI system and then hiring a writer to do a polish, which is a lot less money."

SEE MORE: Hollywood and a history of strikes: How did they turn out?

The potential threat of AI is one issue behind the Writers Guild of Americas most recent strike. Part of the unions demands when they struck aimed to limit studios ability to use AI to cut costs on projects.

AI fears also motivated actors to walk off the job alongside the writers. The actors union, SAG-AFTRA, cited concerns that actors performances could be replicated by artificial intelligence as one justification for their strike.

Writers in Hollywood have already seen their contracts and opportunities shrink in the face of studios efforts to save money. In that environment, its hard not to look at AI in Hollywood as less of a creative engine and more of a cost-cutting measure.

Helen Silverstein is a video game writer and the co-chair of DSA-LA's Hollywood Labor Committee. She told Next Level:"So many writers who despite writing on Emmy award winning shows, are on food stamps or struggling, living paycheck to paycheck, struggling to survive. It is not just about writing or even just creativity at all. It's about working people being able to live, and create, and work, survive, and thrive."

There may not be a whole lot workers can do to protect themselves from being replaced; strikes only work when AI isnt developed enough to cross the picket line. Strikes and protests from workers might not change how the technology behind AI develops, but they can try to shape how its used by the profit-driven industries around them.

Trending stories at Scrippsnews.com

Read the original here:

AI fears are fueling the labor strikes in Hollywood - LEX 18 News - Lexington, KY

Anyone seduced by A.I.-powered chatbots like ChatGPT and Bard wow, they can write essays and recipes! eventually runs into what are known as hallucinations, the tendency for artificial intelligence to fabricate information.

The chatbots, which guess what to say based on information obtained from all over the internet, cant help but get things wrong. And when they fail by publishing a cake recipe with wildly inaccurate flour measurements, for instance it can be a real buzzkill.

Yet as mainstream tech tools continue to integrate A.I., its crucial to get a handle on how to use it to serve us. After testing dozens of A.I. products over the last two months, I concluded that most of us are using the technology in a suboptimal way, largely because the tech companies gave us poor directions.

The chatbots are the least beneficial when we ask them questions and then hope whatever answers they come up with on their own are true, which is how they were designed to be used. But when directed to use information from trusted sources, such as credible websites and research papers, A.I. can carry out helpful tasks with a high degree of accuracy.

If you give them the right information, they can do interesting things with it, said Sam Heutmaker, the founder of Context, an A.I. start-up. But on their own, 70 percent of what you get is not going to be accurate.

With the simple tweak of advising the chatbots to work with specific data, they generated intelligible answers and useful advice. That transformed me over the last few months from a cranky A.I. skeptic into an enthusiastic power user. When I went on a trip using a travel itinerary planned by ChatGPT, it went well because the recommendations came from my favorite travel websites.

Directing the chatbots to specific high-quality sources like websites from well-established media outlets and academic publications can also help reduce the production and spread of misinformation. Let me share some of the approaches I used to get help with cooking, research and travel planning.

Chatbots like ChatGPT and Bard can write recipes that look good in theory but dont work in practice. In an experiment by The New York Timess Food desk in November, an early A.I. model created recipes for a Thanksgiving menu that included an extremely dry turkey and a dense cake.

I also ran into underwhelming results with A.I.-generated seafood recipes. But that changed when I experimented with ChatGPT plug-ins, which are essentially third-party apps that work with the chatbot. (Only subscribers who pay $20 a month for access to ChatGPT4, the latest version of the chatbot, can use plug-ins, which can be activated in the settings menu.)

On ChatGPTs plug-ins menu, I selected Tasty Recipes, which pulls data from the Tasty website owned by BuzzFeed, a well-known media site. I then asked the chatbot to come up with a meal plan including seafood dishes, ground pork and vegetable sides using recipes from the site. The bot presented an inspiring meal plan, including lemongrass pork banh mi, grilled tofu tacos and everything-in-the-fridge pasta; each meal suggestion included a link to a recipe on Tasty.

For recipes from other publications, I used Link Reader, a plug-in that let me paste in a web link to generate meal plans using recipes from other credible sites like Serious Eats. The chatbot pulled data from the sites to create meal plans and told me to visit the websites to read the recipes. That took extra work, but it beat an A.I.-concocted meal plan.

When I did research for an article on a popular video game series, I turned to ChatGPT and Bard to refresh my memory on past games by summarizing their plots. They messed up on important details about the games stories and characters.

After testing many other A.I. tools, I concluded that for research, it was crucial to fixate on trusted sources and quickly double-check the data for accuracy. I eventually found a tool that delivers that: Humata.AI, a free web app that has become popular among academic researchers and lawyers.

The app lets you upload a document such as a PDF, and from there a chatbot answers your questions about the material alongside a copy of the document, highlighting relevant portions.

In one test, I uploaded a research paper I found on PubMed, a government-run search engine for scientific literature. The tool produced a relevant summary of the lengthy document in minutes, a process that would have taken me hours, and I glanced at the highlights to double-check that the summaries were accurate.

Cyrus Khajvandi, a founder of Humata, which is based in Austin, Texas, developed the app when he was a researcher at Stanford and needed help reading dense scientific articles, he said. The problem with chatbots like ChatGPT, he said, is that they rely on outdated models of the web, so the data may lack relevant context.

When a Times travel writer recently asked ChatGPT to compose a travel itinerary for Milan, the bot guided her to visit a central part of town that was deserted because it was an Italian holiday, among other snafus.

I had better luck when I requested a vacation itinerary for me, my wife and our dogs in Mendocino County, Calif. As I did when planning a meal, I asked ChatGPT to incorporate suggestions from some of my favorite travel sites, such as Thrillist, which is owned by Vox, and The Timess travel section.

Within minutes, the chatbot generated an itinerary that included dog-friendly restaurants and activities, including a farm with wine and cheese pairings and a train to a popular hiking trail. This spared me several hours of planning, and most important, the dogs had a wonderful time.

Google and OpenAI, which works closely with Microsoft, say they are working to reduce hallucinations in their chatbots, but we can already reap A.I.s benefits by taking control of the data that the bots rely on to come up with answers.

To put it another way: The main benefit of training machines with enormous data sets is that they can now use language to simulate human reasoning, said Nathan Benaich, a venture capitalist who invests in A.I. companies. The important step for us, he said, is to pair that ability with high-quality information.

Original post:

How to Direct A.I. Chatbots to Make Them More Useful - The New York Times

Elon Musk recently announced his latest startup, xAI, will be focused on artificial intelligence. According to the companys website, the goal of xAI is to understand the true nature of the universe. The xAI team will be led by Musk and others who have previously worked with OpenAI, DeepMind, Google Research, Microsoft Research, and Tesla.

Musks new AI venture is the latest in a list of companies he has founded and leads including Tesla, SpaceX, and The Boring Company.

As of July 2023, Musk is the richest person in the world, with a net worth of $254 billion. Heres how the Tesla CEO and Twitter owner made his billions.

Tesla is the largest carmaker in the world by market value. The company builds and designs fully electric vehicles (EV) and energy generation and storage systems. Its cars include sedans and compact and mid-size SUVs.

Tesla (TSLA) was founded in 2003 as Tesla Motors by Martin Eberhard and Marc Tarpenning. Musk invested in the company and was a member of the board starting in 2004, and later became CEO in 2008.

Musk was allowed to claim the title of cofounder, thanks to an out-of-court settlement. Tesla went public in an initial public offering (IPO) on June 29, 2010. In 2021, Tesla moved its headquarters from its native Palo Alto, California, to Austin, Texas.

In July 2023, Tesla unveiled its first Cybertruck built in its Texas factory, almost two years behind the original schedule.

Musk has a 13% ownership stake in Tesla, worth $108 billion. In 2022, Teslas total revenue was $81.46 billion.

Musk is also the cofounder and CEO of SpaceX, a rocket manufacturing company that counts NASA as one of its clients, and helps resupply the space station.

SpaceX is valued at $137 billion as of January 2023 and raised $2.2 billion in 2022, making it the most valuable private company in the country. Musk owns 42% of SpaceX, which launched its 200th rocket in January and has more than 1 million subscribers for its Starlink internet service.

In April 2022, Musk bought Twitter for $44 million after threatening a hostile takeover. The deal was finalized in October 2022, after Twitter sued Musk for trying to back out of the deal.

His takeover has been controversial, as he laid off half of the companys workforce and added a paid subscription service ($8 per month) for anyone who wants their account verified. Musk owns about 79% of Twitter. The company is valued at about $20 billion as of March 2023.

Musk is also the founder of The Boring Company, a tunnel construction company that aims to solve traffic by building freight tunnels. The company raised $675 million in April 2022, at a valuation of $5.7 billion, according to Forbes.

Musk also co-founded a company called Neuralink which designed a "brain-computer interface," a chip that can be implanted into the brain. Neuralink is valued at about $5 billion, according to reporting by Reuters.

Link:

Elon Musk Launched His Own AI StartupHere's Musk's Net Worth - Investopedia