1 big thing: Game makers put generative AI to imaginative work

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2. High court weighs claim Twitter aided terrorism

3. More layoffs loom at Meta

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Apparently, it was National Margarita Day yesterday! This may call for time-travel.

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Thanks to Peter Allen Clark for editing and Bryan McBournie for copy editing this newsletter.

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1 big thing: Chatbots trigger next misinformation nightmare

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2. Supreme Court's internet smarts put to test

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3. New fees for user services at Meta, Twitter

Welcome back after the long weekend! (Or, if you had to work yesterday, our condolences.) Ina's taking some time off this week so you've got me, Scott Rosenberg, at the wheel for the next few days.

Today's Login is 1,244 words, a 5-minute read. 

1 big thing: Tech's moonshots fizzle and crash

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2. Twitter's checkmark chaos

3. Musk's SpaceX buys ads on Musk's Twitter 

5. After you Login 

Happy Monday. Ina's out for a couple of days, so I'm here once again as your back-up host, with a whole lot of Twitter news to catch up on after the long weekend, so let's get right to it.

💰 Situational awareness: Amazon founder Jeff Bezos told CNN he plans to donate the majority of his $124 billion net worth to charity over his lifetime.

Today's Login is 1,217 words, a 5-minute read.

Thanks to Peter Allen Clark for editing and Nick Aspinwall for copy editing this newsletter. 

1 big thing: Web3 in FTX's blast radius 

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2. Tech layoffs are soaring this month

3. Qualcomm sees upside to glut of chips

Good morning. Join Axios tomorrow at 8am ET in Washington, D.C., for an event about closing the U.S.'s economic equity gaps with Council of Economic Advisers member Jared Bernstein, 1863 Ventures founder and managing partner Melissa Bradley, and National Bankers Association CEO Nicole A. Elam. Register here to attend in person or virtually.

Today's newsletter is 1,241 words, a 5-minute read.

Thanks to Peter Allen Clark for editing and Nick Aspinwall for copy-editing this newsletter.

1 big thing: AI generates a new job title — "prompt engineer" 

2.  Justices seem skeptical on Section 230 limits

3. ChatGPT-written books, stories start to pile up

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Welcome to Login for 2/22/23 — numbers that may have some significance, but probably don't. 

Today's newsletter is 1,218 words, a 5-minute read. 

National

The lightning collapse of Silicon Valley Bank Friday raised the specter of a broad tech-industry crash for the first time since the dot-com bubble burst in 2000.

Driving the news: That threat, which loomed all weekend as legions of the startups that made up the bank's clientele worried about meeting next week's payrolls, receded after the federal government intervened Sunday to backstop depositors' assets even over the $250,000 FDIC threshold.

Yes, but: After a year of layoffs and market retreats, the run on the industry's own community bank put tech's new status as a troubled business in sharp relief.

Why it matters: The federal rescue of Silicon Valley Bank customers offers a visceral reminder of just how deeply dependent on government the industry remains. 

For decades much of the tech intelligentsia has argued that the nation-state is outmoded, the public sector is more nuisance than necessity, and tech products offer efficient replacements for the old-fashioned institutions that undergird civic life.

The crypto movement has long preached that new currencies and institutions built on computer code will turn today's financial system into a relic.

But in a financial crisis, it sure is nice to have a government that can arrest a confidence meltdown and block a bank failure from taking out an entire sector.

The big picture: Silicon Valley Bank was an institution uniquely centered on the needs of the startup ecosystem. 

Small companies whose meager cashflow gave traditional bankers heartburn found SVB was willing to take their business.

Scott Rosenberg's thought bubble: If you've been around the industry for a while, odds are good you've had some kind of experience with Silicon Valley Bank. It was, for instance, the only bank that would extend a loan to the overextended digital media startup I worked for when the bottom fell out of the market in the early 2000s.

Those experiences with SVB gave people who work in tech a very different sense of what was at stake in this crisis from most Americans.

To much of the country beyond the San Francisco Bay Area, the bank just sounded like a place for tech people to stash their riches. In an era of growing unease with big tech firms' power and wealth, some cheered the bank's woes.

"I believe that if Silicon Valley Bank were instead called Farmers Bank Of Santa Clara (they bank a lot of winegrowers!) we would have had this easily resolved," veteran investor and OpenAI CEO Sam Altman tweeted Sunday. 

In reality, SVB was simply the bank closest to the most startups. Founders would park the money they raised from investors there so they could pay their employees and bills.

SVB took into account the nuances of an industry whose main assets were people, whose young companies often had little or no revenue, and whose workers often had wealth concentrated in stock options that could not yet be exercised or sold.

The company funded and sponsored all manner of organizations, from civic institutions to sports teams to efforts aimed at diversifying the tech industry. Just last month, for example, it led funding for LabCentral Ignite, an effort to address racial, gender, and other underrepresentation  in the life sciences and biotech industry.

It has also served as the financial home for a disproportionate share of Bay Area nonprofits.

Startup founders and venture capitalists spent the weekend in conversations and on social media to ensure that more people — especially politicians — understood that preventing a wipe-out of the bank's customers was less about protecting billionaire portfolios than meeting payrolls.

A host of venture investors wrote a letter pledging to support a new, well capitalized bank that serves the role Silicon Valley Bank used to play.

Startup CEOs, such as RevenueCat's Jacob Eiting, took to Twitter to put human faces on the crisis to help sway public sentiment. "I didn't make risky bets," the 36-year old employer of 60 wrote on Twitter. "I wasn't doing anything illegal. We just put our money in a bank account and now, our business is a precarious position for it."

What's next: It is still unclear what will happen to the various parts of Silicon Valley Bank itself — as well as who, if anyone, will fill its unique role.

Silicon Valley pulls back from bank failure abyss

The feds will rescue the failed bank's depositors, but the tech industry will still take some blows.

Silicon Valley Bank

Technology

After a record economic expansion, the coronavirus pandemic sent the U.S. economy into a recession as unemployment soared to staggering heights. The country now faces urgent questions about how much stimulus is needed for reeling consumers and businesses, and what a recovery might look like.

Economy & Business

The generative AI revolution will be monetized, but nobody can yet say exactly how.

The big picture: It seems logical that if AI can conduct conversations and produce images, companies will figure out how to use it to build revenue and  profits — but there's no guarantee, and the technology could also become a money sink for early adopters.

What's happening: In the short to medium term, the winners will likely be the owners of the foundational AI models — like Microsoft and OpenAI — who can charge others to use them for experiments and new applications.

If those experiments in applying generative AI's capabilities to specific commercial problems and consumer desires succeed, then we might see broader new businesses emerge built on tech's two time-tested business models, advertising and fees or subscriptions.

In the meantime, the news around projects like ChatGPT and Bing AI may quickly shift from the gee-whiz world of mindblowing sci-fi breakthroughs to very mundane nuances of B2B pricing.

Driving the news: As it rolled out the generative-AI-enabled version of its Bing search engine, Microsoft also announced big hikes in the price for outside developers to plug their programs into Bing via its API. Many in the industry expect OpenAI's pricing to jump too.

As part of its wide-ranging deal with OpenAI, Microsoft is getting broad rights to commercialize OpenAI's technologies as well as the ability to bundle and resell them as part of its broader Azure cloud.

Between the lines: The most advanced generative AI services today demand costly computing power.

That means any AI boom will inevitably also create huge windfalls for the big cloud providers — Amazon, Microsoft and Google.

It also means that the days of ChatGPT as a free romp for casual dabblers are probably numbered, as OpenAI starts trying to underwrite its expenses.

A partnership between OpenAI and consulting giant Bain announced last week is one sign of the monetization drive kicking in.

The companies are planning early deployment experiments in "next generation contact centers" for customer service, creative development for marketing campaigns, and "helping financial advisors improve their productivity and responsiveness to clients."

Bain said Coca-Cola is the first company to "engage with" the Bain/OpenAI partnership.

Software-as-a-service platforms are also rolling out AI enhancements as a quick path to enrolling new paying customers.

Last week Notion, the popular information-organizing and collaboration service, began offering a Notion AI tool at a $10 per user per month fee.

Notion's AI helper serves as an auto-completer, summarizer and brainstorming tool.

Yes, but: Notion's and similar new rollouts bolster the skeptical argument that AI is "just a feature" — destined not to become its own independent new business but instead to be widely incorporated into existing platforms, tools and industries.

The search arena, where AI-powered chat is already in wide testing, illustrates the business' promise and perils.

Bing's AI move has brought Microsoft's long-lagging service into the spotlight.

But the chat model also undermines the ads that make search so profitable today, mostly for Google.

Integrating advertising with AI chat could prove cumbersome or unappealing. Voice systems like Alexa have yet to come up with a satisfying way to mix ads with useful information.

Newcomers and underdogs like Bing or You.com, a startup with an early entrant in AI-chat search, are more likely to figure out this new business than incumbents like Google.

Be smart: The AI story is following the same track as previous tech explosions.

When the web burst on the scene 30 years ago, the first profits flowed not to web publishers or online stores but to internet service providers.

What they're saying: "ChatGPT and Bing’s chatbot were never the end product," Alex Kantrowitz of Big Technology writes. "They were demos meant to sell other companies on tools they could use to build their own."

The bottom line: Right now the biggest beneficiaries of the AI boom look likely to be the AI providers themselves. They can start charging today, and outsource bigger risks downstream to a wave of startups and early-adopter experimenters — who might see big new efficiencies, or learn painful lessons.

Go deeper: Read more in Axios' AI Revolution series —

Chatbots trigger next misinformation nightmare

AI's rise generates new job title: Prompt engineer

How generative AI is upending the cybersecurity world

Game makers put generative AI to imaginative work  

Generative AI's money game

The first winners in this money race will be the companies that own the underlying AI models.

Artificial intelligence

Automation and AI

The generative AI revolution will be monetized, but nobody can yet say exactly how.The big picture: It seems logical that if AI can conduct conversations and produce images, companies will figure out how to use it to build revenue and profits — but there&#x27;s no guarantee, and the technology could also become a money sink for early adopters.

Commerce Secretary Gina Raimondo said Thursday the Biden administration wants to use the $52 billion CHIPS Act to create two new "clusters" in the U.S. for manufacturing semiconductors.

What's happening: The Commerce Department plans to open applications next week for companies to seek funding under the law, passed last year.

What they're saying: In a speech at Georgetown University, Raimondo said the purpose of the spending was to bolster national security, not pick favorites in the chip business.

"Each cluster will include a robust supplier ecosystem, R&D facilities to continuously innovate new process technologies, and specialized infrastructure," Raimondo said. "Each of those clusters will employ thousands of workers in well-paying jobs."

The big picture: The U.S. aims to boost domestic chip manufacturing to boost jobs and protect its supply chain from disruption during international conflict.

The spending aims to promote both the most advanced chipmaking, which is dominated by Taiwan and South Korea today, and the production of the kind of older chips that faced a shortage during the COVID pandemic.

Raimondo compared the chip funding effort to the 1960s-era moon-landing program or the development of nuclear power, per the AP.

Go deeper: Chip billions won't be a quick fix

Raimondo: New funding will build two chipmaking "clusters"

The Commerce Department next week will start taking applications for funding under the CHIPS Act.

Gina Raimondo, US secretary of commerce, during an event at Georgetown University's School of Foreign Service in Washington, DC, on Thursday. Photo: Al Drago/Bloomberg via Getty Images

Semiconductors

Commerce Secretary Gina Raimondo said Thursday the Biden administration wants to use the <a class="gtmContentClick" data-vars-link-text="$52 billion CHIPS Act" data-vars-click-url="https://www.axios.com/2022/08/09/biden-chips-bill-signing" data-vars-content-id="6a8738b3-61d8-455f-8d01-71a9dbda8206" data-vars-headline="Raimondo: New funding will build two chipmaking &quot;clusters&quot;" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2022/08/09/biden-chips-bill-signing" target="_self">$52 billion CHIPS Act</a> to create two new &quot;clusters&quot; in the U.S. for manufacturing semiconductors.What&#x27;s happening: The Commerce Department plans to open applications next week for companies to seek funding under the law, passed last year.

Every 15 years or so, it seems, the U.S. economy rolls into a ditch — and the tech industry pulls something remarkable out of its labs. Here we are again!

State of play: Silicon Valley's favorite bank has failed, while its top firms continue to lay off hordes of workers — but at the same time, industry leaders foresee vast new growth spurred by AI.

Be smart: If that split-screen snapshot looks confusing, remember that tech's story is one long boom-bust cycle. Each new era gets built upon the ruins of the past.

Look closely at that story and you'll see that all of tech's great transitions have unfolded in times of financial turmoil.

Experts and economists agree that a key factor behind today's industry woes has been the Federal Reserve's inflation-countering interest-rate hikes.

But if you think today's 4.5% rates are high, turn your clock back to when the IBM PC was introduced in the summer of 1981: In that grim season, the Fed was charging borrowers around 17%.

The first great platform leap of modern times — from mainframes and minicomputers to the personal computers we  still use now — occurred as Fed chair Paul Volcker induced the sickeningly painful recession of 1981-82.

The rates Volcker set back then, duplicated today, would flatten 2023's overextended banks and businesses.

Tech's next leap, onto the global internet in the early '90s, happened as the U.S. struggled to restart its business engines after another recession — and Bill Clinton captured the White House under the banner, "It's the economy, stupid." 

The industry's third great shift in the late 2000s — as the iPhone's arrival heralded the smartphone era — took place in a landscape of business failure that we now call the Great Recession.

What's happening: Today, tech's optimists are casting ChatGPT and the new generation of AI it symbolizes as the industry's latest platform shift. 

They predict that, as in previous eras of business downturn and tech transition, innovation will slip the U.S. economic machine back into gear.

Yes, but: Tech's previous leaps have involved breakthroughs that promised to empower individuals, streamline businesses and summon entire new waves of startups into being.

For now, today's generative AI projects like ChatGPT, the new Bing, and image-creation tools like Midjourney and DALL-E require vast computing resources and cost a fortune to run. 

That means they're being developed directly by tech's dominant giant firms, or with their partnership and support.

Between the lines: Those big firms are the same ones that right now are laying off droves of employees.

Some of those cuts involve specialists in ethics, diversity and privacy who would otherwise have a chance to guide the early development of the technology in socially beneficial ways.

The big picture: Although tech has become an increasingly central economic player over the decades, the economy remains a much bigger machine, with retail, real estate, energy, health care and other sectors following their own dynamics.

Tech's innovations have changed how we work and play, but their impact on productivity remains a contested question among economists. 

The jury's still out on whether the generative AI boom will change the world as dramatically as proponents believe.

Tech industry builds in the ruins again

Silicon Valley's platform leaps always seem to happen in times of economic turmoil.

Illustration of hand cursor holding a hammer

Silicon Valley

Every 15 years or so, it seems, the U.S. economy rolls into a ditch — and the tech industry pulls something remarkable out of its labs. Here we are again!State of play: Silicon Valley&#x27;s <a class="gtmContentClick" data-vars-link-text="favorite bank has failed" data-vars-click-url="https://www.axios.com/economy-business/svb-silicon-valley-bank" data-vars-content-id="a7c2b805-9a59-4331-8380-0ca905336bfe" data-vars-headline="Tech industry builds in the ruins again" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/economy-business/svb-silicon-valley-bank" target="_self">favorite bank has failed</a>, while its top firms <a class="gtmContentClick" data-vars-link-text="continue" data-vars-click-url="https://www.axios.com/2023/03/14/meta-facebook-layoffs-jobs" data-vars-content-id="a7c2b805-9a59-4331-8380-0ca905336bfe" data-vars-headline="Tech industry builds in the ruins again" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/03/14/meta-facebook-layoffs-jobs" target="_self">continue</a> to lay off <a class="gtmContentClick" data-vars-link-text="hordes of workers" data-vars-click-url="https://www.axios.com/2023/01/20/tech-layoffs-2023-google-alphabet-meta-amazon" data-vars-content-id="a7c2b805-9a59-4331-8380-0ca905336bfe" data-vars-headline="Tech industry builds in the ruins again" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/01/20/tech-layoffs-2023-google-alphabet-meta-amazon" target="_self">hordes of workers</a> — but at the same time, industry leaders foresee vast new growth <a class="gtmContentClick" data-vars-link-text="spurred by AI" data-vars-click-url="https://www.axios.com/2023/02/17/chatgpt-ai-next-platform-tech" data-vars-content-id="a7c2b805-9a59-4331-8380-0ca905336bfe" data-vars-headline="Tech industry builds in the ruins again" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/02/17/chatgpt-ai-next-platform-tech" target="_self">spurred by AI</a>.

This week's tech headlines offer a compendium of data-loss nightmares:

The personal data of members of Congress was potentially exposed after hackers broke into a D.C. health-insurance system.

Police asked an Ohio businessman for video from his Ring doorbell camera, then issued a warrant for footage from more than 20 other cameras at his home and business.

Chinese-owned TikTok faces the threat of a ban over fears that the user data it collects could get fed to Beijing. 

And users are sharing their mental health woes with OpenAI's ChatGPT with no concern for confidentiality.

What's happening: Congress' long-running inability to pass a comprehensive privacy law has left online personal information vulnerable to be mined, hoarded and poached.

Why it matters: Virtually every major technology today opens data vulnerabilities that can cause havoc.

 "Data privacy" may sound like an abstraction to much of the U.S. public, but our national failure to set privacy rules can have very concrete consequences.

Zoom out: Legal experts and privacy advocates have long warned of the dangers of the U.S.'s failure to bring privacy law into the 21st century.

It means that government authorities have a freer hand to seize digital information as evidence.

Private companies are freer to gather and resell the personal information of their customers and users.

In both public and private sectors, the absence of tough rules governing data handling makes every breach and hack more potentially damaging. 

What's next:  The frenzy over generative AI is adding a whole new dimension of worry. 

AI experts fear that chatbots like ChatGPT trained on vast troves of internet text will already be seeded with an unknowable volume of personal data.

On its own, that's little different from what's available on Google or any other search engine today.

The difference is that ChatGPT and similar programs are capable of "remembering" and reusing information users share with them in unpredictable ways.

That means that details from any legal document, medical report,  financial calculation or other input that someone shares with these systems might turn up again — accurately or erroneously — in answers to someone else's query, with no indication of the original source.

Our thought bubble: Every time you type at ChatGPT, consider that you might be sharing secrets with a thing that has an impossibly vast memory — and doesn't have a clue what a secret even is.

Between the lines: There may well be ways to equip generative AI systems with guardrails to protect against this kind of unintended sharing. 

But right now developers have little incentive to build them, and the rest of us have no visibility into what data the systems are holding onto.

The bottom line: The faster technology advances and the more central it becomes in our lives, the more we'll miss having a good privacy law.

Data spills in the age of AI

Every new technology reminds us how badly we still need a good national law protecting privacy.

Privacy

This week&#x27;s tech headlines offer a compendium of data-loss nightmares:<ul><li>The <a class="gtmContentClick" data-vars-link-text="personal data of members of Congress" data-vars-click-url="https://www.axios.com/2023/03/08/health-data-breach-congress" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/03/08/health-data-breach-congress" target="_self">personal data of members of Congress</a> was potentially exposed after hackers broke into a D.C. health-insurance system.</li><li>Police asked an Ohio businessman for video from his Ring doorbell camera, then issued a <a class="gtmContentClick" data-vars-link-text="warrant" data-vars-click-url="https://www.politico.com/news/2023/03/07/privacy-loophole-ring-doorbell-00084979" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.politico.com/news/2023/03/07/privacy-loophole-ring-doorbell-00084979" target="_blank">warrant</a> for footage from more than 20 other cameras at his home and business.</li><li>Chinese-owned TikTok faces the <a class="gtmContentClick" data-vars-link-text="threat of a ban" data-vars-click-url="https://www.axios.com/2023/03/06/us-tiktok-ban-china" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/03/06/us-tiktok-ban-china" target="_self">threat of a ban</a> over fears that the user data it collects could get fed to Beijing. </li><li>And users are <a class="gtmContentClick" data-vars-link-text="sharing their mental health woes" data-vars-click-url="https://www.axios.com/2023/03/08/therapy-chatbots-chatgpt-ai" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/03/08/therapy-chatbots-chatgpt-ai" target="_self">sharing their mental health woes</a> with OpenAI&#x27;s ChatGPT with no concern for confidentiality.</li></ul>What&#x27;s happening: Congress&#x27; long-running inability to pass a comprehensive privacy law has left online personal information vulnerable to be mined, hoarded and poached.Why it matters: Virtually every major technology today opens data vulnerabilities that can cause havoc.<ul><li> &quot;Data privacy&quot; may sound like an abstraction to much of the U.S. public, but our national failure to set privacy rules can have very concrete consequences.</li></ul>Zoom out: Legal experts and privacy advocates have long warned of the dangers of the U.S.&#x27;s failure to bring privacy law into the 21st century.<ul><li>It means that government authorities have a freer hand to seize digital information as evidence.</li><li>Private companies are freer to gather and resell the personal information of their customers and users.</li><li>In both public and private sectors, the absence of tough rules governing data handling makes every breach and hack more potentially damaging. </li></ul>What&#x27;s next: The <a class="gtmContentClick" data-vars-link-text="frenzy over generative AI" data-vars-click-url="https://www.axios.com/2023/02/17/chatgpt-ai-next-platform-tech" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/2023/02/17/chatgpt-ai-next-platform-tech" target="_self">frenzy over generative AI</a> is adding a whole new dimension of worry. <ul><li>AI experts fear that chatbots like ChatGPT trained on vast troves of internet text will already be seeded with <a class="gtmContentClick" data-vars-link-text="an unknowable volume of personal data" data-vars-click-url="https://www.technologyreview.com/2022/08/31/1058800/what-does-gpt-3-know-about-me/" data-vars-content-id="cafdff83-1cc3-4197-9737-a3ef750d31d6" data-vars-headline="Data spills in the age of AI" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.technologyreview.com/2022/08/31/1058800/what-does-gpt-3-know-about-me/" target="_blank">an unknowable volume of personal data</a>.</li><li>On its own, that&#x27;s little different from what&#x27;s available on Google or any other search engine today.</li><li>The difference is that ChatGPT and similar programs are capable of &quot;remembering&quot; and reusing information users share with them in unpredictable ways.</li></ul><ul><li>That means that details from any legal document, medical report, financial calculation or other input that someone shares with these systems might turn up again — accurately or erroneously — in answers to someone else&#x27;s query, with no indication of the original source.</li></ul>Our thought bubble: Every time you type at ChatGPT, consider that you might be sharing secrets with a thing that has an impossibly vast memory — and doesn&#x27;t have a clue what a secret even is.Between the lines: There may well be ways to equip generative AI systems with guardrails to protect against this kind of unintended sharing. <ul><li>But right now developers have little incentive to build them, and the rest of us have no visibility into what data the systems are holding onto.</li></ul>The bottom line: The faster technology advances and the more central it becomes in our lives, the more we&#x27;ll miss having a good privacy law.

Scott Rosenberg

Stories

Tech industry builds in the ruins again

Silicon Valley pulls back from bank failure abyss

Data spills in the age of AI

Generative AI's money game

Raimondo: New funding will build two chipmaking "clusters"

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