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Author Invited to Give Speech at OpenAI Headquarters, Uses Opportunity to Trash AI to Their Faces
"I had a ball."
OpenAI projects ChatGPT ad growth amid market doubts
OpenAI, led by CEO Sam Altman, is working to grow its ChatGPT ad business amid skepticism about its ambitious revenue projections.
OpenAI has seen a 'resurgence' of interest in secondary markets.
For most of this year, investors couldn't get enough of Anthropic while ignoring OpenAI. Now the tide is turning following the release of new models.
Small Business Technology News Roundup: IBM Shares Crash, ChatGPT To Replace Wall Street Analysts
IBM shares collapse, OpenAI says AI will replace workers, Upwork says AI is reshaping freelancing, Microsoft will let you pause Windows 11 updates, Expensify consolidates travel billing
Joanna Stern: An open letter to OpenAI’s secret gadget
The ChatGPT maker is working on its own physical device, which is shrouded in mystery — and controversy.
CHAI seeks to support public health agency uptake of genAI
Its new national initiative will engage 2,000 public health practitioners to arrive at and pilot five key generative artificial intelligence use cases with large language model access through enterprise licenses donated by Anthropic and OpenAI.
OpenAI Employees Are Funding a Political Fight Against Their Own President
Researchers charged with studying AI’s risks are spending their own money to counter the political influence of one of their company's co-founders.
Why is OpenAI selling a ChatGPT basketball?
You may have heard that OpenAI released its first piece of hardware this week. You may not have heard about the ChatGPT basketball.
OpenAI Just Launched Its First Hardware Product—and It’s a Tiny Keyboard for Bossing Around AI Agents
The AI company teamed up with Work Louder on a programmable keyboard designed specifically for Codex.
Amid hardware legal battle, OpenAI releases a $230 keyboard for Codex
OpenAI, which is in the middle of a legal battle with Apple over hardware trade theft allegations, just released a light-up keyboard designed to be paired with its agentic coding app.
OpenAI launches a keypad for AI agents
Codex Micro is a remote control for your AI agents.
OpenAI's new $230 mini keyboard is for Codex power users
OpenAI launched Codex Micro, a shortcut keyboard for users of its AI coding product. It was engineered by Work Louder and priced at $230.
OpenAI's first branded hardware is... a light-up keyboard?
The Codex Micro is designed to monitor multiple agentic threads at a glance.
OpenAI finally launches hardware… for Codex
The collaboration with Work Louder is separate from OpenAI’s main hardware project, rumored to be some kind of smart speaker.
What to watch as Apple, OpenAI face off over trade secret claims
A lawyer says a lawsuit between OpenAI and Apple over trade secret theft could set the stage for a legal battle that may reshape tech industry norms.
OpenAI's first hardware device is reportedly a screenless speaker that can move
OpenAI's first hardware device is reported to be a screenless, AI-guided smart speaker that can move. Weird enough for you?
OpenAI may announce a ChatGPT smart speaker this year
And it’s working on even more hardware projects.
OpenAI's First Device Will Be Movable, Screenless Speaker Built as AI Companion
(Bloomberg) -- OpenAI's much-anticipated push into consumer devices is slated to begin with a mobile, screen-free smart speaker designed to be a new type of home computer for the AI era, according to people familiar with the matter.Most Read from BloombergUS Hits Iran With Strikes, Blockade as Trump Plans Hormuz ChargeTrump Shelves 20% Fee for Hormuz Cargo After Gulf PressureA Cocaine Bust in Spain Leads All the Way to Wall StreetUS CPI Falls for the First Time Since 2020, Core Gauge Flat'We Fal
OpenAI’s IPO Conundrum | AI & Business for July 14
Plus, Apple’s legal sparring, and Wall Street’s problem with AI drug discovery.
Apple is mad because OpenAI breaks Silicon Valley's unspoken rule
OpenAI is defying Silicon Valley's oldest playbook, helping explain why Apple is fighting so hard.
OpenAI Is Showing Kalshi’s World Cup Odds in ChatGPT
The partnership, a first of its kind for the artificial intelligence company, will use the prediction market’s data to power some search results about the soccer tournament.
Satya Nadella has issued a shocking warning to companies using AI
In a surprising blog post on Monday, Microsoft CEO is warning enterprises of the dangers of using proprietary models like Anthropic's and OpenAI's.
The Quintessential Trump-era Politician
In 2020, I wrote an article about collaboration and collaborators. The title was History Will Judge the Complicit, and it started with the story of two famous East Germans, Markus Wolf and Wolfgang Leonhard, who both landed in East Berlin just after the end of the war. Although they came from very similar backgrounds, the former stuck with the regime, eventually becoming its spy boss; the latter, horrified by the brutal reality of Soviet-style communism, escaped. By way of juxtaposition, I also wrote about Lyndsey Graham and Mitt Romney. These two men also made very different decisions when confronted by Donald Trump’s assault on the ideals that they had both grown up believing: A glance at their biographies would not have led many to predict what happened next. On paper, Graham would have seemed, in 2016, like the man with deeper ties to the military, to the rule of law, and to an old-fashioned idea of American patriotism and American responsibility in the world. Romney, by contrast, with his shifts between the center and the right, with his multiple careers in business and politics, would have seemed less deeply attached to those same old-fashioned patriotic ideals. Most of us register soldiers as loyal patriots, and management consultants as self-interested. We assume people from small towns in South Carolina are more likely to resist political pressure than people who have lived in many places. Intuitively, we think that loyalty to a particular place implies loyalty to a set of values. But in this case the clichés were wrong. It was Graham who made excuses for Trump’s abuse of power. It was Graham—a JAG Corps lawyer—who downplayed the evidence that the president had attempted to manipulate foreign courts and blackmail a foreign leader into launching a phony investigation into a political rival. It was Graham who abandoned his own stated support for bipartisanship and instead pushed for a hyperpartisan Senate Judiciary Committee investigation into former Vice President Joe Biden’s son. It was Graham who played golf with Trump, who made excuses for him on television, who supported the president even as he slowly destroyed the American alliances—with Europeans, with the Kurds—that Graham had defended all his life. By contrast, it was Romney who, in February, became the only Republican senator to break ranks with his colleagues, voting to impeach the president. “Corrupting an election to keep oneself in office,” he said, is “perhaps the most abusive and destructive violation of one’s oath of office that I can imagine.” In the wake of Graham’s unexpected death on Saturday, I wrote about him again. He was, in many ways, the quintessential politician of Trump’s Washington, a man who shifted 180 degrees. Graham had been a fervent American patriot, proud reserve officer and military lawyer; he became one of the most important defenders of a president who believes soldiers are “suckers and losers” and shows no respect for law of any kind. As his politics changed, his language grew coarser and his behavior grew worse: He urged Israel to “level the place” in Gaza, and insulted the Danish prime minister in Munich, prompting a colleague, Senator Elissa Slotkin, to issue an apology. Here’s an excerpt from the article, which you can read in The Atlantic (gift link here) Like his close friend John McCain, Graham believed that America should stand at the center of a broad democratic alliance. The few times I met him were in that context, at the Munich Security Conference or at other European-American gatherings, which he once attended with great regularity. He also took seriously the practice of American democracy at home. In a 2014 conversation with The Atlantic, he described himself as a pragmatic politician who eschewed populist slogans. “I know Washington is broken, but what’s broken about it is everybody yelling and nobody trying to fix it,” he said. “I’m trying.” When Donald Trump first appeared in U.S. politics, Graham recognized him immediately for what he was: the spokesman for an alien ideology, one radically different from the idealistic patriotism that Graham had practiced and preached since childhood. Trump privately mocked the military that Graham loved as nothing but “suckers and losers.” He put falsehoods, cynicism, and personal greed at the center of his politics, while expressing disdain for transparency, accountability, and democracy itself. In 2015, Graham described Trump as a “race-baiting, xenophobic, religious bigot” who should “go to hell.” Also as a “nutjob.” When Trump won, Graham understood, as did so many others, that he would have to make some important choices. For a while, he went silent. In the spring of 2016, I saw him at one of those conferences in Europe. He seemed too depressed to speak. But then, like many other Republicans—and, more important, like many other people who have lived under political occupation or experienced radical regime change—he made the decision to abandon his previous ideals, to bury the patriotism that was once so important to him, and to become, instead, a loud, opportunistic collaborator. As I wrote in 2020, it’s very hard to look in to anyone’s heart and to understand their motivations from the outside. But it does seem that Graham had a deep need to be relevant, to be in the game, to be a player, at any cost. And that, rather than any particular achievement, is what he will be remembered for. Continuing to monitor conflicts of interest, ostentatious emoluments, outright corruption and policy changes that will facilitate outright corruption. (Read my original article, Kleptocracy Inc and check out the SNF Agora Institute chart) June 27 Trump diverted funds from more than 900 projects nationwide—including safety upgrades at national parks—to finance beautification projects around Washington, including $700,000 used to fix a White House walkway. June 28 After a years-long Department of Justice investigation into Abbott Laboratories over its management of a baby formula facility where potentially deadly bacteria turned up enough evidence to criminally charge the firm, top department officials instead opted for a financial penalty—illustrating the department’s move away from strict corporate enforcement under the Trump administration. June 29 Defense Secretary Pete Hegseth stacked the Defense Policy Board—which is charged with providing independent national security recommendations to the Office of the Secretary of Defense—with Trump allies, including tech billionaire Marc Andreessen, who has invested in defense contractors like OpenAI and SpaceX, after purging the panel last year. Trump purchased between $1 million and $5 million worth of stock in Axon—which makes about 90% of US tasers—two weeks before ICE solicited bids for a $220 million taser contract. The White House unveiled limited-edition US passports for America’s 250th birthday, featuring a portrait of Trump overlaid on the Declaration of Independence. June 30 Trump made around $1.2 billion from his various crypto companies last year, including more than $500 million from World Liberty Financial and $600 million from sales of his meme coin. Trump is considering issuing 250 pardons to commemorate America’s 250th birthday. These are expected to be largely doled out through the Office of the Pardon Attorney’s informal network of intermediaries. White-collar defense attorneys say they can typically win pardons for clients for $2 million. Last year, Trump administration officials awarded a no-bid contract worth up to $500 million to Clark Construction for the White House ballroom—negotiations in which the president was directly involved. July 1 The Amazon MGM Studios documentary about Melania Trump earned the First Lady more than $10 million. Trump made hundreds of individual stock purchases worth as much as $12.8 million the day before his announcement pausing “Liberation Day” tariffs for 90 days sent the S&P 500 soaring nearly 10%—one of the largest single-day gains ever. Mar-a-Lago and Trump National Doral saw record surges in revenue during Trump’s first year in office, earning $77.5 million and $121.9 million respectively, compared to average annual revenues of $25 million and $75 million during Trump’s first term. Entities across the Persian Gulf paid more than $300 million to Trump’s businesses last year, including $263 million from the sale of half his stake in World Liberty Financial to a firm backed by Sheikh Tahnoon bin Zayed Al Nahyan, a top UAE royal and brother of the country’s president. Kash Patel failed to properly disclose his stock purchase of a Department of Justice contractor, MicroStrategy, worth up to $250,000 last year, despite laws requiring disclosure within 45 days of the trade. July 2 Trump has been directing administration officials to steer more government contracts—so far worth more than $2.4 billion—to Jeff Bezos’s Blue Origin aerospace firm, after Amazon gave $1 million to Trump’s inaugural fund, donated to the White House ballroom project, and reached a $40 million deal to license a Melania Trump documentary. Alongside the billions he made from cryptocurrency last year, Trump earned millions of dollars from real estate licensing fees, including $21 million from organizations in the UAE and $9.2 million in Saudi Arabia, along with smaller sums from merchandise sales, including $4.7 million from Trump Watches and $35,920 from 45 Guitar, a guitar brand endorsed by the president. House Democrats accused consultants tied to the Trump administration of financial fraud, alleging they gave prospective donors to America250—the bipartisan committee created by Congress to celebrate the nation’s semiquincentennial—the banking and routing numbers for Freedom 250, the White House’s fund for events like the UFC cage fight. Democrats also allege that Freedom 250’s CEO traveled to the World Economic Forum in Davos to solicit donations from foreign government officials and business leaders. The Trump administration’s proposed rollback of gun regulations would lift the prohibition on mailing handguns to individuals, a significant win for GrabAGun—the direct-to-consumer firearm retailer on whose board Donald Trump Jr. sits and in which he holds a 1.1% ownership stake. GrabAGun currently must rely on a middleman to transfer firearms to customers. Trump’s financial disclosure revealed that he made more than 21,000 securities trades during his first year back in office, growing his investment account to at least $858 million across stakes in around 1,600 companies, compared to the 13 total trades Joe Biden made during his entire presidency. July 4 Nearly 1 million people who bought the president’s meme coin—Trump Coin—collectively lost $3.8 billion on the token, while he walked away with $636 million. July 6 Shares of Dell closed up 4.4% after Trump recommended people buy the firm’s computers during a speech announcing the launch of Trump investment accounts for children, boosting the more than $1 million worth of shares the president owns in the company. July 9 Federal Reserve Chair Kevin Warsh named crypto investor and Trump ally Marc Andreessen to a task force aimed at modernizing the Federal Reserve, including rethinking its approach to inflation—a key factor keeping interest rates elevated. Palm Beach International Airport has officially changed its name to Trump International Airport—a move that will require Florida to pay royalties to the president’s family for licensing his name. I was there a few months ago, during a trip to Barcelona. The sculptures were a revelation, I’d never seen so many together before. Each one has its own personality. Enjoy the good weather, if you are lucky enough to have it. History Will Judge the Complicit The Quintessential Politician Autocracy Inc Open Letters, from Anne Applebaum is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
When Partners Become Competitors: Business Takeaways From Apple OpenAI Lawsuit
Vital business lessons from the Apple OpenAI lawsuit. When partners become competitors, protect employee taste as a business asset, avoid intellectual property tainting.
200 economists and executives warn on AI's job impact: read the letter
Executives and researchers from OpenAI, Google DeepMind, and Anthropic all signed the 88-word letter released on Monday.
Elon Musk and Sam Altman are fighting in public again
OpenAI CEO Sam Altman and SpaceX CEO Elon Musk do not like each other. That dislike was on full display on social media over the weekend.
OpenAI keeps losing the people in charge of AI safety
OpenAI just lost another leader of one of its safety teams. The company's safety and alignment teams have had high turnover in recent years.
What smart people are saying about Apple's lawsuit against OpenAI
Apple sued OpenAI on Friday, accusing the AI startup of orchestrating a campaign to steal trade secrets from iPhone maker.
OpenAI bets on families as ChatGPT goes deeper into households
ChatGPT is hiring a dedicated product manager to build experiences for families, caregivers, and older adults, according to a job posting.
A niche MacBook idea. Five minutes. One Codex app.
Business Insider's Stephen Council used OpenAI Codex to build a custom Mac clipboard app in minutes—no coding required.
Apple says OpenAI stole trade secrets. That sounds familiar.
Apple says OpenAI stole its trade secrets. Here's how Apple has faced similar accusations from rivals in the past.
Apple accuses OpenAI of playing dirty in the AI talent wars
Apple accused OpenAI of stealing trade secrets in a lawsuit filed Friday. OpenAI's recruiting techniques were put on blast.
Apple Calls OpenAI's Hardware Business 'Rotten To Its Core' In Trade Secret Theft Lawsuit
The lawsuit also names io Products, the hardware company led by Jony Ive.
Apple accuses OpenAI of telling recruits to bring Apple prototypes to interviews
Apple accuses OpenAI of telling recruits to bring confidential prototypes and hardware to job interviews in a new trade secrets lawsuit
Apple sues OpenAI over alleged trade secret theft
In a filing, Apple says former employees who left for OpenAI had access to its systems after leaving.
The whirlwind 72 hours of rival AI announcements
The major AI labs, from OpenAI to Meta, have released a parade of new products in the last three days. Here's your rundown.
With ChatGPT Atlas shutting down, here are the AI browsers people actually use
OpenAI is pulling the plug on its dedicated web browser, ChatGPT Atlas. Instead of investing in an AI browser with...
Fidji Simo: The health advice from Zuckerberg she wishes she'd listened to
Fidji Simo, who worked at Facebook before later joining OpenAI, said she regretted not taking up Mark Zuckerberg offer's of a year of medical leave as she struggled with or POTS.
OpenAI's No. 2 executive stepping down over health issues
Simo's departure removes one of OpenAI's highest-profile executives.
Top OpenAI executive Fidji Simo is stepping down
Fidji Simo, a top OpenAI exec, steps down amid a chronic illness. She is shifting to an advisor role after medical leave.
OpenAI is shutting down Atlas, but its AI browser ambitions are still growing
OpenAI is sunsetting its AI-powered browser after less than a year. But it's moving some agentic browsing features to its desktop app and a Chrome extension.
OpenAI wants its new tool to do your work for you and with you
Rebranded Codex promises independent workflows that can run "for hours if needed."
OpenAI Just Can’t Beat This TikToker
The dunks on OpenAI's Voice Mode will continue until the model improves.
OpenAI is discontinuing ChatGPT Atlas, its standalone desktop browser
ChatGPT Atlas, OpenAI’s standalone desktop browser, is being sunset in favor of the new ChatGPT desktop app. OpenAI released an...
Codex joins ChatGPT app as OpenAI releases GPT-5.6 models
OpenAI merges Codex into ChatGPT and launches GPT-5.6 models, aiming to enhance AI capabilities and compete in an increasingly crowded market.
OpenAI launches ChatGPT Work
OpenAI on Thursday unveiled ChatGPT Work, an agent in its popular chatbot designed to execute tasks across different applications and files, marking the startup's latest push into workplace automation.
OpenAI launches GPT-Live voice models that listen and speak simultaneously
OpenAI on Wednesday launched GPT-Live, a new family of voice models capable of listening and speaking simultaneously in real time.
OpenAI releases new voice models for more natural live conversations
OpenAI says its new voice mode can speak and listen at the same time, a key ability for live translation.
OpenAI upgrading ChatGPT with all-new voice mode experience, watch here
A shiny new model isn’t the only upgrade coming to ChatGPT this week. In addition to GPT-5.6’s release tomorrow, OpenAI...
Anthropic’s Political Risks Are Real, but OpenAI’s Loom Even Larger
The U.S. government’s targeting of Anthropic might not last—especially if political winds shift.
7+ Florida Politics Now: Discussing Liberty County High School’s newest addition
On this episode, we’re discussing Governor Ron DeSantis’ stop in Liberty County and the OpenAI lawsuit underway.
OpenAI’s Chief Futurist Is Leaving the Company
Joshua Achiam spent nearly nine years at OpenAI researching AI safety and made a memorable appearance in the Musk v. Altman trial.
Pre-Deployment Simulations Are Vital To Developing Generative AI That Can Best Provide Mental Health Advice
Pre-deployment simulation is a new technique from OpenAI. It can be used to better shape AI-led mental health guidance. An AI Insider analysis and scoop.
OpenAI proposes 5% stake to Trump administration to ease Washington pressure: report
Trump said in June that the U.S. taking an ownership stake in AI giants would be "a beautiful thing" and make American public "partners in this revolution."
OpenAI proposes handing Trump administration 5% stake, FT reports
OpenAI has discussed giving a 5% stake to the U.S. government, the Financial Times reported on Thursday.
Simon Says... Buy This OpenAI Mechanical Keyboard Thingy
It's a collaboration between OpenAI and Work Louder. It does something or other with Codex.
OpenAI is teasing new hardware… for Codex
OpenAI is releasing Codex hardware on July 15th.
OpenAI teases Codex-branded hardware collaboration coming, here's what to expect
OpenAI just teased an upcoming collaborative hardware project that’s set to launch in July. From the looks of it, OpenAI...
OpenAI sets up 'warroom' to fix Codex limit issues
OpenAI investigates Codex's usage limit depletion that's impacting some users. The company has reset user caps to address the problem.
AI As Conscious As That Toy Bird Is Thirsty
OpenAI and the like are using our fantasies about technology to bilk investors, if we want to protect the public we need to establish the difference consciousness and something mimicking it
OpenAI launches limited preview of GPT-5.6 at US government's request
OpenAI said they were complying as part of its agreement with the Department of Defense, which allows the department to use its AI models.
Enterprise AI spending grows, OpenAI leads, RBC reveals
RBC's latest CIO survey finds no AI token panic, no SaaSpocalypse, and surging enterprise AI spending, led by OpenAI.
OpenAI triumphs in brutal $26M political fight against Anthropic
Bores quickly became the pawn between the two California AI companies.
OpenAI Touts Progress in 19-Week-Old Ad Business
OpenAI is promoting progress in what it expects to become a $100 billion ad business. The artificial intelligence (AI) startup is making its inaugural
Hollywood is bending the knee to OpenAI
Buy Luca Guadagnino’s Sam Altman film, you cowards.
Mamdani and AI industry flex political power in New York, plus more to watch in Tuesday's primaries
Two factions in the AI industry are clashing in a Democratic primary for a U.S. House seat. New York Assemblyman Alex Bores, a pro-regulation candidate, faces opposition from a group funded by OpenAI investors. The group spent over $7 million on ads against him. In response, groups partly backed ...
At Its First-Ever Cannes, OpenAI Says ‘We Are Clearly In The Advertising Business Now’
Bonjour, ChatGPT ads. OpenAI’s inaugural Cannes Lions appearance doubled as a coming‑out party for its baby ad business.
What Amazon's first ChatGPT ads say about its AI ambitions
Amazon buys ChatGPT ads to reach more shoppers while limiting OpenAI's access to its shopping data.
Amazon dropped Luca Guadagnino's OpenAI film, months after partnering with OpenAI
Could "Artificial," starring Andrew Garfield as Sam Altman, still see the light of day?
The Most Important AI Company Isn't OpenAI. It Might Just Be This Under-the-Radar Business
While everyone is debating which model is best, one AI chip company is focused on something different.
Amazon no longer releasing Sam Altman biopic 'Artificial' starring Andrew Garfield
Amazon announced that it will no longer release Luca Guadagnino's Sam Altman biopic 'Artificial' starring Andrew Garfield. The news comes four months after OpenAI announced a strategic partnership with Amazon.
Amazon drops Sam Altman movie months after OpenAI investment
Luca Guadagnino's "Artificial," a movie about Sam Altman, has been dropped by Amazon MGM Studios. Earlier this year, OpenAI and Amazon deepened ties.
Why everybody wants to work at Anthropic or OpenAI
Anthropic and OpenAI are the new top-end employers. We spoke to applicants, Big Tech workers, and job coaches about why they're so in demand.
Microsoft (MSFT) Is Building A Billion Dollar AI Business In China
Microsoft (NasdaqGS:MSFT) is building a large AI and cloud business in China, supplying OpenAI models through Azure to major local technology companies. ByteDance is reported to spend over US$1b annually on Microsoft AI and cloud services, with Ant Group, Meituan, and Tencent also using Microsoft models. Microsoft has emerged as a key provider of OpenAI technology in China at a time when several US competitors are not active in the region. For investors watching Microsoft, this growing AI...
OpenAI's health care threat is getting real
Generalized LLMs outperform specialized models, a new study finds.
OpenAI's Karan Singhal on how he's driving ChatGPT health advancements
Researcher Karan Singhal drives OpenAI's goal to elevate ChatGPT's health advice, reaching millions of users weekly for wellness guidance.
A Google veteran who founded character.AI is jumping to OpenAI
Noam Shazeer, a co-lead at Gemini and the founder of Character.AI is leaving Google to join OpenAI in the latest AI talent war move.
Microsoft Makes Big AI Inroads in China by Selling OpenAI Models
Microsoft Corp. has built a big business selling AI models to Chinese companies despite the growing rivalry between the US and China over artificial intelligence.
OpenAI launches scheduled tasks in ChatGPT, details here
OpenAI is updating ChatGPT with a new scheduled tasks feature. The new ability is rolling out starting today. Scheduled tasks...
Anthropic CEO Dario Amodei throws shade at Sam Altman
Anthropic CEO Dario Amodei, who famously left OpenAI in 2020, says he's "at peace" on where things stand with his chief AI rival.
OpenAI Just Started Selling What Your Consulting Business Sells
OpenAI and Anthropic just launched their own AI consulting firms. Here is what independent advisors and small firms should do to keep their clients.
Japan's tech business SoftBank rolls out OpenAI 'patches' against cyberattacks
TOKYO (AP) — Japanese technology giant SoftBank Group Corp. is launching a service using OpenAI technology to protect against the looming threat of cyberattacks, both companies said Tuesday.
Japan's tech business SoftBank rolls out OpenAI 'patches' against cyberattacks
Japanese technology giant SoftBank Group Corp. is launching a service using OpenAI technology to protect against the looming threat of cyberattacks
Japan's tech business SoftBank rolls out OpenAI 'patches' against cyberattacks
Japanese technology giant SoftBank Group Corp. is launching a service using OpenAI technology to protect against the looming threat of cyberattacks. Chief Executive Masayoshi Son called Japan’s...
Businesses feeling strain from AI spending, so OpenAI reportedly weighs price cuts
OpenAI CEO Sam Altman acknowledged the cost concerns he’s hearing from customers, with some corporate users blowing through their annual AI budgets in a fraction of their fiscal years. “That went from, at the beginning of this year, an iss…
States launch investigation into ChatGPT's impact on young users
New York State Attorney General Letitia James served OpenAI a subpoena on Friday seeking a wide range of documents, The Wall Street Journal reported.
AI leaders shift how they talk about AI job impact
OpenAI CEO Sam Altman said the focus on maintaining the "human" part of roles means the AI job wipeout some expected is going to happen.
A Price War Is Brewing Between OpenAI and Anthropic — And It Could Make AI a Lot Cheaper for Your Business
OpenAI is weighing drastic cuts to what it charges for AI tokens. It expects Anthropic to do the same.
Trump’s strange flirtation with AI socialism, explained
Uncle Sam and OpenAI may go into business together.
Businesses feeling the pain from AI spending, so OpenAI reportedly weighs price cuts
An artificial intelligence price war between OpenAI and Anthropic might be brewing, with The Wall Street Journal reporting that OpenAI, the maker of ChatGPT, is considering "drastic" price cuts for business clients.
As OpenAI leans into enterprise business, Apple and Google set sights on the masses
OpenAI's aggressive push into the enterprise, where it competes with Anthropic, coincides with efforts by Apple and Google to bring advanced AI to consumers.
OpenAI and Anthropic keep warning about a future they're building
Both Anthropic and OpenAI have released papers warning that frontier models are being deployed before government regulation can catch up.
OpenAI suspects China-linked campaign tried to sway data center debate
OpenAI said the effort "sought to exploit and amplify existing public concerns about energy prices and local impacts of data center development."
Large language model helps radiology department boost patients’ report comprehension
Emory University has utilized OpenAI’s GPT-5 to create LLM-produced radiology report summaries, clickable terms with embedded educational content, and AI-generated videos.
Chip stocks bounce back as OpenAI files for Wall Street float
Rolling coverage of the latest economic and financial news
Perplexity stays course on 2028 IPO amid OpenAI, Anthropic IPOs
Investors are closely watching whether OpenAI and Anthropic can justify their lofty valuations.
OpenAI files confidential S-1, but says IPO 'may be a while'
OpenAI has filed its confidential S-1, the first official step on its path to a blockbuster IPO. The ChatGPT-maker announced the filing on Monday.
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
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