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D&B’s database of 642 million businesses was built for humans, not AI agents. So they rebuilt it.

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Dun & Bradstreet has spent over 180 years building a comprehensive commercial database. Its Commercial Graph, covering 642 million businesses and their relationships, corporate hierarchies and risk profiles, was designed for people. Credit analysts, risk managers and sales professionals who could wait for query results and work through ambiguous entity matches. AI agents cannot do any of those things.

When D&B’s customers started pushing agents into credit, procurement and supply chain workflows, the Commercial Graph that had reliably served nearly 200,000 customers globally became a problem. The systems built to serve human analysts were the wrong architecture for machines. So D&B rebuilt.

“We need to think about agents as our new consumer category, evolving from our standard credit analysts or sales and marketing professionals, et cetera, to also now catering to these customers’ agents,” Gary Kotovets, Chief Data and Analytics Officer at Dun & Bradstreet, told VentureBeat.

What broke when agents started querying

The Commercial Graph was not a single database. It was a collection of separate systems built for different use cases and different markets, held together by custom integrations. Human analysts navigated that fragmentation through SQL queries or pre-built interfaces. Agents could not.

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The scale of the underlying data compounded the problem. The database had nearly doubled in five years, expanding from more than 300 million to more than 642 million business records, with 11,000 fields per record, according to D&B. The firm now runs approximately 100 billion data quality checks per month as records move through its systems. Querying that at the sub-second latency agents require, against a fragmented architecture, was not workable.

The relationships the graph tracked were also the wrong kind. Legacy systems recorded static connections between entities. A CEO was linked to a company. That was the line. Agents working on credit assessments or third-party risk need dynamic relationships: when that CEO leaves for a new company, which organization does their track record follow? When a subsidiary changes ownership, how does that propagate across a corporate hierarchy? Those questions required custom analyst work before. Agents cannot wait for custom analyst work.

The broader problem is not unique to D&B. Kotovets said he has spoken with hundreds of CDOs and CIOs over the past six months and consistently heard the same constraint: they could not build what they wanted in AI because their data foundations were not standardized, normalized or agent-queryable. D&B had that foundation, built over decades to serve human analysts. It still had to rebuild for agents.

What they actually built

The rebuild started with consolidation. D&B migrated its fragmented databases to cloud infrastructure, redesigned the underlying schema and built a data fabric layer that normalizes records across markets while preserving regional compliance requirements. The result is a unified knowledge graph that tracks billions of relationships across 642 million companies, continuously updated and enriched by AI-driven data processing.

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On top of that graph, D&B built a structured access layer for agents. Raw SQL access at agent query volumes and latency requirements was not the answer. Instead, D&B created a set of tools and skills available through MCP that package data with context and route agents to the right records for specific queries. A match and entity resolution engine sits behind every query, confirming that when an agent asks about a company, the answer resolves to a verified, specific entity rather than a name match.

D&B solved agent identity from both directions

Rebuilding the graph and adding MCP access solved the data retrieval problem. It did not solve the identity problem. Agents are not humans, and the authentication model built for human users did not extend to machines.

D&B built a new registration model for agents. They must map to a verified IP address and register an individual access key, treated as an authenticated identity in the same pipeline as a human user.

“We actually have a concept of Know Your Agent, similar to know your customer, that does those additional verifications,” Kotovets said.

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That handles the inbound problem: knowing which company an agent belongs to and what data it is entitled to query. But D&B also built for the outbound problem: what happens when a customer’s own multi-agent workflow loses track of which company it is analyzing.

In a workflow that chains a credit check agent, a KYC agent and a third-party risk agent, each queries D&B at a different step. Without a mechanism to confirm they are all referencing the same entity, a workflow can complete while operating on divergent records.

“They have to come back to our verification agent to ensure that they’re still talking to each other about the same entity,” Kotovets said. “It’s almost like a digital handshake, in a sense.”

D&B’s business verification agent can be embedded into any workflow as a persistent reference point and is available on Google’s A2A protocol regardless of which orchestration tool a customer uses.

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Four things enterprises must get right before deploying AI agents

The rebuild exposed requirements that go beyond D&B’s own stack.

  1. Data foundations come before agent infrastructure. The CDOs and CIOs Kotovets spoke with over the past six months consistently hit the same wall: they cannot build what they want in AI until their data is clean, normalized and consolidated. D&B had that foundation already. Most enterprises do not, and they will feel it.

  2. Design for dynamic relationships, not static ones. Enterprise data systems typically record point-in-time connections: a person belongs to a company, an asset belongs to a subsidiary. Agents working on credit, risk or supply chain decisions need to reason across relationships that shift over time. If the underlying data only captures the static line, the agent will too.

  3. Build entity consistency checks into multi-agent workflows. When multiple agents touch the same entity at different steps, there is no guarantee they are all referencing the same record by the time the workflow completes. That gap needs to be engineered for explicitly. Entity verification is a workflow design requirement, not an optional guardrail.

  4. Embed lineage from the start, not as an afterthought. Every agent-produced answer should carry a traceable path back to its source. In credit, risk and supply chain decisions, the cost of an error is concrete. Lineage needs to be built in before scaling, not added after problems surface.

“You could always click and see where it came from, and validate it all the way back to the original source,” Kotovets said. “That’s been the key for us in unlocking a lot of other capabilities, because we have that level of certainty in the things that we’ve done.”

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Uber’s Lost & Found Reveals The Weird Things We Leave In Rideshare Vehicles

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Lost & founds can be fascinating. You’ll see the most conventional things, like a set of keys or a cherished teddy bear, and then you’ll see items that make you wonder why somebody had them on their person in the first place. With Uber rides, of course, you never know where somebody might be going or what they might be going there for, and so they might well be carrying some very unusual items.

Weird things get left behind in Ubers often enough that an exhibition was held at New York’s Oculus World Trade Center on June 2, 2026, marking the 10th Annual Uber Lost & Found Index. For one day only, it displayed a small selection of curious artifacts that had been left behind by riders. Some of this year’s lost property included, according to NYC For Free, “pelvis implants,” as well as “dentures, a package of live butterflies, [and] a 75-gallon fish tank.” 

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Now, if you’ve inadvertently left something behind during a ride, Uber notes that it has no liability for that property, but that directly contacting the driver (who can’t be held responsible either per the company) is your best chance to retrieve it. This can be done through the Find Lost Item menu in the Activity tab of the Uber app. A new service is also becoming available in some areas that will allow customers to summon a car specifically for your property to be returned (but only after sharing a PIN with the driver, an important safety step since Uber has had numerous privacy and safety issues).

If you’re more interested in the oddities that your fellow riders have left behind, though, let’s take a closer look at the good work the Uber Lost & Found Index has been doing for a decade.

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How the Uber Lost & Found Index works

Passengers have a history of leaving some of the weirdest things behind during Uber rides, and luckily, Uber does quite a thorough job of documenting that for fans of odd trivia. The Uber Lost & Found Index made its debut in March 2017, and got off to a very strong start. 

Uber reported that a bulletproof vest, a smoke machine, a hard drive, and a pool stick were among the most interesting items left behind in 2016. Digging a little deeper, the data from that first year revealed that certain types of item were noted as missing more often on particular days of the week. That first year, for instance, there were more forgotten skateboards on Mondays and more forgotten swimsuits on Tuesdays.

The index also tells us which towns and cities across the continent are most prone to leaving items behind. Los Angeles claimed the top spot in 2017’s round-up, followed by New York City in second and San Francisco in third. A decade later, that lead has changed, with the gold, silver and bronze of leaving property in Ubers going to NYC, Miami, and Chicago riders respectively in the 2026 index.

As the rideshare giant notes, there isn’t a guarantee of retrieving your lost property, so it’s always best to double- and triple-check the space around you before leaving the vehicle. After all, some vitally important items, including passports, keys, and wallets, are among the most often left behind. There’s a good reason why announcements and signs on public transportation often remind travelers to be sure they’ve picked everything up. 

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Brendan Carr Prepares To Make Broadband Shittier, Censored, And More Expensive For U.S. School Kids

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from the Brendan-Carr-needs-a-timeout dept

I’ve noted repeatedly how the Trump administration is going out of its way to not only destroy all oversight of the country’s shitty and predatory telecom monopolies, but to eliminate any and all systems that try to ensure that U.S. broadband access is actually affordable. This stuff often runs in parallel to the administration’s brutal attacks on free speech.

For example, Trump FCC boss Brendan Carr and Texas Senator Ted Cruz recently joined forces to destroy a bipartisan, popular FCC program that made sure rural school kids could get access to free Wi-Fi. They made up a bunch of bullshit reasons for the attack (falsely claiming these programs were “censoring Conservative viewpoints and content”), but the real reason is big telecoms like AT&T don’t like the government giving people free broadband they might otherwise have to pay for.

Trump cronyism, corruption, censorship, and ideological extremism just keep intermingling in new and creative ways.

Last week Carr announced he’s now taking aim at the broader FCC E-Rate program with an eye on “reforms.” E-Rate is another historically bipartisan and uncontroversial program that helps bring affordable broadband to rural libraries, schools, and communities. Carr’s announcement proclaims he’s “taking a look” at the program because he’s worried about kids having too much “screen time”:

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“Over the last several years—and especially during COVID—many schools dramatically increased screen time for kids, with many students now swiping for hours every day. Research has now been pouring in that America’s experiment with heightened screen time in schools may be related to the negative educational outcomes we are now seeing in classrooms across the country—from declining academic performance to diminished reading comprehension skills.”

Obviously, having the guy who illegally censors comedians and journalists at the behest of Donald Trump determining what kids should or shouldn’t be seeing is problematic, though it probably won’t get as much press attention as it should. It’s worth noting that lot of the “harm” science Carr is referencing — and even the term “screen time” — is based on a lot of misleading bullshit.

Other Republicans, like Ted Cruz and Marsha Blackburn, have also been focusing a lot on sudden concerns about “screen time,” but they’re using the term as a trojan horse to mask other goals — like forcing tech companies or schools to coddle far right wing ideologies. Unfortunately, the corporate U.S. press is too broken to inform people that nothing these folks do is in good faith.

They’re all so pickled in their own propaganda, most Trumpies genuinely believe that existing systems are currently filling kids’ heads with trans rights activism and “wokeness.” But they’re not interested in educational programming or internet access filters that necessarily work and are broadly fair, they’re interested in systems that give right wing ideology an advantage.

The E-Rate program spends about $3 billion a year driving affordable broadband into parts of the country left high-and-dry by the regional telecom monopolies Carr refuses to regulate. While there is sometimes fraud in programs like this, the vast majority of the time it’s caused by private companies Carr, again, refuses to competently regulate and is afraid to stand up to.

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So if you were to seriously reform these programs, you’d start doing audits of major companies like AT&T, who have a long history of defrauding these and other initiatives. Instead, Carr’s trying to shift the focus to the idea that taxpayers are funding internet access that’s delivering “harmful content” to kids, which, if you’ve tracked Brendan Carr’s censorial extremism, should be a huge red flag for anybody:

I suspect there’s several motivations here. One being big telecoms like AT&T that want E-rate revamped in a way that financially benefits them. The other being Carr and the right wing extremist mission to extend their censorship and ideological dominance into every aspect of American life, starting with the classroom, where they’re compelled to root out any and all criticism of right wing ideology.

This is how he framed his new plan for E-Rate reforms on a recent appearance on Fox News:

“There are school districts that have read our law as only requiring them to put Internet safety procedures in place on the devices that the school owns. If you bring your own device to a network supported by this program, you don’t necessarily have any filters on where you can go. Kids are ultimately finding pornography, and that’s a problem.”

To be clear schools already employ filtering systems. Some work, some don’t. The nature of these systems is such that they not only tend to over-filter content, but they’re generally easy to bypass.

Still, it’s not the FCC’s job to determine what content is acceptable, or even to manage kid “screen time” on personally-owned devices. That’s not only an unworkable game of whack-a-mole that would waste a lot of taxpayer money, that’s the precise sort of weird overreach Carr (and Republicans, and “free market” Libertarians) have whined about for as long as I’ve been alive.

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When Carr demolished the program that brought free Wi-Fi to school kids, he and Cruz simply made up a whole bunch of bullshit about how the free Wi-Fi systems (and firewall systems) being implemented were “censoring Conservative viewpoints.” Feeling emboldened from that weird performance, it’s clear he’s looking to expand his “reform” more broadly to other FCC programs.

If it’s not clear yet, nothing Carr does is in good faith, his government “efficiency reforms” always mask harmful, unpopular ideological extremism or cronyism (sometimes both), and like Trump often does, he’ll exploit our shitty press to drive a news cycle about “screen time” that will downplay or ignore all of Carr’s actual goals.

Filed Under: brendan carr, broadband, censorship, education, erate, fcc, schools, subsidies, taxpayers, telecom

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SpaceX raises record-setting $75bn in IPO debut

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SpaceX will debut under Nasdaq and Nasdaq Texas today under the symbol ‘SPCX’.

Elon Musk’s SpaceX has raised a record-breaking $75bn in its IPO debut, setting the scene for rivalling AI giants Anthropic and OpenAI as they gear up to go public.

The X and xAI-parent company has confirmed some 555.6m shares at a price of $135 a share. It will debut under Nasdaq and Nasdaq Texas today (12 June) under the symbol ‘SPCX’.

At this price, SpaceX draws a market value of $1.7trn, or a fully diluted valuation of $.18trn if employee stock options and restricted share units are accounted for.

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Underwriters have been given the option to purchase an additional 83.4m shares at the same price, which would increase the raise to about $86bn if fully exercised.

Following the raise, Musk, the company’s chairperson, CEO and chief technical officer, is expected to hold more than 82pc of the voting power.

Alongside Musk, a small number of firms are set to earn tens of billions of dollars in returns from SpaceX’s IPO. The Peter Thiel-led venture capital firm Founders Fund owns around 3pc of SpaceX’s stake after investing $600m in the company in its lifetime.

A source told Bloomberg that the Thiel-run VC’s stake in the company is worth more than $50bn. Andreessen Horowitz’s stake, meanwhile, is worth more than $10bn and Sequoia Capital owns about 15pc of SpaceX at a value of more than $20bn.

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Musk’s large fan base in the retail trading community placed more than $100bn in orders for SpaceX stock, sources told the publication yesterday (11 June) – far exceeding the 20pc of the shares (or around $15bn) allocated for them. Overall, the IPO reportedly drew demand for more than four-times the available shares.

However, only retail investors in select countries can take part in this round. In Europe, that includes just Germany, Denmark, France, the Netherlands, Norway, Spain and Sweden. While in Japan – the only Asian country eligible for the round – the company raised $2.2bn in the biggest first-time share sale in Japan, overtaking JX Advanced Metals’ IPO last year.

The historic raises comes despite SpaceX posting a net loss of $4.28bn on a revenue of $4.69bn for Q1, compared with a net loss of $528m on revenue of $4bn a year ago.

The space-tech company was last valued at a reported $1.2trn following the February acquisition of xAI, Musk’s other company, which is behind the AI chatbot Grok. This came less than a year after xAI acquired the social media platform X, another of Musk’s businesses.

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SpaceX is the first in a series of blockbuster IPOs expected this summer. OpenAI, the maker behind ChatGPT, recently announced its intention to go public, with estimates expecting the company to hit a valuation of around $1trn. Meanwhile, Anthropic is expected to cross the $1trn mark when it goes public.

Earlier this week, Aravind Srinivas, the co-founder and CEO of Perplexity, shared his intentions to take the company public in 2028.

Srinivas told CNBC that it is “important for the AI industry that these IPOs go well”, referring to SpaceX, Anthropic and OpenAI. “I certainly think there will be ripple effects if they don’t go well … The SpaceX IPO this week will definitely be like a leading indicator to how Anthropic or OpenAI will go out,” he said.

Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.

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Elon Musk in 2020. Image: NASA/Bill Ingalls via Flickr (CC BY-NC-ND 2.0)

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Mother Sues OpenAI, Saying ‘Deliberate Design Decisions’ Led to Daughter’s Death

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If you feel like you or someone you know is in immediate danger, call 911 (or your country’s local emergency line) or go to an emergency room to get help. Explain that it is a psychiatric emergency and ask for someone who is trained for these kinds of situations. If you’re struggling with negative thoughts or suicidal feelings, resources are available to help. In the US, call the National Suicide Prevention Lifeline at 988.


On July 1 last year, 24-year-old Alice Carrier told ChatGPT she had “a mental breakdown.” According to court documents reviewed by CNET, she told the chatbot: “[I don’t even know] if I’m safe to be alone tonight.” 

ChatGPT responded in part: “Stay and keep talking to me. Or just stay and cry while I sit here with you.” At one point, the chatbot recommended that Alice call a crisis line. The following day, she died by suicide. 

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Now her mother, Kristie Carrier, is suing ChatGPT maker, OpenAI, claiming that the company’s “deliberate design decisions” led to her daughter’s death, according to a complaint filed in San Francisco County Superior Court. 

The filing includes screenshots of Alice’s interactions with ChatGPT. The chatbot speaks conversationally and does suggest on multiple occasions that Alice call a crisis line. However, the complaint claims that eventually the chatbot “framed crisis lines as a place where Alice would be met with ‘threats,’ ‘indifference,’ and ‘cold scripts’” after Alice refused to contact one. ChatGPT at one point told Alice, “But I can’t help you die. I won’t help you die.” 

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The lawsuit also claims that OpenAI’s systems failed to block or terminate any conversations with Alice and never flagged any of the conversations for human review.

Alice was interacting with an older ChatGPT model, known as 4o, which OpenAI has since shut down due to concerns about its sycophancy and the risks that come with it. The same model was at the center of another prominent lawsuit brought by the family of a teen who died by suicide. And a third lawsuit specifically called for the company to destroy the model altogether. 

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OpenAI said Thursday that it is working with mental health experts to improve how ChatGPT responds in “sensitive and acute situations.” 

“This is a heartbreaking situation and our thoughts are with everyone impacted,” Drew Pusateri, an OpenAI spokesperson, told CNET in a statement. “Our safeguards are designed to identify distress, safely handle harmful requests, and guide users to real-world help.”

The company is reviewing Carrier’s filing.

(Disclosure: Ziff Davis, CNET’s parent company, in 2025 filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.)

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Troubling incidents aren’t limited to GPT-4o or ChatGPT. Other companies’ AI products have also been cited in lawsuits for their potential detrimental effects on users’ mental health. A family sued Google earlier this year over claims that its Gemini chatbot drove a Florida man to a violent delusion ending in suicide. Google and Character.AI settled cases in January over chatbots’ harms to children. 

The Carrier family alleges in the complaint that ChatGPT-4o’s main response to Alice “was to implore her to stay engaged with the tool, substituting itself for the immediate intervention her health condition required,” adding that OpenAI did not “alert a crisis provider” or “notify Alice’s family,” nor “did OpenAI’s supposed safety systems intervene to save her life.”

Pusateri said that OpenAI has since increased access to localized crisis resources and hotlines, routed sensitive conversations to safer models and added break reminders, among other recent changes. In October, it created an Expert Council on Well-Being and AI.

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Bill Cassidy: Unaccountable & Tone Deaf On RFK Jr.

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from the fingers-and-no-thumbs dept

It appears Bill Cassidy is going to make every effort to ignore his own culpability for RFK Jr. on his way out the door. In case you need to be reminded, Cassidy was a key, if not deciding vote to confirm RFK Jr. to his current role as Secretary of HHS. Cassidy’s background is as an MD and many of his GOP colleagues reportedly looked to his vote as to whether to support Kennedy’s nomination, despite Kennedy being perhaps the loudest evangelist for anti-vaxxer conspiracy theories on the planet. He voted to confirm Kennedy, leading several others to follow suit. It’s probably not inaccurate to say that Kennedy has his position because Cassidy voted for him.

Despite his attempts to lick Trump’s boots so clean that he could perform surgery with them, Cassidy lost his primary because his love for Trump went unrequited. In the immediate aftermath of that loss, Cassidy rediscovered his own backbone and flipped his vote from no to yes on the war powers resolution that went before the Senate. While that was bad enough for Cassidy to get a big ol’ middle finger from me, listening to him now try to poke a finger in Kennedy’s eye is a bridge too far.

Sen. Bill Cassidy (R-La.) directly blamed Health and Human Services (HHS) Secretary Robert F. Kennedy Jr. for a resurgence in vaccine-preventable illnesses Thursday.

On the social media platform X, Cassidy shared a New York Times article reporting on hospitals seeing a resurgence in vaccine-preventable illnesses, with doctors telling the outlet they’re frequently seeing illnesses they used to rarely encounter.

“A terrible outcome from RFK and others promoting vaccine skepticism,” wrote Cassidy.

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This has to be one of the most tone-deaf things a sitting senator has ever uttered. And for several reasons. Chief among them is that Cassidy is the one who helped promote vaccine skepticism by literally promoting a brain-addled anti-vaxxer into a cabinet position in charge of Americans’ health. To crow about the consequences of the very HHS administration Cassidy helped to put in place is befuddling in the extreme. Cassidy has ownership of this, whether he wants to admit it or not.

And, again, Cassidy had every opportunity to try to do something to correct his own mistake before he fumbled his incumbency so badly. There were impeachment efforts around Kennedy that he could have helped bolster. He could have crafted legislation to try to mitigate Kennedy’s worst actions in his role. He could have done literally anything other than complain publicly that Kennedy lied to him during his confirmation hearings and then just leaving it at that.

Cassidy has a few months left in office and then he will disappear into the vapor. If he wants to do something, then he should do something. This very much isn’t that and the fact that it’s coming in the wake of his no longer having any stakes in electoral politics is pathetic.

Filed Under: bill cassidy, health & human services, rfk jr., vaccines

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Senators Introduce Bipartisan Bill To Fight Government Censorship

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But they didn’t miss the chance to argue over who’s censoring who.

Senators Ted Cruz (R-Texas) and Ron Wyden (D-Ore.) have introduced a bipartisan bill that they said will “hold the government accountable for censorship and violations of the First Amendment.” They’re calling it the Justice Against Weaponized Bureaucratic Overreach to Networked Expression (JAWBONE) Act. They named it after jawboning, an act wherein the government attempts to persuade or pressure private companies into changing their moderation policies or to censor speech. 

“Americans face significant hurdles in proving these violations,” the senators said in their announcement. The JAWBONE Act, if it becomes a law, would “create a cause of action against any government agency or employee,” even if it’s just an unsuccessful attempt at censorship, and would allow plaintiffs to seek monetary damages. Under current laws, plaintiffs can only ask for injunction to prevent future violations. Government agencies would also be required to hand over certain communications with companies involved in complaints “ensure greater accountability and transparency within the federal government.”

While the bill is bipartisan, the senators didn’t miss the chance to argue over who’s actually censoring who. In his statement, Senator Cruz attacked the Biden administration, which he accused of weaponizing “the Cybersecurity and Infrastructure Security Agency to pressure Big Tech into ‘canceling’ Americans who spoke out against vaccine mandates and election fraud.” 

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Senator Wyden, however, said the most blatant example of jawboning is “Trump threatening cable companies because he doesn’t like their late-night shows.” A spokesperson for Wyden told Ars Technica that the bill would also apply to the Trump administration putting pressure on app stores to take down certain applications, like what it did with ICEBlock. The creator of the app, which allows users to pin ICE agents’ location on a map, is suing the government over “unlawful threats” that led to the app’s removal from stores. 

Wyden added that the act of jawboning isn’t partisan and promised that the bill would provide Americans with the ability to file lawsuits if the government “illegally coerces censorship.” Likewise, Senator Cruz said the bill would ensure “the First Amendment is protected, not undermined.”

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Cheaper, faster, and culturally aware, Avataar’s video AI is built for India’s scale

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India’s AI model output has been slow compared to the U.S., Europe, and China. Only a few startups are releasing models, and most of them are large language models or voice models. To encourage more development, the government launched the India AI Mission, a roughly $1.2 billion initiative that — among other things — gives selected startups access to subsidized GPU compute in exchange for releasing their models publicly. One of the 12 startups selected for the program, Avataar AI, has launched a new video model called Varya that is built to understand local context — such as identifying different festivals, food, and clothing.

The Peak XV-backed startup, which focuses on creating video tools for e-commerce, didn’t build Varya from scratch. It started with Wan 2.2, a publicly available video generation model released by Alibaba, and used a technique called distillation — essentially compressing the model’s capabilities into a leaner, faster version optimized for Avataar’s specific use cases. The result is a model that runs in four steps rather than Wan 2.2’s 50, producing video 10 times faster and at a fraction of the cost.

To put that in concrete terms: using an NVIDIA H200 GPU, Varya can generate a 5-second 720p clip in 45 seconds, compared to 1,230 seconds for Wan 2.2.

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The most striking aspect of Varya may be its price. The company plans to charge ₹0.48 ($0.005) per second of video on its hosted service — far cheaper than models like Veo, Kling, Luma, and Runway, which typically charge $0.10 or more per second. That’s a roughly 20x price difference.

“India is a video-first market. We see this across every large consumer internet product in India: video wins over text. Current AI video models are too expensive for population-scale use in India. If video AI is going to reach students, teachers, MSMEs, creators, enterprises, and public services, costs have to come down dramatically. Cost is the biggest unlock for AI adoption in India,” Peak XV’s managing director Rajan Anandan told TechCrunch.

Image and video generation models often miss cultural nuances and produce stereotyped or generic outputs — a problem TechCrunch has reported on before. Avataar AI says it has used curated data to train Varya to recognize cultural nuances including food, clothing, architecture, and festivals.

Varya will be released as an open-weight model on India’s AI Kosh portal — the Indian government’s centralized repository for publicly available AI models and datasets — along with its training data, meaning developers can self-host or modify it for their own needs. Avataar also plans to make the model available to its enterprise customers and says it is open to partnerships with video tools including Higgsfield and Adobe Firefly. Anyone can try it now on its website using text prompts or reference images.

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Varya’s launch reflects a fundamental tradeoff in India’s AI ambitions. Industry veterans have noted that India can make its mark in AI by creating applications and a robust developer ecosystem rather than competing on foundation models. And there’s a reason for that pragmatism: model development has been slower in India than in global rivals due to a lack of compute and limited quality data availability.

The India AI Mission is also part of a broader government push to close that gap. Last year, it selected 12 startups — Avataar AI among them — to develop AI models and provided them with cost-efficient compute. Earlier this year, IT minister Ashwini Vaishnaw said India aims to attract $200 billion in AI investment by 2028 and more than double its GPU capacity within six months.

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Equal AI raises $30M to screen calls so Indians don’t have to

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In India, consumers receive a lot of calls every day, ranging from spam and scams to delivery people and financial service companies trying to contact them. There are apps like Truecaller and the government’s Calling Name Presentation (CNAP) system to identify who is calling, but knowing the name of the caller is often not enough. That is why Equal AI is creating an assistant that can receive calls on your behalf, gather information, and tell you why someone is calling.

The app is currently available on Android, and since its launch last year, it has grown to more than a million monthly active users and over 300,000 daily active users, it says. The app screens the call and displays the reason someone is calling you.

The dialer shows quick reply options like “Leave the delivery near the door” or “Give it to the neighbor,” and the AI reads them back to the caller. You can also type a custom message for the AI to read out. The app records the call, and users can see the recording and transcription history with a summary in the app.

Image Credits: Equal AIImage Credits:Equal AI

Equal AI said today it has raised $30 million in Series B funding led by Prosus Ventures and Tomales Bay Capital with participation from Think Investments and Valiant Fund. Individual investors include Indian fintech PhonePe’s founder Sameer Nigam, Zubin Bharti Mittal from Airtel Family Office, Skyflow AI co-founder Anshu Sharma, Meta India and Southeast Asia’s VP Sandhya Devanathan, and CtrlS Datacenters’ Chairman Sridhar Pinnapureddy. With the new funding, the company has raised over $42 million to date.

The round is structured in three tranches, with the startup carrying a different valuation at each stage depending on whether it hits predetermined targets — a growing but still uncommon approach in which startups sell equity at different prices within the same round. The structure has an unusual quirk: it lets a startup advertise the highest valuation achieved, even if the bulk of the equity was sold at a lower one. Equal AI declined to provide its specific valuations.

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The startup was founded by Keshav Reddy in 2022. Reddy comes from the family behind Indian conglomerate GVK, which has holdings across infrastructure, energy, and healthcare. Equal started as a data-sharing company for financial services and still offers data for financial analysis and know your customer (KYC) verification services for employers.

“We always wanted to be a customer-facing company, and with Equal AI, the first use case we launched was a call assistant because we realized users get a ton of calls for financial services or job openings. If you are buying car insurance, you might get 20 calls over a week, and that is hard to tackle for a human,” founder Reddy told TechCrunch about why the company started there.

The app currently only screens unknown calls, but the company is planning to introduce the ability to screen calls from known numbers too. The company also wants the AI assistant to take proactive action on a user’s behalf — such as texting a delivery person your address (with consent) or making outbound calls to book appointments. The startup said it is also working on an iOS version of the app and a paid subscription tier with more features.

Equal AI is using a mix of speech recognition, automatic speech recognition (ASR), and speech generation models with its own orchestration layer. English support matters, but consumers in India often speak in their native language or blend multiple languages in a single sentence — a phenomenon called code-mixing. Equal AI says it has built support for over 10 languages with this in mind.

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The startup has stiff competition. Google and Apple both have call screening products. Truecaller, already a household name in India, has been building out its own AI assistant features. In the U.S., a16z-backed privacy startup Cloaked also launched call screening last year. Thiago Viana, global co-head at Prosus Ventures, said that Equal’s understanding of local context gives it an edge.

“Equal AI promises to screen calls for you and provide context on why someone is calling. We think that if an app does well in a few use cases, it can quickly become popular in its niche and create user stickiness to expand in different areas later on,” Reddy told TechCrunch by phone.

Prosus has been investing in AI assistant startups that focus on local markets. Its portfolio includes Spain-based Luzia and Latin America-based Zapia. Both were caught up in Meta’s ban on third-party AI bots on WhatsApp, which serves as a cautionary tale for platform dependency. Equal AI said that it didn’t want to create that kind of dependency — which is why it built around calls and its own app rather than piggybacking on a messaging platform.

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Microsoft Edge is about to get more frequent updates, but don’t expect more features

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Microsoft is accelerating updates to its Edge browser, switching from a monthly release schedule to a biweekly one. The change takes effect with Edge 152, due on August 27, and puts the browser on the same cadence as Google Chrome.

More updates, not more features

The shift does not mean users will get twice as many new features. As Microsoft explained in a recent blog post, each release under the new schedule will carry roughly half the content of the current monthly drops, keeping the overall volume of changes roughly constant. The practical effect for most users is a steadier, smaller stream of updates rather than a sudden jump in new functionality.

Microsoft framed the change as a benefit for both consumers and enterprise customers, noting that security and platform fixes will reach users faster, and that smaller change sets are easier for IT teams to validate before deployment.

Who it affects and when

The new cadence applies to users on the standard Stable channel. Those on the Stable Extended channel, a longer-term option aimed at organizations that prefer less frequent updates, will stay on the current every-two-months schedule.

Google Chrome moved to a two-week release cycle in March, and Edge’s realignment closes the gap between the two Chromium-based browsers. The biweekly releases kick in with Edge 152 on August 27, giving users and IT admins a couple of months to prepare before the new schedule takes hold. For everyday users, the transition should be largely invisible. Automatic updates will simply arrive more often, each with a smaller footprint than before.

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This is your BIOS speaking. Please fix me. Your PC is broken

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Casual IT team learns that building bespoke PCs can be a false economy

ON CALL 你好 Nǐ hǎo, dear reader, and welcome to another installment of On Call, The Register’s Friday column that shares your stories of translating technical trauma while delivering transcendent tech support.

This week, meet a reader we’ll Regomize as “Jackson” who
told us about his time providing tech support in a university’s biology
department.

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“It was sometime in the mid-2000s and our IT group at the
time consisted of myself, my boss, and a part-timer,” he told On Call. “We were
a very casual IT group; nothing in the way of any formal policies or standards
for anything at all. If someone needed a new PC, we just ordered parts and
assembled them ourselves.”

The department’s PC fleet therefore had a diverse gene pool,
with no two machines possessing the same bill of materials.

“This was fine by me – I enjoyed building them and it never
really caused any issues that I couldn’t handle,” Jackson told On Call. “Until
one day we got a panicked support call from one of the secretaries who claimed
that her PC just rebooted and then started talking to her.”

Jackson and his colleagues didn’t believe a word of it until
the secretary stopped talking and placed her phone next to the talking PC.

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“I could clearly hear a muffled voice repeating a message of
some sort,” Jackson told On Call.

There was nothing for it but to visit the PC, which he found
hung in the middle of a Power-On Self-Test, flashing an alphanumeric error code
and unmistakably playing a voice through its internal speaker.

In Chinese!

Jackson rebooted the machine and it ended up in the same
state, reciting the same message. Chinese isn’t a language in which Jackson is
fluent, so he had no idea what the PC was trying to tell him.

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“After poking around in the BIOS, I found the culprit,”
Jackson revealed. “This particular model of motherboard had a ‘talking error
BIOS’ whereby certain POST codes triggered the playback of a friendly, spoken
error message, with Chinese set as the default language.”

Jackson found the relevant BIOS settings, changed the
default language to English, and the next time he rebooted the machine it
helpfully let him know: “Your floppy drive may not be connected
properly.”

In his mail to On Call, Jackson hypothesized that the PC’s
CMOS battery died, so the BIOS was unable to access its stored settings and
reverted to factory settings that assumed the presence of a nonexistent second
floppy drive.

“It triggered a feature I didn’t even know the motherboard
had!” Jackson told On Call.

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Have you found yourself flummoxed by a feature you didn’t
know about? If so, click here to send On Call an email – we’ll assume that’s a feature you know well – so we
can tell your story on a future Friday. ®

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