GitHub said in a blog post today that it is moving Copilot to usage-based billing starting June 1. Base subscription prices will remain the same but premium requests will be replaced with monthly AI Credits that are consumed based on token usage.

"Instead of counting premium requests, every Copilot plan will include a monthly allotment of GitHub AI Credits, with the option for paid plans to purchase additional usage," the platform said. "Usage will be calculated based on token consumption, including input, output, and cached tokens, using the listed API rates for each model. This change aligns Copilot pricing with actual usage and is an important step toward a sustainable, reliable Copilot business and experience for all users."

Documentation for individuals, businesses and enterprises, and an FAQ can be found at their respective links.

California's proposed billionaire tax appears headed for the November ballot after backers said they gathered more than 1.5 million signatures, well above the threshold needed to qualify. SF Standard reports: Backers of the initiative announced this weekend that more than 1.5 million people signed a petition to bring the one-time, 5% wealth tax to a statewide vote come November. That's well beyond the 875,000 names needed to qualify the measure, and likely sufficient to account for illegible or invalid signatures. The Service Employees International Union United Healthcare Workers West, a union representing more than 120,000 healthcare workers, pitched the tax to make up for federal spending cuts that threaten to shutter hospitals(opens in new tab) and kick millions of people off medical insurance.

Proponents of California's wealth tax estimate it would raise $100 billion in one-time revenue, even if some billionaires leave because of the measure. The nonpartisan California Legislative Analyst's Office forecasts tens of billions in upfront revenue, but cautioned that the tax could cost hundreds of millions or more a year if some billionaires move out of state. The proposal, which needs a simple majority to pass, would apply to assets of people with net worth of $1 billion or more who lived in California as of Jan. 1 this year. That means it would affect about 200 people, according to the SEIU-UHW.

An anonymous reader quotes a report from VentureBeat: The whale has resurfaced. DeepSeek, the Chinese AI startup offshoot of High-Flyer Capital Management quantitative analysis firm, became a near-overnight sensation globally in January 2025 with the release of its open source R1 model that matched proprietary U.S. giants. It's been an epoch in AI since then, and while DeepSeek has released several updates to that model and its other V3 series, the international AI and business community has been largely waiting with baited breath for the follow-up to the R1 moment.

Now it's arrived with last night's release of DeepSeek-V4, a 1.6-trillion-parameter Mixture-of-Experts (MoE) model available free under commercially-friendly open source MIT License, which nears -- and on some benchmarks, surpasses -- the performance of the world's most advanced closed-source systems at approximately 1/6th the cost over the application programming interface (API).

This release -- which DeepSeek AI researcher Deli Chen described on X as a "labor of love" 484 days after the launch of V3 -- is being hailed as the "second DeepSeek moment." As Chen noted in his post, "AGI belongs to everyone". It's available now on AI code sharing community Hugging Face and through DeepSeek's API. The new DeepSeek-V4-Pro model delivers "near-frontier performance" at a much lower price, costing $5.22 for 1 million input and 1 million output tokens compared with $35 for GPT-5.5 and $30 for Claude Opus 4.7. That makes it roughly 1/7th the cost of GPT-5.5 and 1/6th the cost of Claude Opus 4.7, reinforcing VentureBeat's point that DeepSeek is "compressing advanced model economics into a much lower band."

While GPT-5.5 and Claude Opus 4.7 still lead on most benchmarks, DeepSeek-V4-Pro gets close enough that its lower cost could "force a major rethink of the economics of advanced AI deployment."

"There are about 70% more bookstores now than there were six years ago in the United States," says Andy Hunter, the founder/CEO of Bookshop.org. Fast Company checks in on his site, which gives over 80% of its profit margin to independent bookstores, structuring itself as a B Corporation (a for-profit company certified for its social-impact) while providing an alternative to Amazon and other online booksellers: Hunter created Bookshop.org in January 2020 to help independent bookstores survive by utilizing e-commerce... "There were over 5,000 bookstores in the American Booksellers Association in 1995, which is one year after Amazon launched. By 2019, that had gone down to 1,889, so more than half of them disappeared." He says he never could have predicted how the pandemic would accelerate his company's growth... "All these stores that had been trying to get around e-commerce or never really launching or building their website, they had to sell online. That was the only way they could survive during the pandemic...."

"Our goal is to help independent local bookstores get their fair share of online sales, which would end up being maybe 10% of Amazon's market share," he says. "And right now we're at about 2%, so we have a long way to go. But a lot of people didn't even think we could ever get 1%...." Bookshop.org has given almost $47 million back to local bookstores. For Hunter, it's not just about the money but changing the way society thinks. He's delighted that many big organizations no longer use Amazon affiliate links, choosing to send people his way instead. "People have absorbed the message that they should support independent bookstores when they buy books," he says.

Public stock exchanges "appear to be warming to climate tech startups," reports TechCrunch. "Or at least some of them." This week, nuclear startup X-energy went public, raising $1 billion in an upsized share offering that appears to have delivered a windfall for its investors, including Amazon [and Google]. Retail investors apparently can't get enough, with the stock popping 25% in its first hour of trading. Also this week, geothermal startup Fervo said it filed for an initial public offering. The size of the Fervo IPO has yet to be disclosed, but private investors have valued the company at around $3 billion, according to PitchBook.

The move to go public aligns with what investors told TechCrunch at the end of last year. After years of tepid attitudes toward climate tech companies, they expected public markets to start welcoming energy-related startups. Nearly every investor that weighed in on the question said the startups with the best chances of going public specialize in either nuclear fission or enhanced geothermal. Fervo, specifically, was mentioned several times. Thank data centers for that. The AI craze has taken a trend of rising demand for electricity and made it sexy and salable.

"California, Colorado, Minnesota, New York, Connecticut, Oregon and Washington have all passed comprehensive right-to-repair regulations," reports CNBC, "covering everything from consumer electronics and farm equipment to wheelchairs and automobiles."

And the consumer movement "continues to gain political momentum" across America... As of this year, advocates are tracking 57 right-to-repair bills across 22 states. In Maine, the state senate just advanced a bill that would bring the right to repair to electronics in the state. Texas's new right-to-repair law kicks in on Sept. 1 and covers phones, laptops, and tablets, but excludes medical and farm equipment, and game consoles.... [U.S.] Senator Ben Ray Luján (D-NM) and Josh Hawley (R-Mo.) are unlikely political bedfellows but have joined together to sponsor the REPAIR Act... The REPAIR Act would require automakers to give vehicle owners, independent repair shops, and aftermarket manufacturers secure access to vehicle repair and maintenance data, preventing manufacturers from funneling consumers into their own exclusive and more expensive dealership repair networks... Hawley criticized big corporations in his arguments in favor of right-to-repair legislation.

"Big corporations have a history of gatekeeping basic information that belongs to car owners, effectively forcing consumers to pay a fixed price whenever their car is in the shop," Hawley told CNBC. "The bipartisan REPAIR Act would end corporations' control over diagnostics and service information and give consumers the right to repair their own equipment at a price most feasible for them." The largest small business lobby in the U.S., the NFIB, says 89% of its members support right-to-repair legislation, making it a top legislative priority for 2026.

An anonymous reader shared this report from Bloomberg: More than three years after acquiring Twitter, Elon Musk says he's nearing his long-stated goal of turning it into an "everything app" with a new financial services tool that he pledged to launch for the public this month... Early users testing the service have touted competitive perks, including 3% cash back on eligible purchases and a 6% interest rate on cash savings — the latter of which is roughly 15 times the national average. Musk's new product is also expected to offer free peer-to-peer transfers, a metal Visa debit card personalised with a user's X handle, and an AI concierge built by Musk's xAI startup that tracks spending and sorts through past transactions, according to reports from users with early access.

Musk, who first rose to prominence in Silicon Valley by co-founding PayPal Holdings Inc, sees payments as crucial to creating a so-called super app similar to social products that have flourished in China. WeChat, for example, lets users hail a ride, book a flight and pay off their credit card... If it works, X Money would sit at the intersection of social media and finance in a way no American product has attempted at this scale... Creators who currently receive payments from X for engagement will be switched from Stripe to X Money as their payment platform, according to early users — a move that guarantees an initial base of active accounts. Some have already been testing X Money to send payments to one another through the app's chat feature or directly through their profiles, according to early participants in the rollout...

X currently holds licences in 44 states, according to its website, and likely won't be able to operate in states where it hasn't obtained a licence.

Framework began shipping its new Laptop 13 Pro this week. And the Ubuntu variant is outselling the Windows variant, reports PC World: [I]t's selling quickly by Framework's internal metrics, with six batches of the Intel version of the laptop already sold out. [A later Framework social media post added "Spoke too soon, we're onto Batch 8."]

"Also nice validation of our approach, the Ubuntu configurations are outselling the Windows ones!"

That's not really surprising, for a few reasons. One, if you're buying a Framework laptop, you have a good reason to order it without an OS, even if you want Windows 11. It's easy to get it free or cheap elsewhere. (Framework says it's not counting the "None (bring your own)" option in these Ubuntu numbers.) Two, there are precious few places to order a new laptop with any kind of Linux pre-loaded — you've got Framework, a few smaller vendors like System76 and Slimbook, and a few models from Dell. Lenovo sold Ubuntu-loaded laptops at one point, but I can't find any on the site right now...

Perhaps it doesn't hurt that Microsoft and Windows are currently on a bit of an apology tour. After a couple of years of pushing hard on "AI" features that no one wants — not even the people who do want "AI" want the Copilot flavor — Microsoft is pulling back its integration into everything and now promising features that Windows has been missing ever since Windows 10.
Framework also reports that:

• More than one third of purchasers say they're replacing a MacBook Pro, "and almost all of them are switching to Linux (based on our optional post-purchase survey)."

• "Also in interesting sales data, the Gray/Black keyboard is vastly outselling the traditional Black one!"

The Washington Post reports that some teachers are now implementing "brain breaks" in their classrooms to cope with shorter attention spans, "including limiting screen time; cutting the time students spend on one activity; adding more engaging, hands-on projects; and practicing meditation." Some teachers say the efforts are helping, at least a little... To engage students, teachers say they often feel the need to deliver teaching not only in shorter bursts, but also in more entertaining ways. "The new word is 'edutainment,'" said Curtis Finch, superintendent of Deer Valley Unified School District in Arizona. "How can you make your lesson applicable, interactive? Teachers are going to have to be more engaging for students...."

In a kindergarten classroom at McKinley STEAM [a K-8 public school], students start the day with a meditation. The classroom of two dozen children is perhaps its quietest during this short activity every morning. Imagine you're in the Arctic, a voice from a meditation video tells them, with snowflakes melting on your skin. Silently, the children lay down on the carpet and close their eyes for a moment. After the meditation, the students gather in a circle and do a few deep breathing exercises before taking turns proclaiming what they are capable of each day. "I can be a good student," one little boy said before the child next to him replied: "I can listen to the teacher." The goal is that these mantras will stay with the children hours later, when they have to sit through the more tedious lessons of the day.
An instructional coach at McKinley STEAM says the strategies are working students aren't reaching for their phones during class and sometimes actually get drawn into lessons.

The article also explains why some teachers find this necessary: In recent years, educators say, it has grown more challenging to get students to pay attention. Eighty-eight percent of respondents in an international survey from 2025 of more than 3,000 teachers believed their students' attention spans were getting shorter. In a study published last year about kindergarten through second-grade classrooms in the United States, 75 percent of teachers said attention spans had dropped since the coronavirus pandemic, when the use of laptops and other technology for schooling spread rapidly. A growing body of research says that excessive screen time and short-form content such as TikTok videos are part of the problem. At least 36 states, including Ohio, have laws requiring schools to have some form of a cellphone ban.

There is debate over whether screen time reduces people's ability to focus or their desire to — many developmental experts lean toward the latter, suggesting that it is possible to help students regain longer attention spans.

The AI industry is largely failing to ask a key design question, argues theoretical neuroscientist/cognitive scientist Vivienne Ming. Are their AI products building human capacity or consuming it?

In the Wall Street Journal Ming shares her experiment about which group performed best at predicting real-world events (compared to forecasters on prediction market Polymarket) — AI, human, or human-AI hybrid teams. The human groups performed poorly, relying on instinct or whatever information had come across their feeds that morning. The large AI models — ChatGPT and Gemini, in this case — performed considerably better, though still short of the market itself. But when we combined AI with humans, things got more interesting. Most hybrid teams used AI for the answer and submitted it as their own, performing no better than the AI alone. Others fed their own predictions into AI and asked it to come up with supporting evidence. These "validators" had stumbled into a classic confirmation bias-loop: the sycophancy that leads chatbots to tell you what you want to hear, even if it isn't true. They ended up performing worse than an AI working solo.

But in roughly 5% to 10% of teams, something different emerged. The AI became a sparring partner. The teams pushed back, demanding evidence and interrogating assumptions. When the AI expressed high confidence, the humans questioned it. When the humans felt strongly about an intuition, they asked the AI to come up with a counterargument... These teams reached insightful conclusions that neither a human nor a machine could have produced on its own. They were the only group to consistently rival the prediction market's accuracy. On certain questions, they even outperformed it...

We are building AI systems specifically designed to give us the answer before we feel the discomfort of not having it. What my experiment suggests is that the human qualities most likely to matter are not the feel-good ones. They're the uncomfortable ones: the capacity to be wrong in public and stay curious; to sit with a question your phone could answer in three seconds and resist the urge to reach for it. To read a confident, fluent response from an AI and ask yourself, "What's missing?" rather than default to "Great, that's done." To disagree with something that sounds authoritative and to trust your instinct enough to follow it. We don't build these capacities by avoiding discomfort. We build them by choosing it, repeatedly, in small ways: the student who struggles through a problem before checking the answer; the person who asks a follow-up question in a conversation; the reader who sits with a difficult idea long enough for it to actually change one's mind. Most AI chatbots today default to easy answers, which is hurting our ability to think critically.

I call this the Information-Exploration Paradox. As the cost of information approaches zero, human exploration collapses. We see it in students who perform better on AI-assisted tasks and worse on everything afterward. We see it in developers shipping more code and understanding it less. We are, in ways that feel like progress, slowly optimizing ourselves out of the loop.
The author just published a book called " Robot-Proof: When Machines Have All The Answers, Build Better People." They suggest using AI to "explore uncertainty.... before you accept an AI's answer, ask it for the strongest argument against itself."

And they're also urging new performance benchmarks for AI-human hybrid teams.

America's National Science Board (NSB) "was established in 1950 to guide the governance of the National Science Foundation," writes the Washington Post, "in an unusual structure within the federal government that echoes the setup of a company board in the private sector. It helps guide an agency that operates Antarctic research stations, telescopes, a fleet of research vessels and supports basic science research in laboratories across the United States." (NSF research has helped evolve the technology used in MRIs, cellphones and LASIK eye surgery.)

But yesterday President Trump fired all 24 members of the National Science Board (NSB), the body that oversees the National Science Foundation (NSF), reports Science magazine: In addition to advising the administration and Congress on national science policy, it has statutory authority to oversee the actions of the $9-billion NSF, setting policy and approving large expenditures. Its presidentially appointed members, typically prominent academics and industry leaders, serve 6-year terms, with eight members chosen every 2 years....

Keivan Stassun, one of the dismissed board members, says the mass firing is the latest indication that the White House is ignoring the board's authority and dictating policies at NSF, which has been without a permanent director since Sethuraman Panchanathan resigned exactly one year ago. Stassun, an astrophysicist at Vanderbilt University who was appointed to the board in 2022, thinks the board's public criticism in May 2025 of Trump's proposed 55% cut to NSF's current budget — which Congress ultimately ignored — antagonized the administration. "Maybe one way to say it from the administration's perspective," Stassun says, "is that this group of presidential appointees was advising the Congress to not follow the president's wishes."
The Washington Post adds that "The White House did not immediately respond to inquiries about why the members were terminated."

It's the U.S. government's main link to the AI industry, reports The Washington Post, working to assess national security risks of new models like Anthropic's "Mythos".

To run it they'd hired Collin Burns, who'd worked at OpenAI and then Anthropic. But Burns started work Monday at the Center for AI Standards and Innovation — and then "was pushed out Thursday by the White House, according to the people, who spoke on the condition of anonymity to describe private conversations." Officials were concerned about Burns having worked at the AI company, which has fought bitterly with the Trump administration in recent months, according to one of the people and another person. That person said some senior figures at the White House had not been briefed on Burns's selection in advance... The new pick was Chris Fall, a scientist with a long career spanning the federal government and academia. Burns had been asked to resign that afternoon, according to one of the people familiar with the situation...

Dean Ball, a former Trump administration AI adviser, said on social media that Burns had given up valuable Anthropic stock and moved across the country to take the government position, and had been "rewarded by his country with a punch in the face." "Obviously what happened is Burns was bumped because of his association with Anthropic," Ball wrote. "A dumb but predictable own goal."

The Free Software Foundation's Licensing and Compliance Manager published a blog post this week to explicitly state that"Responsible AI" Licenses (RAIL) are nonfree and unethical. The licenses restrict AI and ML software "from being used in a specific list of harmful applications," according to the license's web site, "e.g. in surveillance and crime prediction." (The license's steering committee is volunteers from multiple academic institutions.)

But even though Responsible AI licenses are marketed as addressing ethical challenges, the FSF argues "they do not require anything that is really necessary for users to control their computing done with machine learning, including: complete training inputs, training configuration settings, trained model, or — last, but not least — the source code of software used for training, testing, and running tools based on machine learning." Thus, RAILed machine learning can be, and most probably will be, unethical. Use restrictions do not prevent these licenses from being used to exercise power over users...

RAIL contribute to unethical marketing of machine learning, again under the disguise of morally-loaded restrictions they purport to enforce. If we want software to help decrease social injustice, we should oppose licenses that restrict how software can be used. We should focus on effective ways of addressing injustices: government and community support for freedom-respecting tools and services; releasing programs under strong copyleft licenses; and entrusting copyrights to organizations that have the resources to enforce copyleft.

Software freedom must be defended, not denied. More specifically, the more free software is out there, the more likely people will collaborate on tools and services that do not pose moral dangers and help solve existing ones. Free software also makes it more likely that users have real choices when looking for freedom-respecting ethical programs and tools based on machine learning. Denying people the freedom to a particular program, as RAIL or similar licenses would have it, prevents them from using such program for the common good.

Maine Gov. Janet Mills vetoed a bill that would have imposed the nation's first statewide moratorium on new data centers, saying she supported the idea in principle but would not block a major redevelopment project tied to jobs and local investment. Instead, she said she will create a council to study data centers' effects while also signing a separate measure to deny them certain state tax incentives. Politico reports: "After prior redevelopment efforts failed, the Town of Jay worked for two years on a $550 million data center redevelopment project to finally bring jobs and investment back to the mill site," Mills wrote, adding that she would issue an executive order establishing a council to examine the impact of data centers in Maine.

The legislation would have made Maine the first state to block the construction of new data centers, as both political parties grapple with how voters view them ahead of the midterm elections. In a statement accompanying the letter, the governor said she had signed a separate bill that would prohibit data center projects from receiving Maine's business development tax incentive programs

A report says Samsung's mobile division could post its first-ever annual loss in 2026, as rising memory costs, tougher competition, and pressure across products like foldables and smartwatches weigh on the business. SammyGuru reports: Samsung boss TM Roh reportedly told company leaders that the mobile (MX) business could lose money this year. That warning has clearly rattled management. The MX unit has long been a key pillar for Samsung. That's why the idea of it slipping into the red is a serious concern for the company's overall performance.

If this prediction holds, it would mark the first time the MX business reports a yearly loss since its inception. That's a sharp turn from its track record so far. It also raises bigger questions about future growth, rising competition, and how Samsung plans to steady the ship in its mobile division.

And it's not like the challenges are easing up. Samsung's foldable market share in the US, where it currently enjoys a dominant position, doesn't look as solid as before, and Apple could shake things up if it enters the segment. On top of that, market reports suggest Samsung's overall smartwatch share could dip in 2026. The Galaxy S26 series seems to be selling well for now, but whether that's enough to move the needle is still up in the air.