Amazon CEO Andy Jassy was reportedly the source of security concerns that led the US government to force Anthropic to shut down Fable 5 and Mythos 5 for every customer on Friday. The Wall Street Journal reported that Jassy told Treasury Secretary Scott Bessent and other officials that Amazon researchers used Fable 5 to obtain information that could be used in cyberattacks. The government then imposed an export control ban on both models.

The revelation adds an uncomfortable dimension to the story. Amazon is one of Anthropic’s largest investors, having put in billions and receiving a $100 billion cloud spending commitment in return. The company that bankrolls Anthropic’s infrastructure is also the one that told the government its models are dangerous.

An Amazon spokesperson said it is “not uncommon for governments to seek our counsel on potential security risks” but declined to share details of the discussions. The spokesperson also pointed to an AWS status update confirming that Amazon’s own cloud platform was affected by the model shutdown.

David Sacks, Trump’s former AI czar who now co-chairs the President’s Council of Advisors on Science and Technology, offered a different account. He said “a highly credible trusted partner of both Anthropic and the USG came forward with a jailbreak.” Sacks added: “The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused.”

Anthropic’s version is different. The company said it reviewed the jailbreak technique and found it surfaced “a small number of previously known, minor vulnerabilities.” It called the government’s response disproportionate and said the capabilities causing concern are already available in other publicly accessible models. The shutdown affected every customer globally because Anthropic cannot filter foreign nationals from US users in real time.

The sequence matters for the AI industry. Amazon invested billions in Anthropic. Anthropic built models on AWS. Amazon’s CEO told the government those models pose security risks. The government used export controls to force them offline. AWS was then affected by the shutdown. It is an ouroboros of corporate dependency and regulatory blowback.

For Anthropic, the immediate question is how quickly it can restore access. For the broader industry, the precedent is what matters. If a major cloud provider can trigger an export control action against its own portfolio company by raising concerns with the Treasury Secretary, the competitive dynamics of the AI market just gained a new weapon. Mythos is used by banks and government agencies for vulnerability discovery. Every one of those customers lost access because of a dispute between Anthropic’s biggest investor and the government its CEO has been lobbying for more regulatory power.

Good morning! Let’s play Connections, the NYT’s clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you’ve finished? Why, play some more word games of course. I’ve also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc’s Wordle today page covers the original viral word game.

The model is open for the public to view as part of the Heart exhibition in RCSI’s Humanarium.

Researchers at RCSI University of Medicine and Health Sciences hope to better understand diseases in the mitral heart valve with an artificial model that mimics the valve’s complex mechanisms.

The heart’s mitral valve opens and closes around 100,000 times each day, making its mechanical properties key to healthy heart function.

When the valve does not work properly, blood can leak backwards through the heart in a condition called ‘mitral regurgitation’. This condition affects millions worldwide, with that number growing alongside global life expectancy.

“Advancing our understanding of mitral valve function is dependent on developing synthetic alternatives that capture the valve’s complex mechanical behaviour, which is achieved in this study,” explained Dr Claire Conway, a lecturer in RCSI’s department of anatomy and regenerative medicine, and one of the authors of the new study published in Acta Biomaterialia.

The study was funded through an RCSI Star Lectureship and the Research Ireland Frontiers for the Future Programme, and carried out by the RCSI Tissue Engineering Research Group.

Generally, synthetic mitral valves lack multi-directional mechanical properties and are unable to withstand the blood pressure and flow of a human heart, the researchers said.

This new model makes a marked change by being the “first of its kind” to incorporate the mechanical properties of real heart valve tissue, while also operating under realistic heart pressures and flow conditions, they explained.

The model also allows control over the tension and thickness of the parts that allow the valve to open and close effectively.

“This model captures native anatomy and the fabrication is precise and repeatable,” said Conway. “Physical and digital tests of the valve revealed it successfully functioned under physiological flow and physiological pressure, representing a significant advance in the field.”

Dr Sina Javadpour, first author of the study and a postdoctoral fellow at Trinity College Dublin, said: “This model gives us precise control over key features of the mitral valve while still reproducing the way it functions in the heart.

“That makes it a powerful tool for studying valve disease and testing new repair strategies in a controlled laboratory environment.”

The model is open for the public to view as part of the Heart exhibition in Humanarium at RCSI.

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.

Looking for the most recent Connections answers? Click here for today’s Connections hints, as well as our daily answers and hints for The New York Times Mini Crossword, Wordle, Connections: Sports Edition and Strands puzzles.

Today’s NYT Connections puzzle offers some fun categories. I actually liked the purple grouping today! Read on for clues and today’s Connections answers.

The Times has a Connections Bot, like the one for Wordle. Go there after you play to receive a numeric score and to have the program analyze your answers. Players who are registered with the Times Games section can now nerd out by following their progress, including the number of puzzles completed, win rate, number of times they nabbed a perfect score and their win streak.

Read more: Hints, Tips and Strategies to Help You Win at NYT Connections Every Time

Hints for today’s Connections groups

Here are four hints for the groupings in today’s Connections puzzle, ranked from the easiest yellow group to the tough (and sometimes bizarre) purple group.

Yellow group hint: Think about The Three Stooges.

Green group hint: Round and round.

Blue group hint: Curiouser and curiouser.

Purple group hint: Not Pa, but close.

Answers for today’s Connections groups

Yellow group: Classic slapstick props.

Green group: Things that spin.

Blue group: Featured in “Alice’s Adventures in Wonderland.”

Purple group: What “MA” might refer to.

Read more: Wordle Cheat Sheet: Here Are the Most Popular Letters Used in English Words

What are today’s Connections answers?

The yellow words in today’s Connections

The theme is classic slapstick props. The four answers are banana peel, cream pie, rubber chicken and seltzer bottle.

The green words in today’s Connections

The theme is things that spin. The four answers are globe, grindstone, gyroscope and roulette wheel.

The blue words in today’s Connections

The theme is featured in “Alice’s Adventures in Wonderland.” The four answers are caterpillar, pocket watch, rabbit hole and tea party.

The purple words in today’s Connections

The theme is what “MA” might refer to. The four answers are Massachusetts, master of arts, milliampere and mother.

Frequent flyers and daily commuters have a common frustration. Engine drone on flights, train clatter, and workplace background noise all compete for attention over extended periods of travel or sitting at a computer. Many noise-cancelling headphones provide relief, but they come with software, touch controls, and expensive pricing that appear unnecessary for just basic needs. ONANOFF’s Made for Amazon headphones, priced at $19.99 (was $80), cut through the noise in a refreshingly practical manner.

The over-ear design promotes comfort, with lightweight materials and the softest ear cushions to keep you comfortable even after hours of listening. People have commended the seal’s endurance, even on long, multi-hour flights or back-to-back meetings, because there is no need to fuss with it to ensure a correct fit.

Active noise cancellation is as simple as pressing a single button, and it effectively reduces low-frequency sounds that can be bothersome in contexts such as airplane cabins and autos. Many users have used these for long flights and noted that engine rumbling is practically eliminated, allowing them to listen to podcasts or music without having to crank up the volume to the limit. The experience is heightened by the passive noise isolation provided by the ear cups, which effectively provides a comfortable listening environment without the need to constantly tinker with it.

When it comes to real-world schedules, the battery life is spot on, boasting roughly 20 hours of wireless listening with noise cancellation running, which is enough to span the duration of many flights as well as all of your regular commutes for several days before it needs to be recharged. There is also a useful old-fashioned auxiliary cable available in case you run out of power mid-flight or on a plane with all of its entertainment systems, which serves as an excellent backup option.

The controls are simple and intuitive, with old-school buttons on the ear cups that let you to control music, volume, and calls without having to swipe. There’s also an extra little switch there that activates FOKUS mode, which allows you to prioritize vocal clarity, guaranteeing that your podcasts and phone calls are perfectly clear with no background noise in the mix. It’s especially beneficial when you’re traveling and need to catch up on audio content or make business calls in a congested terminal.

The sound is good and balanced, with just enough bass to give your music weight while not overpowering the rest of the mix. The mids and highs are clear and sharp, letting you to listen to anything you desire, including music, podcasts, and spoken word. They’re not striving to be ultra-high-end, show-off-spec headphones; instead, they provide nice, reliable listening that won’t wear you out after a few hours. If all you need is something practical, this is it.

Pairing with your phone, laptop, or tablet is simple; all you need is a short tap and you’re done. The “Made for Amazon” label indicates that it will perform well in the Amazon environment, but it will also work well with all other Bluetooth devices. There’s no worry, no mess, and no need to set up any ridiculous apps; simply plug in and go.

Strands is the NYT’s latest word game after the likes of Wordle, Spelling Bee and Connections – and it’s great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc’s Wordle today page for the original viral word game.

I want to share a story of struggle. Actually, two kinds of struggle.

My father completed his doctorate at the University of Utah in the early 1970s. For his dissertation, he ran a statistical analysis on genealogical records to determine the impact of certain economic conditions on family size.

He accomplished this on one of the most advanced computers of the time. His method? Literally punching out little rectangles in dozens of stiff paper cards, and feeding the stack into the computer.

My father was a lowly graduate student, and because the demand for computing time at the university was sky high, he had to run his analysis in the middle of the night. He spent many nights punching cards and running them through the machine. Even a single mispunch would cause the entire program to stop running and require painstaking troubleshooting, re-punching, and another night at the computer lab.

Unproductive vs. Productive Struggle

The soul-sapping sleep deprivation and endless paper punching that stood between my father and his goals represents the first kind of struggle in my story: unproductive struggle — the challenging, unavoidable tasks we must perform toward a learning goal, but which add no value to the intellectual outcome.

The real intellectual challenge in my father’s work was in deciding which variables belonged in the model, determining how to represent economic conditions over time, and interpreting the data. This is the second kind of struggle: productive struggle. That is, the effort a learner expends to make sense of concepts, to figure something out that is not immediately apparent. This struggle leads to growth and insight. It builds judgment, expertise and understanding.

What is frustrating about my father’s story in hindsight is that so much of his time and cognitive energy were consumed by the unproductive struggle of punching cards and managing the computer. Without those barriers, he would have had more capacity for the productive struggle that leads to meaningful learning.

Thinking About What Matters

When it comes to AI in schools, some educators fear that it will lead to learning becoming too easy. This is referred to as “cognitive laziness.” The assumption is that we will offload our thinking to AI and eventually lose our ability to think critically. This is a risk with any technology that makes our mental work more efficient, and AI is uniquely adept at taking on cognitively demanding tasks. But ceding our reasoning power to AI isn’t a foregone conclusion. And simply not using AI in learning settings doesn’t have to be our solution for preserving our mental capacities.

Just as better computing tools would have freed my father from punching cards without removing the intellectual rigor of his work, today’s tools, including AI, have the potential to offload unproductive struggle, while preserving, and even amplifying, the productive struggle that is central to learning.

Here’s an example: When reading comprehension is not the goal of a lesson but a necessary prerequisite — a student having to read an article to understand the causes of the French Revolution, for example — AI tools can adjust reading levels on the fly to assist learners who are below grade level or for whom English is not their first language. This allows them to focus on the history rather than on decoding the text.

Refining Rigor

So what does this mean for educators who are grappling with how to help students use AI effectively?

First, we need to remind ourselves and help our students understand that the goal of learning has never been to make learning easy. It is to make it meaningful. We must ensure that learners are spending their time wrestling with big ideas, not battling logistics or bogged down by rote tasks.

Second, educators need to face a hard truth about the assignments we give students. Many assignments contain a mix of productive and unproductive struggle, and we are not always very intentional about which is which. Under crushing time and resource pressure, we can become unreflective about the distinction between productive and unproductive work. We inherit assignments, reuse problem sets, and value rigor without always asking where the rigor actually lies.

If AI forces us to confront that, it may be one of the most useful disruptions education has experienced in decades.

For instance, requiring students to write citations according to a set format may feel rigorous, but the cognitive work of formatting has little to do with the intellectual work of evaluating sources and integrating evidence into an argument. This shift requires us to redesign tasks, rethink assessments and, if necessary, let go of practices that feel rigorous but don’t meaningfully deepen understanding.

Sharpening Learning

If we do this well, AI won’t hollow out learning; it will sharpen it. It will give students more space to wrestle with ideas instead of mechanics, more time to interpret instead of transcribe, and more opportunity to make active sense of the world. It will give us a chance to be far more intentional about the kind of struggle we ask students to engage in.

In the end, AI won’t decide whether our students experience cognitive laziness or cognitive growth. We will decide that by how we design assignments and assessments, and by the choices we make about which AI tools to adopt and how we choose to use them.

This is our chance to weed out the punch cards and open up more time for students to struggle over things that truly matter.