Happy Monday, listeners! And happy November. For Scientific American’s Science Quickly, I’m Rachel Feltman. You’re listening to our weekly science news roundup.

We’ll start with an update on the ongoing Ebola outbreak in the Democratic Republic of the Congo. Last Tuesday, data from the country’s Ministry of Health confirmed more than 10,000 cases since May. And nearly half of those people have died.

This is the fastest known Ebola outbreak in history. For context, the deadliest outbreak on record, which occurred in West Africa between 2014 and 2016, resulted in 28,000 cases and 11,000 deaths. But that outbreak lasted more than two years, and the current outbreak in the DRC was declared less than 200 days ago. And the difference in their trajectories is striking. On day 187 of the current outbreak, the official case count was 10,060. On day 186 of the West Africa outbreak, just 544 cases had been recorded.

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There are a few factors making this outbreak tough to manage. The first is the actual species of Ebola-causing virus fueling the outbreak. Of the six known species in this genus, four cause the kind of severe hemorrhagic fever you probably think of when you hear the word “Ebola.” The West African epidemic was caused by one of those four viruses, which is somewhat confusingly now called the Ebola virus but used to be called the Zaire virus, and which has the highest fatality rate of the four. Fortunately, an extremely effective vaccine was developed and deployed to help end that epidemic.

This latest outbreak is caused by a different species: the Bundibugyo virus. It’s much less common, having only caused two other known outbreaks in the past.

Another factor in the outbreak’s breakneck growth is that the DRC is really struggling to track cases and administer care. The Associated Press reports that at least half of all deaths have been in people who were never admitted to treatment centers. And contact tracing isn’t going well, either. An outbreak is considered under control when 95% of all new cases come from contact with previously known and recorded cases. But at present, something like 80% of new cases are emerging from unknown sources.

In other words, there are still lots of people out transmitting the disease that haven’t yet been identified by contact tracers. Distrust of the government and, by extension, of health workers is also a huge issue, with many reportedly believing the outbreak is a hoax. Last month a nurse was killed and another health care worker was severely injured as they attempted to respond to reports of Ebola.

However there is some good news, which is that clinical trials are ongoing to find a good vaccine candidate. Last Monday the first participant was vaccinated. The clinical trial is called Tumaini, which means “hope” in Swahili. The trial is made up of people who have recently been in close contact with individuals now confirmed to have the Bundibugyo virus. The first vaccine up for testing is the one tailored to prevent the Ebola virus, but several Bundibugyo-specific inoculations are currently in development and will be tested as well.

Now let’s get into some news about artificial intelligence. Just a few weeks after dropping hundreds of AI-generated math breakthroughs on a field that’s already in crisis, OpenAI is piling on more. Here to tell us more about this shake-up is artificial intelligence and technology reporter Peter Hall. He’s currently working as an editorial fellow at Scientific American. Thanks so much for coming on to chat, Peter.

Peter Hall: Good to meet you and good to talk with you.

Feltman: So could you give our listeners a little bit of backstory for how this has been heating up?

Hall: Yeah. So over the past few months OpenAI and Anthropic, as well as other players, have really been trying to flex the ability of their models by, um, proving or disproving famous math conjectures.

And last week OpenAI introduced these three results across math, physics and theoretical computer science that are quite big. And Anthropic also released the same result, almost at the same time on the same day.

Feltman: And so, to give our listeners a little bit of context, what kinds of problems are we talking about and what does this process usually look like, you know, when human mathematicians are involved?

Hall: So there’s a huge collection of problems that mathematicians have conjectured or guessed over decades of research. For the proofs from last week, these centered around problems related to Millennium Prize Problems, which are these group of seven problems that the Clay Mathematics Institute published in 2000 as a collection of problems that have existed across math and physics and computer science that are so noteworthy and so important and so difficult that they would get a million-dollar prize for a solution to them.

Feltman: So is there any controversy about whether what OpenAI and Anthropic are presenting are actually solutions to these problems, that they’re solved?

Hall: Right. So that’s the other side of the coin is that, usually, you know, math research is published in journals or on preprint servers or in conferences. It’s discussed among mathematicians.

These don’t really follow the same blueprint there. These are just kind of, like, put in GitHub repos as just a collection of AI-generated text and programming that they claim not only shows that the result is true but also has verified it in a programming language called Lean, which is meant specifically for mathematics.

So definitely the aspect of, like, how intelligible these results are and what kind of insights people are gaining from them has been a huge point of controversy—and you know, who gets the credit when a model is just outputting a bunch of ideas that we don’t really know exactly what they’re building off of.

Feltman: It’s like when that monkey took a selfie, except I had more respect for both the monkey and the photographer than I unfortunately do for a lot of AI companies. Well, what are the potential benefits to the mathematics community of these proofs being out there? You know, are there any upsides?

Hall: You know with previous drops, there has been efforts from the communities to go through the proof, really, you know, with a very fine-tooth comb and turn it into something that is expository and something that we can look at the techniques for and really understand some sort of mathematical insight for it.

You know, the hope is that solutions like these and the proof steps, even if they’re not written the best right now, can at some point down the line be turned into something that is useful. Like, you know, I can use the ideas from this to solve some other problem that I’ve seen elsewhere in my research.

Feltman: Well thank you so much for coming on to talk through this with us.

Hall: Of course. Thank you.

Feltman: Now for some research on an extremely timely subject: daylight saving time. DST just ended for those of us in the United States—not counting several territories, including Puerto Rico, and the exempt states Hawaii and Arizona,minus the Navajo Nation, which does still observe DST. Complicated, right? And it’s not like “springing forward” and “falling back” are much fun to deal with, either. Research suggests that shifting our clocks back and forth by an hour takes a toll on the body and the mind.

So it’s not surprising that this practice is pretty unpopular, and you might have celebrated when the House of Representatives passed the Sunshine Protection Act in July. That bill, which has yet to clear the Senate, would make DST permanent and therefore “preserve” an hour of afternoon sunlight as we head deeper into fall. Last week President Donald Trump blasted the Senate for failing to take a vote in time to implement permanent DST this year, claiming in a social media post that literally no one wanted to change their clocks. While that’s characteristically hyperbolic, recent survey data does suggest that almost half of U.S. adults are opposed to all the falling and springing.

But according to a new analysis published in Current Biology, making DST permanent could have serious, dangerous consequences for school-age children. Researchers at the University of Washington who study how school start times impact adolescent health decided to quantify exactly how many more trips to school would happen in darkness if we switched to year-round DST. They found that the Sunshine Protection Act would lead to more than two billion dark morning commutes for children. They also confirmed that fatal morning crashes involving kids aged five to 18 are more likely to occur if the sun has yet to rise. So those additional dark commutes really do pose a risk.

The researchers aren’t arguing in favor of continuing to swap our clocks back and forth; in fact, they point out that while permanent DST would be the worst-case scenario for dark school commutes, our current system creates twice as many dark mornings as would occur under permanent standard time.

Listen: I’m as bummed out by an afternoon sunset as anyone else. But as long as we can get rid of the twice-a-year upheaval, I’m personally good with whatever. And keeping kids safe as they wait for the bus—or, even better, as they walk or bike to school, because we love a pedestrian-friendly commute—seems pretty worthwhile to me.

That’s all for this week’s science news roundup. We’ll be back on Wednesday to talk about how soybeans quietly swept the nation and on Friday we’re going to talk about how AI swept everywhere.

Science Quickly is produced by me, Rachel Feltman, along with Fonda Mwangi, Sushmita Pathak, Allison Rodgers and Jeff DelViscio. This episode was edited by Alex Sugiura. Marielle Issa and Aaron Shattuck fact-check our show. Our theme music was composed by Dominic Smith. Subscribe to Scientific American for more up-to-date and in-depth science news.

For Scientific American, this is Rachel Feltman. Have a great week!