The Super Nintendo World theme park in Orlando is nearly ready for visitors. Universal Orlando Resort just announced that the Mario-friendly attraction will open its doors on May 22, 2025. That gives you over six months to find the perfect Goomba costume to wear on opening day.

This is the third Nintendo theme park throughout the world, as the Orlando location joins pre-existing parks in Los Angeles and Japan. If the layout looks anything like the other two parks, you should expect a large interactive area to explore, special themed rides and, of course, all kinds of Nintendo-adjacent dining and shopping. The original Japanese park just got a nifty Donkey Kong Country area, and Nintendo confirmed earlier this year that it would come to Orlando as well.

This is part of a larger expansion of Universal Resort Orlando, called Universal Epic Universe. This includes five areas to explore. There’s the aforementioned Super Nintendo World, but this expansion will also host the pre-existing Harry Potter attraction.

The area will be home to a theme park based on the How to Train Your Dragon franchise and another based on the Dark Universe franchise. That last one is pretty odd to me, being as how the Dark Universe franchise peaked with a few middling horror films in the 2010s. Most of the planned films in this shared cinematic universe were scrapped after 2017’s The Mummy crashed and burned.

Finally, there’s Celestial Park. This looks to be a standard amusement park with a slight sci-fi bent. There are space-themed roller coasters and the like.

Correction, October 18 2024, 8:45AM ET: This story originally stated that it wasn’t clear if the Donkey Kong Country attraction was coming to Orlando. Nintendo had announced that it would be in the Orlando park earlier this year.

It’s been decades since Australia’s thylacine, known as the Tasmanian tiger, was declared extinct and scientists say they’ve made a breakthrough as they research ways to bring back the carnivore. 

Colossal Biosciences in a Thursday press release said its reconstructed thylacine genome is about 99.9% complete, with 45 gaps that they’ll work to close through additional sequencing in the coming months. The company also isolated long RNA molecules from a 110-year-old preserved head, which was skinned and kept in ethanol. 

“The thylacine samples used for our new reference genome are among the best preserved ancient specimens my team has worked with,” said Beth Shapiro, Colossal’s chief science officer and the director of the UCSC Paleogenomics Lab, where the samples were processed. “It’s rare to have a sample that allows you to push the envelope in ancient DNA methods to such an extent.”

Efforts to bring back the Tasmanian tiger

The preservation of a complete Tasmanian tiger head meant that scientists could study RNA samples from several important tissue areas, including the tongue, nasal cavity, brain and eye. It will allow researchers to determine what a thylacine could taste and smell, along with what type of vision it had and how its brain worked, according to Andrew Park, a member of Colossal’s Scientific Advisory Board and a researcher at the University of Melbourne’s TIGRR Lab.

“We’re getting closer every day to being able to place the thylacine back into the ecosystem – which of course is a major conservation benefit as well,” Pask said.

Pask, speaking with 60 Minutes earlier this year, said researchers were working with the closest living relative of the Tasmanian tiger — a small marsupial called the fat-tailed dunnart — as a way to bring the animal back. 

“But that little dunnart is a ferocious carnivore, even though it’s very, very small,” Pask said. “And it’s a very good surrogate for us to be able to do all of this editing in.”

Scientists have been comparing the DNA of the dunnart and the thylacine, Pask told 60 Minutes. From there, it’s a matter of going in and editing the DNA to turn a fat-tailed dunnart cell into a thylacine cell.

Colossal Biosciences on Thursday said it had edited more than 300 unique genetic changes into a dunnart cell, making it “the most edited animal cell to date.”

“We are really pushing forward the frontier of de-extinction technologies,” Pask said, “from innovative ways of finding the regions of the genome driving evolution to novel methods to determine gene function. We are in the best place ever to rebuild this species using the most thorough genome resources and the best informed experiments to determine function.”

Efforts aiding the revival of the Tasmanian tiger are not confined to Australia. Last year, scientists recovered and sequenced RNA from a 130-year-old Tasmanian tiger specimen preserved at room temperature in Sweden’s Museum of Natural History. 

How the Tasmanian tiger died off

Thylacines roamed Tasmania for thousands of years. Despite the Tasmanian tiger moniker, the carnivores were marsupials, like kangaroos, koalas and Tasmanian devils.

The local government in the late 1800s paid out bounties to hunters presenting carcasses of Tasmanian tigers because the animals had been eating farmers’ sheep, 60 Minutes previously reported. By the mid-1930s, the Tasmanian tiger population had dwindled to a single thylacine at the Beaumaris Zoo in Hobart, Tasmania’s capital. It died there in 1936.

Australia has similarly allowed the culling of Kangaroos, approving the deaths of thousands of kangaroos over the years. Officials have said the kangaroo population was eating through grassy habitats of endangered species. Officials have also warned in the past that there isn’t enough food available to sustain large kangaroo populations. 

For many a year, Windows users have been dragging their program windows over to the borders of the screen to snap them into position, splitting the screen up evenly into halves or quarters. Now, with the rollout of macOS Sequoia, Mac users can do the same. You can get a Spotify playlist up alongside your email inbox, for example, or a report you’re writing up alongside the online articles you’re reporting on. It means less switching between windows and more information on the screen.

Once you’ve got macOS Sequoia installed on your Mac, you can take advantage of what Apple calls window tiling. There are several methods you can use.

Alternatively, you can click and drag an open window into position to tile it. 

The third method for window tiling is via the Window drop-down menu in whatever app you’re using.

If you want to keep your fingers on the keyboard, keyboard shortcuts are supported as well. (Note: unfortunately, there aren’t any specific keyboard shortcuts for moving windows into the quarter sections of the screen.)

Here’s the list for controlling individual windows:

There are also shortcuts for moving the active window and arranging other windows to match:

You can customize a few aspects of window tiling using System Settings on the Apple menu. Choose Desktop & Dock to find them. You can turn drag-to-tile and the Option key shortcut on or off and choose whether tiled windows have margins between them.

Several third-party tools have previously filled the feature gap when it comes to window tiling, and generally speaking, they give you more options and more control than macOS Sequoia does, at least for now — they’re not completely Sherlocked yet.

I can only speak firsthand about two that I’ve personally used. One is Magnet, which will set you back $9.99 but is very much worth it, especially if you use a larger display. You can divide the screen up by thirds and sixths as well as halves and quarters and set up trigger areas for dragging and custom keyboard shortcuts.

The other is Rectangle; the basic version is free, but if you pay $9.99 for the Pro version, you can customize snap areas and keyboard shortcuts, set up specific layouts for specific apps, and pin certain program windows into position. It’s packed with every feature you could possibly want, though I think Magnet is a little more intuitive to use.

The Titan A900 might look like an ordinary desktop PC at first glance, but it’s a powerful workstation designed for deep learning and AI applications.

The machine from Titan Computers is built around AMD’s EPYC Genoa 9004 series, featuring dual EPYC Genoa 9124 CPUs with 32 cores each, providing a total of 64 cores in the default configuration.

For users who need even more computational power you can customize the choice of processor all the way up to EPYC Genoa 9124 CPUs supporting up to 256 cores.

It isn’t cheap

It might have taken a while, and slumping sales of its most popular SUV, but Nissan has finally taken the step to offer hybrid vehicles in the U.S.

The Japanese automaker will add a plug-in hybrid (PHEV) powertrain to the 2026 Rogue compact SUV, which should be available stateside sometime next year, Nissan Americas chief planning officer Ponz Pandikuthira told Automotive News.

A plug-in hybrid electric vehicle (PHEV) typically runs on electric power until its battery is almost depleted, at which point it automatically switches over to using a gasoline-powered internal combustion engine. The battery can be recharged conventionally from the outside or through regenerative braking.

While Nissan has been offering popular fully electric vehicles (EVs) such as the Leaf and the Ariya for years, it has surprised many by not joining the hybrid bandwagon, especially for the Rogue. Competitors such as the Toyota RAV4 and the Honda CR-V, which do provide the part-fuel, part-electric power capacity, have seen their sales surging. Meanwhile, sales of the Rogue have slumped this year.

That’s why Nissan is partnering with Mitsubishi to start offering its first-ever electrically assisted car in the U.S. next year.

According to the Automotive News report, the Rogue will be outfitted with a similar powertrain found in the Mitsubishi Outlander. In that model, a 2.4-liter gas engine powers the front wheels, while two electric motors create an all-wheel drive system that can either work on its own or in conjunction with the gas engine. As the Outlander is able to deliver 248 horsepower, that would make the Rogue PHEV more powerful than the existing model’s 201 hp. The Outlander is also rated for 38 miles of electric driving by the EPA.

In addition, Nissan is planning to bring its non-plug-in, e-Power series hybrid technology to the U.S. in 2026. This technology, already available outside the U.S., also uses electric motors to power the wheels while using the gas engine to charge the battery.

These days, artificial intelligence is everywhere. The majority of large tech companies have embraced artificial intelligence, either by creating their own models or incorporating third-party models into their services or new features. Meta, one of the industry’s big players, has announced a new “Self-Taught Evaluator” AI model that aims to autonomously evaluate and train other AI models.

One of the main problems with developing AI models is the related costs. In the current state of the industry, large investments are needed to catch up and be competitive. Furthermore, developers use a technique known as “Reinforcement Learning from Human Feedback” (RLAIF) during the training process. As its name suggests, RLAIF requires human participation, which can slow down the process. That said, Meta’s new Self-Taught Evaluator aims to eliminate such a requirement.

Meta’s Self-Taught Evaluator AI model can train and evaluate other AIs without human intervention

RLAIF makes use of human experts to ensure that the AI in development gives solid and reliable answers. After all, it doesn’t matter how powerful an AI is if it has a high error rate. Human parties must also ensure that the data used for the AI training process is factually correct. This not only increases development times but also associated costs.

However, Meta’s Self-Taught Evaluator model is capable of evaluating and training other AI models. To achieve this, Self-Taught Evaluator uses the “chain of thought” technique that OpenAI implemented in the o1 models. This technique is based on addressing complex problems by dividing them into smaller logical steps. This results in more precise answers in advanced areas such as science, coding, and mathematics.

In fact, Meta developed the Self-Taught Evaluator model itself with the chain of thought technique. They used data purely generated by AI to train it. “We hope, as AI becomes more and more super-human, that it will get better and better at checking its work so that it will actually be better than the average human,” said Jason Weston, one of the researchers involved.

Teasing a potential future full of autonomous AIs

AI capable of learning and evaluating by itself without human intervention sounds like a futuristic concept straight out of a science fiction movie. However, recent developments suggest that we might not be too far away from something like this. AI experts suggest that the implementation of such models in various fields could largely eliminate human intervention.