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Prime Day is here, and although Amazon might not be an official retailer for the Nintendo Switch 2 console, you can still find deals on original Switch consoles, games, accessories, and more during the annual Prime Day sale. 

Get daily deals straight to your inbox during Prime Day when you sign up for ZDNET Recommends, your one-stop newsletter for the sale.

Also: The best Prime Day deals so far

If you’ve been disappointed in Amazon’s early Prime Day offerings in the way of Nintendo deals, other retailers like Best Buy, Walmart, and even the Nintendo eShop are offering markdowns on everything from refurbished consoles to pro-grade controllers and popular titles. To help you find the best deals, I put together the steepest markdowns I could find on everything Nintendo ahead of Prime Day.

Best Prime Day 2025 Nintendo Switch and Switch 2 deals

More Prime Day 2025 Nintendo Switch and Switch 2 deals

• Final Fantasy 1-6 Collection: $45 (save $30): All 6 original NES and SNES Final Fantasy games in one modern collection with updated 2D pixel art, streamlined controls, and modernized UI.
• Samsung Pro Plus Sonic the Hedgehog 1TB micro SDXC: $70 (save $50): Instantly add up to 1TB of storage to your original Switch or Switch 2 console for downloading large game files and managing your digital library.
• Bluey: The Videogame: $20 (save $20): Based on the popular kid’s show, players can work together to complete puzzles and challenges and recreate moments from the show.
• Just Dance 2025 Limited Edition: $20 (save $30): The latest entry in the wildly popular Just Dance series includes tracks from Sabrina Carpenter, Billie Eilish, and other top artists. This version also includes an exclusive unicorn avatar.
• Metal Gear Solid Master Collection Vol. 1: $17 (save $13): A collection of the first three Metal Gear Solid games originally released for the PS1 as well as the NES version of the original Metal Gear and Snake’s Revenge.
• TMNT Mutants Unleashed: $18 (save $12): An all-new adventure starring everyone’s favorite heroes in the half-shell as you and a friend team up to patrol the streets and save the city from a wave of mutant invaders.
• Teenage Mutant Ninja Turtles: Shredder’s Revenge: $23 (save $12): A new beat-em-up game starring the TMNT and harkens back to the heydays of arcade action.

More Nintendo Switch and Switch 2 deals from other retailers

TL;DR: Through July 15, you can own multiple AI models by grabbing a $30 1min.AI Pro lifetime subscription.

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If you’re using multiple AI apps to write content, generate images, summarize PDFs, or even clean up your grammar, there’s now a single platform that brings many of those tools together — and it’s currently available for a one-time payment of $29.97 (reg. $234) until July 15.

1minAI isn’t just one tool — it’s more like a personal AI dashboard that connects to some of the biggest models available today, including GPT-4, Claude 3, Gemini Pro, Llama 3, and others. You’ll get access to writing assistants, keyword researchers, image generators, audio-to-text transcription, translation, PDF summarizing, code helpers, and more — all bundled into one platform.

With the Pro Plan, you receive 1 million AI credits per month, with rollover for unused credits, plus 450,000 bonus credits if you use the platform consistently. That’s enough to generate a significant amount of content each month, whether you’re drafting articles, creating images for social posts, or just experimenting with AI tools for work or personal use.

Mashable Trend Report

There’s also no need to juggle multiple subscriptions — everything is covered under the lifetime license, and AI models include ChatGPT, Claude, Gemini, and so many others. The platform includes unlimited prompt storage, saved brand voices, file handling, and weekly updates as features improve over time.

This deal isn’t for everyone. If you only use AI occasionally or prefer to stick with free versions, it might be more than you need. But if you regularly tap into AI for content creation, marketing, or productivity tasks, the math works out: this is one of the lowest lifetime-cost-per-feature AI plans out there right now — and it’s a one-time payment.

Just note: supplies are limited, and deals like this don’t tend to stick around. If it fits your workflow, now might be the right time to grab it, especially since the price goes back up on July 15 at 11:59 p.m. PT.

Grab your 1min.AI lifetime license now for just $29.97.

StackSocial prices subject to change.

Topics
Artificial Intelligence

A novel artificial intelligence (AI) tool using motion-tracking data may one day help diagnose autism and attention-deficit/hyperactivity disorder (ADHD) in children with greater speed and precision, according to a study published in Scientific Reports.¹

The study was led by Jorge V. José, PhD, James H. Rudy professor of physics and adjunct professor of anatomy, cell biology, and physiology at Indiana University, who said this new tool has the potential to change how neurodivergent conditions are assessed.² His team demonstrated that deep learning models trained on high-resolution kinematic data could accurately distinguish between patients who are neurotypical and those with autism, ADHD, or both, based on subtle movement biomarkers invisible to the naked eye.³

Motion as a Diagnostic Window

Children with neurodivergent disorders often face long delays before receiving a formal diagnosis—up to 18 months in some areas, including Indiana, according to the news release.² Current diagnosis methods largely rely on behavioral observations and surveys, which can be time-consuming and subjective. This study proposes an objective and scalable alternative: using movement data captured during a simple reaching task to screen for neurodivergent traits.

“By studying the statistics of the motion fluctuations, invisible to the naked eye, we can assess the severity of a disorder in terms of a new set of biometrics,” José said. “No psychiatrist can currently tell you how serious a condition is.”

To test this, participants wore wireless motion sensors while performing touchscreen-based reaching tasks.¹ The sensors recorded linear acceleration, angular velocity, and roll-pitch-yaw (RPY) orientation at millisecond resolution. These data streams were then analyzed using a long short-term memory deep learning model, trained to classify participants into 1 of 4 categories based on whether they were neurotypical, had autism, had ADHD, or had comorbid autism and ADHD.

Strong Accuracy in Classification

The deep learning models achieved a mean test accuracy of 71.48% when using all 3 kinematic signal types, but classification performance varied by input type. RPY data alone yielded the highest individual signal accuracy at 67.83%, compared with just 44.44% with linear acceleration data and 32.17% with angular velocity.

Looking at combinations, RPY and linear acceleration data together yielded a 71.79% accuracy in categorizing participants, performing better as a pair than with angular velocity and with all 3 combined.

Notably, classification was most accurate for distinguishing patients who are neurotypical from those with neurodivergence. The tool was less reliable for identifying children who have both autism and ADHD, echoing clinical challenges with comorbid diagnoses.

“After training on a larger and more comprehensive dataset, the Deep Learning approach could play an important role as an early screening tool for participants suspected of having a neurodivergent disorder, not only in the clinic but also in schools and other non-medical settings,” the study team wrote. “With rapid improvements in sensor technology, MEM [micro-electromechanical] sensors are becoming more affordable, reliable, and ubiquitous (such as in smartphones and smartwatches) making the study of kinematic data for applications such as this increasingly relevant.”

Quantifying Severity With Biometrics

Beyond simply identifying neurodivergent conditions, the study also looked at novel biomarkers, specifically the Fano Factor and Shannon Entropy, based on the statistical patterns in participants’ micromovements. These metrics quantified randomness in movement, which the researchers linked to symptom severity.

Children with more severe autism or ADHD tended to have higher entropy and distinct fluctuation patterns in their acceleration data. For example, participants with low-functioning autism exhibited much greater variability in their hand motions than those with milder forms of the condition.

While the technology is not intended to replace physicians or a clinical diagnosis, the authors envision it as a triage or screening tool that could be deployed in primary care offices, schools, or telehealth settings, especially in underserved or high-wait regions.² José’s team estimates that a 15-minute session could be sufficient for data collection, making it suitable for early screening interventions.

“Some patients will need a significant number of services and specialized treatments,” José said in the news release. “If, however, the severity of a patient’s disorder is in the middle of the spectrum, their treatments can be more minutely adjusted, will be less demanding and often can be carried out at home, making their care more affordable and easier to carry out.”

References

1. Doctor KP, McKeever C, Wu D, et al. Deep learning diagnosis plus kinematic severity assessments of neurodivergent disorders. Sci Rep. Published online July 8, 2025. doi:10.1038/s41598-025-04294-9
2. Artificial intelligence used to improve speed and accuracy of autism and ADHD diagnoses. News release. EurekAlert. July 8, 2025. Accessed July 8, 2025. https://www.eurekalert.org/news-releases/1090448
3. Wu D, José JV, Nurnberger JI, Torres EB. A biomarker characterizing neurodevelopment with applications in autism. Sci Rep. 2018;8(1):614. doi:10.1038/s41598-017-18902-w