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Game

Switch Online’s Expansion Pack Costs Double The Base Version

While today’s Animal Crossing Direct was largely about the game’s upcoming 2.0 update and newly revealed DLC, Nintendo also snuck in pricing details for its new version of Nintendo Switch Online. Titled Nintendo Switch Online + Expansion Pack, the service will cost individual users $50 per year, while a family plan version that lets up to eight accounts use the service will cost $80.

Nintendo Switch Online + Expansion Pack was revealed during Nintendo’s last Direct showcase. The upgraded version of Nintendo Switch Online will give its users access to a library of Nintendo 64 and Sega Genesis titles, as well as to the new Animal Crossing: New Horizons paid DLC, Happy Home Paradise. While pricing for the service has been revealed, Nintendo has not revealed when users will actually be able to subscribe to Nintendo Switch Online + Expansion Pack.

It’s worth noting that Nintendo Switch Online + Expansion Pack’s pricing is a fair leap from what users pay for the base version of the service. A yearlong individual membership for Nintendo Switch Online costs only $20, while a family plan runs customers just $35. In both cases, Nintendo Switch Online + Expansion Pack is more than twice the cost of its basic counterpart.

For users, that pricing might be a bit high. Nintendo Switch Online itself has drawn criticism over the years for its lackluster library of games and Nintendo’s own subpar multiplayer service, which doesn’t offer any voice chat capability. Users may be hesitant to shell more money out to the company without being assured that the service’s base issues will also be addressed in the Nintendo Switch Online + Expansion Pack.

Editors’ Choice




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Categories
Game

Nintendo’s Switch Online ‘Expansion Pack’ costs $50 a year, launches October 25th

Nintendo held a Direct video presentation this morning, announcing two major updates for Animal Crossing: New Horizons. One is a free bit of DLC, and the other is a paid, $25 expansion called Happy Home Paradise. Unexpectedly, Nintendo used this announcement to reveal the price of the upcoming Switch Online “expansion pack.” The service, which adds classic N64 and Sega Genesis games to the existing Switch Online offerings, will cost $50 per year or $80 for a family plan. This expansion will include access to the $25 Happy Home Paradise DLC — so if you’re an Animal Crossing: New Horizons player, it’s like getting the rest of the Expansion Pack benefits for $5.

Shortly after this story was published, Nintendo released more details about the expansion pack, including its October 25th launch date. If you already have a Switch Online subscription, you’ll be able to upgrade at a pro-rated cost depending on how much time was left on your original plan.There are more details about the expansion pack in the video above as well as on Nintendo’s site.

Finally, you can now pre-order the N64 and Sega Genesis controllers that are compatible with the Switch. A single controller will cost $50, and there doesn’t appear to be any discount for pairs. Given how good Nintendo’s previous classic controllers have been, we expect these should feel like authentic reproductions.

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AI

AI Weekly: AI model training costs on the rise, highlighting need for new solutions

This week, Microsoft and Nvidia announced that they trained what they claim is one of the largest and most capable AI language models to date: Megatron-Turing Natural Language Generation (MT-NLP). MT-NLP contains 530 billion parameters — the parts of the model learned from historical data — and achieves leading accuracy in a broad set of tasks, including reading comprehension and natural language inferences.

But building it didn’t come cheap. Training took place across 560 Nvidia DGX A100 servers, each containing 8 Nvidia A100 80GB GPUs. Experts peg the cost in the millions of dollars.

Like other large AI systems, MT-NLP raises questions about the accessibility of cutting-edge research approaches in machine learning. AI training costs dropped 100-fold between 2017 and 2019, but the totals still exceed the compute budgets of most startups, governments, nonprofits, and colleges. The inequity favors corporations and world superpowers with extraordinary access to resources at the expense of smaller players, cementing incumbent advantages.

For example, in early October, researchers at Alibaba detailed M6-10T, a language model containing 10 trillion parameters (roughly 57 times the size of OpenAI’s GPT-3) trained across 512 Nvidia V100 GPUs for 10 days. The cheapest V100 plan available through Google Cloud Platform costs $2.28 per hour, which would equate to over $300,000 ($2.28 per hour multiplied by 24 hours over 10 days) — further than most research teams can stretch.

Google subsidiary DeepMind is estimated to have spent $35 million training a system to learn the Chinese board game Go. And when the company’s researchers designed a model to play StarCraft II, they purposefully didn’t try multiple ways of architecting a key component because the training cost would have been too high. Similarly, OpenAI didn’t fix a mistake when it implemented GPT-3 because the cost of training made retraining the model infeasible.

Paths forward

It’s important to keep in mind that training costs can be inflated by factors other than an algorithm’s technical aspects. As Yoav Shoham, Stanford University professor emeritus and cofounder of AI startup AI21 Labs, recently told Synced, personal and organizational considerations often contribute to a model’s final price tag.

“[A] researcher might be impatient to wait three weeks to do a thorough analysis and their organization may not be able or wish to pay for it,” he said. “So for the same task, one could spend $100,000 or $1 million.”

Still, the increasing cost of training — and storing — algorithms like Huawei’s PanGu-Alpha, Naver’s HyperCLOVA, and the Beijing Academy of Artificial Intelligence’s Wu Dao 2.0 is giving rise to a cottage industry of startups aiming to “optimize”  models without degrading accuracy. This week, former Intel exec Naveen Rao launched a new company, Mosaic ML, to offer tools, services, and training methods that improve AI system accuracy while lowering costs and saving time. Mosaic ML — which has raised $37 million in venture capital — competes with Codeplay Software, OctoML, Neural Magic, Deci, CoCoPie, and NeuReality in a market that’s expected to grow exponentially in the coming years.

In a sliver of good news, the cost of basic machine learning operations has been falling over the past few years. A 2020 OpenAI survey found that since 2012, the amount of compute needed to train a model to the same performance on classifying images in a popular benchmark — ImageNet — has been decreasing by a factor of two every 16 months.

Approaches like network pruning prior to training could lead to further gains. Research has shown that parameters pruned after training, a process that decreases the model size, could have been pruned before training without any effect on the network’s ability to learn. Called the “lottery ticket hypothesis,” the idea is that the initial values parameters in a model receive are crucial for determining whether they’re important. Parameters kept after pruning receive “lucky” initial values; the network can train successfully with only those parameters present.

Network pruning is far from a solved science, however. New ways of pruning that work before or in early training will have to be developed, as most current methods apply only retroactively. And when parameters are pruned, the resulting structures aren’t always a fit for the training hardware (e.g., GPUs), meaning that pruning 90% of parameters won’t necessarily reduce the cost of training a model by 90%.

Whether through pruning, novel AI accelerator hardware, or techniques like meta-learning and neural architecture search, the need for alternatives to unattainably large models is quickly becoming clear. A University of Massachusetts Amherst study showed that using 2019-era approaches, training an image recognition model with a 5% error rate would cost $100 billion and produce as much carbon emissions as New York City does in a month. As IEEE Spectrum’s editorial team wrote in a recent piece, “we must either adapt how we do deep learning or face a future of much slower progress.”

For AI coverage, send news tips to Kyle Wiggers — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI channel, The Machine.

Thanks for reading,

Kyle Wiggers

AI Staff Writer

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AI

Google’s Unattended Project Recommender aims to cut cloud costs

All the sessions from Transform 2021 are available on-demand now. Watch now.


Google today announced Unattended Project Recommender, a new feature of Active Assist, Google’s collection of tools designed to help optimize Google Cloud environments. Unattended Project Recommender is intended to provide a “a one-stop shop” for discovering, reclaiming, and shutting down unattended cloud computing projects, Google says, via actionable and automatic recommendations powered by machine learning algorithms.

In enterprise environments, it’s not uncommon for cloud resources to occasionally be forgotten about. Not only can these resources can be difficult to identify, but they also tend to create a lot of headaches for product teams down the road — including unnecessary waste. A recent Anodot survey found fewer than 20% of companies were able to immediately detect spikes in cloud costs and 77% of companies with over $2 million in cloud costs were often surprised by how much they spent.

Unattended Project Recommender, which is available through Google Cloud’s Recommender API, aims to address this by identifying projects that are likely abandoned based on API and networking activity, billing, usage of cloud services, and other signals. As product managers Dima Melnyk and Bakh Inamov explain in a blog post, the tool was first tested with teams at Google over the course of 2021, where it was used to clean up internal unattended projects and eventually the projects of select Google Cloud customers, who helped to tune Unattended Project Recommender based on real-life data.

Machine learning

Unattended Project Recommender analyzes usage activity across all projects within an organization, including items like service accounts with authentication activity, API calls consumed, network ingress and egress, services with billable usage, active project owners, the number of active virtual machines, BigQuery jobs, and storage requests. Google Cloud customers can automatically export recommendations for investigation or use spreadsheets to interact with the data, as well as Google Workspace.

“Based on [various] signals, Unattended Project Recommender can generate recommendations to clean up projects that have low usage activity, where ‘low usage’ is defined using a machine learning model that ranks projects in [an] organization by level of usage, or recommendations to reclaim projects that have high usage activity but no active project owners,” Melnyk and Inamov wrote. “We hope that [customers] can leverage Unattended Project Recommender to improve [their] cloud security posture and reduce cost.”

Google notes that, as with any other tool, customers can choose to opt out of data processing by disabling the corresponding groups in the “Transparency & control” tab under Google Cloud’s Privacy & Security settings.

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AI

Spell unveils deep learning operations platform to cut AI training costs

All the sessions from Transform 2021 are available on-demand now. Watch now.


Spell today unveiled an operations platform that provides the tooling needed to train AI models based on deep learning algorithms.

The platforms currently employed to train AI models are optimized for machine learning algorithms. AI models based on deep learning algorithms require their own deep learning operations (DLOps) platform, Spell head of marketing Tim Negris told VentureBeat.

The Spell platform automates the entire deep learning workflow using tools the company developed in the course of helping organizations build and train AI models for computer vision and speech recognition applications that require deep learning algorithms.

Deep roots

Deep learning algorithms trace their lineage back to neural networks in a field of machine learning that structures algorithms in layers to create a neural network that can learn and make intelligent decisions on its own. The artifacts and models that are created using deep learning algorithms, however, don’t lend themselves to the same platforms used to manage machine learning operations (MLOps), Negris said.

An AI model based on deep learning algorithms can require tracking and managing hundreds of experiments with thousands of parameters spanning large numbers of graphical processor units (GPUs), Negris noted. The Spell platform specifically addresses the need to manage, automate, orchestrate, document, optimize, deploy, and monitor deep learning models throughout their entire lifecycle, he said. “Data science teams need to be able to explain and reproduce deep learning results,” Negris added.

While most existing MLOps platforms are not well suited to managing deep learning algorithms, Negris said the Spell platform can also be employed to manage AI models based on machine learning algorithms. Spell does not provide any tools to manage the lifecycle of those models, but data science teams can add their own third-party framework for managing them to the Spell platform.

The Spell platform also reduces cost by automatically invoking spot instances that cloud service providers make available for a finite amount of time whenever feasible, Negris said. That capability can reduce the total cost of training an AI model by as much as 66%, he added. That’s significant because the cost of training AI models based on deep learning algorithms can in some cases reach millions of dollars.

A hybrid approach

In time, most AI applications will be constructed using a mix of machine and deep learning algorithms. In fact, as the building of AI models using machine learning algorithms becomes more automated, many data science teams will spend more of their time constructing increasingly complex AI models based on deep learning algorithms. The cost of building AI models based on deep learning algorithms should also steadily decline as GPUs deployed in an on-premises IT environment or accessed via a cloud service become more affordable.

In the meantime, Negris said that while the workflows for building AI models will converge, it’s unlikely traditional approaches to managing application development processes based on DevOps platforms will be extended to incorporate AI models. The continuous retraining of AI models that are subject to drift does not lend itself to the more linear processes that are employed today to build and deploy traditional applications, he said.

Nevertheless, all the AI models being trained eventually need to find their way into an application deployed in a production environment. The challenge many organizations face today is aligning the rate at which AI models are developed with the faster pace at which applications are now deployed and updated.

One way or another, it’s only a matter of time before every application — to varying degrees — incorporates one or more AI models. The issue going forward is finding a way to reduce the level of friction that occurs whenever an AI model needs to be deployed within an application.

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Computing

This HP Chromebook Costs $299 and Is Perfect for Students

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Chromebooks occupy a weird space between a full desktop experience and a workstation or laptop, as they’re running Chrome OS instead of Windows or another operating system. Most people don’t even know there are a lot of things Chromebooks can do.

Take HP’s Pro c645 Chromebook, for example, which is on sale for super cheap right now. Dropping $125 off the price, HP has it available for $299 with free shipping. Plus, you can earn some member rewards through HP and get an additional 5% off select accessories you grab with it.

Okay, so it may not be on our list of the best Chromebooks for 2021, but that doesn’t mean the Pro c645 Chromebook is not impressive — it is. It’s sleek and lightweight, perfect for lugging back and forth between home, work, and school. It has considerably more power than most Chromebooks, too, thanks to an AMD Athlon Silver 3050c processor with a 4MB cache and clock speeds from 2.3GHz to 3.2GHz. It also has integrated AMD Radeon graphics, 4GB of DDR4 SDRAM, and 32GB of eMMC storage.

The 14-inch narrow-bezel HD display runs at a native resolution of 1366 x 768, with a 250-nits brightness rating. A 720P HD webcam rests just inside the top bezel. Ports include two USB Super Speed Type-C, two Super Speed USB Type-A, a headphone and mic combo, an HDMI 1.4, and a microSD card slot. Intel AX200 Wi-Fi 6 ensures you have the latest wireless standard with excellent connectivity, plus there’s Bluetooth 5 onboard for syncing wireless peripherals. The whole thing is wrapped in a beautiful silver aluminum chassis.

Normally $424, HP is offering the Pro c645 Chromebook for $299, which is $125 off. You also get free shipping, HP rewards points, and 5% off select accessories — like a carrying bag, care plan, or monitor. Act soon — we don’t know how long this one is going to be available.

We strive to help our readers find the best deals on quality products and services, and we choose what we cover carefully and independently. The prices, details, and availability of the products and deals in this post may be subject to change at anytime. Be sure to check that they are still in effect before making a purchase.

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Editors’ Choice




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AI

Duke Energy used computer vision and robots to cut costs by $74M

All the sessions from Transform 2021 are available on-demand now. Watch now.


Duke Energy’s AI journey began because the utility company had a business problem to solve,  Duke Energy chief information officer Bonnie Titone told VentureBeat’s head of AI content strategy Hari Sivaraman at the Transform 2021 virtual conference on Thursday.

Duke Energy was facing some significant challenges, such as the growing issue of climate change and the need to transition to clean energy in order to reach net zero emissions by 2050. Duke Energy is considered an essential service, as it supplies 25 million people with electricity daily, and everything the utility company does revolves around a culture of safety and reliability. The variables together was a catalyst for exploring AI technologies, Titone said, because whatever the company chose to do, it had to support the clean energy transition, deliver value to customers, and find a way for employees to work and improve safety.

“We look to emerging data science tools and AI solutions, which in turn brought us to computer vision, and ultimately, drones in order to inspect our solar farms,” Titone said.

There is a significant amount of solar farms in the shift to clean energy — Florida alone has 3 million solar panels, Titone said — and inspecting them is a very labor-intensive, time-consuming, and risky endeavor. It can take about 40 hours to inspect one unit, and a regular solar site may have somewhere between 20 and 25 units to inspect. It’s a dangerous task, as technicians walk around 500-acre solar sites with heat guns so they can inspect the panels and may need to touch live wires. The company began experimenting with advanced drones with infrared cameras to try to streamline the work. The technicians were able to use the images taken by the drones to determine where they’re seeing faults and issues. Thousands of images were stitched together with computer vision, giving technicians the ability to look for issues using the images in a much safer way, Titone said.

After finding the computer vision, Duke Energy began to consider automating the process. The company developed a MOVES model (Mobile Observation Vehicle and Equipment Solutions) that collects and processes the data and images from the drones and identifies the faults within minutes. Through applying AI and machine learning technologies, the program has significantly reduced labor and time costs for the company. Accuracy also continued to improve over the time; the latest model used in the inspection reached 91% accuracy.

“We compiled that information for the technicians and gave them the ability to navigate pretty easily to where we can schedule maintenance for customers, and we did this all without a technician ever having to go out to the site,” Titone said. The program has led to more than $74 million reductions in cost and 385,000 in man-hours.

Cloud and edge processing

Duke Energy had to consider the question of how to process the data the drones were collecting. A typical drone flight can produce thousands of photos, sometimes with no precise location data associated with the images. Trying to do the analysis in the cloud to figure out if the drone image showed a solar site would be impossible because of the sheer amount of data and information involved. Duke Energy had to process the images at the edge so that it could make real-time decisions. The images had to be stitched together to make a precise picture of the solar farm without having to require somebody go and actually walk around the site.

Instead of trying to do everything at once, Duke Energy worked on small increments of the project. Once one thing worked, the team moved on to the next step. Since Duke Energy had its own software engineering team, it was able to build its own models with its own methodologies as part of a one-stop shop. This process eventually led to creating over 40 products.

Titone said, “Had we not had that footprint in the cloud journey, we wouldn’t have been able to develop these models and be able to process that data as quickly as we could.”

Working with data

Titone also discussed best practices with storing and cleaning data. As the team has moved toward a cloud-based data strategy, it uses a lot of data lakes. The data lakes are accessible by other systems and also by some data analysis and data science components that must quickly process the information.

“I would say we’re using a lot of the traditional methods around data lakes in order to process all of that,” Titone said, and the team models the data with “what we call our MATLAB, which stands for machine learning, AI and deep learning.”

Reflecting upon the high accuracy that the product reached, Titone said that it was important to be OK with failing in the beginning. “I think at the beginning of the journey, we didn’t have an expectation that we would get right out of the gate,” she said. As time moved on, the team learned and continued to modify the model according to the results. For example, in the journey with iterations and reflections, the team realized that they should not only extract images but piece different processing techniques together. They also adjusted the angle and height of the drone.

AI as a career opportunity

The fact that AI is more efficient and cost-effective does result in reduced labor hours, which raises the concern that AI is taking jobs away from people. Titone said the better perspective was to view this as an opportunity. She said that upskilling employees to be able to work with AI was an investment in the workforce. If the employees understand AI, she said, they become more valuable as workers because they qualify for more advanced roles.

“I never approach AI as taking somebody’s job or role; the way I’ve always approached AI is that it should complement our workforce, that it should give us a set of skills and career paths that our teammates can take,” Titone said.

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Tech News

You can ace three key CompTIA certification exams — and it costs under $25 for the training

TLDR: The Premium Core CompTIA Certification Prep Bundle gets students ready to take and ace three of CompTIA premiere IT training certification exams.

“While a number of technologists might not think certifications are vital to their job, possessing one (or more) can help them stand out in a crowded market, as well as give them leverage in negotiations for better roles, salaries and benefits.” — Dice Insights

Earn a top-flight IT certification and it can be a game-changer for your job prospects. Those are the findings of Dice Insights, who broke it all down in their Dice 2021 Tech Salary Report

And right there on their list of the top 20 IT certifications students can earn to add extra zeros to their paycheck are three certs from longtime IT training authority CompTIA: A+, Network+, and Security+.

For those looking to crack six figures as they climb the IT career ladder, the training in The Premium Core CompTIA Certification Prep Bundle ($23.99 after code WELOVEDAD from TNW Deals) can help land those three foundational CompTIA designations.

The package of training here is simple, including three courses tasked with guiding students to mastery over the CompTIA A+, Network+, and Security+ exams.

It starts with CompTIA A+ Core (220-1001/220-1002), geared toward learners with basic computer skills who are ready to get a job as an entry-level IT pro. This course lays that foundation, covering everything from PC installation, configuration, and troubleshooting, to network infrastructure concepts and how to make them work in the real world. By passing the A+ test, a student has shown they’re ready for the intense world of IT work.

Next, the Complete CompTIA Network+ N10-007 digs deeper into the networking portion, again for entry-level network techs. The training covers networks both big and small, including everything from cloud and visualization technologies to network access rules and all the important elements of control protocols.

Finally, Complete CompTIA Security+ SY0-601 rounds out the coursework with a thorough examination of the security issues any IT expert needs to know. Recognized worldwide as a benchmark cert, this training gets into cyber attacks, threats, vulnerabilities and more. Students also learn about risk management, governance, and compliance en route to this vital certification.

Each course in the Premium Core CompTIA Certification Prep Bundle is a $275 value, but in addition to the regular price cut, you can also save an additional 20 percent off this collection by using the code WELOVEDAD when you check out. But the time you’re finished, you’re playing less than $8 per course, only $23.99

Prices are subject to change.

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Computing

This sleek, Core i7-equipped Acer Swift 3 laptop costs just $530 after a massive $240 discount

If you’ve been on the hunt for a sleek yet powerful Windows 10 laptop that won’t leave you penniless, today’s your day. Newegg is selling the Acer Swift 3 for just $530 until Monday. That’s way down from the best price Amazon has ever had on this laptop at $604. And to sweeten this already juicy deal, Newegg will also toss in a $30 promotional gift card that you usually receive four days after invoicing.

This particular laptop comes in gold only at the sale price. It’s rocking a quad-core (eight thread) Core i7-8550U with a clock speed of 1.8GHz and a turbo frequency of 4GHz. This is a last-generation Kaby Lake R processor, but it’s still very powerful, and a solid piece of silicon for running this rig.

The Swift 3 also comes with 8GB of RAM, a 256GB SSD, and a 15.6-inch 1080p IPS display with a 178-degree viewing angle. It’s rocking one HDMI port, two USB 3.0 ports, one USB-C, one USB 2.0 connection, and a multi-card reader. Acer’s notebook also offers a fingerprint reader, a backlit keyboard, and an “aluminum all-metal body.” 

Acer is known for creating well priced, but dependable laptops. If you need a new Windows laptop this is a great choice (as long as you don’t mind the color). You don’t find laptop this fully loaded and this powerful in this price range very often.

[Today’s deal: Acer Swift 3 SF315-52-81HD for $530 plus a $30 gift card at Newegg.]

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Ian is an independent writer based in Israel who has never met a tech subject he didn’t like. He primarily covers Windows, PC and gaming hardware, video and music streaming services, social networks, and browsers. When he’s not covering the news he’s working on how-to tips for PC users, or tuning his eGPU setup.

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Game

Super Mario 3D World + Bowser’s Fury Review: A ton of fun, but it still costs too much

Stop me if you’ve heard this one before: A huge multinational company launches a game platform that’s an abject failure, drops it after just four years on the market, and then launches a new console that turns out to be a huge success. It takes all of the old first-party games it released on that previous console, which all had very limited audiences thanks to poor console sales, and re-releases them on the new, much more successful console for full price despite the fact that they’re all years old at this point. There is no punchline.

Bringing old Wii U games forward to the Nintendo Switch has been Nintendo’s modus operandi since shortly after the Switch launched, with Nintendo kicking things off with Mario Kart 8 Deluxe. Mario Kart 8 Deluxe has gone on to be one of the best-selling games on the Switch (and, in fact, before Animal Crossing: New Horizons came around, it was the single best-selling game on the Switch), and from there, the classics just kept coming forward.

Pokken Tournament, New Super Mario Bros U, Pikmin 3, Hyrule Warriors, and Donkey Kong Tropical Freeze are all included on that list, and in addition to all being Wii U games, the thing they have in common is the fact that they all cost $60 on the Switch. In most cases, these games didn’t add a significant amount of new content, but often we’d see DLC bundled in with the base game for their Switch releases, if there was any DLC to speak of.

Now we’ve got Super Mario 3D World, which was one of the Wii U’s flagship games. It has arrived on Switch with an entirely new expansion called Bowser’s Fury, and it still unsurprisingly has that $60 price tag. Is it worth it? That ultimately depends on how much you like Mario, and maybe more importantly, whether or not you owned a Wii U.

Super Mario 3D World

Even though this new game is titled Super Mario 3D World + Bowser’s Fury, Super Mario 3D World makes up most of the content in this package. To my knowledge, this is more or less a straight port of the game as it appeared on Wii U, save for a few quality of life changes and other tweaks to make up for the fact that there’s no touchscreen or microphone on the Switch controller.

For those who haven’t played Super Mario 3D World before, it’s probably best explained as a cross between traditional 2D Mario games and the newer 3D Mario titles. The game is broken up into worlds and stages just like a 2D Mario game would be, and while some of the stages have side-scrolling elements, many of them are designed in 3D. Super Mario 3D World is the successor to Super Mario 3D Land on the 3DS, which was a very good game in its own right.

Super Mario 3D World can be played solo or multiplayer with up to four players, and when you’re playing the game with three other people, it’s almost always a hectic time. The vast majority of my playtime was spent playing the game solo, and I have to say, I love almost everything about it.

I have a hard time finding any significant flaws with Super Mario 3D World. I think the cat suit – introduced as this game’s signature power-up – is fantastic, as it has you running through stages on all fours, swiping at enemies with your claws, and climbing up walls to discover secrets. You’ll put that cat suit to good use too as there are three green stars and a stamp to find in each level.

If you want to 100% the game, you’ll need to not only find those stars and stamps, but you’ll need to hit the top of the flagpole at the end of each level as well, something that the cat suit makes so much easier as cat Mario (or cat Luigi, cat Peach, or cat Toad) will climb up to the top of the pole – but of course, that requires you to make it to the end of each level with you cat power-up intact.

From a level design standpoint, I think Super Mario 3D World is wonderful. The levels are varied, compelling, and boast some of the strongest designs we’ve seen in any Mario game bar none. Any touchscreen segments that were present in the original game have been replaced with gyro controls, and though those take a little while to get the hang of, eventually they won’t be any issue. Gyro segments are few and far between, too, so it’s not like you’ll have to use motion controls all that often – good news for people who loathe motion controls like me.

Super Mario 3D World is a beautiful looking game too. I really enjoy everything about this game, and as someone who didn’t really dig into it back in the days of the Wii U, it’s nice to have this one come forward to the Switch.

On the whole, I think Super Mario 3D World might be a little easier than some of the other Mario games out there, but there were still plenty of later levels that claimed life after life from me. I also think that the controls in Super Mario 3D World are a little more floaty than I’d usually prefer, but after playing through a few stages, you’ll quickly get used to them.

Beyond those very minor observations, I have no problems whatsoever with Super Mario 3D World. It’s a fantastic game from start to finish, and I intend on going back and collecting the stamps and goalposts I missed to 100% complete this game. If that isn’t a glowing recommendation, I’m not sure what is.

Bowser’s Fury

Then we come to Bowser’s Fury, an “expansion” of sorts that feels like it belongs more in Super Mario Odyssey than in Super Mario 3D World. Or, at least, it would feel that way if literally everything in Bowser’s Fury weren’t cat-themed. If you love cat Mario like I do, you’ll probably love playing through Bowser’s Fury, where you get to collect cat tokens as you do battle with cat Goombas, cat Koopas, and cat Piranha Plants. It’s a cat lover’s dream game, in other words.

Bowser’s Fury is an open world adventure that will last most players 3-6 hours and actually sees Mario teaming up with Bowser Jr. to stop Bowser, who has become a giant, corrupted, and particularly ruthless version of himself. You’ll progress through different areas of this in-game world as you play, collecting cat tokens and occasionally going one-on-one with Bowser himself, growing to his size through the use of the Giga Bell. Those battles definitely have a Godzilla feel to them, as two titans who dwarf everything else in the world square off.

There are a number of stages to explore in the open world of Bowser’s Fury, and each one has a lighthouse that progressively gets more powerful as you complete challenges and collect cat emblems. You only need to complete a handful of relatively easy challenges to finish Bowser’s Fury, but completionists will find a fair amount of difficulty in each stage’s later challenge.

I really enjoyed Bowser’s Fury; I think the stages are fun, the open-world design is fantastic and offers a nice alternative to the structure of Super Mario 3D World, and the challenges you’ll encounter are creative with the right amount of difficulty. The only real issue with Bowser’s Fury is that it’s clear the open world is pushing the Switch to its limit, as even in docked mode, the Switch can’t hit the resolution it achieves in Super Mario 3D World.

Super Mario 3D World + Bowser’s Fury verdict

Really, my major gripe with this game comes down to price. If I’ve said it once, I’ve said it a thousand times: the Wii U ports need to be priced at $40, not $60. I understand that Nintendo, more than any other company out there, tends to overvalue its IP, and here it can also claim that it’s basically a new experience to the many of us who never owned a Wii U. That doesn’t change the fact that Super Mario 3D World is turning 8 years old in 2021 – paying $60 for an eight year old game is outrageous whether you played it the first time around or not.

Bowser’s Fury, as fun as it is, is a relatively short expansion too, and it doesn’t make this pricing acceptable. It’s nice that we’re getting some kind of bonus content considering that most of the Wii U ports don’t typically offer anything new outside of previously-released DLC, but I would have really liked to see this package priced at $40. This is my one consistent criticism of these Wii U ports, and I will keep complaining about it as long as Nintendo keeps pricing them at $60 (though, at this point, it’s running out of games to port over from the Wii U).

I feel like I’m shouting at a brick wall here, because some of these Wii U ports have turned into major hits on the Switch. At this point, all Nintendo needs to do is look at the success of Mario Kart 8 Deluxe for reason to keep pricing these games at $60. Let’s not kid ourselves here: no matter how much I complain about it, Nintendo isn’t going to stop charging so much for these games, which is a disappointing realization to come to.

It isn’t as if this is a bad game, either. In fact it’s quite the opposite, and I think if Mario fans can handle the price tag – a bitter pill though it may be – most of them will love Super Mario 3D World + Bowser’s Fury. I don’t often get the drive to chase 100% completion in the games I play, but I will definitely be returning to Super Mario 3D World to see what secrets await when I collect all of the stamps and gold goalposts (I already made a point of collecting all the green stars I could on my initial playthrough).

Bowser’s Fury is just icing on the cake considering how fantastic Super Mario 3D World is, but more than anything, it makes me wish we had a follow-up to Super Mario Odyssey coming down the pipeline. Still, there’s no denying that this is a fantastic package where the only real sticking point is the price, so even though it hurts a little to say it, it deserves a spot in every Switch library even if it costs more than it should to put it on your shelf.

Repost: Original Source and Author Link