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Computing

This Asus laptop for $150 is the best laptop deal you’ll find today

If you’re in the market for an affordable, go-anywhere computing device, Best Buy has a great deal on an Asus 14-inch laptop right now. Currently you can save $110 on the Asus R410 Laptop, which brings its price down to a super affordable $150. Any laptop for $150 is one of the best laptop deals you’ll come across, and this Asus 14-inch laptop is no slouch when it comes to performance and capability. Read on for more details on this steal of a laptop deal.

Maybe you are a student looking for the best laptops for college, or you have professional computing needs and don’t want to break the bank. But whatever the case may be, this Asus 14-inch laptop is a solid option. It’s a perfect device for users whose primary work consists of creating professional documents and spreadsheets, but it’s also great for taking notes in class, enjoying a movie on the couch, and creating content for a blog or website. In fact, as spec’d for this deal, it has an Intel Celeron processor and 4GB of RAM, as well as lightning-fast 128GB of storage that shortens load times and offers plenty of space for your favorite apps.

When it comes to actually working on the Asus 14-inch laptop, the HD display boasts an impressive color range and presents everything you’re doing in stunning clarity. An energy-efficient LED backlight keeps your work bright without causing too much battery drain. Speaking of battery life, the Asus 14-inch laptop is able to reach up to 12 hours on a single charge, making it a great consideration if you do lots of work on the go and don’t have easy access to an outlet throughout the work day. It has an HD webcam for keeping in touch with friends and family, or for keeping in touch with colleagues and collaborators as well, putting it in with the likes of the best laptops for videoconferencing.

For just $150 you can bring a capable laptop into your digital workflow. While it typically costs $260, the Asus 14-inch laptop is seeing a $110 discount at Best Buy right now. Free shipping is included, and in most areas you can even pick it up in-store within an hour.

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Game

God of War PC requirements revealed: What you’ll need for top performance

Next month, we’ll see what is almost certainly the biggest Sony PC release yet. After bringing Horizon Zero Dawn and Days Gone to PC, Sony will be bringing 2018’s God of War to the platform in January. Today, Sony’s Santa Monica Studio revealed the PC specifications for the game, and it looks like it will run on a rather large array of configurations.

Santa Monica Studios/Sony

Minimum specs and maximum performance

Sony Santa Monica shared lists for five different specifications today, starting with the minimum required specifications ranging all the way up to the hardware needed to run God of War at ultra settings. As you might imagine, there’s a pretty big disparity between those two specs, with “recommended,” “high,” and “performance” specs in between.

The minimum required specifications will be good enough to run the game on the low graphics preset in 720p at 30fps, which isn’t great. Still, we work with what we’ve got in the world of PC gaming, and if you have at least an NVIDIA GTX 960 (4GB)/AMD R9 290X (4GB) GPU in your rig along with an Intel Core i5-2500k/AMD Ryzen 3 1200 CPU and 8GB of RAM, it’s good enough to run God of War.

Compare that to the ultra specification, and you’ll see just how big the difference between the minimum and maximum are. In order to run God of War on the ultra graphics preset in 4K at 60fps, you’ll need an RTX 3080 (10GB)/RX 6800 XT (16GB) along with an Intel Core i9-9900k/AMD Ryzen 9 3950X and 16GB of RAM. Considering how hard it is to get both the RTX 3080 and RX 6800 XT, we’re guessing that most gamers will probably have to settle for a lower spec.

Santa Monica Studios/Sony

Thankfully, that’s what is required to run the game at 4K60, so lower resolutions will ease up on the hardware requirements a fair amount. You can check the other specifications in the image we’ve embedded above, but hardware specifications aren’t the only thing Sony’s Santa Monica Studio revealed about the PC version of God of War today.

The studio also confirmed today that God of War will support NVIDIA DLSS in rigs with an RTX GPU, which uses supersampling to allow the game to run at higher resolutions without sacrificing framerates. The game will also support NVIDIA Reflex to cut back on system latency, though that requires at least a GTX 900-series GPU. Finally, God of War will support AMD’s FidelityFX Super Resolution, so Sony Santa Monica’s partnership with NVIDIA doesn’t mean that AMD users have to be left out in the cold.

You can see a sampling of God of War‘s PC features in the trailer above. Otherwise, look for God of War to land on Steam and the Epic Games Store on January 14th, 2022.

Sony’s PC game port plans

God of War screenshot

Sony/PlayStation Blog

In March 2020, PlayStation Worldwide Studios head Herman Hulst confirmed Sony’s plan at the time to bring Horizon Zero Dawn to PC (via PS Blog). The port raised new questions about the company’s plans for future major PlayStation exclusive games and whether they, too, would eventually make their way to desktop. At the time, Hurst reassured PlayStation fans that Sony is “very committed to dedicated hardware” and “very committed to quality exclusives.”

With that said, Hurst also went on to note that the company was “going to be very open to experimentation,” one example of which was the eventual Horizon Zero Dawn PC release. The studio’s leader indicated bringing a major PS game to PC served as a way to “introduce more people to PlayStation,” potentially making them aware of the kinds of games they can enjoy if they pick up a PlayStation console.

Hurst went on to state that “releasing one first-party AAA title to PC doesn’t necessarily mean that every game now will come to PC.” The statement left many doubtful that select other major PlayStation titles — including God of War — would make their way to PC. Fast-forward nearly two years and it’s clear Sony is continuing with this plan, though if the trend holds, it looks like PC gamers can expect to wait a couple of years after a major game’s release before it (potentially) makes its way to desktop systems.

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Game

‘Suicide Squad’ game trailer shows why you’ll take down the Justice League

It’s been over a year since Rocksteady and Warner Bros. revealed their Suicide Squad game, but now they’re finally ready to offer another peek — if not necessarily the one you were expecting. They’ve released a story trailer for Suicide Squad: Kill the Justice League that shows the formation of Task Force X and explains why your band of supervillains (Harley Quinn, Captain Boomerang, Deadshot and King Shark) has to destroy some of Earth’s greatest heroes.

As it turns out, Brainiac has possessed the Justice League and is using heroes to wreak havoc. The Task Force is the first unit to make it into Metropolis alive, as X organizer Amanda Waller explains. It’s also clear that Harley and crew aren’t exactly eager volunteers, as their heads are “ticking.” Superman, Green Lantern and The Flash also get some attention in the trailer, and even The Penguin makes an unusual cameo appearance.

There’s unfortunately no gameplay in this trailer, and the developers haven’t committed to a more specific release date than “2022” for the PC, PS5 and Xbox Series X/S versions. Even so, this gives you a better idea of what to expect: plenty of witty banter, a world turned on its head and an almost casual approach to violence. The main question is simply whether Rocksteady can build on the reputation from its Batman games and deliver action on par with this teaser footage.

All products recommended by Engadget are selected by our editorial team, independent of our parent company. Some of our stories include affiliate links. If you buy something through one of these links, we may earn an affiliate commission.

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Game

What you’ll get in the ‘Back 4 Blood’ open beta

After playing a few hours of Back 4 Blood, the new co-op survival shooter from Left 4 Dead studio Turtle Rock, I was left with two questions: How is this legal? And, when can I play again? Turns out, right now.

The Back 4 Blood open beta runs from August 5th to 9th, and again from August 12th to 16th, on PC, Xbox and PlayStation consoles. I got a sneak peek at what the beta has to offer on PC, with an emphasis on PvE content, since there were some technical issues with PvP modes during my playtime. Those have been resolved and I’m told PvP is ready to rock for the open beta.

Not that you should expect it to be perfect. Turtle Rock Studios is using the open beta to fine-tune Back 4 Blood ahead of its release on October 12th, and developers are serious about gathering as much feedback as possible. There’s plenty to track: The game uses a Left 4 Dead-style AI director that adjusts the difficulty level in real-time as you plow through hordes of Ridden in your own special way. There’s also a card system that allows players to build decks of class-specific perks, plus corruption cards that apply randomized effects to every level, changing up the gameplay each time. And it’s a true cross-platform game, running across console generations and PC. All of this is on top of a new PvP mode and the core PvE gameplay, which has to feel like butter if it’s going to satisfy Turtle Rock’s Left 4 Dead fans.

I’m one of those fans, and I have to say, I’m enjoying the hell out of Back 4 Blood. Left 4 Dead is a pivotal game of my past, and Back 4 Blood taps into those good feelings in a delicious way.

Back 4 Blood

Turtle Rock Studios

I’m most interested in PvE, since that’s the core of my nostalgia in this case, and I ended up playing about two hours of the main co-op mode with some new friends. The open beta features two PvE maps for co-op runs and two maps for the Swarm PvP mode, where teams of four take turns fighting each other as the Cleaners (the main characters) and the Ridden (the infected former humans). A new character, Mom, joins the roster of playable Cleaners for the first time, too.

One thing that stands out in Back 4 Blood is its sense of replayability. While the levels feel familiar, they’re filled with secrets and they naturally encourage dynamic play, offering various ways to approach any single encounter. The card system adds a lovely layer of customization to the game, while the corruption cards make each new round just a little different, just a little more exciting. There’s a variety of weapons and items to gather as well, and a healthy allotment of ammo drops throughout the maps, especially if you go exploring. 

Shooting the Ridden is immensely satisfying with any gun, while getting snatched up or knocked down by a Special Ridden is shocking basically every time. Meanwhile, the dialogue among the Cleaners is cute, with references to “the new normal,” lizard people in the government and the lamestream media, to name a few joke opportunities. The protagonists of Back 4 Blood aren’t shocked and running for their lives; they’re on a mission to eradicate the Ridden and create safe zones for human life to resume. It’s a refreshing perspective twist.

I ran into a few issues during my time with Back 4 Blood’s open beta content, but nothing that felt insurmountable at this stage of development. Essentially, I trust Turtle Rock to take the feedback from the open beta and apply it to the game in the smartest, most gory way possible for its launch in October.

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Game

R2-D2 is now a Tamagotchi you’ll forget about

R2-D2 might be the most beloved character in the entire Star Wars universe. But some might change their tune about the adorable droid if he becomes too annoying in his latest form: a Tamagotchi.

Disney and Bandai have teamed up to bring Artoo to the pockets of fans who don’t mind training, cleaning and looking after a needy, digital version of the droid wherever they are. The egg-shaped R2-D2 Tamagotchi will be available in two color schemes. There’s a mostly white model that looks like the droid, and a transparent blue model. As you might expect from a Tamagotchi, you’ll interact with the toy using three physical buttons.

There are 19 skills for Artoo to learn. You’ll need to keep him charged and clean. Unlike with other Tamagotchis, you won’t have to clear up any poop from R2-D2 (he’s a droid, after all). A Lucasfilm spokesperson told Engadget that if R2-D2 sits for too long, he’ll accumulate dust. You can clean that away with the press of a button.

There are nine mini-games you can play with him, including firefighting and Star Wars staple Dejarik (or holochess). If you don’t keep the droid happy, some Jawas might arrive to take him away.

Star Wars R2-D2 Tamagotchi

Bandai/Disney

We’re long removed from Tamagotchi’s heyday. The digital pet was everywhere in the late ’90s and early 2000s until it plummeted out of the cultural zeitgeist. There have been other Tamagotchi crossovers. A model based on Neon Genesis Evangelion hit the US earlier this year. A Star Wars collaboration might help revive the brand, but surely a model based on Grogu (aka Baby Yoda) from The Mandalorian would have been a better fit. 

Pre-orders open for the R2-D2 Tamagotchi at midnight ET on August 3rd. The toy will arrive on November 11th.

Update 8/2 5:30PM ET: Added confirmation from Lucasfilm that R2-D2 does not poop and instead accumulates dust.

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Game

Pokemon GO Xerneas raid counters, and how you’ll win

This week it’s time to head out and fight Shiny* Xereas in Pokemon GO, just so long as it’s not Cloudy!
If you’re battling Xereas as a raid boss in Pokemon GO, you’ll need either 3+ players at level 30 or higher, or between 2 and 3 players who are level 40. If you have anything less… you’re in for a bit of a disappointing journey.

The approximate CP for this Pokemon is 2160 in normal weather and 2701 with a Cloudy weather boost. That’s AFTER you’ve beaten Xereas and captured it – and good luck to you on that! You’ll likely be fighting this Pokemon as a raid boss with around 45899 CP right out the gate.

If you’re looking for the absolute best Pokemon to beat Xerneas in a raid battle in Pokemon GO, get yourself a Shadow Metagross. You’ll want to roll with Bullet PUnch and Meteor Mash, and you’ll likely get knocked out around 18 times before it’s all over.

After that, you’ll do well with Mega Gengar with Lick and Sludge Bomb. Metagross (non-Shadow) is also a good bet, so long as it also has Bullet Punch and Meteor Mash. Mega Beedrill with Poison Jab and Sludge Bomb is a strong contender here, followed by Dialga with Metal Claw and Iron Head.

If you have a Shadow Scizor or Shadow Mewtwo, drop them in your team. Scizor is best here with Bullet Punch and Iron Head, Mewtwo is best with Confusion and Psystrike. Genesect with Metal Claw and Magnet Bomb is high powered in this equation, as is Excadrill with Metal Claw and Iron Head.

A few shocking members of the Xerneas battle club include Roserade, Jirachi, and Shadow Victreebel. So long as Roserade has Poison Jab and Sludge Bomb, Victreebel has Acid and Sludge Bomb, and Jirachi has Charge Beam and Doom Desire – you’re good!

Xerneas will be available in standard and *Shiny Pokemon iterations as a raid boss starting on May 4, 2021, 10AM local time, ending on May 17, 2021 at 8PM local time.

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Tech News

New Spotify price date and how much more you’ll pay

Spotify prices are about to change again for some users – not all, but quite a few – as of this Friday. Spotify will begin with the family premium plan in the United States, and both the UK and Europe will have price changes in several areas. Price changes begin this Friday, the 30th of April, 2021.

Some users will get more time with a lower bill than others – but it would appear that the change is coming for all. This isn’t the sort of thing where you get a grandfathered-in price forever. If you were paying one price for one of the affected plans before now, you may have until June before the new, higher price kicks in.

Pricing increases will occur for Family plans in the USA, EU, and UK. If you had a family plan that cost you $14.99 before now, you’ll be paying approximately $15.99 USD. This is the most slight of changes, you’ll find – if you live in the UK, the price increase for a Family plan will go from £14.99 to £16.99 – a price increase of £2. In the EU, this same plan goes from €14.99 to €17.99 – that’s an increase of €3.

If you are a Duo or Student Spotify user in the European Union or the United Kingdom, you’ll find price increases of either €1 or £1, respectively. It’s not a massive change for the individual user, but it should have a massive impact on Spotify’s bottom line.

For the people currently on a free trial of Spotify, it would appear that your first bill will be at the lower price, followed by the new higher price. This is, of course, only for those users who start paying for one of the plans with prices affected by this change.

It’s likely Spotify will release a much more formal notification for price changes at their next earnings report with investors. This report is currently scheduled for Wednesday, the 28th of April, 2021.

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Tech News

Scientists made an AI that reads your mind so it can generate portraits you’ll find attractive

A team of researchers recently developed a mind-reading AI that uses an individual’s personal preferences to generate portraits of attractive people who don’t exist.

Computer-generated beauty truly is in the AI of the beholder.

The big idea: Scientists from the University of Helsinki and the University of Copenhagen today published a paper detailing a system by which a brain-computer-interface is used to transmit data to an AI system which then interprets that data and uses it to train an image generator.

According to a press release from the University of Helsinki:

Initially, the researchers gave a generative adversarial neural network (GAN) the task of creating hundreds of artificial portraits. The images were shown, one at a time, to 30 volunteers who were asked to pay attention to faces they found attractive while their brain responses were recorded via electroencephalography (EEG) …

The researchers analysed the EEG data with machine learning techniques, connecting individual EEG data through a brain-computer-interface (BCI) to a generative neural network.

Once the user’s preferences were interpreted, the machine then generated a new series of images, tweaked to be more attractive to the individual whose data it was trained on. Upon review, the researchers found that 80% of the personalized images generated by the machines stood up to the attractiveness test.

Background: Sentiment analysis is a big deal in AI, but this is a bit different. Typically, machine learning systems designed to observe human sentiment use cameras and rely on facial recognition. That makes them unreliable for use with the general public, at best.

But this system relies on a direct link up to our brainwaves. And that means it should be a fairly reliable indicator of positive or negative sentiment. In other words: the base idea seems sound enough in that you look at a picture you find pleasing and then an AI tries to make more pictures that trigger the same brain response.

Quick take: You could attempt to hypothetically extrapolate the potential uses for such an AI all day long and never decide whether it was ethical or not. On the one hand, there’s a treasure trove of psychological insight to be gleaned from a machine that can abstract what we like about a given image without relying on us to consciously understand it.

But, on the other hand, based on what bad actors can do with just a tiny sprinkling of data, it’s absolutely horrifying to think of what a company such as Facebook (that’s currently developing its own BCIs) or a political influence machine like Cambridge Analytica could do with an AI system that knows how to skip someone’s conscious mind and appeal directly to the part of their brain that likes stuff. 

You can read the whole paper here.

Published March 5, 2021 — 21:11 UTC



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Computing

LastPass to Tweak Free Tier. Find Out If You’ll Need to Pay

LastPass currently offers a free tier that lets a single user access its password manager service on mobile devices and computers. But that’s about to change.

From March 16, the company will limit its free tier to only one device type. So if you select to keep the free tier for mobile, you’ll be asked to pay a fee to continue using the service on computers, and vice versa.

LastPass’ two paid tiers currently include Premium, which starts at $3 a month, and Families, which costs $4 a month and can be used by up to six people. If you’re good to go with Premium, the company is running a limited-time deal costing $2.25 a month (billed annually).

LastPass, which has 20 million users globally, said in a message on its website that free users will have their preferred device type automatically set according to their first login on or after March 16, 2021.

If you’re not happy with the assigned device type, or you’re not sure which is the best fit, you’ll have three opportunities to change between the two.

“Please note that all of your devices sync automatically, so you’ll never lose access to anything stored in your Vault or be locked out of your account due to these changes, regardless of whether you use computers or mobile devices to access LastPass,” the Virginia-based company said.

If you decide to stick with LastPass’ free tier rather than pay to retain access to both device types, you’ll also lose access to email support from May 17, 2021, meaning that you’ll have to find answers to questions via the company’s online support center or community pages, or other places such as external forums.

If you’re currently a LastPass user and feel it’s a good time to check out its competitors, Digital Trends has a recently updated article looking at the best password managers currently available. In a separate post, we take a closer look at how LastPass compares with 1Password, another popular online service for those keen to end the headache of dealing with numerous passwords.

Note: LastPass defines “mobile” as mobile phones, smartwatches, and tablets, and “computers” desktops and laptops.

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AI

Scaling AI: The 4 challenges you’ll face

Organizations of all sizes are embracing AI as a transformative technology to power their digital transformation journeys. Still the challenges around operationalizing AI at scale can still seem insurmountable, with a large number of projects failing.

I’ve worked in big data and AI with several organizations and have seen some clear trends on why AI efforts are floundering after an enthusiastic start. These are large established organizations that have done an amazing job of garnering support from their board, C-suite, business stakeholders, and even customers to embark on AI-powered transformation journeys. They have most likely set up some form of a Center of Excellence (CoE) for AI, with key hires both in leadership and technical roles, and have demonstrated the promise of AI, using a few machine learning projects in a limited scale. Then they move to scale a project into production, and they get stuck.

The reasons why scaling AI is so challenging seem to fall under four themes: customization, data, talent, and trust.

Customization. Solving problems with machine learning (ML) to drive business outcomes requires customization. Most of the models for solving AI problems — ML, deep learning (DL), and natural language processing (NLP), for example — are open sourced or freely available. And these models themselves aren’t the critical factor in solving production-grade problems. Your team will need to customize and train each model to fit your specific problem, data, and domain. Then you need to optimize the model parameters so that they align to your business’s target outcomes/key performance indicators (KPIs). Then, to deploy your models, you need to integrate them into your existing IT architecture. Building AI systems from scratch for every problem and domain thus requires a ton of customization work. Or, if you opt instead to buy off-shelf solutions that are not optimized for your specific needs, you compromise on performance and outcomes. Both paths have their advantages and disadvantages, but it’s important to recognize that AI requires customizations for every project, and every business problem, and that a key part of operationalizing AI is making the customization process as efficient as possible.

Data. I’ve seen a number of organizations fail at AI because they underestimated the effort needed to harness, prepare, and access the data to drive these projects at a production scale, and it becomes a rabbit hole. In most such cases, they realize they don’t have standardized data definitions or proper data management, or they struggle with distributed data sources. This kicks off a multi-year transformation journey. While a ton of big data projects exist to handle accessing, organizing, and curating these disparate datasets, these are not sufficient in providing a scalable solution for this problem. Advanced machine learning techniques to work with smaller data sets and noisier data in production are also needed to eliminate this blockage to getting AI pilots to production. 

Talent. Most organizations where I’ve seen AI projects fail to scale hired ML engineers and data scientists and realized that it was impossible to find someone who has a combination of statistical (ML) skills, domain expertise (both in the business domain and the process domain), and software development experience. So, using classic organizational design, they try to work around it. While you will eventually form a formidable in-house capability if you can retain and develop this highly coveted talent, the need to ramp up a team delays your value realization with AI. This affects your ability to innovate fast enough. I call this the “AI throughput,” the number of AI projects that can be put into production. It takes years for these teams to start producing real results. More successful organizations have brought a holistic ecosystem approach to scaling talent by augmenting internal AI teams with external partners to design a faster pilot-to-production path and improve AI throughput.

Trust. People across the world have mixed feelings towards AI and fear it may make their jobs obsolete or irrelevant. So designing AI systems that emphasise the human-machine collaboration is foundational to scaling AI in these organizations. Although full automation through AI may be the solution for many business challenges, the most impactful and high-alpha processes are still the ones humans run. For large-scale adoption of AI across an organization, you need buy-in, support, and integration across multiple business processes, IT systems, and stakeholder workflows. AI implementation into business processes also introduces a variety of risks. One risk is to business performance in cases where the business impact of the AI system is unclear, costing organizations time, resources, and opportunity cost. Another risk is maintaining compliance with internal audit and regulatory requirements, an area that is largely fast evolving. A third type of risk is reputational, with concerns that biased decisions or decisions made by black box algorithms can negatively impact stakeholder experiences. This is a critical obstacle that even the most advanced teams will run into when trying to scale AI across their organizations.

Overcoming the challenges I’ve outlined here requires more than just technology and toolsets. It involves a combination of organizational processes, being able to bring different teams along, and collaborating actively with a curated ecosystem of internal and external partners. The $15.7 trillion opportunity with AI is in front of us, but it requires us to come together as an industry to solve these key challenges. I will be exploring these areas in future posts with a focus on sharing some best practices.

Ganesh Padmanabhan is VP, Global Business Development & Strategic Partnerships at BeyondMinds. He is also a member of the Cognitive World Think Tank on enterprise AI.

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