Google has shared how it’s using artificial intelligence, including its restaurant-calling Duplex tech, to try and keep business hours up to date on Google Maps. The company says that if it is confident enough in the AI’s prediction of what a business’s hours should be, it will update the information in Maps.
In a blog post, Google outlines the various factors its AI analyzes to determine whether it should do these updates. First, it looks at when the business profile was last updated, other similar shops’ hours, and Popular Times data to decide how likely it is that the hours are incorrect. For example: if Google sees that a lot of people visit the shop when it’s supposedly closed, that may be a red flag.
Google’s post says that its AI looks at even more data if it determines the hours should be updated. It’ll take into account information from the business’s website and can even scrape street view images (which may show business hours signs) to try and figure out when the business is open. Google says it’ll also check with actual humans, including Google Maps users and business owners, to verify the AI’s predictions — the company says it will even use Duplex in some countries to ask businesses about their hours directly.
Google spokesperson Genevieve Park told The Verge that Google will “only publish business hours when we have a high degree of confidence that they’re accurate.” If the AI thinks the hours may be incorrect but doesn’t have a solid prediction, it adds a notice that the hours may have changed.
Park also said that Google doesn’t explicitly tell users when hours were updated by its AI and explained that AI is used prettymucheverywhere else in Google Maps. It seems like Google’s pretty bullish on its AI-driven approach. In its post, the company says it’s “on track to update the hours for over 20 million businesses around the globe in the next six months.”
Google also says it’s piloting another use of AI in Maps to help keep speed limits up to date. In the US, it’ll try to see if its partners have taken images of stretches of road that have speed limit signs and will have AI help its operations team identify the sign and the speed limit posted on it.
While it’s no surprise that Google’s using AI for these problems, it is interesting to see how many interlocking systems are involved. There’s computer vision, pattern recognition in location trends, and analyzing data about similar locations (which, of course, also involves figuring out what the similar locations even are), all to quietly try and keep up with how often businesses change their hours and make sure it knows the speed limit on certain stretches of road.
It took less than six hours for drug-developing AI to invent 40,000 potentially lethal molecules. Researchers put AI normally used to search for helpful drugs into a kind of “bad actor” mode to show how easily it could be abused at a biological arms control conference.
All the researchers had to do was tweak their methodology to seek out, rather than weed out toxicity. The AI came up with tens of thousands of new substances, some of which are similar to VX, the most potent nerve agent ever developed. Shaken, they published their findings this month in the journal Nature Machine Intelligence.
The paper had us at The Verge a little shook, too. So, to figure out how worried we should be, The Verge spoke with Fabio Urbina, lead author of the paper. He’s also a senior scientist at Collaborations Pharmaceuticals, Inc., a company that focuses on finding drug treatments for rare diseases.
This interview has been lightly edited for length and clarity.
This paper seems to flip your normal work on its head. Tell me about what you do in your day-to-day job.
Primarily, my job is to implement new machine learning models in the area of drug discovery. A large fraction of these machine learning models that we use are meant to predict toxicity. No matter what kind of drug you’re trying to develop, you need to make sure that they’re not going to be toxic. If it turns out that you have this wonderful drug that lowers blood pressure fantastically, but it hits one of these really important, say, heart channels — then basically, it’s a no-go because that’s just too dangerous.
So then, why did you do this study on biochemical weapons? What was the spark?
We got an invite to the Convergence conference by the Swiss Federal Institute for Nuclear, Biological and Chemical Protection, Spiez Laboratory. The idea of the conference is to inform the community at large of new developments with tools that may have implications for the Chemical/Biological Weapons Convention.
We got this invite to talk about machine learning and how it can be misused in our space. It’s something we never really thought about before. But it was just very easy to realize that as we’re building these machine learning models to get better and better at predicting toxicity in order to avoid toxicity, all we have to do is sort of flip the switch around and say, “You know, instead of going away from toxicity, what if we do go toward toxicity?”
Can you walk me through how you did that — moved the model to go toward toxicity?
I’ll be a little vague with some details because we were told basically to withhold some of the specifics. Broadly, the way it works for this experiment is that we have a lot of datasets historically of molecules that have been tested to see whether they’re toxic or not.
In particular, the one that we focus on here is VX. It is an inhibitor of what’s known as acetylcholinesterase. Whenever you do anything muscle-related, your neurons use acetylcholinesterase as a signal to basically say “go move your muscles.” The way VX is lethal is it actually stops your diaphragm, your lung muscles, from being able to move so your lungs become paralyzed.
Obviously, this is something you want to avoid. So historically, experiments have been done with different types of molecules to see whether they inhibit acetylcholinesterase. And so, we built up these large datasets of these molecular structures and how toxic they are.
We can use these datasets in order to create a machine learning model, which basically learns what parts of the molecular structure are important for toxicity and which are not. Then we can give this machine learning model new molecules, potentially new drugs that maybe have never been tested before. And it will tell us this is predicted to be toxic, or this is predicted not to be toxic. This is a way for us to virtually screen very, very fast a lot of molecules and sort of kick out ones that are predicted to be toxic. In our study here, what we did is we inverted that, obviously, and we use this model to try to predict toxicity.
The other key part of what we did here are these new generative models. We can give a generative model a whole lot of different structures, and it learns how to put molecules together. And then we can, in a sense, ask it to generate new molecules. Now it can generate new molecules all over the space of chemistry, and they’re just sort of random molecules. But one thing we can do is we can actually tell the generative model which direction we want to go. We do that by giving it a little scoring function, which gives it a high score if the molecules it generates are towards something we want. Instead of giving a low score to toxic molecules, we give a high score to toxic molecules.
Now we see the model start producing all of these molecules, a lot of which look like VX and also like other chemical warfare agents.
Tell me more about what you found. Did anything surprise you?
We weren’t really sure what we were going to get. Our generative models are fairly new technologies. So we haven’t widely used them a lot.
The biggest thing that jumped out at first was that a lot of the generated compounds were predicted to be actually more toxic than VX. And the reason that’s surprising is because VX is basically one of the most potent compounds known. Meaning you need a very, very, very little amount of it to be lethal.
Now, these are predictions that we haven’t verified, and we certainly don’t want to verify that ourselves. But the predictive models are generally pretty good. So even if there’s a lot of false positives, we’re afraid that there are some more potent molecules in there.
Second, we actually looked at a lot of the structures of these newly generated molecules. And a lot of them did look like VX and other warfare agents, and we even found some that were generated from the model that were actual chemical warfare agents. These were generated from the model having never seen these chemical warfare agents. So we knew we were sort of in the right space here and that it was generating molecules that made sense because some of them had already been made before.
For me, the concern was just how easy it was to do. A lot of the things we used are out there for free. You can go and download a toxicity dataset from anywhere. If you have somebody who knows how to code in Python and has some machine learning capabilities, then in probably a good weekend of work, they could build something like this generative model driven by toxic datasets. So that was the thing that got us really thinking about putting this paper out there; it was such a low barrier of entry for this type of misuse.
Your paper says that by doing this work, you and your colleagues “have still crossed a gray moral boundary, demonstrating that it is possible to design virtual potential toxic molecules without much in the way of effort, time or computational resources. We can easily erase the thousands of molecules we created, but we cannot delete the knowledge of how to recreate them.” What was running through your head as you were doing this work?
This was quite an unusual publication. We’ve been back and forth a bit about whether we should publish it or not. This is a potential misuse that didn’t take as much time to perform. And we wanted to get that information out since we really didn’t see it anywhere in the literature. We looked around, and nobody was really talking about it. But at the same time, we didn’t want to give the idea to bad actors.
At the end of the day, we decided that we kind of want to get ahead of this. Because if it’s possible for us to do it, it’s likely that some adversarial agent somewhere is maybe already thinking about it or in the future is going to think about it. By then, our technology may have progressed even beyond what we can do now. And a lot of it’s just going to be open source — which I fully support: the sharing of science, the sharing of data, the sharing of models. But it’s one of these things where we, as scientists, should take care that what we release is done responsibly.
How easy is it for someone to replicate what you did? What would they need?
I don’t want to sound very sensationalist about this, but it is fairly easy for someone to replicate what we did.
If you were to Google generative models, you could find a number of put-together one-liner generative models that people have released for free. And then, if you were to search for toxicity datasets, there’s a large number of open-source tox datasets. So if you just combine those two things, and then you know how to code and build machine learning models — all that requires really is an internet connection and a computer — then, you could easily replicate what we did. And not just for VX, but for pretty much whatever other open-source toxicity datasets exist.
Of course, it does require some expertise. If somebody were to put this together without knowing anything about chemistry, they would ultimately probably generate stuff that was not very useful. And there’s still the next step of having to get those molecules synthesized. Finding a potential drug or potential new toxic molecule is one thing; the next step of synthesis — actually creating a new molecule in the real world — would be another barrier.
Right, there’s still some big leaps between what the AI comes up with and turning that into a real-world threat. What are the gaps there?
The big gap to start with is that you really don’t know if these molecules are actually toxic or not. There’s going to be some amount of false positives. If we’re walking ourselves through what a bad agent would be thinking or doing, they would have to make a decision on which of these new molecules they would want to synthesize ultimately.
As far as synthesis routes, this could be a make it or break it. If you find something that looks like a chemical warfare agent and try to get that synthesized, chances are it’s not going to happen. A lot of the chemical building blocks of these chemical warfare agents are well known and are watched. They’re regulated. But there’s so many synthesis companies. As long as it doesn’t look like a chemical warfare agent, they’re most likely going to just synthesize it and send it right back because who knows what the molecule is being used for, right?
You get at this later in the paper, but what can be done to prevent this kind of misuse of AI? What safeguards would you like to see established?
For context, there are more and more policies about data sharing. And I completely agree with it because it opens up more avenues for research. It allows other researchers to see your data and use it for their own research. But at the same time, that also includes things like toxicity datasets and toxicity models. So it’s a little hard to figure out a good solution for this problem.
We looked over towards Silicon Valley: there’s a group called OpenAI; they released a top-of-the-line language model called GPT-3. It’s almost like a chatbot; it basically can generate sentences and text that is almost indistinguishable from humans. They actually let you use it for free whenever you want, but you have to get a special access token from them to do so. At any point, they could cut off your access from those models. We were thinking something like that could be a useful starting point for potentially sensitive models, such as toxicity models.
Science is all about open communication, open access, open data sharing. Restrictions are antithetical to that notion. But a step going forward could be to at least responsibly account for who’s using your resources.
Your paper also says that “[w]ithout being overly alarmist, this should serve as a wake-up call for our colleagues” — what is it that you want your colleagues to wake up to? And what do you think that being overly alarmist would look like?
We just want more researchers to acknowledge and be aware of potential misuse. When you start working in the chemistry space, you do get informed about misuse of chemistry, and you’re sort of responsible for making sure you avoid that as much as possible. In machine learning, there’s nothing of the sort. There’s no guidance on misuse of the technology.
So putting that awareness out there could help people really be mindful of the issue. Then it’s at least talked about in broader circles and can at least be something that we watch out for as we get better and better at building toxicity models.
I don’t want to propose that machine learning AI is going to start creating toxic molecules and there’s going to be a slew of new biochemical warfare agents just around the corner. That somebody clicks a button and then, you know, chemical warfare agents just sort of appear in their hand.
I don’t want to be alarmist in saying that there’s going to be AI-driven chemical warfare. I don’t think that’s the case now. I don’t think it’s going to be the case anytime soon. But it’s something that’s starting to become a possibility.
Whenever we talk about password managers, especially ones that sync their data to the cloud, there’s always discussion about whether or not your information is secure and what happens if the servers go down. The second thing is exactly what 1Password users in the US experienced earlier today, as a problem affecting 1Password.com kept mobile, desktop, and browser clients from syncing.
A status page first noted the problem at 10:42AM ET and listed it as stabilized, with clients able to connect again by 2:42PM ET. During the outage, the status page noted that the issue didn’t affect any offline data stored in clients, and other domains like 1password.ca, 1password.eu, or ent.1password.com were operational.
Before I knew there was an outage, I saw it on my own account when I tried to save a password, and it simply would not do it. All of my local clients still had all of my current passwords, so I think most people didn’t even notice it was down. However, if you don’t store your passwords on a local device or had lost access to it during the outage, there could have been a real problem.
We’re now operational.
Earlier today, 1Password experienced a brief service outage – this was not a security incident and your data remains safe. We’ve stabilized the system while we investigate further.
In a statement provided to The Verge, 1Password CTO Pedro Canahuati said:
Earlier today, 1Password experienced a brief service outage due to our planned database upgrade. This was not a security incident, and customer data was not affected in any way.
The 1Password.com service was down during this outage and that affected new user signups and syncing new data across devices. Our system is designed to ensure any stored passwords are always safe and accessible locally on their devices.
At this time, we have stabilized the system while we investigate the performance regression. Customers’ devices should be syncing all new data and sign-ups are working.
We’re taking steps to avoid similar disruptions in the future, and will be providing updates on our status page and social media channels, as well as our blog over the next day or two.
Anyone who uses a password manager that stores data in the cloud does have some risk of this happening to them, but it doesn’t seem to have been very disruptive. On the other hand, cloud storage makes keeping tons of logins accessible from every device you use easier and enables features like the Travel Mode that wipes out data stored on your device if you’re in a situation where it may be confiscated or searched. Still, given the fact that the new 1Password 8 client will only sync with the cloud and doesn’t give the option of sticking exclusively to local storage, it’s something to be aware of. For customers who prefer local storage, 1Password has said they can continue using 1Password 7.
It’s been a rough 24 hours for New World. The Amazon-crafted MMO has had its share of problems since launch, but over the last day or so, we’ve seen Amazon grappling with a rather severe gold duplication issue. Amazon’s response to the gold duping exploit was swift but questionable, as it brought New World‘s economy to a screeching halt.
New World’s tricky gold exploit
In MMOs, the economy is often king. Players earn gold and item drops as they complete quests and run dungeons, then trade that gold to other players for services or items they need. For instance, in World of Warcraft, you might take your hard-earned coin to buy some herbs for potions and then pay an herbalist to make those potions for you.
If you’ve played an MMO before, it should come as little surprise to learn that gold plays an important role in New World. Gold can be traded with other players, sent to a player’s company to be used for Town Projects (assuming said company owns a town), or used to purchase items listed by other players on the in-game market. The market is a popular place in each of New World‘s towns, and in more central locations like Windsward, Everfall, or Brightwood, it’s common to see a horde of players wheeling and dealing at the trading post when you enter the town square.
Yesterday, Amazon made the dramatic decision to turn off all wealth transfers between players in response to a gold duplication exploit. This meant players could no longer trade gold with one another or send gold to their companies. It also, importantly, meant that items couldn’t be purchased from the trading post, as that counts as a transfer of wealth.
Why Amazon did this instead of simply putting the game into maintenance to fix the problem is something that I can’t figure out. Without access to the market, anyone trying to grind their crafting skill levels has to go out and gather the raw materials themselves. An enjoyable task for the penny pinchers among us who prefer to gather their own materials and spend gold only when absolutely necessary, but awful for those who would just rather pay gold to buy the materials they need from the market and get to leveling as soon as possible.
Amazon halted gold transfers in response to a gold duplication exploit that was, as the name suggests, allowing players to duplicate quantities of gold and make themselves richer without having to go out and earn that coin first. Obviously, letting a gold dupe exploit run rampant is a wonderful way to kill the economy in an MMO, so it’s understandable that Amazon took quick action, I’m just not sure that bringing the in-game economy to a stand-still was the better option than putting the game into maintenance.
Gold duplication finds a way
Things get worse from there. While Amazon’s halt to wealth transfers should have stopped any potential gold duplication exploits, it actually created an entirely new one. Several hours after the forum post announcing the halt to player gold transfers, New World‘s community managers were notified of another gold duplication exploit that was only possible with the economic restrictions Amazon itself had put into place.
Amazon has made it clear that it will take back any ill-gotten gains and punish those caught using both this exploit and the exploit that started this all, which again makes me feel like it would have been better to take the entire game down and address the issues while New World was offline.
At the time of this writing, wealth transfers between players have been unavailable for a full day. We had gone 16 hours without an update, but mere minutes ago, Amazon posted an update on the matter to its forums. That update says the New World team “is currently zeroing in on a fix for the exploits that necessitated the turning off of all wealth transfer in New World,” and that the company will deploy the fix as soon as testing is finished.
Hopefully that’s soon, because until testing is done, players are left in this limbo where they can play the game but they can’t participate in the economy, one of New World‘s major components.
New World, new bugs
I’ve been playing New World since the day it came out, and on the whole, I’ve been enjoying myself. I think New World is a game that needs a lot of work, but I can see a solid foundation there and I’m interested in seeing how the game progresses from this early point. However, it’s hard not to be frustrated as a player because it seems like every time a new update comes out, it introduces a slate of new bugs that break the game in different ways. Often, those bugs go unresolved until the next weekly patch.
One bug that I’ve been grappling with as I play my full mage build makes the Ice Gauntlet’s Ice Storm ability wholly ineffective more often than not. There’s a rare occasion where the Ice Storm will actually connect, deal damage, and apply its various debuffs, but oftentimes it simply does nothing.
In the past week, one of the bugs we’ve heard about prevents players from getting the gold from trading post sales that complete while they’re offline. As outlined in this video by Callum Upton, there was also a chat exploit that could make other players crash to desktop, though that has been fixed according to Amazon (Upton explains the trading post bug and the gold duplication exploit in his video as well).
At the end of the day, bugs are just a reality of game development – as are patches that introduce new bugs – and it’s hard to think of an MMO that didn’t have problems at launch. MMO launches can be a hectic time for developers, and Amazon is, unfortunately, going through that phase now with New World. With that said, at times it does feel like things are snowballing out of control over at Amazon Game Studios, as the company has spent much of the time since launch responding to critical bugs that keep cropping up.
As a player, it’s exhausting trying to keep up with all the issues. For me at least, not having access to New World‘s economy saps any enthusiasm I had to play. It’s frustrating to see the groundwork for a good game but to then have that image muddied by a host of bugs and exploits that are, in some cases, game-breaking. Hopefully, Amazon can right the ship and get New World to a more stable point, but while it does that, I can’t really blame any fed-up gamers for deciding to put their attention elsewhere.
Right here and now, we’re taking a peek at the most important Pokemon GO Spotlight Hours of the month of November 2021. Before we drop in on November, it’s important to note that the bonuses we’re seeking already exist in the game until the end of October. We’re talking about 2x Transfer Candy and 2x Catch Candy, of course.
If you’re reading this article inside the month of October, 2021, it is high time you opened the Pokemon Candy flood gates. The 2021 Halloween event includes two of the most awesome bonus features of the year, courtesy of the most spooky sugar-filled day of the year. You can get twice as much candy as usual whenever you transfer a Pokemon, and twice as much candy as usual whenever you catch a Pokemon.
This 2x Candy feature works with any Pokemon you have, or any Pokemon you might catch. Better still, if you use a Pinap Berry on a Pokemon before you catch it, you’ll get 4x candy from the catch!
If you’re reading this article after Halloween is over, no worries! You’ll just need to keep an eye on one of the key Spotlight Hour events in November 2021. On November 2 at 6PM local time there is a Cacnea Spotlight Hour. This event includes the 2x Catch Candy feature (for any Pokemon you might find in the wild).
On November 9, a Chinchou Spotlight Hour includes the 2x Transfer Candy feature. The November 30 event features Piplup (regular style, no fancy Halloween hat). This November 30 event features 2x Catch Candy as well.
If you’re looking to stock up on Stardust or XP, the other two Spotlight Hour events in November are most important. On November 16 there’ll be a Turtwig Spotlight Event with 2x Catch Stardust. On November 23 there’ll be a Chimchar Spotlight Hour with 2x Catch XP.
If you’re seeking Shiny Pokemon, the Cacnea event will be a bit of a bummer – there is no Shiny Cacnea in the game as yet. Shiny Chinchou is in the game, as is Shiny Turtwig, Shiny Chimchar, and Shiny Piplup. Tap to your heart’s content!
In the month of August, 2021, Niantic’s ready to roll with a set of Pokemon you’ll most likely want to catch for Spotlight Hours. The best of the bunch might very well be the first, with Magnemite. There’ll also be a Shellos from the East Sea and a Shellos from the West Sea. Late August also has a couple more Pokemon that aren’t yet revealed to the public.
The first Spotlight Hour of the month of August takes place on August 3, 2021. Each Spotlight Hour starts at 6PM (local time) and lasts for an hour. Each Spotlight hour takes place on a Tuesday – so you can pretty much bet that every Tuesday at 6PM local time you’ll find an awesome situation going on in Pokemon GO.
On August 3, 2021, at 6PM, it’s time for Magnemite. This Spotlight Hour will deliver a far more common Magnemite and the potential to find said Magnemite in Shiny form. You’ll also find 2x catch stardust for the duration of this mini event.
On August 10, 2021 there’ll be a Spotlight Hour for Shellos (East Sea). This is one of two Shellos that’ll appear during this month, the next with a Spotlight Hour on August 17, 2021. The August 10 event features 2x Catch XP for the duration of the event, and the August 17 event will deliver 2x Catch Candy for all Pokemon caught during this event.
We do not yet know which Pokemon will appear on August 24 or August 31, but we can safely assume we’ll get 2x Transfer Candy for the 24th, and 2x Evolution XP for the 31st. Remember to keep your special XP and candy-seeking action for these mini-events, they’re on the way!
Which Pokemon do you think will appear for the last two Tuesdays of the month? Could it be something new, or a Pokemon favorite that’s already in the game now?
FidelityFX Super Resolution (FSR) is AMD’s open-source alternative to Nvidia deep learning super sampling (DLSS), and we’re starting to hear opinions from game developers on it. Although both tools achieve the same goal, Midgar Studio CEO and lead programmer of Edge of Eternity Jérémy Zeler-Maury says that FSR is much easier to implement into games and that both tools achieve similar image quality at 4K.
Edge of Eternity is a unique case study. The indie-developed JRPG includes DLSS and FSR, so the developer has experience working with both. In an interview with Wccftech, Zeler-Maury contrasted the “complex” process of integrating DLSS into the game with FSR, saying the latter only took “a few hours” to implement.
“Implementing DLSS was quite complex to integrate into Unity for a small studio like us; it required tweaking the engine and creating an external plugin to bridge Unity and DLSS,” Zeler-Maury said. “FSR, on the other hand, was very easy to implement, it only took me a few hours, requiring only simple data.”
The interview confirms a lot of what we already know about FSR. It’s much easier for developers to use, but Zeler-Maury cautions that it doesn’t work as well at lower resolutions. “For lower resolutions like upscaling to 1080p or 720p, I think DLSS gives a better result since it can reconstruct parts of missing details,” Zeler-Maury said.
DLSS uses machine learning to reconstruct an image, which makes it more equipped to maintain detail at low resolutions. FSR, according to Zeler-Maury, requires “the source data to be as sharp as possible.” As long as it is, the developer says that both tools provide amazing results, even going as far as to say they prefer FSR at 4K resolution because it produces fewer artifacts than DLSS.
In our FidelityFX Super Resolution review, we found that the upscaling technique is capable of delivering much higher frame rates at high resolutions, but the more aggressive upscaling modes give up too much visual quality. Zeler-Maury suggests that might not matter. They assert that the lion’s share of games will receive FSR support simply because it’s easier to implement.
“I think FSR being very easy to integrate means more games are going to get it, DLSS is more complicated to integrate. Aside from pre-integrated versions in engine or AAA games, I don’t think many small developers will integrate it,” Zeler-Maury said.
Still, DLSS isn’t down and out. Although it may not be able to reach as many games as FSR in the future, DLSS’ image reconstruction quality remains unmatched. FSR is providing credible competition with how easy it is to implement into games, however. A modder, for example, was able to patch FSR into Grand Theft Auto 5before it released to the general public.
FSR supports a small list of games right now, including Anno 1800 and Godfall. AMD says that many more games will support the feature in the near future, including Far Cry 6, Resident Evil: Village, and Myst.
TLDR: The Premium Learn to Code 2021 Certification Bundle is a 27-course programming behemoth, including over 270 hours of training in every coding arena a student needs to know.
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The Pokemon GO Spotlight Hour for Pokemon of several sorts appearing in June of 2021 are here. They include Aipom, Slowpoke, Dwebble, Abra, and Swinub. Each of these Pokemon will appear with availability of a Shiny version, which, combined with their far-more-common availability during said event, means you’ll have a far greater chance of filling up your Shiny Pokedex.
On June 1, 2021, the Dwebble Pokemon GO Spotlight Hour will take place. This event’s bonus is 2x Catch XP. That means that during the hour starting at 6PM (local time) on Tuesday, June 1, you’ll get twice the experience points you’d normally get for capturing a Pokemon.
On June 8, there’ll be a Spotlight Hour in Pokemon GO for Abra. This is one of the original 150 Pokemon and a Pokemon that can be particularly helpful as it evolves into its ultimate self. This Spotlight Hour will include 2x Catch Candy! That means it’ll be EXTRA easy to not only capture a Shiny Abra, but evolve said Shiny Pokemon into Alakazam!
There’ll be a June 15 Spotlight Hour with Slowpoke. You’ll want to save all your transfers until this event, as this event’s bonus is 2x Transfer Candy! Every Pokemon you transfer out during this event will give you TWICE the candy you’d normally get!
On June 22 there’ll be a Spotlight Hour for Swinub, and on June 29 you’ll find a Spotlight Hour for Aipom. The Swinub event will feature 2x Evolution XP, and the Aipom event will feature 2x Catch Stardust.
Also starting today is a Pokemon GO Special Weekend. This event begins on Friday, May 28, 2021, starting at noon Central time. It’ll end on May 31, Monday, at noon Central time. You’ll find 2x daily limit for Gift opening, and you’ll find your trade range is increased to 40km! This special weekend also has a set of bonuses if you’ve signed up with Verizon in the USA, 7-Eleven in Mexico, or Yoshinoya in Japan. You might be part of this event with great ease if you’ve already purchased a ticket – or you might just want to open more gifts!
Today we’re taking a peek at each of the four Spotlight Hour Pokemon in Pokemon GO for the month of May, 2021. This set of four is decent! This set of four isn’t absolutely the worst! This set of four might actually be worth keeping an eye on, since they’re all pretty cool. The fun begins on May 4, 2021, (that’s a Tuesday), with Cottonee.
On Tuesday, May 4, 2021, the Pokemon GO Spotlight Hour will focus on Cottonee. During this event, users will earn two times the normal amount of candy for catching Pokemon in the wild. This event, like the rest of the Spotlight Hour events for the month of May, will take place from 6PM to 7Pm local time.
On Tuesday, May 11, 2021, the spotlight will be on Dratini. This might well be the most sought-after monster of the original series when it comes to odd dragons. With this Dratini Spotlight Hour, gamers will find they earn twice the Pokemon Candy for transferring Pokemon. Time to save up, immediately!
The third Spotlight Hour will take place on May 18, 2021, and it’ll feature Alolan Rattata. SO actually, maybe not ALL of the Spotlight Hours this month are really worth the extra effort in catching Pokemon. BUT, this event does give users twice the XP for evolving Pokemon – so that’s worth waiting for.
The final Spotlight Hour of the month of May, 2021, is on May 25. On that day, users will find Marill in focus. During this Spotlight Hour, users will get twice the Stardust for the capture of Pokemon in the wild.
There’ll also be a Community Day event on May 15, 2021. That’ll include new featured Pokemon that’ve not yet been revealed! The May Community Day for 2021 will take place on May 15, 2021, from 11AM to 5PM local time.
In the month of May we’ll also see a “free one-time bundle” with a Remote Raid Pass and “other items” available in the in-game shop. The “one-time” bit just means that each bundle will be unique – we’ll get a new bundle every Monday!