Trending February 2024 # Twitch Is Hosting A Massive Pokemon Marathon Beginning Next Week # Suggested March 2024 # Top 5 Popular

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Twitch is hosting a massive Pokemon marathon beginning next week

In recent years, Twitch has hosted a variety of marathons centered around everything from The Joy of Painting with Bob Ross and Mister Rogers’ Neighborhood to Mystery Science Theater 3000 and even Power Rangers. These marathons lasted for days or weeks at a time, but all of them pale in comparison to the next marathon Twitch has on deck: Pokemon. Starting next week, Twitch will begin broadcasting Pokemon from the very first episode in a marathon that’s going to last a very long time.

To get a little more specific about what to expect, Twitch says that the marathon will cover 19 seasons from the long-running show. That works out to an eye-watering 932 episodes, making this the largest marathon Twitch has ever hosted. On top of that, Twitch will also be broadcasting 16 of Pokemon’s 21 movies.

The Twitch Pokemon Marathon, as it’s officially called, begins on August 27 at 10 AM Pacific. Episodes will be broadcast from Monday through Thursday each week on the Twitch Presents channel, with re-runs broadcast on Twitch Presents 2 on Friday on Saturday. On Sunday, we’ll get Pokemon movie parties back on the main Twitch Presents channel, and then the marathon begins again each Monday with fresh episodes from the TV series. Have a look at the list of TV seasons and movies that will be included in this marathon below:

TV Seasons

● Pokémon: Indigo League

● Pokémon: Adventures on the Orange Islands

● Pokémon: The Johto Journeys

● Pokémon: Johto League Champions

● Pokémon: Master Quest

● Pokémon: Advanced

● Pokémon: Advanced Challenge

● Pokémon: Advanced Battle

● Pokémon: Battle Frontier

● Pokémon: Diamond and Pearl

● Pokémon: Diamond and Pearl Battle Dimensions

● Pokémon: Diamond and Pearl Galactic Battles

● Pokémon: Diamond and Pearl Sinnoh League Victors

● Pokémon: Black & White

● Pokémon: Black & White Rival Destinies

● Pokémon: Black & White Adventures in Unova and Beyond

● Pokémon the Series: XY

● Pokémon the Series: XY Kalos Quest

● Pokémon the Series: XYZ


● Pokémon: The First Movie

● Pokémon: The Movie 2000

● Pokémon 3: The Movie

● Pokémon: Lucario and the Mystery of Mew

● Pokémon Ranger and the Temple of the Sea

● Pokémon: The Rise of Darkrai

● Pokémon: Giratina and the Sky Warrior

● Pokémon: Arceus and the Jewel of Life

● Pokémon—Zoroark: Master of Illusions

● Pokémon the Movie: Black—Victini and Reshiram and Pokémon the Movie: White—Victini and Zekrom

● Pokémon The Movie: Kyurem vs. The Sword of Justice

● Pokémon The Movie: Genesect and the Legend Awakened

● Pokémon the Movie: Diancie and the Cocoon of Destruction

● Pokémon the Movie: Hoopa and the Clash of Ages

● Pokémon the Movie: Volcanion and the Mechanical Marvel

As you watch, you’ll be able to use a special extension to collect Pokemon badges by “catching” the Pokemon that appear on screen. Of course, you’ll have the various joys of Twitch chat to go along with your Pokemon viewing spree, which for many people is part of the appeal of these marathons.

Twitch says that this marathon is just one part of a 10-month Pokemon celebration. More information on what this celebration entails will be revealed around the holidays, so we’ll keep an eye out for that. In the meantime, though, there’s plenty of Pokemon watching to be done, so make sure to follow Twitch Presents if you want to be there to relive some memories.

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This Is The Best Pokemon Go Toy Ever

This is the best Pokemon GO toy ever

Pokemon GO and Pokemon Sun and Moon have brought about a new age of Poke-Popularity – and with it, one very awesome toy. This toy captures the joy of tossing a real Pokeball, ejecting the pocket monster therein. This Pokeball doesn’t just bounce away, like most Pokemon toys would – this one unlatches and sends its contents (a Pokemon figure) flying. This is the Pokemon Throw ‘n’ Pop Poke Ball, and it’s something we’ve been waiting for for years.

We’ve got a bundle of Pokemon toys here sent over by TOMY, the lot of which are enjoying extra popularity this summer thanks to the oncoming release of Pokemon Sun, Pokemon Moon, and Pokemon GO. The first thing we’re going to show here is the best Pokemon toy ever made. Bar none.

This contraption is one of four versions of the Throw n’ Pop Poke Ball. This is Pikachu with an original Pokeball. Three other characters from Pokemon X and Y are also available – only the cutest of the bunch – including Chespin with a Premier Ball, Fennekin with a Great Ball, and Froakie with an Ultra Ball.

Below you’ll see how this oddity works. Each of the sides of the Pokeball are held open with springs, and latched with the side of the Pokeball with the button. When the Pokeball is tossed and the button is hit, the latch unlatches and the entire Pokeball springs inside out, launching the Pokemon inside outward.

It’s crazy. Each of these Throw ‘n’ Pop Poke Balls costs around $13 USD, and they should be in stores soon, if they’re not already in a store near you now. This is the first wave of these toys – we’re rooting for a sandshrew next generation.

2024 is the 20th anniversary of Pokemon – what was originally released in Japan as Pocket Monsters Red and Pocket Monsters Green. One of the most massive celebrations of this anniversary was the Pokemon Super Bowl Commercial – as you’ll see below.

This is also the year in which Pokemon GO launched. This genuine phenomenon of a game has seen massive success, and extreme interest has spanned multiple forms of media and disparate companies of all sorts.

The toymakers at TOMY have combined forces with The Pokemon Company to create toys that are both screen-accurate and very high quality.

Above you’ll see some of the newest in Pokemon stuffed animals by TOMY. Stuffed animals like these are a rare mix of top quality manufacturing and relative low cost.

The Eevee here, for example, costs $11 USD. The stitching on this stuffed animal is amongst the best we’ve ever seen on a stuffed animal – ever.

Below you’ll find one of the several-inches-tall fully articulated action figures from TOMY, Mewtwo. Action figures like these cost around $13 USD.

The quality of these larger action figures from TOMY is good. This isn’t something that’s going to bust apart the first time a child tosses it across the room.

Perhaps the best option for catching ’em all in Pokemon toys for adults is in the 3 and 4-inch toys that come in 4-packs.

Generally these come with a set of one evolution – Charmander, Charmeleon, Charizard, and either Mega Charizard X or Y. We’ve got Y here.

These toys are a little bit more fragile. Some some with parts that aren’t made to be tossed, that is to say.

These miniature Pokemon are far better than any of the low-end toys that came out in the 1990s in the USA, that’s for certain. These seem very much to be made as much for kids as they have been made for adults that were kids when Pokemon was first becoming popular.

You can find most of the toys above wherever fine Pokemon products are sold – and most are the type that will only be sold in stores once.

This Pokemon toy collecting hobby is the least forgiving monster in the Pokemon universe. It’s brutal! That is, unless you compare it to Pokemon GO.

Pokemon Prediction Using Random Forest

This dataset has 721 unique values i.e. it has features of 721 unique pokemon; for further details, visit this link.

import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt %matplotlib inline from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score, classification_report from sklearn.ensemble import RandomForestClassifier

Reading the dataset

pokemon_data = pd.read_csv('Pokemon Data.csv')

Now, let’s see what our dataset has in it!

poke = pd.DataFrame(pokemon_data) poke.head()


Checking out folet’sl values



Number 0 Name 0 Type_1 0 Type_2 371 Total 0 HP 0 Attack 0 Defense 0 Sp_Atk 0 Sp_Def 0 Speed 0 Generation 0 isLegendary 0 Color 0 hasGender 0 Pr_Male 77 Egg_Group_1 0 Egg_Group_2 530 hasMegaEvolution 0 Height_m 0 Weight_kg 0 Catch_Rate 0 Body_Style 0 dtype: int64

We have seen the null values in its users n; let’s visualize them using the heatmap.

plt.figure(figsize=(10,7)) sns.heatmap(poke.isnull(), cbar=False)


Here it’s visible that Type_2, Pr_Male, and Egg_Group_2 have relatively null values.

We have visualized the nucan’tlues using the heatmap but in that kind of visualization, we can’t get the count of Let’s null values, so we are using the dist-plot.

plt.figure(figsize=(20,20)) sns.displot( data=poke.isna().melt(value_name="missing"), y="variable", hue="missing", multiple="fill", aspect=2 )


Let’s know the dimensions of our dataset.



(721, 23)

From the shape, it is clear the dataset is small, meaning we can remove the null values columns as filling them can make the dataset a little biased.

We have seen that type_2, egg_group_2, and Pr_male have null values.



0.500 458 0.875 101 0.000 23 0.250 22 0.750 19 1.000 19 0.125 2 Name: Pr_Male, dtype: int64

Since Type_2 and Egg_group_2 columns have so many NULL values we will be removing those columns, you won’t impute them with other methods, but for simplicity, we won’t do that here. We only set the Pr_Male column since it had only 77 missing values.

poke['Pr_Male'].fillna(0.500, inplace=True) poke['Pr_Male'].isnull().sum()


0 # as we can see that there are no null values now.

Dropping unnecessary columns

new_poke = poke.drop(['Type_2', 'Egg_Group_2'], axis=1)

Now let’s understand the type of each column and its values.



plt.figure(figsize=(10,10)) sns.heatmap(new_poke.corr(),annot=True,cmap='viridis',linewidths=.5)


The above is a correlation graph that tells you how much a feature is correlated to another since a high correlation means one of the two features does not speak much to the model when predicting.

Usually, it is to be determined by you itself for the high value of correlation and removed.

From the above table, it is clear that different features have different ranges of value, which creates complexity for the model, so we tone them down usually using StandardScalar() class which we will do later on.



Water 105 Normal 93 Grass 66 Bug 63 Psychic 47 Fire 47 Rock 41 Electric 36 Ground 30 Poison 28 Dark 28 Fighting 25 Dragon 24 Ice 23 Ghost 23 Steel 22 Fairy 17 Flying 3 Name: Type_1, dtype: int64

Value counts of all the generations



5 156 1 151 3 135 4 107 2 100 6 72 Name: Generation, dtype: int64 Visualizing I’me categorical values

Here for visualizing the categorical data, I’m using seaborn’s cat plot() function. Well, one can use the line plot scatter plot or box plot separately, but here, the cat plot brings up the unified version of using all the plots hence I preferred the cat plot rather than the separate version of eI’m plot.

Here for counting each type (6) category of generations, I’m using the cougeneration’snd in the cat plot to get the number of count of each generation’s column.

sns.catplot(x="Generation",kind="count",palette="ch:.25", data=poke)


Inference: In the above graph, the 5th generation is the most in numbers.

Here we are using the default kind of cat plot, i.e. scatter plot to plot the Generation vs Defense graph where we will be able to figure outPokemonlationship between the defence power of each general  Pokemon.

sns.catplot(x="Generation", y="Defense", data=poke)


Inference: Here, we can see that only two pcan’tn in generation 2 have the highest defence capability. Still, we can’t conclude that generation 2 has the most increased defence capabilities as the outliers. Still, in the graph, it is evident that generation 6 and 4 has the highest defence capabilities.

Here we are using the Box plot because boxplot will help us understand the variations in the large dataset better; it will also let us know about the outliers more clearly.

sns.catplot(x="Generation", y="Attack",kind="boxen", data=poke)


Here in the above boxplot, we can see that there are a lot of outliers in generation 4 and generation 1 when it comes to attacking capabilities.

Also, generation 4 has the highest median values of their attacking capabilities than all the other generations.

Now we are using bar kind via cat plot, which will let us know about the Attacking capabilities of different generations based on their Pokemon. For example, in generation 1, the pokemon power of male Pokemon are higher than those of the female Pokemon of the same generation. Still, that generation also has the least attacking power than other generations.

sns.catplot(x="Generation", y="Attack",kind='bar',hue='hasGender', data=poke)


FromPokemonove graph, we can conclude that,

In generaPokemononly the male Pokemon has more attacking power than the female Pokemon, which contradicts other generations.

Generation 6 has the highest attacking power wLet’sgeneration 1 has the lowest attacking power.



Blue 134 Brown 110 Green 79 Red 75 Grey 69 Purple 65 Yellow 64 White 52 Pink 41 Black 32 Name: Color, dtype: int64 new_poke['Egg_Group_1'].value_counts()


Field 169 Monster 74 Water_1 74 Undiscovered 73 Bug 66 Mineral 46 Flying 44 Amorphous 41 Human-Like 37 Fairy 30 Grass 27 Water_2 15 Water_3 14 Dragon 10 Ditto 1 Name: Egg_Group_1, dtype: int64

Let’s also consider the number of values in our target column



False 675 True 46 Name: isLegendary, dtype: int64 Feature Engineering

This may seem uncomfortable to some, but you will get why I did it like that.

poke_type1 = new_poke.replace(['Water', 'Ice'], 'Water') poke_type1 = poke_type1.replace(['Grass', 'Bug'], 'Grass') poke_type1 = poke_type1.replace(['Ground', 'Rock'], 'Rock') poke_type1 = poke_type1.replace(['Psychic', 'Dark', 'Ghost', 'Fairy'], 'Dark') poke_type1 = poke_type1.replace(['Electric', 'Steel'], 'Electric') poke_type1['Type_1'].value_counts()


Grass 129 Water 128 Dark 115 Normal 93 Rock 71 Electric 58 Fire 47 Poison 28 Fighting 25 Dragon 24 Flying 3 Name: Type_1, dtype: int64 ref1 = dict(poke_type1['Body_Style'].value_counts()) poke_type1['Body_Style_new'] = poke_type1['Body_Style'].map(ref1)

You may be wondering what I did; I took the value counts of each body tyLet’sd replace the body type with the numbers; see below



0 135 1 135 2 135 3 158 4 158 Name: Body_Style_new, dtype: int64

Let’s look towards the Body_style



0 quadruped 1 quadruped 2 quadruped 3 bipedal_tailed 4 bipedal_tailed Name: Body_Style, dtype: object Encoding data – features like Type_1 and Color types_poke = pd.get_dummies(poke_type1['Type_1']) color_poke = pd.get_dummies(poke_type1['Color']) X = pd.concat([poke_type1, types_poke], axis=1) X = pd.concat([X, color_poke], axis=1) X.head()


Now we have built some features and extracted some feature data, what’s left is to remove redundant features



Index(['Number', 'Name', 'Type_1', 'Total', 'HP', 'Attack', 'Defense', 'Sp_Atk', 'Sp_Def', 'Speed', 'Generation', 'isLegendary', 'Color', 'hasGender', 'Pr_Male', 'Egg_Group_1', 'hasMegaEvolution', 'Height_m', 'Weight_kg', 'Catch_Rate', 'Body_Style', 'Body_Style_new', 'Dark', 'Dragon', 'Electric', 'Fighting', 'Fire', 'Flying', 'Grass', 'Normal', 'Poison', 'Rock', 'Water', 'Black', 'Blue', 'Brown', 'Green', 'Grey', 'Pink', 'Purple', 'Red', 'White', 'Yellow'], dtype='object')



(721, 38)

Now, let’s see the shape of our updated feature columns


Lastly, we define our target variable and set it into a variable called y

y = X_['isLegendary'] X_final = X_.drop(['isLegendary', 'Body_Style'], axis = 1) X_final.columns


Index(['Total', 'HP', 'Attack', 'Defense', 'Sp_Atk', 'Sp_Def', 'Speed', 'Generation', 'hasGender', 'Pr_Male', 'hasMegaEvolution', 'Height_m', 'Weight_kg', 'Catch_Rate', 'Body_Style_new', 'Dark', 'Dragon', 'Electric', 'Fighting', 'Fire', 'Flying', 'Grass', 'Normal', 'Poison', 'Rock', 'Water', 'Black', 'Blue', 'Brown', 'Green', 'Grey', 'Pink', 'Purple', 'Red', 'White', 'Yellow'], dtype='object') X_final.head()


Creating and training our model

Splitting the dataset into training and testing dataset

Xtrain, Xtest, ytrain, ytest = train_test_split(X_final, y, test_size=0.2)

Using random forest classifier for training our model

random_model = RandomForestClassifier(n_estimators=500, random_state = 42)

Fitting the model

model_final =, ytrain) y_pred = model_final.predict(Xtest)

Checking the accuracy

random_model_accuracy = round(model_final.score(Xtrain, ytrain)*100,2) print(round(random_model_accuracy, 2), '%')


100.0 %

Getting the accuracy of the model

random_model_accuracy1 = round(random_model.score(Xtest, ytest)*100,2) print(round(random_model_accuracy1, 2), '%')


99.31 %

Saving the model to disk

import pickle filename = 'pokemon_model.pickle' pickle.dump(model_final, open(filename, 'wb'))

Load the model from the disk

filename = 'pokemon_model.pickle' loaded_model = pickle.load(open(filename, 'rb')) result = loaded_model.score(Xtest, ytest) result*100


99.3103448275862 Conclusion

Here I conclude the legendary pokemon prediction with 99% accuracy; this might be a overfit model; having said that, the dataset was not so complex that it will lead to such a situaHere’set all the suggestions and improvements are always welcome.

Here’s the repo link to this article.

Here you can access my other articles, which are published on Analytics Vidhya as a part of the Blogathon (link)

If got any queries you can connect with I’m on LinkedIn, refer to this link

About me

Greeting to everyone, I’m currently working in TCS and previously, I worked as a Data Science AssociI’veAnalyst in Zorba Consulting India. Along with full-time work, I’ve got an immense interest in the same field, i.e. Data Science, along with its other subsets of Artificial Intelligence such as Computer Vision, Machine learning, and Deep learning; feel free to collaborate with me on any project on the domains mentioned above (LinkedIn).

The media shown in this article is not owned by Analytics Vidhya and are used at the Author’s discretion. 

The Cat And Mouse Game Between Apple And Jailbreakers Is Only Just Beginning

Following the news that famed jailbreak hacker Comex was hired by Apple, many in the community called it the “beginning of the end” for jailbreakers. Apple is proving to be smarter than everyone thought. If you can’t beat ’em, hire ’em, right?

With iOS 5 set for a public release this Fall, the cat and mouse game between Apple and jailbreakers is not over. It’s only just beginning…

Apple has hired two notable jailbreak developers recently. First there was Peter Hajas, creator of an innovative iOS notifications replacement called MobileNotifier. While Hajas was not associated with exploiting actual jailbreaks, he was a prominent member of the jailbreak community.

As of a couple days ago, we broke the news that Nicholas Allegra (Comex) had been hired by Apple. Unlike Hajas, Comex was perhaps one of the most key jailbreak hackers currently active in the community. He is most famous for his web-based jailbreak called JailbreakMe. Comex was recently profiled by Forbes, and his work on JailbreakMe was compared to “that of Stuxnet, a worm thought to have been designed by the Israeli or U.S. government to infect Iran’s nuclear facilities.”

Seen as one of the greatest minds in the jailbreak community, Comex’s employment at Apple is definitely a huge blow to jailbreakers everywhere — but it is by no means the beginning of the end for jailbreaking.

The two main groups for iOS hacking are the Dev Team and the Chronic-Dev Team. While the Dev Team is responsible for jailbreak tools like RedSn0w and PwnageTool, the Chronic-Dev Team is known for tools like GreenPois0n. The Chronic-Dev Team has taken a backseat to releasing new jailbreaks since iOS 4.2.1. However, both the Dev Team and Chronic-Dev Team are ready to continue exploiting iOS in the future.

Joshua Hill, better known as P0sixninja, is a prominent hacker and leader of the Chronic-Dev Team. He recently assured everyone on Twitter that the Chronic-Dev Team is not only here to stay, but also adding more talented hackers to its roster.

Yes, losing Comex is an awful loss for the jailbreak community. Is it the straw that broke the camel’s back? Absolutely not.

If you look at the Chronic-Dev Team’s website, 9 astute hackers are officially listed as being apart of the team. The Dev Team currently has 10 official members. There are also independent hackers like iH8Sn0w. (The teenage dev is responsible for a widely used jailbreak tool on Windows called Sn0wbreeze.) There are also plenty of unnamed contributors that help to make jailbreaks possible.

The extensive list of new features in iOS 5 indicate that Apple’s innovation takes a huge cue from the jailbreak community. Many of the new features in iOS 5 have been available to jailbreakers already, and Apple has been known to add features and innovations from jailbreak devs in the past.

Examples of continued jailbreak innovation in iOS 5 include the robust list of third party Notification Center widgets that have already been developed and showcased by jailbreakers on the iOS 5 beta. Apple has yet to open up access for developing third party iOS 5 widgets, and, like usual, jailbreakers have paved the path for others to follow.

iOS 5 is by no means the end of jailbreaking. Jay ‘Saurik’ Freeman has no plans to discontinue the development of Cydia. Hackers and developers are expressing more interest in jailbreaking, and the Dev and Chronic-Dev teams are committed to uncovering exploits in iOS.

When Steve Jobs stepped down as CEO of Apple, the Dev Team bid Steve farewell with a nostalgic message:

“The coolest cat. We loved the chase! Good luck, Steve. Signed, Jailbreakers and tinkerers everywhere.”

With Steve gone, the cat and mouse game definitely won’t be the same. But rest assured that it will continue.

Twitch Extensions Not Working

Twitch is a prevalent streaming platform for gaming users. It is the perfect place to show your hobbies, skills, singing, your talent, and much other cool stuff. By the use of extensions, we can make twitch even better which adds functionality to twitch. But some users reported that Twitch Extensions are not Working on Windows 11/10. In this article, we will guide you on how to fix this issue.

What is the cause of the Twitch Extensions not working?

There are many reasons why the Twitch Extension not working in which some of the most common reasons are described below.

It can happen due to an unstable twitch server

It can happen due to Browser related issues

It can happen due to caches and cookies

Outdated twitch extension can be the reason

Due to slow network connection

Twitch Extension is not Working on Windows 11/10

The below suggestions will help you if the Twitch extension are not working.

Check your Twitch server

Switch to another browser

Update your Twitch Extensions

Clear your browser cache and cookies

Restart your device

Disable your Antivirus

Let’s look at each step in detail one by one.

1] Check your Twitch server

You should first check the Twitch server when the Twitch extension is not working on your computer. To check if the twitch server is up and running, you need to go to the Twitch Status website and you can also use the online troubleshooter called the Twitch Inspector.

Also read: Twitch Freezing, Buffering, and Lag issues

2] Switch to another browser

The browser you are using can also be the reason for the Twitch extensions not working. So, to fix this issue take the easiest and smartest steps and switch to a more reliable browser like Opera GX.

The Opera GX browser is specially designed for gaming and game streaming. So it will be optimized to offer the best experience for that purpose. You can use some other features of Opera GX like free VPN, dedicated to chatting, and streaming apps.

3] Update your Twitch extension

In some cases, this problem arises when the extension is outdated. So, we can fix this problem by updating it. Here I am using the chrome browser for updating it, you can use any browser you have. This process is the same for all browsers. So, if you are a chrome user then follow the below steps to update the Twitch Extension.

First of all, go to your browser(here I am using chrome browser)

Now, turn on the Developer mode shown in the top-right corner

Now, Restart your browser

Now, your Twitch Extensions will update.

4] Clear your browser cache and cookies

Unfortunately, our browser stores temporary data on the devices called caches and cookies. And the excess cache data can be the cause of the twitch extension not working so we should try to clear all the caches and cookies data from our browser. Follow the below steps to do so.

Now, your cache and cookies data will clear.

5] Restart your device

This method is very easiest to resolve most issues on any platform. It will reload all the resources and eliminate temporary errors. Restart your PC by following the below method.

6] Disable your Antivirus

Third-party antivirus can also be the reason your Twitch extension is not working. We know that antivirus programs work great for keeping your system safe. But, unfortunately, some antiviruses get overprotected and flag legitimate applications and restrict their access to your system. Now in this case, when your Twitch extension is not working we should try to disable our antivirus.

Hopefully, the above steps will help you in resolving the problem.

Do extensions work on the Twitch app?

Yes, extensions are now available on twitch for iOS and Android users. You can see which extensions are supported on mobile within your extension manager. Remember that extensions are not available in the twitch console or TV apps.

Read: Fullscreen not working on Twitch

How do I enable the twitch extension?

Follow the below steps to enable twitch extension.

Firstly, go to your Twitch Channel

Scroll down a little bit and you will see the Edit panels

Enable the Edit panels option

Go to the Discovery section

Search extension which you want to install

Now, the extension will enable on your twitch account.

Read: How to fix Twitch error 5000, content not available

Why is Twitch not working on Chrome?

Here are some reasons why Twitch is not working on chrome.

If the Twitch server is down then it will not work

It will not work due to excess of the cache and cookies of the chrome browser

It will not work due to the outdated Twitch extension also.

You can follow the below article to know more.

Read: Twitch not working on Chrome.

A Helicopter Caught And Released A Rocket This Week

Late in the morning of May 3, a rocket blasted off into the heavens from a launchpad in New Zealand. Minutes later, as its second stage continued upwards towards orbit, the first stage of the rocket descended by parachute into the waiting hook from a recovery helicopter. The hook snagged the parachute line, where it was held—and then released. The launch, both a successful orbital delivery and useful feature test for rocket-maker Rocket Lab, highlights a future possible form of recoverable rocket launches.

At the heart of Tuesday’s launch was the novel recovery attempt. Getting to orbit is expensive work, and the ability to recover and reuse rocket components can lower the costs of each launch. Recovery in this instance was attempted by a Sikorsky helicopter.

“At 6,500 ft, Rocket Lab’s Sikorsky S-92 helicopter rendezvoused with the returning stage and used a hook on a long line to capture the parachute line,” Rocket Lab said in a release. “After the catch, the helicopter pilot detected different load characteristics than previously experienced in testing and offloaded the stage for a successful splashdown.”

For this specific launch, the catch ended up being more of a catch-and-release, but that attempt still went an important way to demonstrating the viability of the option. Knowing that the release worked—that the helicopter crew was able to snag the rocket and then determine they needed to jettison the booster—is a key part of proving viability. A method that involves helicopters but jeopardizes them pairs reusability with risk to the human crew.

Rocket Lab founder and CEO Peter Beck noted that it’s a tricky dynamic. “Once we receive confirmation that we’re under a good chute, we’ve got about 10 minutes to get on station and rendezvous with the stage,” he said, on a media call, “and not only rendezvous with the stage in a position in space but also in altitude and a descending altitude, a kind of three-dimensional problem if you will.” 

[Related: SpaceX’s first paying ISS passengers say they’re not ‘space tourists’]

This launch, said Rocket Lab in the release, “is the first time a helicopter catch attempt was introduced to recovery operations and today’s mission will inform future helicopter captures.”

In addition to the helicopter snag, the rocket booster was slowed by its initial drogue parachute, as well as by a large main parachute. The drogue parachute stabilized and slowed the booster as it fell, with the main parachute deployed much closer to impact, working as a harder brake. Both parachutes were deployed by the time of the helicopter intercept.

“Trailing behind the main chute is the little drogue chute with a 150-foot line and there’s a 150-line hanging off the helicopter with the capture mechanism,” said Beck. “It’s kind of like Ghostbusters in a way, you want those two streams to cross, those streams being the helicopter long line and the line between the main chute and the drogue chute—those cross and grapple and capture, and then the helicopter slowly decreases the velocity of its descent.”

In this instance, after recovery from the ocean, the rocket booster stage was collected and sent back to where the company produced it for future analysis. 

“It’s an incredible display of logistics and moving pieces. To even get something that’s entering from space at seven times the speed of sound on a ballistic arc to rendezvous with a helicopter was a huge achievement,” said Beck. “We got an image of it on a boat coming home. Little bit wetter than we hoped but incredibly successful.”

The company has a long history of adapting from imperfect initial results. When Rocket Lab sent its first Electron rocket up in 2023, the rocket did not quite make it into orbit as planned. 

Since then, Rocket Lab claims it has had 26 Electron rocket missions, deploying a total of 146 satellites. Of those, 34 were deployed with the latest launch, and those include satellites that Rocket Lab says are “designed to monitor light pollution, demonstrate space junk removal technologies, improve power restraints in small satellites, validate technology for sustainable satellite systems that can avoid collisions with untrackable space objects, enable internet from space, and build upon a maritime surveillance constellation.”

So why doesn’t Electron just do it the same way SpaceX does? According to CNN, “[t]he company has said Electron is not large enough to carry the fuel supply needed for an upright landing, and a saltwater ocean landing can cause corrosion and physical damage.”

[Related: Jeff Bezos is suing NASA. Here’s why.]

Reusing boosters saves on materials cost, and it also saves on manufacturing time. Provided the rocket is not too badly damaged from seawater, refurbishing is a faster turnaround to readiness than starting from scratch. 

If the helicopter hook technique can succeed in the future, a guided and slowed descent shortens that turnaround time even further, making it increasingly likely the company will be able to field as many launches as it schedules and population orbit with more and more satellites.

In the video of the capture attempt, filmed from a camera mounted on the helicopter, the hook can be seen dangling in the air below, a yellow tether suspended in air. The booster, parachute deployed, drifts into the frame. The sky below orbit is vast, full of room for trial and error. The successful snag is the story Rocket Lab is actively telling about the test, but the release of the cord to save the helicopter proves the concept can be attempted again, now with pilots who know what a catch and release feels like.

Watch the recovery attempt below:

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